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An Econometric Approach to General Equilibrium Modeling

In: Handbook of Computable General Equilibrium Modeling

Author

Listed:
  • Jorgenson, Dale W.
  • Jin, Hui
  • Slesnick, Daniel T.
  • Wilcoxen, Peter J.

Abstract

The first objective of this chapter is to present a new approach to econometric modeling of producer behavior. Our key contribution is to represent the rate and biases of technical change by unobservable or latent variables. We also divide the rate of technical change between components that are induced by changes in prices and those that are autonomous and not affected by prices. In our dataset, production is disaggregated into 35 separate commodities produced by one or more of the 35 industries making up the US economy. Our second objective is to present a new econometric model of aggregate consumer behavior. The model allocates full wealth among time periods for households distinguished by demographic characteristics, and determines the within-period demands for leisure, consumer goods and services. An important feature of our approach is the development of a closed-form representation of aggregate demand and labor supply that accounts for the heterogeneity in household behavior that is observed in micro-level data. Our model of producer behavior is the supply side of general equilibrium models of the US. The aggregate demand functions are important components of the demand side. These general equilibrium models are used to analyze the consequences of a broad spectrum of public policies. These applications are discussed in more detail in Chapter 8 of this Handbook. The third objective of the chapter is to demonstrate an important benefit of the econometric approach to parameterization. The parameter covariances obtained in the course of estimation can be used to construct confidence intervals for endogenous variables in general equilibrium models. Confidence intervals characterize the precision of modeling results more rigorously and systematically than traditional sensitivity analysis.

Suggested Citation

  • Jorgenson, Dale W. & Jin, Hui & Slesnick, Daniel T. & Wilcoxen, Peter J., 2013. "An Econometric Approach to 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 1133-1212, Elsevier.
    • Handle: RePEc:eee:hacchp:v:1:y:2013:i:c:p:1133-1212
    DOI: 10.1016/B978-0-444-59568-3.00017-1
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    1. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-987, December.
    2. Binswanger, Hans P, 1974. "The Measurement of Technical Change Biases with Many Factors of Production," American Economic Review, American Economic Association, vol. 64(6), pages 964-976, December.
    3. Richard Blundell & Martin Browning & Costas Meghir, 1994. "Consumer Demand and the Life-Cycle Allocation of Household Expenditures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(1), pages 57-80.
    4. Dale W. Jorgenson, 1998. "Growth, Volume 2: Energy, the Environment, and Economic Growth," MIT Press Books, The MIT Press, edition 1, volume 2, number 0262100746, April.
    5. Jaffe, Adam B. & Newell, Richard G. & Stavins, Robert N., 2003. "Chapter 11 Technological change and the environment," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 1, chapter 11, pages 461-516, Elsevier.
    6. Attanasio, Orazio P, et al, 1999. "Humps and Bumps in Lifetime Consumption," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 22-35, January.
    7. Binswanger, Hans P, 1974. "A Microeconomic Approach to Induced Innovation," Economic Journal, Royal Economic Society, vol. 84(336), pages 940-958, December.
    8. Attanasio, Orazio P & Weber, Guglielmo, 1995. "Is Consumption Growth Consistent with Intertemporal Optimization? Evidence from the Consumer Expenditure Survey," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1121-1157, December.
    9. Chang-jin Kim & N. Kundan Kishor & Charles R Nelson, 2006. "A Time-Varying Parameter Model for a Forward-Looking Monetary Policy Rule Based on Real-Time Data," Working Papers UWEC-2007-32, University of Washington, Department of Economics.
    10. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    11. Dale Jorgenson & Masahiro Kuroda & Kazuyuki Motohashi (ed.), 2007. "Productivity in Asia," Books, Edward Elgar Publishing, number 12811.
    12. Gallant, A. Ronald & Golub, Gene H., 1984. "Imposing curvature restrictions on flexible functional forms," Journal of Econometrics, Elsevier, vol. 26(3), pages 295-321, December.
    13. Browning, Martin & Hansen, Lars Peter & Heckman, James J., 1999. "Micro data and general equilibrium models," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 8, pages 543-633, Elsevier.
    14. Daron Acemoglu, 2007. "Equilibrium Bias of Technology," Econometrica, Econometric Society, vol. 75(5), pages 1371-1409, September.
    15. Feng, Guohua & Serletis, Apostolos, 2008. "Productivity trends in U.S. manufacturing: Evidence from the NQ and AIM cost functions," Journal of Econometrics, Elsevier, vol. 142(1), pages 281-311, January.
    16. Slesnick, Daniel T., 2002. "Prices and Regional Variation in Welfare," Journal of Urban Economics, Elsevier, vol. 51(3), pages 446-468, May.
    17. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    18. Slesnick,Daniel T., 2001. "Consumption and Social Welfare," Cambridge Books, Cambridge University Press, number 9780521497206, September.
    19. Kim, Chang-Jin & Nelson, Charles R., 2006. "Estimation of a forward-looking monetary policy rule: A time-varying parameter model using ex post data," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1949-1966, November.
    20. Barnett, William A. & Serletis, Apostolos, 2008. "Measuring Consumer Preferences and Estimating Demand Systems," MPRA Paper 12318, University Library of Munich, Germany.
    21. Jin, Hui & Jorgenson, Dale W., 2010. "Econometric modeling of technical change," Journal of Econometrics, Elsevier, vol. 157(2), pages 205-219, August.
    22. Diewart, W Erwin & Morrison, Catherine J, 1986. "Adjusting Output and Productivity Indexes for Changes in the Terms of Trade," Economic Journal, Royal Economic Society, vol. 96(383), pages 659-679, September.
    23. Daron Acemoglu, 2002. "Directed Technical Change," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(4), pages 781-809.
    24. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    25. Timmer,Marcel P. & Inklaar,Robert & O'Mahony,Mary & Ark,Bart van, 2013. "Economic Growth in Europe," Cambridge Books, Cambridge University Press, number 9781107412446, September.
    26. Browning, Martin & Deaton, Angus & Irish, Margaret, 1985. "A Profitable Approach to Labor Supply and Commodity Demands over the Life-Cycle," Econometrica, Econometric Society, vol. 53(3), pages 503-543, May.
    27. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-597, June.
    28. Jorgenson, Dale W., 2005. "Accounting for Growth in the Information Age," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 10, pages 743-815, Elsevier.
    29. Kim, Chang-Jin, 2006. "Time-varying parameter models with endogenous regressors," Economics Letters, Elsevier, vol. 91(1), pages 21-26, April.
    30. Jorgenson, Dale W. & Slesnick, Daniel T., 2008. "Consumption and labor supply," Journal of Econometrics, Elsevier, vol. 147(2), pages 326-335, December.
    31. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2005. "Productivity, Volume 3: Information Technology and the American Growth Resurgence," MIT Press Books, The MIT Press, edition 1, volume 3, number 0262101114, April.
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    Cited by:

    1. Anderson, Kym & Martin, Will & van der Mensbrugghe, Dominique, 2013. "Estimating Effects of Price-Distorting Policies Using Alternative Distortions Databases," 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 877-931, Elsevier.
    2. Aguiar, Angel & Corong, Erwin & van der Mensbrugghe, Dominique, 2020. "The GTAP Recursive Dynamic (GTAP-RD) Model: Version 1.0," Conference papers 333133, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    3. Yizhou Zhang & Geoffrey J.D. Hewings, 2019. "Fiscal Decentralization – A Cautious Tale," Regional Science Policy & Practice, Wiley Blackwell, vol. 11(1), pages 173-187, March.
    4. Aguiar, Angel & Corong, Erwin L. & van der Mensbrugghe, Dominique & Bekkers, Eddy & Koopman, Robert Bernard & Teh, Robert, 2019. "The WTO Global Trade Model: Technical documentation," WTO Staff Working Papers ERSD-2019-10, World Trade Organization (WTO), Economic Research and Statistics Division.
    5. Jean Chateau & Erwin Corong & Elisa Lanzi & Caitlyn Carrico & Jean Fouré & David Laborde, 2020. "Characterizing Supply-Side Drivers of Structural Change in the Construction of Economic Baseline Projections," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 5(1), pages 109-161, June.
    6. Dong, Qi & Murakami, Tomoaki & Nakashima, Yasuhiro, 2021. "Induced Bias of Technological Change in Agriculture and Structural Transformation: A Translog Cost Function Analysis of Chinese Cereal Production," 2021 Conference, August 17-31, 2021, Virtual 315373, International Association of Agricultural Economists.

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    More about this item

    Keywords

    Rate and bias of technical change; latent variables; Kalman filter; aggregate demand; labor supply; confidence intervals; outcome variables;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

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