This paper provides an overview of the version 11 of the Global Trade Analysis Project (GTAP) Power Data Base, which covers 141 individual countries, 19 composite regions and 76 sectors, reporting data for five reference years – 2004, 2007, 2011, 2014 and 2017. The newly constructed database builds on the previous efforts, introducing several new features and updates. First, by extending the coverage across reference years, GTAP-Power 11 Data Base uses updated levelized costs of electricity generation estimates. Second, the database updates the shares of transmission and distribution costs across countries. Finally, the newly constructed database includes complementary accounts of greenhouse gases and air pollutants. In an application of the database, changes in greenhouse gas emissions from electricity generation in each country are decomposed into changes in (1) the amount of electricity generated, (2) the mix of technologies, and (3) the emissions intensity of each technology.
{"title":"GTAP-Power Data Base: Version 11","authors":"M. Chepeliev","doi":"10.21642/jgea.080203af","DOIUrl":"https://doi.org/10.21642/jgea.080203af","url":null,"abstract":"This paper provides an overview of the version 11 of the Global Trade Analysis Project (GTAP) Power Data Base, which covers 141 individual countries, 19 composite regions and 76 sectors, reporting data for five reference years – 2004, 2007, 2011, 2014 and 2017. The newly constructed database builds on the previous efforts, introducing several new features and updates. First, by extending the coverage across reference years, GTAP-Power 11 Data Base uses updated levelized costs of electricity generation estimates. Second, the database updates the shares of transmission and distribution costs across countries. Finally, the newly constructed database includes complementary accounts of greenhouse gases and air pollutants. In an application of the database, changes in greenhouse gas emissions from electricity generation in each country are decomposed into changes in (1) the amount of electricity generated, (2) the mix of technologies, and (3) the emissions intensity of each technology.","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elasticities are often a combination of expert decisions and literature estimates— many of which are outdated. Previous efforts have focused on estimating the most commonly used elasticities in economic models (e.g., the Armington elasticity of trade); however, several elasticities still have little empirical basis. The elasticity of substitution between intermediate inputs and value-added is one example, but this elasticity is quite important as it governs producers’ production regimes across sectors and regions reflecting their level of efficiency. We examine and estimate this elasticity for one of the most widely used CGE models (parameter ESUBT in the GTAP model), using the latest five datasets available (2004, 2007, 2011, 2014, and 2017) in the version 11 GTAP database. Our work finds that the default value of zero in GTAP does not reflect the behavior implied by the data. Using our estimates, we propose a set of new values for the short run (about one year), two medium runs (three years and six years) and the long run (i.e., infinite time horizon). We demonstrate the importance of our new estimates using a scenario from the EU Farm to Fork policy where we find that using the estimated elasticities leads to much milder market and welfare impacts, and that these effects are further dampened as the time horizon of the simulation increases.
{"title":"Estimation of the value-added/intermediate input substitution elasticities consistent with the GTAP data","authors":"M. Ivanic, Jayson Beckman, Noe J. Nava","doi":"10.21642/jgea.080204af","DOIUrl":"https://doi.org/10.21642/jgea.080204af","url":null,"abstract":"Elasticities are often a combination of expert decisions and literature estimates— many of which are outdated. Previous efforts have focused on estimating the most commonly used elasticities in economic models (e.g., the Armington elasticity of trade); however, several elasticities still have little empirical basis. The elasticity of substitution between intermediate inputs and value-added is one example, but this elasticity is quite important as it governs producers’ production regimes across sectors and regions reflecting their level of efficiency. We examine and estimate this elasticity for one of the most widely used CGE models (parameter ESUBT in the GTAP model), using the latest five datasets available (2004, 2007, 2011, 2014, and 2017) in the version 11 GTAP database. Our work finds that the default value of zero in GTAP does not reflect the behavior implied by the data. Using our estimates, we propose a set of new values for the short run (about one year), two medium runs (three years and six years) and the long run (i.e., infinite time horizon). We demonstrate the importance of our new estimates using a scenario from the EU Farm to Fork policy where we find that using the estimated elasticities leads to much milder market and welfare impacts, and that these effects are further dampened as the time horizon of the simulation increases.","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Bekkers, Erwin Corong, Joseph Francois, H. Rojas‐Romagosa
{"title":"A Ricardian Trade Structure in CGE: Modeling Eaton-Kortum Based Trade with GTAP","authors":"E. Bekkers, Erwin Corong, Joseph Francois, H. Rojas‐Romagosa","doi":"10.21642/jgea.080201af","DOIUrl":"https://doi.org/10.21642/jgea.080201af","url":null,"abstract":"","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138944768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a method for calibrating an industry-level technology to engineering (bottom-up) estimates with a particular focus on abatement opportunities. As a demonstration, substitution elasticities across inputs are adjusted in the nested cost function for the electricity sector to best fit a target marginal abatement cost (MAC) curve derived from engineering assessments of available technologies. Elasticities are optimized over an entire relevant range of the MAC, whereas current techniques use local point estimates under little or no abatement. In the context of fitting to a given MAC we evaluate alternative nesting structures and find that, while complexity in nesting improves the fit, even relatively simple nesting structures can reasonably approximate the target MAC. In our example, focused on the electricity sector, we find standard elasticities adopted in top-down models moderately overstate abatement costs relative to the engineering targets. In our preferred specification the most important adjustment is to escalate the substitution elasticity between energy and value-added inputs. This is consistent with an argument that the current set of point estimates fail to properly account for new capital-based technologies. These conclusions, however, are sensitive to our assumption about output-intensity abatement and consumer price responsiveness, both of which are not delineated in engineering estimates.
{"title":"Calibrating Constant Elasticityof Substitution Technologies toBottom-up Cost Estimates","authors":"Edward J. Balistreri, Maxwell Brown","doi":"10.21642/jgea.080103af","DOIUrl":"https://doi.org/10.21642/jgea.080103af","url":null,"abstract":"We propose a method for calibrating an industry-level technology to engineering (bottom-up) estimates with a particular focus on abatement opportunities. As a demonstration, substitution elasticities across inputs are adjusted in the nested cost function for the electricity sector to best fit a target marginal abatement cost (MAC) curve derived from engineering assessments of available technologies. Elasticities are optimized over an entire relevant range of the MAC, whereas current techniques use local point estimates under little or no abatement. In the context of fitting to a given MAC we evaluate alternative nesting structures and find that, while complexity in nesting improves the fit, even relatively simple nesting structures can reasonably approximate the target MAC. In our example, focused on the electricity sector, we find standard elasticities adopted in top-down models moderately overstate abatement costs relative to the engineering targets. In our preferred specification the most important adjustment is to escalate the substitution elasticity between energy and value-added inputs. This is consistent with an argument that the current set of point estimates fail to properly account for new capital-based technologies. These conclusions, however, are sensitive to our assumption about output-intensity abatement and consumer price responsiveness, both of which are not delineated in engineering estimates.","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44071925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the newly available R packages tabloToR and HARr , it is now possible to run General Equilibrium Modelling PACKage (GEMPACK) models expressed in the TABLO language entirely in R without the need for a Fortran compiler, the GEMPACK software or any licenses. Working through a simple Global Trade Analysis Project (GTAP) simulation, we demonstrate how the simulation may be done in R and show that its results are virtually identical to those obtained in GEMPACK. With tabloToR and HARr offering a working replacement for GEMPACK, the packages could benefit those CGE modelers who are more comfortable working in R than in GEMPACK, and bring about benefits to the Computable General Equilibrium (CGE) modeling community through eliminating licensing costs and introducing additional efficiencies through easier integration and development of new features.
{"title":"GEMPACK simulations in R: Ademonstration of running the GTAP modeland processing its results entirely in R using packages HARr and tabloToR","authors":"M. Ivanic","doi":"10.21642/jgea.080101af","DOIUrl":"https://doi.org/10.21642/jgea.080101af","url":null,"abstract":"With the newly available R packages tabloToR and HARr , it is now possible to run General Equilibrium Modelling PACKage (GEMPACK) models expressed in the TABLO language entirely in R without the need for a Fortran compiler, the GEMPACK software or any licenses. Working through a simple Global Trade Analysis Project (GTAP) simulation, we demonstrate how the simulation may be done in R and show that its results are virtually identical to those obtained in GEMPACK. With tabloToR and HARr offering a working replacement for GEMPACK, the packages could benefit those CGE modelers who are more comfortable working in R than in GEMPACK, and bring about benefits to the Computable General Equilibrium (CGE) modeling community through eliminating licensing costs and introducing additional efficiencies through easier integration and development of new features.","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46237300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes the use of a utility that creates a Latin Hypercube Sample (LHS). The LHS approach to sampling has had wide applicability as it represents a Monte Carlo strategy that limits sample size and therefore computer time to study the outcomes of simulations under uncertainty. Other approaches to deal with the ’size’ problem include Gaussian Quadrature (GQ) (Arndt, 1996), often used in the context of large models such as computable general equilibrium models. However, the GQ approach is most suitable for focusing on a small set of uncertain parameters as the number of model evaluations increases substantially with the number of uncertain parameters and/or the moments to track. The utility is a new version of the LHS utility that has been publicly available from Sandia National Labs since the early 2000s. Beyond the recoding from FORTRAN to C/C++, the new version of the utility has some additional features including new output options and additional statistical distributions. This paper demonstrates the use of the new utility by coupling it to an integrated assessment (IAM) model which is derived from the META 21 model developed by Dietz et al. (2021). The META 21 model has many components that can be readily integrated into global economic models that track greenhouse gas emissions—a simple climate module, economic impacts derived from sea-level and temperature rises and bio-physical tipping points such as the Amazon dieback. The IAM results suggest that the social cost of carbon increases by an average of around 26% when taking into account the tipping points and that the tipping points lead to an additional decline of 0-5% in per capita consumption in 2100 on top of the other damages related to climate change. The utility and the code to the IAM model are available as supplementary materials.
{"title":"A Latin Hypercube Sampling Utility: with an application to an Integrated Assessment Model","authors":"Dominique van der Mensbrugghe","doi":"10.21642/jgea.080102af","DOIUrl":"https://doi.org/10.21642/jgea.080102af","url":null,"abstract":"This paper describes the use of a utility that creates a Latin Hypercube Sample (LHS). The LHS approach to sampling has had wide applicability as it represents a Monte Carlo strategy that limits sample size and therefore computer time to study the outcomes of simulations under uncertainty. Other approaches to deal with the ’size’ problem include Gaussian Quadrature (GQ) (Arndt, 1996), often used in the context of large models such as computable general equilibrium models. However, the GQ approach is most suitable for focusing on a small set of uncertain parameters as the number of model evaluations increases substantially with the number of uncertain parameters and/or the moments to track. The utility is a new version of the LHS utility that has been publicly available from Sandia National Labs since the early 2000s. Beyond the recoding from FORTRAN to C/C++, the new version of the utility has some additional features including new output options and additional statistical distributions. This paper demonstrates the use of the new utility by coupling it to an integrated assessment (IAM) model which is derived from the META 21 model developed by Dietz et al. (2021). The META 21 model has many components that can be readily integrated into global economic models that track greenhouse gas emissions—a simple climate module, economic impacts derived from sea-level and temperature rises and bio-physical tipping points such as the Amazon dieback. The IAM results suggest that the social cost of carbon increases by an average of around 26% when taking into account the tipping points and that the tipping points lead to an additional decline of 0-5% in per capita consumption in 2100 on top of the other damages related to climate change. The utility and the code to the IAM model are available as supplementary materials.","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44719186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A general equilibrium model with an asymmetric Armington function: Method and application","authors":"M. Cicowiez, H. Lofgren","doi":"10.21642/jgea.070204af","DOIUrl":"https://doi.org/10.21642/jgea.070204af","url":null,"abstract":"","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42465414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"New Price-based Bilateral Ad-valorem Equivalent Estimates of Non-tariff Measures","authors":"Anna Strutt, C. Utoktham, Y. Duval","doi":"10.21642/jgea.070202af","DOIUrl":"https://doi.org/10.21642/jgea.070202af","url":null,"abstract":"","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43527553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mathematics of Generalized Versions of the Melitz, Krugman and Armington Models with Detailed Derivations","authors":"Edward J. Balistreri, David G. Tarr","doi":"10.21642/jgea.070203af","DOIUrl":"https://doi.org/10.21642/jgea.070203af","url":null,"abstract":"","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42153065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Angel H. Aguiar, M. Chepeliev, Erwin Corong, Dominique van der Mensbrugghe
{"title":"The Global Trade Analysis Project (GTAP) Data Base: Version 11","authors":"Angel H. Aguiar, M. Chepeliev, Erwin Corong, Dominique van der Mensbrugghe","doi":"10.21642/jgea.070201af","DOIUrl":"https://doi.org/10.21642/jgea.070201af","url":null,"abstract":"","PeriodicalId":44607,"journal":{"name":"Journal of Global Economic Analysis","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45296716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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