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Computational accuracy and distributional analysis in models with incomplete markets and aggregate uncertainty

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  • Horvath, Michal

Abstract

This paper shows that grid-based numerical solutions to models with incomplete markets and aggregate uncertainty are sensitive to the number and placement of grid points in the aggregate asset holdings direction. Higher moments of the cross-sectional distribution of asset holdings can be particularly affected, which is important for welfare analysis. The paper recommends using grids that have few grid points for aggregate assets overall but are denser around the mean of the ergodic distribution of individual asset holdings. The fact that the accuracy of the approximation to decision functions can be much improved this way is captured by Den Haan’s (2010) dynamic Euler equation test but not by the traditionally used R2 statistic.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecolet:v:117:y:2012:i:1:p:276-279
    DOI: 10.1016/j.econlet.2012.05.017
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    References listed on IDEAS

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    1. Krusell, Per & Smith, Anthony A., 1997. "Income And Wealth Heterogeneity, Portfolio Choice, And Equilibrium Asset Returns," Macroeconomic Dynamics, Cambridge University Press, vol. 1(2), pages 387-422, June.
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    4. Den Haan, Wouter J. & Judd, Kenneth L. & Juillard, Michel, 2010. "Computational suite of models with heterogeneous agents: Incomplete markets and aggregate uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 1-3, January.
    5. Thomas, Jonathan & Worrall, Tim, 1990. "Income fluctuation and asymmetric information: An example of a repeated principal-agent problem," Journal of Economic Theory, Elsevier, vol. 51(2), pages 367-390, August.
    6. 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.
    7. 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.
    8. Den Haan, Wouter J., 2010. "Comparison of solutions to the incomplete markets model with aggregate uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 34(1), pages 4-27, January.
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    Cited by:

    1. Michael C. Hatcher & Eric M. Scheffel, 2016. "Solving the Incomplete Markets Model in Parallel Using GPU Computing and the Krusell–Smith Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 569-591, December.
    2. Marco Cozzi, 2015. "The Krusell–Smith Algorithm: Are Self-Fulfilling Equilibria Likely?," Computational Economics, Springer;Society for Computational Economics, vol. 46(4), pages 653-670, December.

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    More about this item

    Keywords

    Incomplete markets; Aggregate uncertainty; Heterogeneous agents; Simulations; Numerical solutions;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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