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A Generalized Endogenous Grid Method for Non-concave Problems

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  • Giulio Fella

    (Queen Mary, University of London)

Abstract

This paper extends Carroll's (2006) endogenous grid method and its combination with value function iteration by Barillas and Fernández-Villaverde (2007) to non-concave problems. The method is illustrated using a consumer problem in which consumers choose both durable and non-durable consumption. The durable choice is discrete and subject to non-convex adjustment costs. The algorithm yields substantial gains in accuracy and computational time relative to value function iteration, the standard solution choice for non-concave problems.

Suggested Citation

  • Giulio Fella, 2011. "A Generalized Endogenous Grid Method for Non-concave Problems," Working Papers 677, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:677
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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.
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    4. Carroll, Christopher D., 2006. "The method of endogenous gridpoints for solving dynamic stochastic optimization problems," Economics Letters, Elsevier, vol. 91(3), pages 312-320, June.
    5. Storesletten, Kjetil & Telmer, Christopher I. & Yaron, Amir, 2004. "Consumption and risk sharing over the life cycle," Journal of Monetary Economics, Elsevier, vol. 51(3), pages 609-633, April.
    6. Andrew Clausen & Carlo Strub, 2012. "Envelope theorems for non-smooth and non-concave optimization," ECON - Working Papers 062, Department of Economics - University of Zurich.
    7. John P. Rust, 1989. "A Dynamic Programming Model of Retirement Behavior," NBER Chapters, in: The Economics of Aging, pages 359-404, National Bureau of Economic Research, Inc.
    8. Hintermaier, Thomas & Koeniger, Winfried, 2010. "The method of endogenous gridpoints with occasionally binding constraints among endogenous variables," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 2074-2088, October.
    9. Barillas, Francisco & Fernandez-Villaverde, Jesus, 2007. "A generalization of the endogenous grid method," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2698-2712, August.
    10. Patrick Bajari & Phoebe Chan & Dirk Krueger & Daniel Miller, 2013. "A Dynamic Model Of Housing Demand: Estimation And Policy Implications," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 409-442, May.
    11. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
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    Cited by:

    1. White, Matthew N., 2015. "The method of endogenous gridpoints in theory and practice," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 26-41.
    2. Florian Oswald, 2015. "Regional Shocks, Migration and Homeownership," 2015 Meeting Papers 759, Society for Economic Dynamics.
    3. John Rust & Bertel Schjerning & Fedor Iskhakov, 2012. "A generalized endogenous grid method for discrete-continuous choice," 2012 Meeting Papers 1162, Society for Economic Dynamics.
    4. Matthew N. White, 2014. "Endogenous Gridpoints in Multiple Dimensions: Interpolation on Non-Linear Grids," Working Papers 14-17, University of Delaware, Department of Economics.
    5. Florian Oswald, 2015. "Regional Shocks, Migration and Homeownership," Sciences Po publications info:hdl:2441/n1d9kd7k48k, Sciences Po.
    6. repec:hal:spmain:info:hdl:2441/n1d9kd7k48keoo4brb07foqbd is not listed on IDEAS
    7. Jørgensen, Thomas H., 2013. "Structural estimation of continuous choice models: Evaluating the EGM and MPEC," Economics Letters, Elsevier, vol. 119(3), pages 287-290.

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    More about this item

    Keywords

    Endogenous grid method; Non-concavity;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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