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The estimation of LES demand elasticities for CGE models

  • Jouko Kinnunen
  • Saara Tamminen
  • Mira Jussila
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    Computable general equilibrium (CGE) models require external parameters for proper estimations and can be relatively sensitive to the elasticity estimates used in them. We estimate LES demand elasticities and Frisch parameters for all Finnish household income deciles. These estimates will be used also inVATTAGE CGE model. We use three different methodologies for the estimation of demand elasticities: price index based approach, pseudo-panel dataset based regressions with exogenous Frisch parameters, and finally cross-section data based estimations with the Frisch parameters. Only the last methodology provides adequate results despite the use of detailed and extensive data. We conclude that the estimation of LES demand elasticities for narrow commodity groups is cumbersome with standard household consumption survey data. Typically these surveys account consumption only from a time period of a few weeks. The chance of consuming various durable consumption items during such a short time period is low. Use of longer survey periods could decrease the share of zero consumption observations and help on the identification of elasticities.

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    Paper provided by Government Institute for Economic Research Finland (VATT) in its series Working Papers with number 39.

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    Date of creation: 20 Sep 2012
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    Handle: RePEc:fer:wpaper:39
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    1. Nabil Annabi & John Cockburn & Bernard Decaluwé, 2006. "Functional Forms and Parametrization of CGE Models," Working Papers MPIA 2006-04, PEP-MPIA.
    2. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-71, July.
    3. Dixon, Peter B. & Parmenter, B.R., 1996. "Computable general equilibrium modelling for policy analysis and forecasting," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 1, pages 3-85 Elsevier.
    4. Barnes, Roberta & Gillingham, Robert, 1984. "Demographic Effects in Demand Analysis: Estimation of the Quadratic Expenditure System Using Microdata," The Review of Economics and Statistics, MIT Press, vol. 66(4), pages 591-601, November.
    5. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March.
    6. John Creedy, 2001. "Indirect tax reform and the role of exemptions," Fiscal Studies, Institute for Fiscal Studies, vol. 22(4), pages 457-486., December.
    7. Cornwell, A. & Creedy, J., 1995. "CArbon Taxation, Prices and Inequality in Australia," Department of Economics - Working Papers Series 481, The University of Melbourne.
    8. Willenbockel, Dirk, 2004. "Specification choice and robustness in CGE trade policy analysis with imperfect competition," Economic Modelling, Elsevier, vol. 21(6), pages 1065-1099, December.
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