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Solving heterogeneous-agent models with paramaterized cross-sectional distribution

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.
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Submitted on : Sunday, May 31, 2020 - 12:38:31 PM
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Yann Algan, Olivier Allais, Wouter J. den Haan. Solving heterogeneous-agent models with paramaterized cross-sectional distribution. Journal of Economic Dynamics and Control, 2008, 32 (3), pp.875-908. ⟨10.1016/j.jedc.2007.03.007⟩. ⟨halshs-00754295⟩



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