https://www.coastalwiki.org/w/api.php?action=feedcontributions&user=Mcordier&feedformat=atomCoastal Wiki - User contributions [en]2024-03-28T10:25:29ZUser contributionsMediaWiki 1.31.7https://www.coastalwiki.org/w/index.php?title=Input-output_matrix&diff=11533Input-output matrix2007-08-28T10:27:43Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
<br />
An Input-output matrix is a representation of national or regional economic accounting that records the ways industries trade with one another as well as produce for consumption and investments. <br />
<br />
Input-output matrix is constructed on the simple idea that goods and services produced by economic sectors should be registered in a table simultaneously by origin and by destination [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)]<ref>'''OECD (Organisation for Economic Co-operation and Development), 2006.''' ''Input-output analysis in an increasingly globalised world: applications of OECD’s harmonized international tables.'' STI/Working paper 2006/7. Statistical analysis of Science, Technology and Industry. 31st August. Available on Internet : http://www.oecd.org/dataoecd/6/34/37349386.pdf</ref>.<br />
Commodities are produced by economic sectors (e.g. cotton produced by agriculture) and they serve as inputs in other sectors in order to produce their final products also called outputs (e.g. manufacturing industry such as textile industry using cotton from agriculture as input to produce its own output, i.e. clothes in cotton). Better said, the purchase of agricultural output by manufacturing is for use as inputs in producing manufacturing output. Such purchases are part of what is known as intermediate demand, which term refers to inter-industry transactions, i.e. goods and services bought by firms from other firms and used up in current production (this corresponds to Domestic intermediate matrix – see '''first quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]). The outputs are delivered to the final demand sector that comprises purchases by individuals for consumption, by firms for investment (in fixed capital such as machines, buildings, etc.), by government, and by foreigners (exportations) – this corresponds to the '''fourth quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] called Domestic investment matrix. The use of this terminology “final demand” simply indicates that purchases by this sector are not for the purpose of use in production (Common and Stagl, 2005)<ref>'''Common M., Stagl S., 2005'''. ''Ecological Economic. An Introduction.'' Cambridge University Press, New York, pp.125-136</ref>. In addition to intermediate inputs mentioned above, firms use also primary inputs. Those are services which are not bought from other firms but from individuals : these services are known as factors of production. These refer to wages and salaries as payments for labour services, interests paid on borrowing, rent paid for the use of equipment, building and land, profits paid for the entrepreneurship that is the function of organizing and risk-taking (Common and Stagl, 2005). – this corresponds to the '''second quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1], which is called Imported intermediate products matrix. We are not going to detail the '''third''' and the '''fifth quadrant''' here since they are not essential to the global understanding of the methodology. For more details, look at the legend of [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] or go to [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)] and read pp.7-9.<br />
<br />
[[image:Table_1_Version_4.JPG|thumb|right|[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]. Example of an Input-ouput Matrix for Belgium in the year 2000. Source : OECD (2006a)]]<br />
<br />
[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] shows an example of a real input-output matrix for Belgium in the year 2000. The columns represent the destination of inputs, and the rows sum the output of a sector. <br />
As you can see, only the total outputs (last line called industry output) are shown, not the total inputs. This is because such data is not necessary since the total inputs equal the total outputs. Normally, this total appears in the last column of the table.<br />
<br />
===Practical use of Input-output tables===<br />
<br />
If we want to estimate without Input-output analysis, which additional inputs would be needed if the fishing sector increased its production by one unit, we would need to measure the following : i) first round, direct effects on the industries that supply the fishing sector with nets, boats, fishing rods etc; and ii) a range of secondary (indirect) effects, since these supplier industries themselves require additional inputs for their production, in order to meet the additional demand coming from the fishing sector production system. <br />
<br />
Fortunately, input-output matrices offer a solution to solve such problems immediately taking into account both direct as well as indirect effects. This can be particularly appreciable for assessing economic impact (both ex-ante and ex-post) of policy changes. Environmental impact can even be analyzed if we add environmental data to classical input-output tables in order to build green input-output tables. <br />
<br />
For instance, if a policy option scenario for marine pollution management (e.g. a tax on plastic industry resulting in higher plastic prices or a governmental subsidies to the production of material of substitution that are biodegradable) results in technical changes or in changes in final demand for plastics (a valuable material particularly in construction, packaging and fishing gear applications), I-O analysis can help us to deduce the following (adapted from Leontief, 1974, 193-209 pp.)<ref>'''Leontief V., 1974.''' ''Essais d’économiques.'' Ed. Calman Lévy, pp.133-157 and 193-216. Those two chapters are also available in English in : <br />
* Input-output Analysis, Input-output Economics, New York Oxford University Press, 1966;<br />
* Environmental repercussions and the Economic Structure : An Input-Output Approach, published in The Review of Economics and Statistics, Vol. LII, n°3, August 1970, Copyright by the president and Fellows of Harvard College; published as well in Robert et Nancy DORFMAN, Economics of the Environment, W.W. Norton & Co Inc, 1972.<br />
</ref> :<br />
<br />
*the policy options impact on the total level of pollution by plastic microparticles in the sea <br />
*the amount of pollution reduction in a particular sector resulting from the implementation of a policy option <br />
*the total pollution resulting from the final demand (demand from households, …) for products of each sector. For instance, keeping the example of plastic production, this means that the I-O table can tell us : “from the total amount Y of plastic pollutant in the sea, X tones are linked to agriculture, industrial and services activities contributing directly or indirectly to the supply of agricultural products to households. This is interesting since it does not only take into account the amount of pollutants from the agriculture sector for the production of agricultural products, but it also encompasses pollutants from other sectors intervening in the production of agricultural products. That is important since the agriculture sector also needs industrial products and services to generate its production. The same can be calculated for the supply of industrial products and services to households. <br />
*the impact of policy options on production level in other sectors (and so on the economy)<br />
*the impact of policy options on total employment in the region or in a particular sector<br />
*the impact of policy options on prices of goods and services<br />
<br />
===Limits of the method===<br />
<br />
The input-output (I-O) analysis is not able to capture environmental measures with a small economic impact (on GDP, on production, on employment…at national or regional level) because of data are too aggregated. Therefore, I-O is only relevant for activities having a wide economic impact such as construction of large infrastructures (railways or motorways infrastructure), modification of port activities, implementation of environmental policies targeting a whole sector, subsector or a branch of economic activities, etc. <br />
<br />
Nevertheless, I-O analysis could also be relevant for a package of several policy options, each having a relatively small impact, but whose sum results in a large impact on the regional economy.<br />
<br />
Walter Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> summarized several other limits of I-O analysis. They are mentioned below.<br />
<br />
First of all, environmental measure might affect output prices. For instance, if a governmental policy make compulsory for oil companies to install an oil desulfuration system (that prevents acid rains), the cost of this depollution system will be reflected in oil price. Hence, all products requiring oil in their fabrication process will see their price modified too (e.g.: outputs from agriculture, electricity, ferrous metals, etc.). And due to an increase in their price, the demand for each of these products will probably decrease. The modification of the demand due to price variation must be integrated into I-O models but this makes them heavier to handle because of numerous products and/or diverse response functions. In that case, dynamic model such as CGE might be more suitable.<br />
<br />
Moreover, I-O matrices give a static vision of the economy making difficult projections possibilities. However, it is possible to build dynamic I-O matrices but this is a bit more complicated. <br />
<br />
Another disadvantage is the impossibility of substitution between production factors (labour, technical capital, land) while environmental policies might precisely have a structural effect on the long run on that aspect. Let’s take the example of an environmental policy aiming at decreasing green house gases emissions by promoting research and development in energy efficiency in households. Imagine the instrument of this policy would consist in public subsidies to universities for research in building insulation new technologies. Such a measure might lead to reduction of households energy consumption and so a reduction in natural gas extraction burnt in power plants for electricity generation. In that case, the production factor “land” in the form of a natural resource (natural gas) has been partly substituted by the production factor “labour” (development of human knowledge in new insulation techniques).<br />
<br />
Furthermore, I-O tables are published by national and regional authorities with few years delay. For instance in Belgium in 2007, the last I-O table available dates from 2000. Through the delayed publishing of national I-O tables, factor relations within single sectors can be changed to a quite big extend. Such old data on the status of the economy might make I-O analysis for the subsequent years quite inaccurate. However there are techniques enabling to actualize too old I-O matrices.<br />
<br />
The last limit we would like to highlight is the need of regionalization of national I-O tables. It can happen that you find only national I-O tables while you want to work at regional level (i.e. at a smaller spatial scale). In that case you will need to apply regionalization methods which add to the difficulties.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Green accounting]]<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Input-output_matrix&diff=11532Input-output matrix2007-08-28T10:26:25Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
<br />
An Input-output matrix is a representation of national or regional economic accounting that records the ways industries trade with one another as well as produce for consumption and investments. <br />
<br />
Input-output matrix is constructed on the simple idea that goods and services produced by economic sectors should be registered in a table simultaneously by origin and by destination [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)]<ref>'''OECD (Organisation for Economic Co-operation and Development), 2006.''' ''Input-output analysis in an increasingly globalised world: applications of OECD’s harmonized international tables.'' STI/Working paper 2006/7. Statistical analysis of Science, Technology and Industry. 31st August. Available on Internet : http://www.oecd.org/dataoecd/6/34/37349386.pdf</ref>.<br />
Commodities are produced by economic sectors (e.g. cotton produced by agriculture) and they serve as inputs in other sectors in order to produce their final products also called outputs (e.g. manufacturing industry such as textile industry using cotton from agriculture as input to produce its own output, i.e. clothes in cotton). Better said, the purchase of agricultural output by manufacturing is for use as inputs in producing manufacturing output. Such purchases are part of what is known as intermediate demand, which term refers to inter-industry transactions, i.e. goods and services bought by firms from other firms and used up in current production (this corresponds to Domestic intermediate matrix – see '''first quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]). The outputs are delivered to the final demand sector that comprises purchases by individuals for consumption, by firms for investment (in fixed capital such as machines, buildings, etc.), by government, and by foreigners (exportations) – this corresponds to the '''fourth quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] called Domestic investment matrix. The use of this terminology “final demand” simply indicates that purchases by this sector are not for the purpose of use in production (Common and Stagl, 2005)<ref>'''Common M., Stagl S., 2005'''. ''Ecological Economic. An Introduction.'' Cambridge University Press, New York, pp.125-136</ref>. In addition to intermediate inputs mentioned above, firms use also primary inputs. Those are services which are not bought from other firms but from individuals : these services are known as factors of production. These refer to wages and salaries as payments for labour services, interests paid on borrowing, rent paid for the use of equipment, building and land, profits paid for the entrepreneurship that is the function of organizing and risk-taking (Common and Stagl, 2005). – this corresponds to the '''second quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1], which is called Imported intermediate products matrix. We are not going to detail the '''third''' and the '''fifth quadrant''' here since they are not essential to the global understanding of the methodology. For more details, look at the legend of [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] or go to [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)] and read pp.7-9.<br />
<br />
[[image:Table_1_Version_4.JPG|thumb|right|[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]. Example of an Input-ouput Matrix for Belgium in the year 2000. Source : OECD (2006a)]]<br />
<br />
[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] shows an example of a real input-output matrix for Belgium in the year 2000. The columns represent the destination of inputs, and the rows sum the output of a sector. <br />
As you can see, only the total outputs (last line called industry output) are shown, not the total inputs. This is because such data is not necessary since the total inputs equal the total outputs. Normally, this total appears in the last column of the table.<br />
<br />
===Practical use of Input-output tables===<br />
<br />
If we want to estimate without Input-output analysis, which additional inputs would be needed if the fishing sector increased its production by one unit, we would need to measure the following : i) first round, direct effects on the industries that supply the fishing sector with nets, boats, fishing rods etc; and ii) a range of secondary (indirect) effects, since these supplier industries themselves require additional inputs for their production, in order to meet the additional demand coming from the fishing sector production system. <br />
<br />
Fortunately, input-output matrices offer a solution to solve such problems immediately taking into account both direct as well as indirect effects. This can be particularly appreciable for assessing economic impact (both ex-ante and ex-post) of policy changes. Environmental impact can even be analyzed if we add environmental data to classical input-output tables in order to build green input-output tables. <br />
<br />
For instance, if a policy option scenario for marine pollution management (e.g. a tax on plastic industry resulting in higher plastic prices or a governmental subsidies to the production of material of substitution that are biodegradable) results in technical changes or in changes in final demand for plastics (a valuable material particularly in construction, packaging and fishing gear applications), I-O analysis can help us to deduce the following (adapted from Leontief, 1974, 193-209 pp.)<ref>'''Leontief V., 1974.''' ''Essais d’économiques.'' Ed. Calman Lévy, pp.133-157 and 193-216. Those two chapters are also available in English in : <br />
- Input-output Analysis, Input-output Economics, New York Oxford University Press, 1966;<br />
- Environmental repercussions and the Economic Structure : An Input-Output Approach, published in The Review of Economics and Statistics, Vol. LII, n°3, August 1970, Copyright by the president and Fellows of Harvard College; published as well in Robert et Nancy DORFMAN, Economics of the Environment, W.W. Norton & Co Inc, 1972.<br />
</ref> :<br />
<br />
*the policy options impact on the total level of pollution by plastic microparticles in the sea <br />
*the amount of pollution reduction in a particular sector resulting from the implementation of a policy option <br />
*the total pollution resulting from the final demand (demand from households, …) for products of each sector. For instance, keeping the example of plastic production, this means that the I-O table can tell us : “from the total amount Y of plastic pollutant in the sea, X tones are linked to agriculture, industrial and services activities contributing directly or indirectly to the supply of agricultural products to households. This is interesting since it does not only take into account the amount of pollutants from the agriculture sector for the production of agricultural products, but it also encompasses pollutants from other sectors intervening in the production of agricultural products. That is important since the agriculture sector also needs industrial products and services to generate its production. The same can be calculated for the supply of industrial products and services to households. <br />
*the impact of policy options on production level in other sectors (and so on the economy)<br />
*the impact of policy options on total employment in the region or in a particular sector<br />
*the impact of policy options on prices of goods and services<br />
<br />
===Limits of the method===<br />
<br />
The input-output (I-O) analysis is not able to capture environmental measures with a small economic impact (on GDP, on production, on employment…at national or regional level) because of data are too aggregated. Therefore, I-O is only relevant for activities having a wide economic impact such as construction of large infrastructures (railways or motorways infrastructure), modification of port activities, implementation of environmental policies targeting a whole sector, subsector or a branch of economic activities, etc. <br />
<br />
Nevertheless, I-O analysis could also be relevant for a package of several policy options, each having a relatively small impact, but whose sum results in a large impact on the regional economy.<br />
<br />
Walter Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> summarized several other limits of I-O analysis. They are mentioned below.<br />
<br />
First of all, environmental measure might affect output prices. For instance, if a governmental policy make compulsory for oil companies to install an oil desulfuration system (that prevents acid rains), the cost of this depollution system will be reflected in oil price. Hence, all products requiring oil in their fabrication process will see their price modified too (e.g.: outputs from agriculture, electricity, ferrous metals, etc.). And due to an increase in their price, the demand for each of these products will probably decrease. The modification of the demand due to price variation must be integrated into I-O models but this makes them heavier to handle because of numerous products and/or diverse response functions. In that case, dynamic model such as CGE might be more suitable.<br />
<br />
Moreover, I-O matrices give a static vision of the economy making difficult projections possibilities. However, it is possible to build dynamic I-O matrices but this is a bit more complicated. <br />
<br />
Another disadvantage is the impossibility of substitution between production factors (labour, technical capital, land) while environmental policies might precisely have a structural effect on the long run on that aspect. Let’s take the example of an environmental policy aiming at decreasing green house gases emissions by promoting research and development in energy efficiency in households. Imagine the instrument of this policy would consist in public subsidies to universities for research in building insulation new technologies. Such a measure might lead to reduction of households energy consumption and so a reduction in natural gas extraction burnt in power plants for electricity generation. In that case, the production factor “land” in the form of a natural resource (natural gas) has been partly substituted by the production factor “labour” (development of human knowledge in new insulation techniques).<br />
<br />
Furthermore, I-O tables are published by national and regional authorities with few years delay. For instance in Belgium in 2007, the last I-O table available dates from 2000. Through the delayed publishing of national I-O tables, factor relations within single sectors can be changed to a quite big extend. Such old data on the status of the economy might make I-O analysis for the subsequent years quite inaccurate. However there are techniques enabling to actualize too old I-O matrices.<br />
<br />
The last limit we would like to highlight is the need of regionalization of national I-O tables. It can happen that you find only national I-O tables while you want to work at regional level (i.e. at a smaller spatial scale). In that case you will need to apply regionalization methods which add to the difficulties.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Green accounting]]<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Regional_economic_accounting_methods&diff=11531Regional economic accounting methods2007-08-28T10:15:20Z<p>Mcordier: /* When to use regional economic accounting methodologies ? */</p>
<hr />
<div>===='''This page is a first draft'''==== <br />
(It still needs to pass through an internal and external review process) <br />
<br />
<br />
<br />
Regional economic accounting methodologies may be useful and complementary tools to cost benefit analysis (CBA) for assessing socioeconomic impact of environmental measures or environmental degradations when their indirect impacts may be of such significance and magnitude that important regional income multiplier effects may be generated.<br />
<br />
<br />
=== When to use regional economic accounting methodologies ? ===<br />
<br />
<br />
Assessing the economic impact of environmental measures or environmental degradations may be done through cost benefit analysis (CBA). However, indirect impacts on other sectors (sectors not directly targeted by the measure or not directly impacted by the degradation) often should be excluded from the analysis. When such indirect impacts are important enough to affect the economy of a region (i.e. direct economic benefits or costs result in additional or reduced economic activities in the region), regional accounting methods may be suitable and complementary to CBA. They might be applied for instance for the estimation of the indirect benefits resulting from the restoration of fish yield by reducing suspended sediment concentration in waters of a given coastal area. <br />
<br />
The resulting regional income/employment effects may be quantified through the use of [[input-output matrix]] (I-O), [[supply chain analysis]], [[computable general equilibrium]] (CGE) or [[accounts environmentally adjusted]]. It is important to mention the fact that none of these four accounting methodologies mentioned above is perfect since each present advantages and disadvantages as presented further. For instance, supply chain analysis has the disadvantage of taking into account fewer indirect impacts than I-O tables. I-O tables assume linear relations between inputs and outputs from different sectors as well as linear relations between outputs and final demand, which does not always correspond to reality. However, some have validated their input-output model with historical data and obtained some simulated results quite close to historical data (see [http://www.iioa.org/pdf/13th%20conf/Idenburg&Wilting_DMITRI.pdf Idenburg and Wilting, 2000]<ref>'''Idenburg A. M., Wilting H.C., 2000.''' ''DIMITRI : a dynamic Input-output Model to study the Impacts of technology Related Innovations.'' Paper to be presented at the WIII International Conference on Input-Output techniques, University of Macerata, Italy, August 21-25th 2000. Available on Internet : http://www.iioa.org/pdf/13th%20conf/Idenburg&Wilting_DMITRI.pdf</ref>). CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
For more details on regional accounting, follow these links :<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Green accounting]]<br />
<br />
===References===<br />
<references/><br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[:Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=11530Supply chain analysis2007-08-28T10:14:54Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
===Limits of the method===<br />
<br />
*Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
*Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
*The static aspects making difficult any projection possibilities<br />
*Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Green accounting]]<br />
<br />
<br />
<br />
===references===<br />
<br />
<References/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=11529Computable general equilibrium2007-08-28T10:14:25Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables]can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007<ref>'''Maréchal K. and Lazaric N., 2007.''' ''What Evolutionary Economics has to say about Climate Policy.'' Submitted to Journal of Evolutionary Economics.</ref>), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Green accounting]]<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Input-output_matrix&diff=11528Input-output matrix2007-08-28T10:13:56Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
<br />
An Input-output matrix is a representation of national or regional economic accounting that records the ways industries trade with one another as well as produce for consumption and investments. <br />
<br />
Input-output matrix is constructed on the simple idea that goods and services produced by economic sectors should be registered in a table simultaneously by origin and by destination [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)]<ref>'''OECD (Organisation for Economic Co-operation and Development), 2006.''' ''Input-output analysis in an increasingly globalised world: applications of OECD’s harmonized international tables.'' STI/Working paper 2006/7. Statistical analysis of Science, Technology and Industry. 31st August. Available on Internet : http://www.oecd.org/dataoecd/6/34/37349386.pdf</ref>.<br />
Commodities are produced by economic sectors (e.g. cotton produced by agriculture) and they serve as inputs in other sectors in order to produce their final products also called outputs (e.g. manufacturing industry such as textile industry using cotton from agriculture as input to produce its own output, i.e. clothes in cotton). Better said, the purchase of agricultural output by manufacturing is for use as inputs in producing manufacturing output. Such purchases are part of what is known as intermediate demand, which term refers to inter-industry transactions, i.e. goods and services bought by firms from other firms and used up in current production (this corresponds to Domestic intermediate matrix – see '''first quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]). The outputs are delivered to the final demand sector that comprises purchases by individuals for consumption, by firms for investment (in fixed capital such as machines, buildings, etc.), by government, and by foreigners (exportations) – this corresponds to the '''fourth quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] called Domestic investment matrix. The use of this terminology “final demand” simply indicates that purchases by this sector are not for the purpose of use in production (Common and Stagl, 2005)<ref>'''Common M., Stagl S., 2005'''. ''Ecological Economic. An Introduction.'' Cambridge University Press, New York, pp.125-136</ref>. In addition to intermediate inputs mentioned above, firms use also primary inputs. Those are services which are not bought from other firms but from individuals : these services are known as factors of production. These refer to wages and salaries as payments for labour services, interests paid on borrowing, rent paid for the use of equipment, building and land, profits paid for the entrepreneurship that is the function of organizing and risk-taking (Common and Stagl, 2005). – this corresponds to the '''second quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1], which is called Imported intermediate products matrix. We are not going to detail the '''third''' and the '''fifth quadrant''' here since they are not essential to the global understanding of the methodology. For more details, look at the legend of [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] or go to [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)] and read pp.7-9.<br />
<br />
[[image:Table_1_Version_4.JPG|thumb|right|[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]. Example of an Input-ouput Matrix for Belgium in the year 2000. Source : OECD (2006a)]]<br />
<br />
[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] shows an example of a real input-output matrix for Belgium in the year 2000. The columns represent the destination of inputs, and the rows sum the output of a sector. <br />
As you can see, only the total outputs (last line called industry output) are shown, not the total inputs. This is because such data is not necessary since the total inputs equal the total outputs. Normally, this total appears in the last column of the table.<br />
<br />
===Practical use of Input-output tables===<br />
<br />
If we want to estimate without Input-output analysis, which additional inputs would be needed if the fishing sector increased its production by one unit, we would need to measure the following : i) first round, direct effects on the industries that supply the fishing sector with nets, boats, fishing rods etc; and ii) a range of secondary (indirect) effects, since these supplier industries themselves require additional inputs for their production, in order to meet the additional demand coming from the fishing sector production system. <br />
<br />
Fortunately, input-output matrices offer a solution to solve such problems immediately taking into account both direct as well as indirect effects. This can be particularly appreciable for assessing economic impact (both ex-ante and ex-post) of policy changes. Environmental impact can even be analyzed if we add environmental data to classical input-output tables in order to build green input-output tables. <br />
<br />
For instance, if a policy option scenario for marine pollution management (e.g. a tax on plastic industry resulting in higher plastic prices or a governmental subsidies to the production of material of substitution that are biodegradable) results in technical changes or in changes in final demand for plastics (a valuable material particularly in construction, packaging and fishing gear applications), I-O analysis can help us to deduce the following (adapted from Leontief, 1974, 193-209 pp.)<ref>'''Leontief V., 1974.''' ''Essais d’économiques.'' Ed. Calman Lévy, 316 p.</ref> :<br />
<br />
*the policy options impact on the total level of pollution by plastic microparticles in the sea <br />
*the amount of pollution reduction in a particular sector resulting from the implementation of a policy option <br />
*the total pollution resulting from the final demand (demand from households, …) for products of each sector. For instance, keeping the example of plastic production, this means that the I-O table can tell us : “from the total amount Y of plastic pollutant in the sea, X tones are linked to agriculture, industrial and services activities contributing directly or indirectly to the supply of agricultural products to households. This is interesting since it does not only take into account the amount of pollutants from the agriculture sector for the production of agricultural products, but it also encompasses pollutants from other sectors intervening in the production of agricultural products. That is important since the agriculture sector also needs industrial products and services to generate its production. The same can be calculated for the supply of industrial products and services to households. <br />
*the impact of policy options on production level in other sectors (and so on the economy)<br />
*the impact of policy options on total employment in the region or in a particular sector<br />
*the impact of policy options on prices of goods and services<br />
<br />
===Limits of the method===<br />
<br />
The input-output (I-O) analysis is not able to capture environmental measures with a small economic impact (on GDP, on production, on employment…at national or regional level) because of data are too aggregated. Therefore, I-O is only relevant for activities having a wide economic impact such as construction of large infrastructures (railways or motorways infrastructure), modification of port activities, implementation of environmental policies targeting a whole sector, subsector or a branch of economic activities, etc. <br />
<br />
Nevertheless, I-O analysis could also be relevant for a package of several policy options, each having a relatively small impact, but whose sum results in a large impact on the regional economy.<br />
<br />
Walter Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> summarized several other limits of I-O analysis. They are mentioned below.<br />
<br />
First of all, environmental measure might affect output prices. For instance, if a governmental policy make compulsory for oil companies to install an oil desulfuration system (that prevents acid rains), the cost of this depollution system will be reflected in oil price. Hence, all products requiring oil in their fabrication process will see their price modified too (e.g.: outputs from agriculture, electricity, ferrous metals, etc.). And due to an increase in their price, the demand for each of these products will probably decrease. The modification of the demand due to price variation must be integrated into I-O models but this makes them heavier to handle because of numerous products and/or diverse response functions. In that case, dynamic model such as CGE might be more suitable.<br />
<br />
Moreover, I-O matrices give a static vision of the economy making difficult projections possibilities. However, it is possible to build dynamic I-O matrices but this is a bit more complicated. <br />
<br />
Another disadvantage is the impossibility of substitution between production factors (labour, technical capital, land) while environmental policies might precisely have a structural effect on the long run on that aspect. Let’s take the example of an environmental policy aiming at decreasing green house gases emissions by promoting research and development in energy efficiency in households. Imagine the instrument of this policy would consist in public subsidies to universities for research in building insulation new technologies. Such a measure might lead to reduction of households energy consumption and so a reduction in natural gas extraction burnt in power plants for electricity generation. In that case, the production factor “land” in the form of a natural resource (natural gas) has been partly substituted by the production factor “labour” (development of human knowledge in new insulation techniques).<br />
<br />
Furthermore, I-O tables are published by national and regional authorities with few years delay. For instance in Belgium in 2007, the last I-O table available dates from 2000. Through the delayed publishing of national I-O tables, factor relations within single sectors can be changed to a quite big extend. Such old data on the status of the economy might make I-O analysis for the subsequent years quite inaccurate. However there are techniques enabling to actualize too old I-O matrices.<br />
<br />
The last limit we would like to highlight is the need of regionalization of national I-O tables. It can happen that you find only national I-O tables while you want to work at regional level (i.e. at a smaller spatial scale). In that case you will need to apply regionalization methods which add to the difficulties.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Green accounting]]<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10695Green accounting2007-07-09T12:39:04Z<p>Mcordier: Accounts environmentally adjusted moved to Green accounting</p>
<hr />
<div>'''Page still in construction. Take care to the fact that the information given in this page is not complete at all at the moment. Will be soon actualized'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated ([http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf CBS, 2006, p. 8]<ref>'''CBS (Centraal Buureau voor de Statistiek), 2006.''' ''Present status and future developments of the Dutch NAMEA.'' Paper for the international Workshop for Interactive Analysis on Economy and Environment. March 4th, Tokyo. Available on Internet : http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf</ref>). An example is shown Tableau 3.<br />
<br />
<br />
[[image:Table 3.JPG|thumb|right|Table 3. The NAMEA matrix (shaded areas are physical accounts). CBS (2006).]]<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Accounts_environmentally_adjusted&diff=10696Accounts environmentally adjusted2007-07-09T12:39:04Z<p>Mcordier: Accounts environmentally adjusted moved to Green accounting</p>
<hr />
<div>#REDIRECT [[Green accounting]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10671Green accounting2007-07-06T09:40:47Z<p>Mcordier: </p>
<hr />
<div>'''Page still in construction. Take care to the fact that the information given in this page is not complete at all at the moment. Will be soon actualized'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated ([http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf CBS, 2006, p. 8]<ref>'''CBS (Centraal Buureau voor de Statistiek), 2006.''' ''Present status and future developments of the Dutch NAMEA.'' Paper for the international Workshop for Interactive Analysis on Economy and Environment. March 4th, Tokyo. Available on Internet : http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf</ref>). An example is shown Tableau 3.<br />
<br />
<br />
[[image:Table 3.JPG|thumb|right|Table 3. The NAMEA matrix (shaded areas are physical accounts). CBS (2006).]]<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Regional_economic_accounting_methods&diff=10660Regional economic accounting methods2007-07-04T07:58:22Z<p>Mcordier: </p>
<hr />
<div>===='''This page is a first draft'''==== <br />
(It still needs to pass through an internal and external review process) <br />
<br />
<br />
<br />
Regional economic accounting methodologies may be useful and complementary tools to cost benefit analysis (CBA) for assessing socioeconomic impact of environmental measures or environmental degradations when their indirect impacts may be of such significance and magnitude that important regional income multiplier effects may be generated.<br />
<br />
<br />
=== When to use regional economic accounting methodologies ? ===<br />
<br />
<br />
Assessing the economic impact of environmental measures or environmental degradations may be done through cost benefit analysis (CBA). However, indirect impacts on other sectors (sectors not directly targeted by the measure or not directly impacted by the degradation) often should be excluded from the analysis. When such indirect impacts are important enough to affect the economy of a region (i.e. direct economic benefits or costs result in additional or reduced economic activities in the region), regional accounting methods may be suitable and complementary to CBA. They might be applied for instance for the estimation of the indirect benefits resulting from the restoration of fish yield by reducing suspended sediment concentration in waters of a given coastal area. <br />
<br />
The resulting regional income/employment effects may be quantified through the use of [[input-output matrix]] (I-O), [[supply chain analysis]], [[computable general equilibrium]] (CGE) or [[accounts environmentally adjusted]]. It is important to mention the fact that none of these four accounting methodologies mentioned above is perfect since each present advantages and disadvantages as presented further. For instance, supply chain analysis has the disadvantage of taking into account fewer indirect impacts than I-O tables. I-O tables assume linear relations between inputs and outputs from different sectors as well as linear relations between outputs and final demand, which does not always correspond to reality. However, some have validated their input-output model with historical data and obtained some simulated results quite close to historical data (see [http://www.iioa.org/pdf/13th%20conf/Idenburg&Wilting_DMITRI.pdf Idenburg and Wilting, 2000]<ref>'''Idenburg A. M., Wilting H.C., 2000.''' ''DIMITRI : a dynamic Input-output Model to study the Impacts of technology Related Innovations.'' Paper to be presented at the WIII International Conference on Input-Output techniques, University of Macerata, Italy, August 21-25th 2000. Available on Internet : http://www.iioa.org/pdf/13th%20conf/Idenburg&Wilting_DMITRI.pdf</ref>). CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
For more details on regional accounting, follow these links :<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10659Green accounting2007-07-04T07:55:35Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated ([http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf CBS, 2006, p. 8]<ref>'''CBS (Centraal Buureau voor de Statistiek), 2006.''' ''Present status and future developments of the Dutch NAMEA.'' Paper for the international Workshop for Interactive Analysis on Economy and Environment. March 4th, Tokyo. Available on Internet : http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf</ref>). An example is shown Tableau 3.<br />
<br />
<br />
[[image:Table 3.JPG|thumb|right|Table 3. The NAMEA matrix (shaded areas are physical accounts). CBS (2006).]]<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10658Computable general equilibrium2007-07-04T07:55:04Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables]can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007<ref>'''Maréchal K. and Lazaric N., 2007.''' ''What Evolutionary Economics has to say about Climate Policy.'' Submitted to Journal of Evolutionary Economics.</ref>), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10657Supply chain analysis2007-07-04T07:54:39Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
===Limits of the method===<br />
<br />
*Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
*Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
*The static aspects making difficult any projection possibilities<br />
*Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
===references===<br />
<br />
<References/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Input-output_matrix&diff=10656Input-output matrix2007-07-04T07:54:12Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
<br />
An Input-output matrix is a representation of national or regional economic accounting that records the ways industries trade with one another as well as produce for consumption and investments. <br />
<br />
Input-output matrix is constructed on the simple idea that goods and services produced by economic sectors should be registered in a table simultaneously by origin and by destination [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)]<ref>'''OECD (Organisation for Economic Co-operation and Development), 2006.''' ''Input-output analysis in an increasingly globalised world: applications of OECD’s harmonized international tables.'' STI/Working paper 2006/7. Statistical analysis of Science, Technology and Industry. 31st August. Available on Internet : http://www.oecd.org/dataoecd/6/34/37349386.pdf</ref>.<br />
Commodities are produced by economic sectors (e.g. cotton produced by agriculture) and they serve as inputs in other sectors in order to produce their final products also called outputs (e.g. manufacturing industry such as textile industry using cotton from agriculture as input to produce its own output, i.e. clothes in cotton). Better said, the purchase of agricultural output by manufacturing is for use as inputs in producing manufacturing output. Such purchases are part of what is known as intermediate demand, which term refers to inter-industry transactions, i.e. goods and services bought by firms from other firms and used up in current production (this corresponds to Domestic intermediate matrix – see '''first quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]). The outputs are delivered to the final demand sector that comprises purchases by individuals for consumption, by firms for investment (in fixed capital such as machines, buildings, etc.), by government, and by foreigners (exportations) – this corresponds to the '''fourth quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] called Domestic investment matrix. The use of this terminology “final demand” simply indicates that purchases by this sector are not for the purpose of use in production (Common and Stagl, 2005)<ref>'''Common M., Stagl S., 2005'''. ''Ecological Economic. An Introduction.'' Cambridge University Press, New York, pp.125-136</ref>. In addition to intermediate inputs mentioned above, firms use also primary inputs. Those are services which are not bought from other firms but from individuals : these services are known as factors of production. These refer to wages and salaries as payments for labour services, interests paid on borrowing, rent paid for the use of equipment, building and land, profits paid for the entrepreneurship that is the function of organizing and risk-taking (Common and Stagl, 2005). – this corresponds to the '''second quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1], which is called Imported intermediate products matrix. We are not going to detail the '''third''' and the '''fifth quadrant''' here since they are not essential to the global understanding of the methodology. For more details, look at the legend of [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] or go to [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)] and read pp.7-9.<br />
<br />
[[image:Table_1_Version_4.JPG|thumb|right|[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]. Example of an Input-ouput Matrix for Belgium in the year 2000. Source : OECD (2006a)]]<br />
<br />
[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] shows an example of a real input-output matrix for Belgium in the year 2000. The columns represent the destination of inputs, and the rows sum the output of a sector. <br />
As you can see, only the total outputs (last line called industry output) are shown, not the total inputs. This is because such data is not necessary since the total inputs equal the total outputs. Normally, this total appears in the last column of the table.<br />
<br />
===Practical use of Input-output tables===<br />
<br />
If we want to estimate without Input-output analysis, which additional inputs would be needed if the fishing sector increased its production by one unit, we would need to measure the following : i) first round, direct effects on the industries that supply the fishing sector with nets, boats, fishing rods etc; and ii) a range of secondary (indirect) effects, since these supplier industries themselves require additional inputs for their production, in order to meet the additional demand coming from the fishing sector production system. <br />
<br />
Fortunately, input-output matrices offer a solution to solve such problems immediately taking into account both direct as well as indirect effects. This can be particularly appreciable for assessing economic impact (both ex-ante and ex-post) of policy changes. Environmental impact can even be analyzed if we add environmental data to classical input-output tables in order to build green input-output tables. <br />
<br />
For instance, if a policy option scenario for marine pollution management (e.g. a tax on plastic industry resulting in higher plastic prices or a governmental subsidies to the production of material of substitution that are biodegradable) results in technical changes or in changes in final demand for plastics (a valuable material particularly in construction, packaging and fishing gear applications), I-O analysis can help us to deduce the following (adapted from Leontief, 1974, 193-209 pp.)<ref>'''Leontief V., 1974.''' ''Essais d’économiques.'' Ed. Calman Lévy, 316 p.</ref> :<br />
<br />
*the policy options impact on the total level of pollution by plastic microparticles in the sea <br />
*the amount of pollution reduction in a particular sector resulting from the implementation of a policy option <br />
*the total pollution resulting from the final demand (demand from households, …) for products of each sector. For instance, keeping the example of plastic production, this means that the I-O table can tell us : “from the total amount Y of plastic pollutant in the sea, X tones are linked to agriculture, industrial and services activities contributing directly or indirectly to the supply of agricultural products to households. This is interesting since it does not only take into account the amount of pollutants from the agriculture sector for the production of agricultural products, but it also encompasses pollutants from other sectors intervening in the production of agricultural products. That is important since the agriculture sector also needs industrial products and services to generate its production. The same can be calculated for the supply of industrial products and services to households. <br />
*the impact of policy options on production level in other sectors (and so on the economy)<br />
*the impact of policy options on total employment in the region or in a particular sector<br />
*the impact of policy options on prices of goods and services<br />
<br />
===Limits of the method===<br />
<br />
The input-output (I-O) analysis is not able to capture environmental measures with a small economic impact (on GDP, on production, on employment…at national or regional level) because of data are too aggregated. Therefore, I-O is only relevant for activities having a wide economic impact such as construction of large infrastructures (railways or motorways infrastructure), modification of port activities, implementation of environmental policies targeting a whole sector, subsector or a branch of economic activities, etc. <br />
<br />
Nevertheless, I-O analysis could also be relevant for a package of several policy options, each having a relatively small impact, but whose sum results in a large impact on the regional economy.<br />
<br />
Walter Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> summarized several other limits of I-O analysis. They are mentioned below.<br />
<br />
First of all, environmental measure might affect output prices. For instance, if a governmental policy make compulsory for oil companies to install an oil desulfuration system (that prevents acid rains), the cost of this depollution system will be reflected in oil price. Hence, all products requiring oil in their fabrication process will see their price modified too (e.g.: outputs from agriculture, electricity, ferrous metals, etc.). And due to an increase in their price, the demand for each of these products will probably decrease. The modification of the demand due to price variation must be integrated into I-O models but this makes them heavier to handle because of numerous products and/or diverse response functions. In that case, dynamic model such as CGE might be more suitable.<br />
<br />
Moreover, I-O matrices give a static vision of the economy making difficult projections possibilities. However, it is possible to build dynamic I-O matrices but this is a bit more complicated. <br />
<br />
Another disadvantage is the impossibility of substitution between production factors (labour, technical capital, land) while environmental policies might precisely have a structural effect on the long run on that aspect. Let’s take the example of an environmental policy aiming at decreasing green house gases emissions by promoting research and development in energy efficiency in households. Imagine the instrument of this policy would consist in public subsidies to universities for research in building insulation new technologies. Such a measure might lead to reduction of households energy consumption and so a reduction in natural gas extraction burnt in power plants for electricity generation. In that case, the production factor “land” in the form of a natural resource (natural gas) has been partly substituted by the production factor “labour” (development of human knowledge in new insulation techniques).<br />
<br />
Furthermore, I-O tables are published by national and regional authorities with few years delay. For instance in Belgium in 2007, the last I-O table available dates from 2000. Through the delayed publishing of national I-O tables, factor relations within single sectors can be changed to a quite big extend. Such old data on the status of the economy might make I-O analysis for the subsequent years quite inaccurate. However there are techniques enabling to actualize too old I-O matrices.<br />
<br />
The last limit we would like to highlight is the need of regionalization of national I-O tables. It can happen that you find only national I-O tables while you want to work at regional level (i.e. at a smaller spatial scale). In that case you will need to apply regionalization methods which add to the difficulties.<br />
<br />
===Other [[regional economic accounting methods]]===<br />
<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Input-output_matrix&diff=10655Input-output matrix2007-07-04T07:53:22Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
<br />
An Input-output matrix is a representation of national or regional economic accounting that records the ways industries trade with one another as well as produce for consumption and investments. <br />
<br />
Input-output matrix is constructed on the simple idea that goods and services produced by economic sectors should be registered in a table simultaneously by origin and by destination [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)]<ref>'''OECD (Organisation for Economic Co-operation and Development), 2006.''' ''Input-output analysis in an increasingly globalised world: applications of OECD’s harmonized international tables.'' STI/Working paper 2006/7. Statistical analysis of Science, Technology and Industry. 31st August. Available on Internet : http://www.oecd.org/dataoecd/6/34/37349386.pdf</ref>.<br />
Commodities are produced by economic sectors (e.g. cotton produced by agriculture) and they serve as inputs in other sectors in order to produce their final products also called outputs (e.g. manufacturing industry such as textile industry using cotton from agriculture as input to produce its own output, i.e. clothes in cotton). Better said, the purchase of agricultural output by manufacturing is for use as inputs in producing manufacturing output. Such purchases are part of what is known as intermediate demand, which term refers to inter-industry transactions, i.e. goods and services bought by firms from other firms and used up in current production (this corresponds to Domestic intermediate matrix – see '''first quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]). The outputs are delivered to the final demand sector that comprises purchases by individuals for consumption, by firms for investment (in fixed capital such as machines, buildings, etc.), by government, and by foreigners (exportations) – this corresponds to the '''fourth quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] called Domestic investment matrix. The use of this terminology “final demand” simply indicates that purchases by this sector are not for the purpose of use in production (Common and Stagl, 2005)<ref>'''Common M., Stagl S., 2005'''. ''Ecological Economic. An Introduction.'' Cambridge University Press, New York, pp.125-136</ref>. In addition to intermediate inputs mentioned above, firms use also primary inputs. Those are services which are not bought from other firms but from individuals : these services are known as factors of production. These refer to wages and salaries as payments for labour services, interests paid on borrowing, rent paid for the use of equipment, building and land, profits paid for the entrepreneurship that is the function of organizing and risk-taking (Common and Stagl, 2005). – this corresponds to the '''second quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1], which is called Imported intermediate products matrix. We are not going to detail the '''third''' and the '''fifth quadrant''' here since they are not essential to the global understanding of the methodology. For more details, look at the legend of [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] or go to [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)] and read pp.7-9.<br />
<br />
[[image:Table_1_Version_4.JPG|thumb|right|[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]. Example of an Input-ouput Matrix for Belgium in the year 2000. Source : OECD (2006a)]]<br />
<br />
[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] shows an example of a real input-output matrix for Belgium in the year 2000. The columns represent the destination of inputs, and the rows sum the output of a sector. <br />
As you can see, only the total outputs (last line called industry output) are shown, not the total inputs. This is because such data is not necessary since the total inputs equal the total outputs. Normally, this total appears in the last column of the table.<br />
<br />
===Practical use of Input-output tables===<br />
<br />
If we want to estimate without Input-output analysis, which additional inputs would be needed if the fishing sector increased its production by one unit, we would need to measure the following : i) first round, direct effects on the industries that supply the fishing sector with nets, boats, fishing rods etc; and ii) a range of secondary (indirect) effects, since these supplier industries themselves require additional inputs for their production, in order to meet the additional demand coming from the fishing sector production system. <br />
<br />
Fortunately, input-output matrices offer a solution to solve such problems immediately taking into account both direct as well as indirect effects. This can be particularly appreciable for assessing economic impact (both ex-ante and ex-post) of policy changes. Environmental impact can even be analyzed if we add environmental data to classical input-output tables in order to build green input-output tables. <br />
<br />
For instance, if a policy option scenario for marine pollution management (e.g. a tax on plastic industry resulting in higher plastic prices or a governmental subsidies to the production of material of substitution that are biodegradable) results in technical changes or in changes in final demand for plastics (a valuable material particularly in construction, packaging and fishing gear applications), I-O analysis can help us to deduce the following (adapted from Leontief, 1974, 193-209 pp.)<ref>'''Leontief V., 1974.''' ''Essais d’économiques.'' Ed. Calman Lévy, 316 p.</ref> :<br />
<br />
*the policy options impact on the total level of pollution by plastic microparticles in the sea <br />
*the amount of pollution reduction in a particular sector resulting from the implementation of a policy option <br />
*the total pollution resulting from the final demand (demand from households, …) for products of each sector. For instance, keeping the example of plastic production, this means that the I-O table can tell us : “from the total amount Y of plastic pollutant in the sea, X tones are linked to agriculture, industrial and services activities contributing directly or indirectly to the supply of agricultural products to households. This is interesting since it does not only take into account the amount of pollutants from the agriculture sector for the production of agricultural products, but it also encompasses pollutants from other sectors intervening in the production of agricultural products. That is important since the agriculture sector also needs industrial products and services to generate its production. The same can be calculated for the supply of industrial products and services to households. <br />
*the impact of policy options on production level in other sectors (and so on the economy)<br />
*the impact of policy options on total employment in the region or in a particular sector<br />
*the impact of policy options on prices of goods and services<br />
<br />
===Limits of the method===<br />
<br />
The input-output (I-O) analysis is not able to capture environmental measures with a small economic impact (on GDP, on production, on employment…at national or regional level) because of data are too aggregated. Therefore, I-O is only relevant for activities having a wide economic impact such as construction of large infrastructures (railways or motorways infrastructure), modification of port activities, implementation of environmental policies targeting a whole sector, subsector or a branch of economic activities, etc. <br />
<br />
Nevertheless, I-O analysis could also be relevant for a package of several policy options, each having a relatively small impact, but whose sum results in a large impact on the regional economy.<br />
<br />
Walter Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> summarized several other limits of I-O analysis. They are mentioned below.<br />
<br />
First of all, environmental measure might affect output prices. For instance, if a governmental policy make compulsory for oil companies to install an oil desulfuration system (that prevents acid rains), the cost of this depollution system will be reflected in oil price. Hence, all products requiring oil in their fabrication process will see their price modified too (e.g.: outputs from agriculture, electricity, ferrous metals, etc.). And due to an increase in their price, the demand for each of these products will probably decrease. The modification of the demand due to price variation must be integrated into I-O models but this makes them heavier to handle because of numerous products and/or diverse response functions. In that case, dynamic model such as CGE might be more suitable.<br />
<br />
Moreover, I-O matrices give a static vision of the economy making difficult projections possibilities. However, it is possible to build dynamic I-O matrices but this is a bit more complicated. <br />
<br />
Another disadvantage is the impossibility of substitution between production factors (labour, technical capital, land) while environmental policies might precisely have a structural effect on the long run on that aspect. Let’s take the example of an environmental policy aiming at decreasing green house gases emissions by promoting research and development in energy efficiency in households. Imagine the instrument of this policy would consist in public subsidies to universities for research in building insulation new technologies. Such a measure might lead to reduction of households energy consumption and so a reduction in natural gas extraction burnt in power plants for electricity generation. In that case, the production factor “land” in the form of a natural resource (natural gas) has been partly substituted by the production factor “labour” (development of human knowledge in new insulation techniques).<br />
<br />
Furthermore, I-O tables are published by national and regional authorities with few years delay. For instance in Belgium in 2007, the last I-O table available dates from 2000. Through the delayed publishing of national I-O tables, factor relations within single sectors can be changed to a quite big extend. Such old data on the status of the economy might make I-O analysis for the subsequent years quite inaccurate. However there are techniques enabling to actualize too old I-O matrices.<br />
<br />
The last limit we would like to highlight is the need of regionalization of national I-O tables. It can happen that you find only national I-O tables while you want to work at regional level (i.e. at a smaller spatial scale). In that case you will need to apply regionalization methods which add to the difficulties.<br />
<br />
===Other [[Regional economic accounting methods]]===<br />
<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}<br />
[[Category:Theme_1]]<br />
[[Category:Tools & Methodologies]]</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10443Green accounting2007-06-19T11:39:40Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated ([http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf CBS, 2006, p. 8]<ref>'''CBS (Centraal Buureau voor de Statistiek), 2006.''' ''Present status and future developments of the Dutch NAMEA.'' Paper for the international Workshop for Interactive Analysis on Economy and Environment. March 4th, Tokyo. Available on Internet : http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf</ref>). An example is shown Tableau 3.<br />
<br />
<br />
[[image:Table 3.JPG|thumb|right|Table 3. The NAMEA matrix (shaded areas are physical accounts). CBS (2006).]]<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=File:Table_3.JPG&diff=10440File:Table 3.JPG2007-06-19T11:37:17Z<p>Mcordier: </p>
<hr />
<div></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10436Green accounting2007-06-19T11:23:00Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated ([http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf CBS, 2006, p. 8]<ref>'''CBS (Centraal Buureau voor de Statistiek), 2006.''' ''Present status and future developments of the Dutch NAMEA.'' Paper for the international Workshop for Interactive Analysis on Economy and Environment. March 4th, Tokyo. Available on Internet : http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf</ref>). An example is shown Tableau 3.<br />
<br />
<br />
[[image: .jpg]]<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10435Green accounting2007-06-19T11:21:38Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated ([http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf CBS, 2006]<ref>'''CBS (Centraal Buureau voor de Statistiek), 2006.''' ''Present status and future developments of the Dutch NAMEA.'' Paper for the international Workshop for Interactive Analysis on Economy and Environment. March 4th, Tokyo. Available on Internet : http://www.esri.go.jp/jp/archive/hou/hou020/hou20-2b-1.pdf</ref>). An example is shown Tableau 3.<br />
<br />
<br />
[[image: .jpg]]<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10433Green accounting2007-06-19T11:05:23Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated (CBS, 2006). An example is shown Tableau 3.<br />
<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Green_accounting&diff=10431Green accounting2007-06-19T11:01:44Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Accounts environmentally adjusted has resulted from the necessity to modify the worldwide System of National Accounts (SNA) for calculating Gross Domestic Product (GDP), economic growth over time and other related aggregate measures in order to better reflect natural resources depletion and environmental degradation (O’Connor et al., 2001). That is why since 1980s, there were attempts to correct SNA to take full account of the depletion of natural resources and the deterioration of environmental functions. This led to accounts environmentally adjusted. This methodology can be complementary to I-O analysis and CGE since it can serve to greening I-O tables with the aim to use them for economic assessment of environmental policy options.<br />
<br />
Accounts environmentally adjusted can be grouped under three main approaches even though these methods are often very closely interlinked and built upon each other ([http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf O’Connor et al., 2001]<ref>'''O’Connor M., Steurer A., Tamborra M., 2001.''' ''Greening National Accounts.'' Environmental Valuation Europe. Policy Research Brief Number 9. Cambridge Research for the Environment, 24 p. Available on Internet : http://kerbabel.c3ed.uvsq.fr/_Documents/CACT-FIC-DICT-C3ED-MOC-20010301-00001.pdf</ref>): <br />
<br />
a) National Accounts Matrix including Environmental Accounts (NAMEA) :<br />
<br />
The basic principle of the NAMEA, also called Directly Expanded National Accounts, is to directly expand national accounts with environmental information in physical or monetary units, or both. This allows us tracing back the origin of the environmental pressures to industrial branches responsible for it as well as allocating pressures to final demand categories (e.g. to household consumption) using input–output analysis. <br />
<br />
In the NAMEA, a link has been established between the national accounts and environmental statistics. By doing so, NAMEA reveals the interrelation between macro-indicators for the economy (net domestic product, net saving, external balance etc.) and the environment. The NAMEA can function as an instrument for all kinds of analysis. For example, the direct and indirect environmental effects of consumption or export of certain products can be demonstrated (CBS, 2006). An example is shown Tableau 3.</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10427Computable general equilibrium2007-06-19T10:58:45Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables]can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007<ref>'''Maréchal K. and Lazaric N., 2007.''' ''What Evolutionary Economics has to say about Climate Policy.'' Submitted to Journal of Evolutionary Economics.</ref>), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10426Computable general equilibrium2007-06-19T10:57:08Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables]can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007<ref>'''Maréchal K. and Lazaric N., 2007.''' ''What Evolutionary Economics has to say about Climate Policy.'' Submitted to Journal of Evolutionary Economics.</ref>), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10425Computable general equilibrium2007-06-19T10:56:29Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables]can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007<ref>'''Maréchal K. and N. Lazaric, 2007.''' ''What Evolutionary Economics has to say about Climate Policy.'' Submitted to Journal of Evolutionary Economics.</ref>), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10424Computable general equilibrium2007-06-19T10:55:04Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables]can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10423Computable general equilibrium2007-06-19T10:53:44Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] (I-O) or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. [http://www.encora.eu/coastalwiki/Input-output_matrix I-O tables] can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10422Computable general equilibrium2007-06-19T10:51:56Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[Regional economic accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10421Computable general equilibrium2007-06-19T10:51:08Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “[[regional accounting methods]] by [[Input-output matrix]]”). Usually the database is presented as an [[Input-output matrix]] or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10420Computable general equilibrium2007-06-19T10:49:43Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
::Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
::Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10419Computable general equilibrium2007-06-19T10:49:11Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
**Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
**Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10417Computable general equilibrium2007-06-19T10:48:17Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10416Supply chain analysis2007-06-19T10:47:59Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
===Limits of the method===<br />
<br />
*Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
*Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
*The static aspects making difficult any projection possibilities<br />
*Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
===references===<br />
<br />
<References/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10414Computable general equilibrium2007-06-19T10:46:37Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
*Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
*Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
===Practical use of CGE models===<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
===Limits of the method===<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
#non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
#imperfect competition (e.g. monopoly pricing) <br />
#demands not influenced by price (e.g. government demands) <br />
#a range of taxes <br />
#externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===references===<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10412Computable general equilibrium2007-06-19T10:45:15Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===references===<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10408Computable general equilibrium2007-06-19T10:44:22Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004)<ref>'''Böhringer C., 2004.''' ''Sustainability impact assessment : the use of computable general equilibrium models.'' Economie internationale 2004/3, n° 99, pp. 9-26.</ref>.<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a) categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===references===<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10406Computable general equilibrium2007-06-19T10:43:29Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004).<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a) categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===references===<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10403Computable general equilibrium2007-06-19T10:39:59Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985)<ref>'''Pyatt and Round, 1985.''' ''Social Accounting Matrices: A Basis for Planning.'' The World Bank.</ref>.<br />
<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004).<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a) categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===references===<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10400Computable general equilibrium2007-06-19T10:38:45Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985).<br />
<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004).<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a) categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.<br />
<br />
===references===<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10399Computable general equilibrium2007-06-19T10:38:06Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
#Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from [http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT) Eurostat] (consulted in January 2007)<ref>'''EUROSTAT, consulted in January 2007.''' ''ESA 95 Input-Output tables.'' Available on Internet : http://epp.eurostat.ec.europa.eu/portal/page?_pageid=2474,54156821,2474_54764840&_dad=portal&_schema=PORTAL#IOT)</ref>, from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985).<br />
<br />
#Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004).<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a) categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Computable_general_equilibrium&diff=10395Computable general equilibrium2007-06-19T10:34:24Z<p>Mcordier: </p>
<hr />
<div>'''First draft'''<br />
<br />
Computable general equilibrium (CGE) models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors. The word « equilibrium » means that values taken by endogenous variables in the model allow the resolution of all equations. CGE models are descended from the input-output models pioneered by Wassily Leontief, but assign a more important role to prices. Thus, where Leontief assumed that, say, a fixed amount of labour was required to produce a ton of iron, a CGE model would normally allow wage levels to (negatively) affect labour demands. One of the main interests of CGE models is their dynamic characteristic enabling to make projections up to 100 years.<br />
<br />
A CGE model consists of (a) equations describing model variables and (b) a database (usually very detailed) consistent with the model equations. Data required are the following :<br />
<br />
1. Tables of transaction values, showing, for example, the value of coal used by the iron industry (read the section above “regional accounting by matrix Input-output”). Usually the database is presented as an input-output table or as a social accounting matrix (SAM). In either case, it covers the whole economy of a country (or even the whole world), and distinguishes a number of sectors, commodities, primary factors and perhaps types of household. I-O tables can be taken from Eurostat (consulted in January 2007), from the national statistic of the studied country or from the governmental (or regional) economic department. For more details on SAM, read Pyatt and Round (1985).<br />
<br />
2. Elasticities: dimensionless parameters that capture behavioural response to policy scenarios. For example, export demand elasticities specify by how much export volumes might fall if export prices went up (e.g. due to a tax on green house gas emitted by merchandise transportation). Data on elasticities are usually taken from literature survey (Böhringer, 2004).<br />
<br />
Nowadays, CGE models are made of thousands of equations. They can give simulations till 100 years time horizon and have regional, national and international spatial dimensions. Hecq (2006a) categorized those models by economical mechanisms, and identified four categories described below. They can be divided into two families : "bottom-up" et "top-down".<br />
<br />
Bottom-up models are built on a detailed representation of productive system (supply side) and demand (demand side). Based on data on cost and effectiveness of technologies as well as on basic resources utilization such as energy, they calculate minimum cost strategies. Their weakness stems from the translation of feedback in term of macroeconomic equilibrium.<br />
<br />
Example of bottom-up model : Technological optimization models (MARKAL, DNE21+, GMM, MESSAGE,…). They are based on technological data for each sector of a country. They model energetic demand taking into account technical constrains. They allow us to highlight optimal technological options (cost-effectiveness) in order to achieve environmental targets at diverse horizons (e.g. CO2 emissions).<br />
<br />
Top-down models describe the economic system in a global way through aggregates and their interrelations in the frame of a general equilibrium built on the base of microeconomic theory.<br />
<br />
Example of top-down model : Macroeconometric models (NEMESIS, E3MG, HERMES, etc.). They are numerous and are more developed and accurate than the previous models mentioned above. However, they are neo-Keynesians. Therefore, they operate according to the demand in the economy, which is not always in equilibrium with the supply (structural unemployment is possible to take into account in those models). In addition, production functions are stemming from econometric techniques based on historical series that affect their structure. <br />
<br />
Practical use of CGE models<br />
<br />
Though models are still subject to discussions, they find numerous applications (simulation, prevision, research) among others evaluation of environmental policies impacts such as taxes on CO2/energy and polluting emissions trading schemes. CGE are relevant when willing to evaluate the economic implications of policy intervention on resource allocation and incomes of agents (for example, a tax on energy and green house gas emissions might affect fuel prices, the consumer price index, and hence perhaps wages and employment). For instance a relevant question to be answered by CGE would be “what is the optimal tax policy to maximize economic performance given minimum constraints on the level of environmental quality or distributional concerns.”<br />
<br />
Since CGE are partly based on I-O tables, what is written above in section “regional accounting by matrix Input-output” applies also to CGE. See there for additional information concerning relevancy of CGE.<br />
<br />
Limits of the method<br />
<br />
CGE models are complex to implement and their results are highly dependents on key economic parameters on which remain uncertainties. In addition, those models are expensive and time consuming (it takes months to years to build a CGE model).<br />
<br />
In addition, the model equations tend to be built upon an underlying theory (i.e. traditional economics, as defined by Maréchal and Lazaric, 2007), often assuming cost-minimizing behaviour by producers, average-cost pricing, and household demands based on optimizing behaviour. However, most CGE models conform only loosely to the theoretical general equilibrium paradigm. For example, they may allow for:<br />
<br />
1. non-market clearing (general equilibrium is not reached : supply is not equal to demand), especially for labour (unemployment) or for commodities (inventories) <br />
2. imperfect competition (e.g. monopoly pricing) <br />
3. demands not influenced by price (e.g. government demands) <br />
4. a range of taxes <br />
5. externalities, such as pollution<br />
<br />
However, even with these corrections to match more the economic reality, Maréchal and Lazaric (2007) estimate that the use of CGE models is highly disputable because of their inadequate account of the real behaviour of economic agents. Indeed, CGE models are built upon a traditional economics that has been strongly questioned by scholars from different fields. For instance, the Homo Oeconomicus paradigm is completely at odds with empirical evidence contained in studies showing that economic decisions are partly guided by feelings and thus emotionally coloured (providing human beings with "intelligent emotions and emotional intelligence"). An individual is not able to make optimal decisions in order to reach its goals. He can only make satisfactory decisions because he is limited by its capacity, its habits and unconscious reflexes; its values and concepts of the goal to reach (which can even be different from the goal decided by the enterprise); and by its knowledge and the imperfect information he has access to. Not grasping this, is a major drawback of CGE models.<br />
<br />
Lastly, CGE, similarly to I-O tables, are not able to take into account issues with small impacts because of their too high aggregation level.</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10394Supply chain analysis2007-06-19T10:33:40Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
===Limits of the method===<br />
<br />
*Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
*Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
*The static aspects making difficult any projection possibilities<br />
*Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Input-output matrix]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
===references===<br />
<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Input-output_matrix&diff=10393Input-output matrix2007-06-19T10:32:40Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
<br />
An Input-output matrix is a representation of national or regional economic accounting that records the ways industries trade with one another as well as produce for consumption and investments. <br />
<br />
Input-output matrix is constructed on the simple idea that goods and services produced by economic sectors should be registered in a table simultaneously by origin and by destination [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)]<ref>'''OECD (Organisation for Economic Co-operation and Development), 2006.''' ''Input-output analysis in an increasingly globalised world: applications of OECD’s harmonized international tables.'' STI/Working paper 2006/7. Statistical analysis of Science, Technology and Industry. 31st August. Available on Internet : http://www.oecd.org/dataoecd/6/34/37349386.pdf</ref>.<br />
Commodities are produced by economic sectors (e.g. cotton produced by agriculture) and they serve as inputs in other sectors in order to produce their final products also called outputs (e.g. manufacturing industry such as textile industry using cotton from agriculture as input to produce its own output, i.e. clothes in cotton). Better said, the purchase of agricultural output by manufacturing is for use as inputs in producing manufacturing output. Such purchases are part of what is known as intermediate demand, which term refers to inter-industry transactions, i.e. goods and services bought by firms from other firms and used up in current production (this corresponds to Domestic intermediate matrix – see '''first quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]). The outputs are delivered to the final demand sector that comprises purchases by individuals for consumption, by firms for investment (in fixed capital such as machines, buildings, etc.), by government, and by foreigners (exportations) – this corresponds to the '''fourth quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] called Domestic investment matrix. The use of this terminology “final demand” simply indicates that purchases by this sector are not for the purpose of use in production (Common and Stagl, 2005)<ref>'''Common M., Stagl S., 2005'''. ''Ecological Economic. An Introduction.'' Cambridge University Press, New York, pp.125-136</ref>. In addition to intermediate inputs mentioned above, firms use also primary inputs. Those are services which are not bought from other firms but from individuals : these services are known as factors of production. These refer to wages and salaries as payments for labour services, interests paid on borrowing, rent paid for the use of equipment, building and land, profits paid for the entrepreneurship that is the function of organizing and risk-taking (Common and Stagl, 2005). – this corresponds to the '''second quadrant''' in [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1], which is called Imported intermediate products matrix. We are not going to detail the '''third''' and the '''fifth quadrant''' here since they are not essential to the global understanding of the methodology. For more details, look at the legend of [http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] or go to [http://www.oecd.org/dataoecd/6/34/37349386.pdf (OECD, 2006)] and read pp.7-9.<br />
<br />
[[image:Table_1_Version_4.JPG|thumb|right|[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1]. Example of an Input-ouput Matrix for Belgium in the year 2000. Source : OECD (2006a)]]<br />
<br />
[http://dev.ulb.ac.be/~sameyer/CEESE/documents/Table%201.pdf Table 1] shows an example of a real input-output matrix for Belgium in the year 2000. The columns represent the destination of inputs, and the rows sum the output of a sector. <br />
As you can see, only the total outputs (last line called industry output) are shown, not the total inputs. This is because such data is not necessary since the total inputs equal the total outputs. Normally, this total appears in the last column of the table.<br />
<br />
===Practical use of Input-output tables===<br />
<br />
If we want to estimate without Input-output analysis, which additional inputs would be needed if the fishing sector increased its production by one unit, we would need to measure the following : i) first round, direct effects on the industries that supply the fishing sector with nets, boats, fishing rods etc; and ii) a range of secondary (indirect) effects, since these supplier industries themselves require additional inputs for their production, in order to meet the additional demand coming from the fishing sector production system. <br />
<br />
Fortunately, input-output matrices offer a solution to solve such problems immediately taking into account both direct as well as indirect effects. This can be particularly appreciable for assessing economic impact (both ex-ante and ex-post) of policy changes. Environmental impact can even be analyzed if we add environmental data to classical input-output tables in order to build green input-output tables. <br />
<br />
For instance, if a policy option scenario for marine pollution management (e.g. a tax on plastic industry resulting in higher plastic prices or a governmental subsidies to the production of material of substitution that are biodegradable) results in technical changes or in changes in final demand for plastics (a valuable material particularly in construction, packaging and fishing gear applications), I-O analysis can help us to deduce the following (adapted from Leontief, 1974, 193-209 pp.)<ref>'''Leontief V., 1974.''' ''Essais d’économiques.'' Ed. Calman Lévy, 316 p.</ref> :<br />
<br />
*the policy options impact on the total level of pollution by plastic microparticles in the sea <br />
*the amount of pollution reduction in a particular sector resulting from the implementation of a policy option <br />
*the total pollution resulting from the final demand (demand from households, …) for products of each sector. For instance, keeping the example of plastic production, this means that the I-O table can tell us : “from the total amount Y of plastic pollutant in the sea, X tones are linked to agriculture, industrial and services activities contributing directly or indirectly to the supply of agricultural products to households. This is interesting since it does not only take into account the amount of pollutants from the agriculture sector for the production of agricultural products, but it also encompasses pollutants from other sectors intervening in the production of agricultural products. That is important since the agriculture sector also needs industrial products and services to generate its production. The same can be calculated for the supply of industrial products and services to households. <br />
*the impact of policy options on production level in other sectors (and so on the economy)<br />
*the impact of policy options on total employment in the region or in a particular sector<br />
*the impact of policy options on prices of goods and services<br />
<br />
===Limits of the method===<br />
<br />
The input-output (I-O) analysis is not able to capture environmental measures with a small economic impact (on GDP, on production, on employment…at national or regional level) because of data are too aggregated. Therefore, I-O is only relevant for activities having a wide economic impact such as construction of large infrastructures (railways or motorways infrastructure), modification of port activities, implementation of environmental policies targeting a whole sector, subsector or a branch of economic activities, etc. <br />
<br />
Nevertheless, I-O analysis could also be relevant for a package of several policy options, each having a relatively small impact, but whose sum results in a large impact on the regional economy.<br />
<br />
Walter Hecq (2006a)<ref>'''Hecq W., 2006a.''' ''Aspects économiques de l’environnement. Fascicule 4. Economie de l’environnement.'' Université Libre de Bruxelles, 12ème édition, P.U.B.</ref> summarized several other limits of I-O analysis. They are mentioned below.<br />
<br />
First of all, environmental measure might affect output prices. For instance, if a governmental policy make compulsory for oil companies to install an oil desulfuration system (that prevents acid rains), the cost of this depollution system will be reflected in oil price. Hence, all products requiring oil in their fabrication process will see their price modified too (e.g.: outputs from agriculture, electricity, ferrous metals, etc.). And due to an increase in their price, the demand for each of these products will probably decrease. The modification of the demand due to price variation must be integrated into I-O models but this makes them heavier to handle because of numerous products and/or diverse response functions. In that case, dynamic model such as CGE might be more suitable.<br />
<br />
Moreover, I-O matrices give a static vision of the economy making difficult projections possibilities. However, it is possible to build dynamic I-O matrices but this is a bit more complicated. <br />
<br />
Another disadvantage is the impossibility of substitution between production factors (labour, technical capital, land) while environmental policies might precisely have a structural effect on the long run on that aspect. Let’s take the example of an environmental policy aiming at decreasing green house gases emissions by promoting research and development in energy efficiency in households. Imagine the instrument of this policy would consist in public subsidies to universities for research in building insulation new technologies. Such a measure might lead to reduction of households energy consumption and so a reduction in natural gas extraction burnt in power plants for electricity generation. In that case, the production factor “land” in the form of a natural resource (natural gas) has been partly substituted by the production factor “labour” (development of human knowledge in new insulation techniques).<br />
<br />
Furthermore, I-O tables are published by national and regional authorities with few years delay. For instance in Belgium in 2007, the last I-O table available dates from 2000. Through the delayed publishing of national I-O tables, factor relations within single sectors can be changed to a quite big extend. Such old data on the status of the economy might make I-O analysis for the subsequent years quite inaccurate. However there are techniques enabling to actualize too old I-O matrices.<br />
<br />
The last limit we would like to highlight is the need of regionalization of national I-O tables. It can happen that you find only national I-O tables while you want to work at regional level (i.e. at a smaller spatial scale). In that case you will need to apply regionalization methods which add to the difficulties.<br />
<br />
===Other regional accounting methods===<br />
<br />
<br />
*[[Supply chain analysis]]<br />
<br />
*[[Computable general equilibrium]]<br />
<br />
*[[Accounts environmentally adjusted]]<br />
<br />
<br />
<br />
===References===<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10390Supply chain analysis2007-06-19T10:31:18Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
===Limits of the method===<br />
<br />
*Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
*Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
*The static aspects making difficult any projection possibilities<br />
*Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/><br />
<br />
<br />
{{author <br />
|AuthorID=13756 <br />
|AuthorName= Mateo Cordier, Walter Hecq - Centre d'Etudes Economiques et Sociales de l'Université Libre de Bruxelles (CEESE-ULB)}}</div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10389Supply chain analysis2007-06-19T10:29:16Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
===Limits of the method===<br />
<br />
*Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
*Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
*The static aspects making difficult any projection possibilities<br />
*Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10388Supply chain analysis2007-06-19T10:28:17Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
Limits of the method<br />
<br />
o Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
o Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
o The static aspects making difficult any projection possibilities<br />
o Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10387Supply chain analysis2007-06-19T10:27:38Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [[computable general equilibrium]], [[input-output matrix]] and [[Accounts environmentally adjusted]], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
Limits of the method<br />
<br />
o Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
o Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
o The static aspects making difficult any projection possibilities<br />
o Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10386Supply chain analysis2007-06-19T10:26:41Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [computable general equilibrium], [input-output matrix] and [Accounts environmentally adjusted], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
Limits of the method<br />
<br />
o Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
o Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
o The static aspects making difficult any projection possibilities<br />
o Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10384Supply chain analysis2007-06-19T10:22:14Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
===Practical use of supply chain analysis ===<br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than [CGE], [Input Output] analysis and [Accounts environmentally adjusted], since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
Limits of the method<br />
<br />
o Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
o Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
o The static aspects making difficult any projection possibilities<br />
o Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10383Supply chain analysis2007-06-19T10:19:45Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005b'''. ''FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices.'' Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>'''FAO (Food and Agriculture Organization of the United Nations), 2005c.''' ''EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price.'' Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
Practical use of supply chain analysis <br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than CGE, I-O analysis and Accounts environmentally adjusted, since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
Limits of the method<br />
<br />
o Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
o Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
o The static aspects making difficult any projection possibilities<br />
o Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordierhttps://www.coastalwiki.org/w/index.php?title=Supply_chain_analysis&diff=10382Supply chain analysis2007-06-19T10:16:07Z<p>Mcordier: </p>
<hr />
<div>'''This page is a first draft'''<br />
<br />
Supply chain analysis consists in a quantitative analysis of inputs and outputs between firms, prices and value added along a supply chain through agent accounts. These inputs and outputs can be expressed in physical flows of material and services needed to manufacture a final product as well as in their monetary equivalents). The term Supply Chain analysis is used to refer to the overall group of economic agents (a physical person such as a farmer, a trader or a consumer, as well as legal entities such as a business, an authority or a development organisation) that contribute directly to the determination of a final product. Thus the chain encompasses the complete sequence of operations which, starting from the raw material, or an intermediate product, finishes downstream, after several stages of transformation or increases in value, at one or several final products at the level of the consumer ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf Food and Agriculture Organization of the United Nations, 2005a]<ref>'''FAO (Food and Agriculture Organization of the United Nations) , 2005a.''' ''Commodity Chain Analysis. Constructing the Commodity Chain Functional Analysis and Flow Charts.'' EASYPol, On-line resource materials for policy marking, Module 043. Available on Internet : http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf</ref>). <br />
<br />
Building a supply chain analysis requires to spend time in the followings tasks (see example figure 2 [[image:Figure 2 bis bis.JPG|thumb|right|Figure 2. Example of a flowshart showing flows of material in physical and monetary terms through a paddy and rice production chain ([http://www.fao.org/docs/up/easypol/330/cca_043EN.pdf FAO, 2005a, p. 15])]]):<br />
<br />
#Mapping the chain (through a flowchart) to obtain an overview of the chain, the product flows, the position of the chain actors and type of interaction between the actors. <br />
<br />
#Developing the economic accounts corresponding to the activities of the agents involved in the chain. This consists in quantifying the activities observed and their flow of material both in physical and in monetary terms. This allows the analyst to assess the relative importance of the different segments or sub-chains of the chain, which in turn will allow an appropriate use of time and resources. For more details on how building economic accounts, read FAO ([http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf 2005b]<ref>Food and Agriculture Organization of the United Nations (FAO), 2005b. FEASYPol Module 045. Commodity Chain Analysis: Impact Analysis Using Market Prices. Available on Internet: http://www.fao.org/docs/up/easypol//332/CCA_045EN.pdf</ref> and [http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf 2005c]<ref>Food and Agriculture Organization of the United Nations (FAO), 2005c. EASYPol Modules 046. Commodity Chain Analysis: Impact Analysis Using Shadow Price. Available on Internet: http://www.fao.org/docs/up/easypol/333/CCA_046EN.pdf</ref>).<br />
<br />
Practical use of supply chain analysis <br />
<br />
Supply chain analysis is a tool that allows us to assess the impact of an environmental policy through a simple Excel table with data on complete financial accounts of the various agents along the length of the chain. Then the impact of an environmental policy option on financial accounts and material flow of economic agents targeted by this policy is entered in the Excel table. This will automatically induce a change in the financial account of all other agents connected to him and directly or indirectly depending on his production to ensure their own production.<br />
Supply chain analysis offers an economic simulation model, not a model of optimization. This method can be used for assessment of policies targeting a whole sector, a sub-sector or a branch of economic activities (e.g. dairy quota limiting milk production, taxes on chemical nitrogen fertilizers) or for macroeconomic policies (e.g. aiming at unemployment decrease, inflation stabilization, keeping the balance of payment in equilibrium, achieving a higher economic growth…). <br />
<br />
In that sense, supply chain analysis is relevant for the same cases than CGE, I-O analysis and Accounts environmentally adjusted, since this methodology is able to capture the impact of a policy scenario that cover a great number of economic activities (at least one sector, a sub-sector or a branch but not few economic agents).<br />
<br />
It could also be used at lower economic level (a small number of economic agents) but in that case, national and regional data would be too aggregated and more detailed and disaggregated data should be found by surveys on field.<br />
<br />
Limits of the method<br />
<br />
o Capture fewer indirect impacts on other sectors than I-O. Indeed, supply Chain analysis is in a sense, quite similar to I-O analysis but deals with fewer sectors (only those linked to the analyzed product for which a supply chain is mapped) while I-O table deals with most of economic sectors (available in national or regional statistical offices).<br />
<br />
o Supply chain analysis cover fewer sectors but goes more into details concerning data (on material flows between agents). However, this high level of details achievement is time consuming since most data are not published and require visiting national statistic offices, official institutions, and enterprises for collecting data.<br />
<br />
Several limits are the same as for I-O analysis :<br />
<br />
o The static aspects making difficult any projection possibilities<br />
o Dependence on availability of regional data or data at watershed level (or any other environmental unit of the territory). When not available, need to go to industrial federations etc. for data collecting.<br />
<br />
===references===<br />
<br />
<references/></div>Mcordier