Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows

A basic underlying assumption in most of the research to date is that intermediate industry accounts of the economies in multiregional input-output (MRIO) tables exist and are accurate. In fact, if they exist at the subnational level, such accounts are, at best, roughly estimated and predicated on f...

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Autores: Sargento, Ana Lúcia Marto, Lahr, Michael L., Ferreira, João Pedro, Torre Cuevas, Fernando de la
Formato: artículo
Fecha de publicación:2024
País:España
Recursos:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/46073
Acesso em linha:https://hdl.handle.net/10347/46073
Access Level:acceso abierto
Palavra-chave:Input-output analysis
Multiregional input-output
RAS
Gravity models
Regional purchase coefficients
Economic modelling
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spelling Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flowsSargento, Ana Lúcia MartoLahr, Michael L.Ferreira, João PedroTorre Cuevas, Fernando de laInput-output analysisMultiregional input-outputRASGravity modelsRegional purchase coefficientsEconomic modellingA basic underlying assumption in most of the research to date is that intermediate industry accounts of the economies in multiregional input-output (MRIO) tables exist and are accurate. In fact, if they exist at the subnational level, such accounts are, at best, roughly estimated and predicated on far less empirical information than is available for economies of nations. Moreover, intra-economy intermediate-industry flows are typically larger than the set of a region's commodity in- and out-flows. So, if intermediate industry flows in a set of MRIO accounts are noticeably mis-estimated, it follows that interregional trade coincidentally derived using them must be even more conspicuously in error. We hypothesize as more information is used to estimate MRIO accounts, the better the estimates should be. We start our experiment by consolidating 2019 FIGARO accounts of the 27 member states of the European Union, while maintaining sectoral detail, to produce a “national account”. We then test several approaches to constructing MRIO tables. The approaches distribute interregional trade fully by receiving industry, as in FIGARO, as well as strictly in the form of a diagonalized matrix as if the commodity inflows are competitive imports. To do this, both a gravity model and RAS are applied to each approach. We then test to see how well the approaches estimate main features of FIGARO's MRIO accounts and detail a rather consistent ranking of the relative accuracy of them. We also find that the level of error inherent to the estimated MRIOs is markedly similar across approaches, particularly for multipliers. Further, relaxing interregional trade to a diagonalized matrix tends to add very little error. The approach that uses the least data is, however, markedly worse in replicating countries’ direct requirements matrices and Leontief inverses, which suggests its use in a more-limited set of applicationsElsevierUniversidade de Santiago de Compostela. Departamento de Fundamentos da Análise EconómicaUniversidade de Santiago de Compostela. Instituto de Estudos e Desenvolvemento de Galicia (IDEGA)20242024-04-1720242024-04-17journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10347/46073reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostelainstname:Universidad de Santiago de Compostela (USC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:minerva.usc.gal:10347/460732026-06-15T12:47:27Z
dc.title.none.fl_str_mv Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
title Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
spellingShingle Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
Sargento, Ana Lúcia Marto
Input-output analysis
Multiregional input-output
RAS
Gravity models
Regional purchase coefficients
Economic modelling
title_short Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
title_full Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
title_fullStr Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
title_full_unstemmed Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
title_sort Revisiting methods for estimating interregional input-output accounts: It’s not just about trade flows
dc.creator.none.fl_str_mv Sargento, Ana Lúcia Marto
Lahr, Michael L.
Ferreira, João Pedro
Torre Cuevas, Fernando de la
author Sargento, Ana Lúcia Marto
author_facet Sargento, Ana Lúcia Marto
Lahr, Michael L.
Ferreira, João Pedro
Torre Cuevas, Fernando de la
author_role author
author2 Lahr, Michael L.
Ferreira, João Pedro
Torre Cuevas, Fernando de la
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de Santiago de Compostela. Departamento de Fundamentos da Análise Económica
Universidade de Santiago de Compostela. Instituto de Estudos e Desenvolvemento de Galicia (IDEGA)
dc.subject.none.fl_str_mv Input-output analysis
Multiregional input-output
RAS
Gravity models
Regional purchase coefficients
Economic modelling
topic Input-output analysis
Multiregional input-output
RAS
Gravity models
Regional purchase coefficients
Economic modelling
description A basic underlying assumption in most of the research to date is that intermediate industry accounts of the economies in multiregional input-output (MRIO) tables exist and are accurate. In fact, if they exist at the subnational level, such accounts are, at best, roughly estimated and predicated on far less empirical information than is available for economies of nations. Moreover, intra-economy intermediate-industry flows are typically larger than the set of a region's commodity in- and out-flows. So, if intermediate industry flows in a set of MRIO accounts are noticeably mis-estimated, it follows that interregional trade coincidentally derived using them must be even more conspicuously in error. We hypothesize as more information is used to estimate MRIO accounts, the better the estimates should be. We start our experiment by consolidating 2019 FIGARO accounts of the 27 member states of the European Union, while maintaining sectoral detail, to produce a “national account”. We then test several approaches to constructing MRIO tables. The approaches distribute interregional trade fully by receiving industry, as in FIGARO, as well as strictly in the form of a diagonalized matrix as if the commodity inflows are competitive imports. To do this, both a gravity model and RAS are applied to each approach. We then test to see how well the approaches estimate main features of FIGARO's MRIO accounts and detail a rather consistent ranking of the relative accuracy of them. We also find that the level of error inherent to the estimated MRIOs is markedly similar across approaches, particularly for multipliers. Further, relaxing interregional trade to a diagonalized matrix tends to add very little error. The approach that uses the least data is, however, markedly worse in replicating countries’ direct requirements matrices and Leontief inverses, which suggests its use in a more-limited set of applications
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-04-17
2024
2024-04-17
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10347/46073
url https://hdl.handle.net/10347/46073
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
instname:Universidad de Santiago de Compostela (USC)
instname_str Universidad de Santiago de Compostela (USC)
reponame_str Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
collection Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
repository.name.fl_str_mv
repository.mail.fl_str_mv
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