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Identifying key elasticities in a CGE model: a Monte Carlo approach

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  • Antoine Belgodere
  • Charles Vellutini

Abstract

This article presents a simple Monte Carlo (MC) procedure to improve sensitivity analysis in Computable general equilibrium (CGE) modelling. MC experiments provide the modeller with a population of randomly drawn exogenous parameters and corresponding endogenous outcomes. Standard econometrics can then shed light on the relationship between them and help to identify key parameters, particularly key elasticities.

Suggested Citation

  • Antoine Belgodere & Charles Vellutini, 2011. "Identifying key elasticities in a CGE model: a Monte Carlo approach," Applied Economics Letters, Taylor & Francis Journals, vol. 18(17), pages 1619-1622.
    • Handle: RePEc:taf:apeclt:v:18:y:2011:i:17:p:1619-1622
    DOI: 10.1080/13504851.2011.554366
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    Cited by:

    1. Korrakot Phomsoda & Nattapong Puttanapong & Mongkut Piantanakulchai, 2021. "Economic Impacts of Thailand’s Biofuel Subsidy Reallocation Using a Dynamic Computable General Equilibrium (CGE) Model," Energies, MDPI, vol. 14(8), pages 1-21, April.
    2. Yingying Lu & David I. Stern, 2016. "Substitutability and the Cost of Climate Mitigation Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(1), pages 81-107, May.
    3. Korrakot Phomsoda & Nattapong Puttanapong & Mongkut Piantanakulchai, 2021. "Assessing Economic Impacts of Thailand’s Fiscal Reallocation between Biofuel Subsidy and Transportation Investment: Application of Recursive Dynamic General Equilibrium Model," Energies, MDPI, vol. 14(14), pages 1-32, July.
    4. Rehab Osman & Emanuele Ferrari & Scott McDonald, 2016. "Water Scarcity and Irrigation Efficiency in Egypt," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-28, December.
    5. Jared C. Carbone & Linda T.M. Bui & Don Fullerton & Sergey Paltsev & Ian Sue Wing, 2022. "When and How to Use Economy-Wide Models for Environmental Policy Analysis," Annual Review of Resource Economics, Annual Reviews, vol. 14(1), pages 447-465, October.
    6. Osman, Rehab & Ferrari, Emanuele & McDonald, Scott, 2015. "Water Quality Assessment SAM/CGE and Satellite Accounts Integrated Framework," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204291, Agricultural Economics Society.
    7. Sébastien Mary & Euan Phimister & Deborah Roberts & Fabien Santini, 2013. "Testing the sensitivity of CGE results: A Monte Carlo Filtering approach to an application to rural development policies in Aberdeenshire," JRC Research Reports JRC85290, Joint Research Centre.
    8. Britz, Wolfgang & Li, Jingwen & Shang, Linmei, 2021. "Combining large-scale sensitivity analysis in Computable General Equilibrium models with Machine Learning: An Example Application to policy supporting the bio-economy," Conference papers 333285, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    9. Osman, Rehab & Ferrari, Emanuele & McDonald, Scott, 2019. "Is improving Nile water quality ‘fruitful’?," Ecological Economics, Elsevier, vol. 161(C), pages 20-31.
    10. Osman, Rehab & Ferrari, Emanuele & McDonald, Scott, 2015. "Water Quality Assessment SAM/CGE and Satellite Accounts Integrated Framework-Egypt," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204292, Agricultural Economics Society.
    11. Kim, Euijune & Hewings, Geoffrey J.D. & Lee, Changkeun, 2016. "Impact of educational investments on economic losses from population ageing using an interregional CGE-population model," Economic Modelling, Elsevier, vol. 54(C), pages 126-138.
    12. Skelton, Alexandra C.H. & Paroussos, Leonidas & Allwood, Julian M., 2020. "Comparing energy and material efficiency rebound effects: an exploration of scenarios in the GEM-E3 macroeconomic model," Ecological Economics, Elsevier, vol. 173(C).

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    Keywords

    Monte Carlo; elasticities; CGE;
    All these keywords.

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