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Solving Heterogeneous-Agent Models with Parameterized Cross-Sectional Distributions Author info | Abstract | Publisher info | Download info | Related research | Statistics Algan, Yann
Allais, Olivier
Den Haan, Wouter
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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.
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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number
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Date of creation: Jan 2007Date of revision:
Handle: RePEc:cpr:ceprdp:6062Contact details of provider: Postal: Centre for Economic Policy Research, 53--56 Great Sutton Street, London EC1V 0DG Phone: 44 - 20 - 7183 8801 Fax: 44 - 20 - 7183 8820
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Keywords: incomplete markets ; numerical solution ; projection method ; simulation ; Other versions of this item:
Find related papers by JEL classification: C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
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Other versions: Michael Reiter, 2006.
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