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Endogenous Grids in Higher Dimensions: Delaunay Interpolation and Hybrid Methods

Author

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  • Alexander Ludwig

    (SAFE, Goethe University Frankfurt; CMR; MEA; Netspar)

  • Matthias Schön

    (CMR, University of Cologne)

Abstract

This paper investigates extensions of the method of endogenous gridpoints (ENDGM) introduced by Carroll (Econ Lett 91(3):312–320, 2006) to higher dimensions with more than one continuous endogenous state variable. We compare three different categories of algorithms: (i) the conventional method with exogenous grids (EXOGM), (ii) the pure method of endogenous gridpoints (ENDGM) and (iii) a hybrid method (HYBGM). ENDGM comes along with Delaunay interpolation on irregular grids. Comparison of methods is done by evaluating speed and accuracy by using a specific model with two endogenous state variables. We find that HYBGM and ENDGM both dominate EXOGM. In an infinite horizon model, ENDGM also always dominates HYBGM. In a finite horizon model, the choice between HYBGM and ENDGM depends on the number of gridpoints in each dimension. With less than 150 gridpoints in each dimension ENDGM is faster than HYBGM, and vice versa. For a standard choice of 25–50 gridpoints in each dimension, ENDGM is 1.4–1.7 times faster than HYBGM in the finite horizon version and 2.4–2.5 times faster in the infinite horizon version of the model.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:51:y:2018:i:3:d:10.1007_s10614-016-9611-2
    DOI: 10.1007/s10614-016-9611-2
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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. Matthew N. White, 2014. "Endogenous Gridpoints in Multiple Dimensions: Interpolation on Non-Linear Grids," Working Papers 14-17, University of Delaware, Department of Economics.
    3. Enrique Mendoza & Sergio Villalvazo, 2020. "FiPIt: A Simple, Fast Global Method for Solving Models with Two Endogenous States & Occasionally Binding Constraints," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 81-102, July.
    4. Iskhakov, Fedor, 2015. "Multidimensional endogenous gridpoint method: Solving triangular dynamic stochastic optimization problems without root-finding operations," Economics Letters, Elsevier, vol. 135(C), pages 72-76.
    5. Xu, Mengyi & Alonso-García, Jennifer & Sherris, Michael & Shao, Adam W., 2023. "Insuring longevity risk and long-term care: Bequest, housing and liquidity," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 121-141.
    6. Mengyi Xu & Jennifer Alonso Garcia & Michael Sherris & Adam Shao, 2022. "Insuring Longevity Risk and Long-Term Care: Bequest, Housing and Liquidity," ULB Institutional Repository 2013/340821, ULB -- Universite Libre de Bruxelles.
    7. Druedahl, Jeppe & Jørgensen, Thomas Høgholm, 2017. "A general endogenous grid method for multi-dimensional models with non-convexities and constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 87-107.
    8. Jeppe Druedahl, 2021. "A Guide on Solving Non-convex Consumption-Saving Models," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 747-775, October.

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    More about this item

    Keywords

    Dynamic models; Numerical solution; Method of endogenous gridpoints; Delaunay interpolation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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