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Computing Densities and Expectations in Stochastic Recursive Economies: Generalized Look-Ahead Techniques

Author

Listed:
  • Richard Anton Braun

    (Faculty of Economics, University of Tokyo)

  • Huiyu Li

    (Graduate School of Economics, University of Tokyo)

  • John Stachurski

    (Institute of Economic Research, Kyoto University)

Abstract

We propose a generalized look-ahead estimator for computing densities and expectations in economic models. We provide conditions under which the estimator converges globally with probability one, and exhibit the asymptotic distribution of the error. Our estimator is more efficient than other Monte Carlo based approaches. Numerical experiments indicate that the estimator can provide large increases in accuracy and speed relative to traditional methods. Particular applications we consider are the stochastic growth model and an income fluctuation problem.

Suggested Citation

  • Richard Anton Braun & Huiyu Li & John Stachurski, 2009. "Computing Densities and Expectations in Stochastic Recursive Economies: Generalized Look-Ahead Techniques," CIRJE F-Series CIRJE-F-620, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2009cf620
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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf620.pdf
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    References listed on IDEAS

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    1. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
    2. Aubhik Khan & Julia K. Thomas, 2008. "Idiosyncratic Shocks and the Role of Nonconvexities in Plant and Aggregate Investment Dynamics," Econometrica, Econometric Society, vol. 76(2), pages 395-436, March.
    3. William A. Brock & Leonard J. Mirman, 2001. "Optimal Economic Growth And Uncertainty: The Discounted Case," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 1, pages 3-37, Edward Elgar Publishing.
    4. S. Rao Aiyagari, 1994. "Uninsured Idiosyncratic Risk and Aggregate Saving," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 659-684.
    5. John Stachurski, 2008. "Continuous State Dynamic Programming via Nonexpansive Approximation," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 141-160, March.
    6. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    7. John Stachurski, 2009. "Economic Dynamics: Theory and Computation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012774, December.
    8. Shane G. Henderson & Peter W. Glynn, 2001. "Computing Densities for Markov Chains via Simulation," Mathematics of Operations Research, INFORMS, vol. 26(2), pages 375-400, May.
    9. Lars Ljungqvist & Thomas J. Sargent, 2004. "Recursive Macroeconomic Theory, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026212274x, December.
    10. Anthony A Smith & Fatih Guvenen, 2006. "What Do Labor and Consumption Data Jointly Tell About Labor Income Risk?," 2006 Meeting Papers 500, Society for Economic Dynamics.
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