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Solving Heterogeneous-agent Models with Parameterized Cross-sectional Distributions

Author

Listed:
  • Yann Algan

    (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

  • Olivier Allais

    (CORELA - Laboratoire de Recherche sur la Consommation - INRA - Institut National de la Recherche Agronomique)

  • Wouter J den Haan

    (Department of Economics - Tilburg University [Netherlands])

Abstract
A new algorithm is developed to solve models with heterogeneous agents and aggregate uncertainty that avoids some disadvantages of the prevailing algorithm that strongly relies on simulation techniques and is easier to implement than existing algorithms. A key aspect of the algorithm is a new procedure that parameterizes the cross-sectional distribution, which makes it possible to avoid Monte Carlo integration. The paper also develops a new simulation procedure that not only avoids cross-sectional sampling variation but is also more than ten times faster than the standard procedure of simulating an economy with a large but finite number of agents. This procedure can help to improve the efficiency of the most popular algorithm in which simulation procedures play a key role.

Suggested Citation

  • Yann Algan & Olivier Allais & Wouter J den Haan, 2007. "Solving Heterogeneous-agent Models with Parameterized Cross-sectional Distributions," Working Papers hal-01065666, HAL.
    • Handle: RePEc:hal:wpaper:hal-01065666
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-01065666
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    References listed on IDEAS

    as
    1. Den Haan, Wouter J, 1996. "Heterogeneity, Aggregate Uncertainty, and the Short-Term Interest Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 399-411, October.
    2. Christiano, Lawrence J. & Fisher, Jonas D. M., 2000. "Algorithms for solving dynamic models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 24(8), pages 1179-1232, July.
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    7. Krueger, Dirk & Kubler, Felix, 2004. "Computing equilibrium in OLG models with stochastic production," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1411-1436, April.
    8. Reiter, Michael, 2009. "Solving heterogeneous-agent models by projection and perturbation," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 649-665, March.
    9. Eric R Young, 2005. "Approximate Aggregation," Computing in Economics and Finance 2005 141, Society for Computational Economics.
    10. Bruce Preston & Mauro Roca, 2007. "Incomplete Markets, Heterogeneity and Macroeconomic Dynamics," NBER Working Papers 13260, National Bureau of Economic Research, Inc.
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    12. Michael Reiter, 2001. "Recursive Solution Of Heterogeneous Agent Models," Computing in Economics and Finance 2001 167, Society for Computational Economics.
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    More about this item

    Keywords

    Incomplete markets; numerical solutions; projection methods; simulations;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets

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