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Solving heterogeneous-agent models with parameterized cross-sectional distributions

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Author Info
Yann Algan
Olivier Allais
Wouter J. Den Haan

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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.

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Paper provided by PSE (Ecole normale supérieure) in its series PSE Working Papers with number 2006-46.

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Date of creation: 2006
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Handle: RePEc:pse:psecon:2006-46

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  1. Bruce Preston & Mauro Roca, 2007. "Incomplete Markets, Heterogeneity and Macroeconomic Dynamics," NBER Working Papers 13260, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  2. Miao, Jianjun, 2006. "Competitive equilibria of economies with a continuum of consumers and aggregate shocks," Journal of Economic Theory, Elsevier, vol. 128(1), pages 274-298, May. [Downloadable!] (restricted)
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  3. 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. [Downloadable!] (restricted)
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  4. den Haan, Wouter J & Marcet, Albert, 1990. "Solving the Stochastic Growth Model by Parameterizing Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 31-34, January.
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  5. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December. [Downloadable!] (restricted)
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  6. 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. [Downloadable!] (restricted)
  7. Jose-Victor Rios-Rull, 1997. "Computation of equilibria in heterogeneous agent models," Staff Report 231, Federal Reserve Bank of Minneapolis. [Downloadable!]
  8. Per Krusell & Anthony A. Smith & Jr., 1998. "Income and Wealth Heterogeneity in the Macroeconomy," Journal of Political Economy, University of Chicago Press, vol. 106(5), pages 867-896, October. [Downloadable!] (restricted)
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  9. repec:cup:macdyn:v:1:y:1997:i:2:p:355-86 is not listed on IDEAS
  10. Michael Reiter, 2006. "Solving Heterogeneous-Agent Models by Projection and Perturbation," Economics Working Papers 972, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
  11. Eric R Young, 2005. "Approximate Aggregation," Computing in Economics and Finance 2005 141, Society for Computational Economics. [Downloadable!]
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  12. Marcelo L. Veracierto, 2002. "Plant-Level Irreversible Investment and Equilibrium Business Cycles," American Economic Review, American Economic Association, vol. 92(1), pages 181-197, March. [Downloadable!]
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  1. Covas, Francisco & Den Haan, Wouter, 2007. "The Role of Debt and Equity Finance over the Business Cycle," CEPR Discussion Papers 6145, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  2. Michael Reiter, 2006. "Solving Heterogeneous-Agent Models by Projection and Perturbation," Economics Working Papers 972, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
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