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Testing the Statistical Significance of Microsimulation Results: A Plea

Author

Listed:
  • Tim Goedemé

    (Herman Deleeck Centre for Social Policy, University of Antwerp)

  • Karel Van den Bosch

    (Belgian Federal Planning Bureau, Herman Deleeck Centre for Social Policy, University of Antwerp)

  • Lina Salanauskaite

    (Herman Deleeck Centre for Social Policy, University of Antwerp)

  • Gerlinde Verbist

    (Herman Deleeck Centre for Social Policy, University of Antwerp)

Abstract

In the microsimulation literature, it is still uncommon to test the statistical significance of results. In this article we argue that this situation is both undesirable and unnecessary. Provided the parameters used in the microsimulation are exogenous, as is often the case in static microsimulation of the first-order effects of policy changes, simple statistical tests can be sufficient. Moreover, standard routines have been developed which enable applied researchers to calculate the sampling variance of microsimulation results, while taking the sample design into account, even of relatively complex statistics such as relative poverty, inequality measures and indicators of polarization, with relative ease and a limited time investment. We stress that when comparing simulated and baseline variables, as well as when comparing two simulated variables, it is crucial to take account of the covariance between those variables. Due to this covariance, the mean difference between the variables can generally (though not always) be estimated with much greater precision than the means of the separate variables.

Suggested Citation

  • Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: A Plea," International Journal of Microsimulation, International Microsimulation Association, vol. 6(3), pages 50-77.
    • Handle: RePEc:ijm:journl:v:6:y:2013:i:3:p:50-77
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    Cited by:

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    2. Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin & Kopasker, Daniel & Vittal Katikireddi, Srinivasa, 2023. "SimPaths: an open-source microsimulation model for life course analysis," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA6/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    3. Ross Richardson & Lia Pacelli & Ambra Poggi & Matteo Richiardi, 2018. "Female Labour Force Projections Using Microsimulation for Six EU Countries," International Journal of Microsimulation, International Microsimulation Association, vol. 11(2), pages 5-51.
    4. Leventi, Chrysa & Katsimi, Margarita & Tsakloglou, Panos, 2022. "Going regional: distributional effect of taxes and transfers in six EU countries and the UK," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA4/22, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    5. Filauro Stefano & Grünberger Klaus & Narazani Edlira, 2025. "Coordinated Minimum Wage Policies: Impacts on EU-Level Income Inequality," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 25(2), pages 209-246.
    6. Leventi, Chrysa & Rastrigina, Olga & Sutherland, Holly, 2015. "Nowcasting: estimating developments in the risk of poverty and income distribution in 2013 and 2014," EUROMOD Working Papers EM12/15, EUROMOD at the Institute for Social and Economic Research.
    7. Manos Matsaganis & Chrysa Leventi, 2014. "Distributive Effects of the Crisis and Austerity in Seven EU Countries," ImPRovE Working Papers 14/04, Herman Deleeck Centre for Social Policy, University of Antwerp.
    8. Jan Pablo Burgard & Hanna Dieckmann & Joscha Krause & Hariolf Merkle & Ralf Münnich & Kristina M. Neufang & Simon Schmaus, 2020. "A generic business process model for conducting microsimulation studies," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 191-211, August.
    9. Andrea Albarea & Michele Bernasconi & Anna Marenzi & Dino Rizzi, 2020. "Income Underreporting and Tax Evasion in Italy: Estimates and Distributional Effects," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(4), pages 904-930, December.
    10. Fidel Picos & Marie-Luise Schmitz, 2016. "In-depth analysis of tax reforms using the EUROMOD microsimulation model," JRC Working Papers on Taxation & Structural Reforms 2016-06, Joint Research Centre.

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    More about this item

    Keywords

    Microsimulation; statistical inference; EUROMOD.;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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