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Meta-Regression Estimates for CGE Models: A Case Study for Input Substitution Elasticities in Production Agriculture


  • Boys, Kathryn A.
  • Florax, Raymond J.G.M.


The selection of appropriate parameters for computable general equilibrium (CGE) models critically affects the results of applied economic modeling exercises. Valid and reliable parameter selection models are needed, and typically comprise direct estimation, expert opinion, or copycatting of results from seminal studies. The purpose of this study is to use meta-analysis to summarize and more accurately estimate elasticities of input substitution, specifically between labor and other inputs in agricultural production. We construct a comprehensive database of elasticity estimates through an extensive literature review, and perform a meta-regression analysis to identify structural sources of variation in elasticity estimates sampled from primary studies. The use of meta-analysis contributes to improved baseline analysis in CGE simulations because it allows for the computation of input parameters tailored to a specific CGE model setup. We correct for variations in research design, which are typically constant within studies, and account for bias associated with undue selection effects associated with editorial publication decision processes. Improved accuracy and knowledge of the distribution of imputed input parameters derived from a meta-analysis contributes to improved performance of CGE sensitivity analyses.

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  • Boys, Kathryn A. & Florax, Raymond J.G.M., 2007. "Meta-Regression Estimates for CGE Models: A Case Study for Input Substitution Elasticities in Production Agriculture," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 9683, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea07:9683

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    References listed on IDEAS

    1. Gregory S. Amacher & Arun S. Malik & Robert G. Haight, 2005. "Not Getting Burned: The Importance of Fire Prevention in Forest Management," Land Economics, University of Wisconsin Press, vol. 81(2).
    2. Jonathan Yoder, 2004. "Playing with Fire: Endogenous Risk in Resource Management," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 933-948.
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    Cited by:

    1. Ricardo Argüello C & Daniel Valderrama G. & Sandra Acero W., 2011. "Poverty impacts of agricultural policy adjustments in an opening economy: the case of Colombia," DOCUMENTOS DE TRABAJO 008575, UNIVERSIDAD DEL ROSARIO.
    2. David I. Stern, 2012. "Interfuel Substitution: A Meta‐Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 26(2), pages 307-331, April.
    3. Hess, Sebastian & von Cramon-Taubadel, Stephan, 2008. "Agricultural Trade Policy Modelling: Insights from a Meta-Analysis of Doha Development Agenda Outcomes," Commissioned Papers 43466, Canadian Agricultural Trade Policy Research Network.
    4. Liu, Boying & Richard Shumway, C., 2016. "Substitution elasticities between GHG-polluting and nonpolluting inputs in agricultural production: A meta-regression," Energy Economics, Elsevier, vol. 54(C), pages 123-132.

    More about this item


    meta-analysis; cross-price elasticity; input substitu¬tion; agricultural production; CGE parameters; Demand and Price Analysis; C13; C68; Q13;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness


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