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A Toolkit for Value Function Iteration

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  • Robert Kirkby

    (Victoria University of Wellington)

Abstract

This article introduces a Toolkit for Value Function Iteration. The toolkit is implemented in Matlab and makes automatic use of the GPU and of parallel CPUs. Likely uses are Teaching, Testing Algorithms, Replication, and Research. I here provide a description of some of the main components and algorithms. I also describe the design philosophy underlying choices about how to structure the toolkit and which algorithms to use. Rather than provide simple examples, something best done online (links are given), I instead perform a replication of a classic paper from the real business cycle literature as a demonstration of the use of such a toolkit. The Toolkit, Documentation, Examples, Replications, and more can be found at vfitoolkit.com

Suggested Citation

  • Robert Kirkby, 2017. "A Toolkit for Value Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 1-15, January.
    • Handle: RePEc:kap:compec:v:49:y:2017:i:1:d:10.1007_s10614-015-9544-1
    DOI: 10.1007/s10614-015-9544-1
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    References listed on IDEAS

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    7. Aldrich, Eric M. & Fernández-Villaverde, Jesús & Ronald Gallant, A. & Rubio-Ramírez, Juan F., 2011. "Tapping the supercomputer under your desk: Solving dynamic equilibrium models with graphics processors," Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 386-393, March.
    8. Lorenzo Garlappi & Georgios Skoulakis, 2009. "Numerical Solutions to Dynamic Portfolio Problems: The Case for Value Function Iteration using Taylor Approximation," Computational Economics, Springer;Society for Computational Economics, vol. 33(2), pages 193-207, March.
    9. Robert Kirkby Author-Email: robertkirkby@gmail.com|, 2017. "Convergence of Discretized Value Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 117-153, January.
    10. Marimon, Ramon & Scott, Andrew (ed.), 2001. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780199248278.
    11. Lucas C. Coffman & Muriel Niederle, 2015. "Pre-analysis Plans Have Limited Upside, Especially Where Replications Are Feasible," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 81-98, Summer.
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    Cited by:

    1. Christopher Ferrall, 2020. "Object Oriented (Dynamic) Programming: Replication, Innovation and "Structural" Estimation," Working Paper 1432, Economics Department, Queen's University.
    2. Darío Serrano-Puente, 2020. "Optimal progressivity of personal income tax: a general equilibrium evaluation for Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 11(4), pages 407-455, December.
    3. Hirokuni Iiboshi & Daikuke Ozaki & Yui Yoshii, 2023. "Child Care, Time Allocation, and the Life Cycle," Papers 2304.11531, arXiv.org, revised Jul 2024.
    4. Joseph Farrington & Wai Keong Wong & Kezhi Li & Martin Utley, 2025. "Going faster to see further: graphics processing unit-accelerated value iteration and simulation for perishable inventory control using JAX," Annals of Operations Research, Springer, vol. 349(3), pages 1609-1638, June.
    5. Robert Kirkby Author-Email: robertkirkby@gmail.com|, 2017. "Convergence of Discretized Value Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 117-153, January.
    6. Robert Kirkby, 2023. "Quantitative Macroeconomics: Lessons Learned from Fourteen Replications," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 875-896, February.

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    More about this item

    Keywords

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    JEL classification:

    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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