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What do GTAP databases tell us about technologies for industries and regions?

Author

Listed:
  • Peter B. Dixon
  • Maureen T. Rimmer

Abstract

We conduct an historical simulation from 2004 to 2014 with a 57-commodity, 13-region version of the GTAP model. The simulation generates estimates of changes in industry technologies, household preferences and several other unobservable variables by calculating the changes required to connect GTAP databases for the two years. The historical simulation starts from the 2004 database and then in a single-period (10-year) computation produces a picture of 2014. We require this picture to be consistent with a large number of data points in the GTAP database for 2014 and with data on a selection of other variables brought in from non-GTAP sources. The GTAP data are entirely in values. The non-GTAP sources provide movements between 2004 and 2014 in quantity variables. The combination of exogenously set GTAP value targets for 2014 and non-GTAP quantity targets enables the historical simulation to generate a comprehensive set of price movements for 2004 to 2014. Simultaneously, the historical simulation translates commodity and industry value movements into quantity movements. With input and output quantity movements in place, technology and preference movements are revealed.

Suggested Citation

  • Peter B. Dixon & Maureen T. Rimmer, 2023. "What do GTAP databases tell us about technologies for industries and regions?," Centre of Policy Studies/IMPACT Centre Working Papers g-340, Victoria University, Centre of Policy Studies/IMPACT Centre.
    • Handle: RePEc:cop:wpaper:g-340
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    References listed on IDEAS

    as
    1. Dixon, Peter B. & Koopman, Robert B. & Rimmer, Maureen T., 2013. "The MONASH Style of Computable General Equilibrium Modeling: A Framework for Practical Policy Analysis," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 23-103, Elsevier.
    2. James Giesecke, 2002. "Explaining regional economic performance: An historical application of a dynamic multi-regional CGE model," Review of Economic Design, Springer;Society for Economic Design, vol. 81(2), pages 247-278, April.
    3. Adams, Philip D. & Dixon, Peter B. & McDonald, Daina & Meagher, G. A. & Parmenter, Brian R., 1994. "Forecasts for the Australian economy using the MONASH model," International Journal of Forecasting, Elsevier, vol. 10(4), pages 557-571, December.
    4. Bela Balassa, 1964. "The Purchasing-Power Parity Doctrine: A Reappraisal," Journal of Political Economy, University of Chicago Press, vol. 72(6), pages 584-584.
    5. Wolfgang Britz & Roberto Roson, 2019. "G-RDEM: A GTAP-Based Recursive Dynamic CGE Model for Long-Term Baseline Generation and Analysis," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 4(1), pages 50-96, June.
    6. Peter B. Dixon & Maureen T. Rimmer, 2004. "The US Economy from 1992 to 1998: Results from a Detailed CGE Model," The Economic Record, The Economic Society of Australia, vol. 80(s1), pages 13-23, September.
    7. Peter B. Dixon & Jayant Menon & Maureen T. Rimmer, 2000. "Changes in Technology and Preferences: A General Equilibrium Explanation of Rapid Growth in Trade," Australian Economic Papers, Wiley Blackwell, vol. 39(1), pages 33-55, March.
    8. Dixon, Peter B. & Rimmer, Maureen T., 2013. "Validation in Computable General Equilibrium Modeling," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 1271-1330, Elsevier.
    9. Hertel, Thomas, 1997. "Global Trade Analysis: Modeling and applications," GTAP Books, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, number 7685, December.
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    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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