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Solving Heterogeneous-agent Models with Parameterized Cross-sectional Distributions

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  • Olivier Allais

    (Laboratoire de Recherche sur la Consommation)

  • Wouter J Den Haan

    (Department of Economics (LSE))

  • Yann Algan

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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Bibliographic Info

Paper provided by Sciences Po in its series Sciences Po publications with number 2006 - 46.

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Date of creation: 19 Dec 2006
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Handle: RePEc:spo:wpmain:info:hdl:2441/8845

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Keywords: incomplete markets; numerical solutions; projection methods; simulations;

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References

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  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. 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.
  3. 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.
  4. Marcelo Veracierto, 1997. "Plant level irreversible investment and equilibrium business cycles," Discussion Paper / Institute for Empirical Macroeconomics 115, Federal Reserve Bank of Minneapolis.
  5. repec:cup:macdyn:v:1:y:1997:i:2:p:355-86 is not listed on IDEAS
  6. 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.
  7. Lawrence J. Christiano & Jonas D.M. Fisher, 1997. "Algorithms for solving dynamic models with occasionally binding constraints," Working Paper Series, Macroeconomic Issues WP-97-15, Federal Reserve Bank of Chicago.
  8. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
  9. 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.
  10. Jose-Victor Rios-Rull, 1997. "Computation of equilibria in heterogeneous agent models," Staff Report 231, Federal Reserve Bank of Minneapolis.
  11. Den Haan, Wouter J., 1997. "Solving Dynamic Models With Aggregate Shocks And Heterogeneous Agents," Macroeconomic Dynamics, Cambridge University Press, vol. 1(02), pages 355-386, June.
  12. 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.
  13. Michael Reiter, 2001. "Recursive Solution Of Heterogeneous Agent Models," Computing in Economics and Finance 2001 167, Society for Computational Economics.
  14. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
  15. Eric R Young, 2005. "Approximate Aggregation," Computing in Economics and Finance 2005 141, Society for Computational Economics.
  16. 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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Citations

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Cited by:
  1. Den Haan, Wouter, 2008. "Assessing the Accuracy of the Aggregate Law of Motion in Models with Heterogeneous Agents," CEPR Discussion Papers 6971, C.E.P.R. Discussion Papers.
  2. Algan, Yann & Allais, Olivier & Den Haan, Wouter J., 2010. "Solving the incomplete markets model with aggregate uncertainty using parameterized cross-sectional distributions," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 59-68, January.
  3. Den Haan, Wouter & Rendahl, Pontus, 2008. "Solving the Incomplete Markets Model with Aggregate Uncertainty using Explicit Aggregation," CEPR Discussion Papers 6963, C.E.P.R. Discussion Papers.
  4. Michael W. L. Elsby & Ryan Michaels, 2013. "Marginal Jobs, Heterogeneous Firms, and Unemployment Flows," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(1), pages 1-48, January.
  5. Young, Eric R., 2010. "Solving the incomplete markets model with aggregate uncertainty using the Krusell-Smith algorithm and non-stochastic simulations," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 36-41, January.
  6. Yann Algan & Olivier Allais & Eva Carceles-Poveda, 2009. "Macroeconomic Effects of Financial Policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(4), pages 678-696, October.
  7. Francisco Covas & Wouter J. den Haan, 2006. "The Role of Debt and Equity Finance over the Business Cycle," Working Papers 06-45, Bank of Canada.
  8. Bruce Preston & Mauro Roca, 2007. "Incomplete Markets, Heterogeneity and Macroeconomic Dynamics," NBER Working Papers 13260, National Bureau of Economic Research, Inc.
  9. Michael Reiter, 2006. "Solving heterogeneous-agent models by projection and perturbation," Economics Working Papers 972, Department of Economics and Business, Universitat Pompeu Fabra.
  10. Reiter, Michael, 2010. "Solving the incomplete markets model with aggregate uncertainty by backward induction," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 28-35, January.
  11. Lilia Maliar & Fernando Valli & Serguei Maliar, 2009. "Solving the incomplete markets model with aggregate uncertainty using the Krusell-Smith algorithm," Working Papers. Serie AD 2009-03, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  12. Giusto, Andrea, 2014. "Adaptive learning and distributional dynamics in an incomplete markets model," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 317-333.

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