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

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

Abstract

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.

Suggested Citation

  • 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," Conference papers 331632, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    • Handle: RePEc:ags:pugtwp:331632
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    Cited by:

    1. David I. Stern, 2012. "Interfuel Substitution: A Meta‐Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 26(2), pages 307-331, April.
    2. Peters, Glen, 2008. "Reassessing Carbon Leakage," Conference papers 331753, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    3. Jian Chai & Huiting Shi & Xiaoyang Zhou & Shouyang Wang, 2018. "The Price Elasticity of Natural Gas Demand in China: A Meta-Regression Analysis," Energies, MDPI, vol. 11(12), pages 1-18, November.
    4. Choumert Nkolo, Johanna & Combes Motel, Pascale & Guegang Djimeli, Charlain, 2018. "Income-generating Effects of Biofuel Policies: A Meta-analysis of the CGE Literature," Ecological Economics, Elsevier, vol. 147(C), pages 230-242.
    5. Ricardo Arguello 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 8575, Universidad del Rosario.
    6. Meyer, Bernd & Ahlert, Gerd, 2019. "Imperfect Markets and the Properties of Macro-economic-environmental Models as Tools for Policy Evaluation," Ecological Economics, Elsevier, vol. 155(C), pages 80-87.
    7. Guèye, Adama, 2014. "Normes SPS et compétitivité-qualité de la filière fruits et légumes frais au Sénégal," Conference papers 332558, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    8. Ricardo Argüello & Daniel Valderrama-Gonzalez, 2015. "Sectoral and poverty impacts of agricultural policy adjustments in Colombia," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 259-280, March.
    9. 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.
    10. 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.

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