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A generalized endogenous grid method for discrete-continuous choice


  • John Rust

    (University of Maryland)

  • Bertel Schjerning

    (University of Copenhagen)

  • Fedor Iskhakov

    (University of Technology Sydney)


This paper extends Carroll's endogenous grid method (2006 "The method of endogenous gridpoints for solving dynamic stochastic optimization problems", Economic Letters) for models with sequential discrete and continuous choice. Unlike existing generalizations, we propose solution algorithm that inherits both advantages of the original method, namely it avoids all root finding operations, and also efficiently deals with restrictions on the continuous decision variable. To further speed up the solution, we perform the inevitable optimization across discrete decisions as more efficient computation of upper envelope of a set of piece-wise linear functions. We formulate the algorithm relying as little as possible on a particular model specification, and precisely define the class of dynamic stochastic optimal control problems it can be applied to. We illustrate our algorithm using finite horizon discrete sector choice model with consumption-savings decisions and borrowing constraints, and show that in comparison to the traditional approach the proposed method runs at least an order of magnitude faster to deliver the same precision of the solution. To implement the method we develop a generic software package that includes pseudo-language for easy model specification and computational modules which support both shared memory and cluster parallelization. The package is wrapped in a Matlab class and incurs low start-up cost to the user. The software package is accessible in public domain.

Suggested Citation

  • John Rust & Bertel Schjerning & Fedor Iskhakov, 2012. "A generalized endogenous grid method for discrete-continuous choice," 2012 Meeting Papers 1162, Society for Economic Dynamics.
  • Handle: RePEc:red:sed012:1162

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    References listed on IDEAS

    1. 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.
    2. 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.
    3. 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.
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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. Alexander Ludwig & Matthias Schön, 2018. "Endogenous Grids in Higher Dimensions: Delaunay Interpolation and Hybrid Methods," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 463-492, March.
    3. Daphne Chen & Shi Qi & Don Schlagenhauf, 2018. "Corporate Income Tax, Legal Form of Organization, and Employment," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(4), pages 270-304, October.
    4. Zuzana Mucka & Ludovit Odor, 2018. "Optimal sovereign debt: Case of Slovakia," Working Papers Working Paper No. 3/2018, Council for Budget Responsibility.
    5. Robert Kirkby Author-Email:|, 2017. "Convergence of Discretized Value Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 117-153, January.
    6. Matthew N. White, 2014. "Endogenous Gridpoints in Multiple Dimensions: Interpolation on Non-Linear Grids," Working Papers 14-17, University of Delaware, Department of Economics.
    7. David Love & Lucie Schmidt, 2015. "Comprehensive Wealth of Immigrants and Natives," Working Papers wp328, University of Michigan, Michigan Retirement Research Center.

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