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Statistical Inference in Micro Simulation Models: Incorporationg External Information

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  • Klevmarken, N.A.

Abstract

In practical applications of micro simulation models very little is usually known about the properties of the simulated values. This paper argues that we need to apply the same rigourous standards for inference in micro simulation work as in scientific worl generally. If not, then micro simulation models will loose in credibility.

Suggested Citation

  • Klevmarken, N.A., 1998. "Statistical Inference in Micro Simulation Models: Incorporationg External Information," Papers 1998:20, Uppsala - Working Paper Series.
  • Handle: RePEc:fth:uppaal:1998:20
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    1. Anders Klevmarken, N., 2002. "Statistical inference in micro-simulation models: incorporating external information," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(1), pages 255-265.
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    Cited by:

    1. repec:ijm:journl:v10:y:2017:i:1:p:106-134 is not listed on IDEAS
    2. Michal Myck & Mateusz Najsztub, 2015. "Data and Model Cross-validation to Improve Accuracy of Microsimulation Results: Estimates for the Polish Household Budget Survey," International Journal of Microsimulation, International Microsimulation Association, vol. 8(1), pages 33-66.
    3. Bianchi, Carlo & Cirillo, Pasquale & Gallegati, Mauro & Vagliasindi, Pietro A., 2008. "Validation in agent-based models: An investigation on the CATS model," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 947-964, September.
    4. Carlo Bianchi & Pasquale Cirillo & Mauro Gallegati & Pietro Vagliasindi, 2007. "Validating and Calibrating Agent-Based Models: A Case Study," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 245-264, October.
    5. Matteo Richiardi & Ross E. Richardson, 2017. "JAS-mine: A new platform for microsimulation and agent-based modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 10(1), pages 106-134.
    6. Eugenio Zucchelli & Andrew M Jones & Nigel Rice, 2012. "The evaluation of health policies through dynamic microsimulation methods," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 2-20.
    7. Vincent Touzé & Cyrille Hagneré & Gaël Dupont, 2003. "Les modèles de microsimulation dynamique dans l’analyse des réformes des systèmes de retraites : une tentative de bilan," Économie et Prévision, Programme National Persée, vol. 160(4), pages 167-191.
    8. Anders Klevmarken, N., 2002. "Statistical inference in micro-simulation models: incorporating external information," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(1), pages 255-265.
    9. Zamac, Jovan & Hallberg, Daniel & Lindh, Thomas, 2008. "Low fertility and long run growth in an economy with a large public sector," Arbetsrapport 2008:11, Institute for Futures Studies.
    10. Zucchelli, E & Jones, A.M & Rice, N, 2010. "The evaluation of health policies through microsimulation methods," Health, Econometrics and Data Group (HEDG) Working Papers 10/03, HEDG, c/o Department of Economics, University of York.
    11. Goedemé, Tim & Van den Bosch, Karel & Salanauskaite, Lina & Verbist, Gerlinde, 2013. "Testing the statistical significance of microsimulation results: often easier than you think. A technical note," EUROMOD Working Papers EM18/13, EUROMOD at the Institute for Social and Economic Research.
    12. 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.
    13. Pasquale Cirillo & Mauro Gallegati, 2012. "The Empirical Validation of an Agent-based Model," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 38(4), pages 525-547.

    More about this item

    Keywords

    ECONOMIC MODELS ; SIMULATION;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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