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Linking Microsimulation and CGE models

Author

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  • Andreas Peichl

    () (ZEW, University of Mannheim, L7, 1, Mannheim, Germany)

Abstract

In this note, I review the history of CGE-Microsimulation modeling, and the main methodological issues involved.

Suggested Citation

  • Andreas Peichl, 2016. "Linking Microsimulation and CGE models," International Journal of Microsimulation, International Microsimulation Association, vol. 9(1), pages 167-174.
  • Handle: RePEc:ijm:journl:v:9:y:2016:i:1:p:167-174
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    File URL: http://microsimulation.org/IJM/V9_1/IJM_9_1_2016_Peichl.pdf
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    References listed on IDEAS

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    1. Dolls, Mathias & Fuest, Clemens & Peichl, Andreas, 2012. "Automatic stabilizers and economic crisis: US vs. Europe," Journal of Public Economics, Elsevier, vol. 96(3), pages 279-294.
    2. Kehoe, Timothy J & Prescott, Edward C, 1995. "Introduction to the Symposium: The Discipline of Applied General Equilibrium," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 6(1), pages 1-11, June.
    3. James B Davies, 2009. "Combining microsimulation with CGE and macro modelling for distributional analysis in developing and transition countries," International Journal of Microsimulation, International Microsimulation Association, vol. 2(1), pages 49-56.
    4. Mankiw, N. Gregory & Weinzierl, Matthew, 2006. "Dynamic scoring: A back-of-the-envelope guide," Journal of Public Economics, Elsevier, vol. 90(8-9), pages 1415-1433, September.
    5. Olivier Bargain & Herwig Immervoll & Andreas Peichl & Sebastian Siegloch, 2012. "Distributional consequences of labor-demand shocks: the 2008–2009 recession in Germany," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(1), pages 118-138, February.
    6. Peichl, Andreas & Siegloch, Sebastian, 2012. "Accounting for labor demand effects in structural labor supply models," Labour Economics, Elsevier, vol. 19(1), pages 129-138.
    7. Magnani, Riccardo & Mercenier, Jean, 2009. "On linking microsimulation and computable general equilibrium models using exact aggregation of heterogeneous discrete-choice making agents," Economic Modelling, Elsevier, vol. 26(3), pages 560-570, May.
    8. Salvador Barrios & Mathias Dolls & Anamaria Maftei & Andreas Peichl & Sara Riscado & Janos Varga & Christian Wittneben, 2016. "Dynamic scoring of tax reforms in the European Union," JRC Working Papers on Taxation & Structural Reforms 2016-03, Joint Research Centre (Seville site).
    9. Olivier Bargain & Kristian Orsini & Andreas Peichl, 2014. "Comparing Labor Supply Elasticities in Europe and the United States: New Results," Journal of Human Resources, University of Wisconsin Press, vol. 49(3), pages 723-838.
    10. Jane G. Gravelle, 2015. "Dynamic Scoring: Counterpoint," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(4), pages 979-981, September.
    11. Andreas Peichl, 2009. "The benefits and problems of linking micro and macromodels - Evidence from a flat tax analysis," Journal of Applied Economics, Universidad del CEMA, vol. 12, pages 301-329, November.
    12. Olivier Bargain & Mathias Dolls & Clemens Fuest & Dirk Neumann & Andreas Peichl & Nico Pestel & Sebastian Siegloch, 2013. "Fiscal union in Europe? Redistributive and stabilizing effects of a European tax-benefit system and fiscal equalization mechanism," Economic Policy, CEPR;CES;MSH, vol. 28(75), pages 375-422, July.
    13. Holly Sutherland & Francesco Figari, 2013. "EUROMOD: the European Union tax-benefit microsimulation model," International Journal of Microsimulation, International Microsimulation Association, vol. 1(6), pages 4-26.
    14. Jane G. Gravelle, 2015. "Dynamic Scoring," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 34(4), pages 970-977, September.
    15. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    16. Peichl, Andreas, 2009. "Benefits and problems of linking micro and macro models - evidence from a flat tax analysis," ISER Working Paper Series 2009-02, Institute for Social and Economic Research.
    17. François Bourguignon & Maurizio Bussolo & John Cockburn, 2010. "Guest Editorial - Macro-micro analytics: background, motivation, advantages and remaining challenges," International Journal of Microsimulation, International Microsimulation Association, vol. 3(1), pages 1-7.
    18. Verboven, Frank, 1996. "The nested logit model and representative consumer theory," Economics Letters, Elsevier, vol. 50(1), pages 57-63, January.
    19. Jinjing Li & Cathal O'Donoghue, 2013. "A survey of dynamic microsimulation models: uses, model structure and methodology," International Journal of Microsimulation, International Microsimulation Association, vol. 6(2), pages 3-55.
    20. Boeters, Stefan & Savard, Luc, 2013. "The Labor Market in Computable General Equilibrium Models," Handbook of Computable General Equilibrium Modeling, Elsevier.
    21. Stuart Adam & Antoine Bozio, 2009. "Dynamic scoring," OECD Journal on Budgeting, OECD Publishing, vol. 9(2), pages 1-26.
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    Cited by:

    1. Salvador Barrios & Mathias Dolls & Anamaria Maftei & Andreas Peichl & Sara Riscado & Janos Varga & Christian Wittneben, 2016. "Dynamic scoring of tax reforms in the European Union," JRC Working Papers on Taxation & Structural Reforms 2016-03, Joint Research Centre (Seville site).

    More about this item

    Keywords

    Microsimulation; CGE; linked micro macro models;

    JEL classification:

    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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