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Comparison of Solutions to the Incomplete Markets Model with Aggregate Uncertainty

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  • Den Haan, Wouter

Abstract

This paper compares numerical solutions to the model of Krusell and Smith (1998) generated by different numerical algorithms. The algorithms have very similar implications for the correlations between different variables. Larger differences are observed for (i) the unconditional means and standard deviations of individual variables, (ii) the behavior of individual agents during particularly bad times, (iii) the volatility of the per capita capital stock, and (iv) the behavior of the higher-order moments of the cross-sectional distribution. For example, the two algorithms that differ the most from each other generate individual consumption series that have an average (maximum) difference of 1.6% (11.4%). Several outcomes of this comparison project should be useful in using these and other algorithms in future work.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 7019.

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Date of creation: Oct 2008
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Handle: RePEc:cpr:ceprdp:7019
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Keywords: approximations; numerical solutions;

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Find related papers by JEL classification:
  • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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  1. 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.
  2. Krusell, Per & Smith, Anthony A., 1997. "Income And Wealth Heterogeneity, Portfolio Choice, And Equilibrium Asset Returns," Macroeconomic Dynamics, Cambridge University Press, vol. 1(02), pages 387-422, June.
  3. Maliar, Lilia & Maliar, Serguei & Valli, Fernando, 2010. "Solving the incomplete markets model with aggregate uncertainty using the Krusell-Smith algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 42-49, January.
  4. Michael Reiter, 2006. "Solving heterogeneous-agent models by projection and perturbation," Economics Working Papers 972, Department of Economics and Business, Universitat Pompeu Fabra.
  5. Christopher D. Carroll, 2005. "The Method of Endogenous Gridpoints for Solving Dynamic Stochastic Optimization Problems," NBER Technical Working Papers 0309, National Bureau of Economic Research, Inc.
  6. Yann Algan & Olivier Allais & Wouter J Den Haan, 2010. "Solving the incomplete markets model with aggregate uncertainty using parameterized cross-sectional distributions," Working Papers 31290, Institut National de la Recherche Agronomique, France.
  7. Jose-Victor Rios-Rull, 1997. "Computation of equilibria in heterogeneous agent models," Staff Report 231, Federal Reserve Bank of Minneapolis.
  8. Per Krusell & Anthony A. Smith, Jr., . "Income and Wealth Heterogeneity in the Macroeconomy," GSIA Working Papers 1997-37, Carnegie Mellon University, Tepper School of Business.
  9. Manuel S. Santos & Adrian Peralta-Alva, 2003. "Accuracy Of Simulations For Stochastic Dynamic Models," Economics Working Papers we034615, Universidad Carlos III, Departamento de Economía.
  10. 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.
  11. Michael Reiter, 2000. "Estimating The Accuracy Of Numerical Solutions To Dynamic Optimization Problems," Computing in Economics and Finance 2000 254, Society for Computational Economics.
  12. Den Haan, Wouter J., 2010. "Assessing the accuracy of the aggregate law of motion in models with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 79-99, January.
  13. Manuel S. Santos, 2000. "Accuracy of Numerical Solutions using the Euler Equation Residuals," Econometrica, Econometric Society, vol. 68(6), pages 1377-1402, November.
  14. Den Haan, Wouter J & Marcet, Albert, 1994. "Accuracy in Simulations," Review of Economic Studies, Wiley Blackwell, vol. 61(1), pages 3-17, January.
  15. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
  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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Cited by:

  1. Muffasir Badshah & Paul Beaumont & Anuj Srivastava, 2013. "Computing Equilibrium Wealth Distributions in Models with Heterogeneous-Agents, Incomplete Markets and Idiosyncratic Risk," Computational Economics, Society for Computational Economics, vol. 41(2), pages 171-193, February.
  2. Jose Lopez, 2012. "Labor Supply, Aggregation and the Labor Wedge," 2012 Meeting Papers 737, Society for Economic Dynamics.
  3. Thomas Mertens, 2012. "Solving General Incomplete Market Models with Substantial Heterogeneity," 2012 Meeting Papers 1173, Society for Economic Dynamics.
  4. Den Haan, Wouter J. & De Wind, Joris, 2012. "Nonlinear and stable perturbation-based approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1477-1497.
  5. Michael Reiter, 2009. "Approximate Aggregation in Heterogeneous-Agent Models," 2009 Meeting Papers 733, Society for Economic Dynamics.
  6. Bilbiie, Florin Ovidiu & Monacelli, Tommaso & Perotti, Roberto, 2012. "Public Debt and Redistribution with Borrowing Constraints," CEPR Discussion Papers 9088, C.E.P.R. Discussion Papers.
  7. 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.
  8. Marco Cozzi, 2014. "The Krusell-Smith Algorithm: Are Self-fulfilling Equilibria Likely?," Working Papers 1323, Queen's University, Department of Economics.
  9. Bi, Huixin & Leeper, Eric M. & Leith, Campbell, 2012. "Uncertain Fiscal Consolidations," SIRE Discussion Papers 2012-09, Scottish Institute for Research in Economics (SIRE).
  10. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2011. "How to Solve Dynamic Stochastic Models Computing Expectations Just Once," NBER Working Papers 17418, National Bureau of Economic Research, Inc.
  11. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2014. "Lower Bounds on Approximation Errors: Testing the Hypothesis That a Numerical Solution Is Accurate?," BYU Macroeconomics and Computational Laboratory Working Paper Series 2014-06, Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory.
  12. Grey Gordon, 2011. "Computing Dynamic Heterogeneous-Agent Economies: Tracking the Distribution," PIER Working Paper Archive 11-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  13. Horvath, Michal, 2012. "Computational accuracy and distributional analysis in models with incomplete markets and aggregate uncertainty," Economics Letters, Elsevier, vol. 117(1), pages 276-279.
  14. Tobias Grasl, 2013. "Solving Incomplete Markets Models by Derivative Aggregation," Birkbeck Working Papers in Economics and Finance 1302, Birkbeck, Department of Economics, Mathematics & Statistics.
  15. Hull, Isaiah, 2013. "Approximate dynamic programming with postdecision states as a solution method for dynamic economic models," Working Paper Series 276, Sveriges Riksbank (Central Bank of Sweden).

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