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Solving heterogeneous-agent models with parameterized cross-sectional distributions

Author

Listed:
  • Yann Algan

    (CEPREMAP - Centre pour la recherche économique et ses applications - ECO ENS-PSL - Département d'économie de l'ENS-PSL - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres)

  • Olivier Allais

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

  • Wouter den Haan

Abstract

A new algorithm is developed to solve models with heterogeneous agents and aggregate uncertainty. Projection methods are the main building blocks of the algorithm and – in contrast to the most popular solution procedure – simulations only play a very minor role. The paper also develops a new simulation procedure that not only avoids cross-sectional sampling variation but is 10 (66) times faster than simulating an economy with 10,000 (100,000) agents. Because it avoids cross-sectional sampling variation, it can generate an accurate representation of the whole cross-sectional distribution. Finally, the paper outlines a set of accuracy tests.

Suggested Citation

  • Yann Algan & Olivier Allais & Wouter den Haan, 2008. "Solving heterogeneous-agent models with parameterized cross-sectional distributions," Post-Print hal-03596370, HAL.
    • Handle: RePEc:hal:journl:hal-03596370
    DOI: 10.1016/j.jedc.2007.03.007
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    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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