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Projecting input-output tables for model baselines

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This technical report describes a multi-regional generalized RAS (MR-GRAS) procedure to update/project input-output tables or social accounting matrices. The method is able to incorporate a number of constraints on row and columns sums as well as specific flows between economic sectors and specific taxes in an input-output table. This feature is particularly useful to reconcile information coming from different data sets. In the application described in this report, the method is tailored towards constraints with regard to the energy system. Specifically, we specify constraints in the updating/projecting algorithm that are able to reproduce the economic values reflected in an energy balance from an energy system model. Here, we show that the method is able to generate input-output tables that are forward projected until 2050 and can be used as a baseline in a computable general equilibrium model like JRC-GEM-E3.

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  • Umed Temursho & Manuel Alejandro Cardenete & Krzysztof Wojtowicz & Luis Rey & Matthias Weitzel & Toon Vandyck & Bert Saveyn, 2020. "Projecting input-output tables for model baselines," JRC Research Reports JRC120513, Joint Research Centre.
    • Handle: RePEc:ipt:iptwpa:jrc120513
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    1. Angel Aguiar & Badri Narayanan & Robert McDougall, 2016. "An Overview of the GTAP 9 Data Base," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 1(1), pages 181-208, June.
    2. Randall Jackson & Alan Murray, 2004. "Alternative Input-Output Matrix Updating Formulations," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 135-148.
    3. Manfred Lenzen & Blanca Gallego & Richard Wood, 2009. "Matrix Balancing Under Conflicting Information," Economic Systems Research, Taylor & Francis Journals, vol. 21(1), pages 23-44.
    4. G. Günlük‐Şenesen & J. M. Bates, 1988. "Some Experiments with Methods of Adjusting Unbalanced Data Matrices," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 151(3), pages 473-490, May.
    5. Umed Temurshoev & Marcel P. Timmer, 2011. "Joint estimation of supply and use tables," Papers in Regional Science, Wiley Blackwell, vol. 90(4), pages 863-882, November.
    6. Donald Gilchrist & Larry St. Louis, 2004. "An Algorithm for the Consistent Inclusion of Partial Information in the Revision of Input-Output Tables," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 149-156.
    7. Umed Temurshoev & Colin Webb & Norihiko Yamano, 2011. "Projection Of Supply And Use Tables: Methods And Their Empirical Assessment," Economic Systems Research, Taylor & Francis Journals, vol. 23(1), pages 91-123.
    8. Wenfeng Huang & Shintaro Kobayashi & Hajime Tanji, 2008. "Updating an Input-Output Matrix with Sign-preservation: Some Improved Objective Functions and their Solutions," Economic Systems Research, Taylor & Francis Journals, vol. 20(1), pages 111-123.
    9. Manfred Lenzen & Richard Wood & Blanca Gallego, 2007. "Some Comments on the GRAS Method," Economic Systems Research, Taylor & Francis Journals, vol. 19(4), pages 461-465.
    10. Donald Gilchrist & Larry V. ST Louis, 1999. "Completing Input-Output Tables using Partial Information, with an Application to Canadian Data," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 185-194.
    11. Golan, Amos & Judge, George & Robinson, Sherman, 1994. "Recovering Information from Incomplete or Partial Multisectoral Economic Data," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 541-549, August.
    12. Randall Jackson, 1998. "Regionalizing National Commodity-by-Industry Accounts," Economic Systems Research, Taylor & Francis Journals, vol. 10(3), pages 223-238.
    13. Michael Lahr & Louis de Mesnard, 2004. "Biproportional Techniques in Input-Output Analysis: Table Updating and Structural Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 16(2), pages 115-134.
    14. Roberto Mínguez & Jan Oosterhaven & Fernando Escobedo, 2009. "Cell‐Corrected Ras Method (Cras) For Updating Or Regionalizing An Input–Output Matrix," Journal of Regional Science, Wiley Blackwell, vol. 49(2), pages 329-348, May.
    15. repec:rre:publsh:v:34:y:2004:i:1:p:37-56 is not listed on IDEAS
    16. REY LOS SANTOS Luis & WOJTOWICZ Krzysztof & TAMBA Marie & VANDYCK Toon & WEITZEL Matthias & SAVEYN Bert & TEMURSHO Umed, 2018. "Global macroeconomic balances for mid-century climate analyses," JRC Research Reports JRC113981, Joint Research Centre.
    17. Anonymous, 1961. "Organization for European Economic Cooperation," International Organization, Cambridge University Press, vol. 15(1), pages 204-205, January.
    18. Theo Junius & Jan Oosterhaven, 2003. "The Solution of Updating or Regionalizing a Matrix with both Positive and Negative Entries," Economic Systems Research, Taylor & Francis Journals, vol. 15(1), pages 87-96, March.
    19. Sherman Robinson & Andrea Cattaneo & Moataz El-Said, 2001. "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods," Economic Systems Research, Taylor & Francis Journals, vol. 13(1), pages 47-64.
    20. Patrick Canning & Zhi Wang, 2005. "A Flexible Mathematical Programming Model to Estimate Interregional Input–Output Accounts," Journal of Regional Science, Wiley Blackwell, vol. 45(3), pages 539-563, August.
    21. Amos Golan & Stephen Vogel, 2000. "Estimation of Non-Stationary Social Accounting Matrix Coefficients with Supply-Side Information," Economic Systems Research, Taylor & Francis Journals, vol. 12(4), pages 447-471.
    22. Umed Temurshoev & Ronald E. Miller & Maaike C. Bouwmeester, 2013. "A Note On The Gras Method," Economic Systems Research, Taylor & Francis Journals, vol. 25(3), pages 361-367, September.
    23. Jan Oosterhaven & Gerrit Piek & Dirk Stelder, 1986. "Theory And Practice Of Updating Regional Versus Interregional Interindustry Tables," Papers in Regional Science, Wiley Blackwell, vol. 59(1), pages 57-72, January.
    24. McDougall, Robert A., 1999. "Entropy Theory and RAS are Friends," Working papers 283439, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    25. Erik Dietzenbacher & Ronald E. Miller, 2009. "Ras‐Ing The Transactions Or The Coefficients: It Makes No Difference," Journal of Regional Science, Wiley Blackwell, vol. 49(3), pages 555-566, August.
    26. McDougall, Robert, 1999. "Entropy Theory and RAS are Friends," GTAP Working Papers 300, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
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    Keywords

    Input-output tables; baseline; MR-GRAS; CGE;
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