IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-22-00646.html
   My bibliography  Save this article

SpMV approaches to dynamic discrete choice models with limited transition

Author

Listed:
  • Yu Wang

    (Torotno Metropolitan University)

  • Yao Luo

    (University of Toronto)

Abstract

Dynamic optimization problems often involve continuous state variables. Casting such problems into dynamic discrete choice models usually requires variable discretization. When there are multiple state variables, many discretized future states will be visited with only very small probability conditional on current states. We investigate pruning these small transition probabilities and applying the sparse matrix-vector multiplication method in value function iterations. We assess our method in a numerical example inspired by Rust (1987) and Barwick and Pathak (2015). Our method substantially improves computational performance and reduces memory requirements with little loss in accuracy.

Suggested Citation

  • Yu Wang & Yao Luo, 2022. "SpMV approaches to dynamic discrete choice models with limited transition," Economics Bulletin, AccessEcon, vol. 42(4), pages 2171-2183.
    • Handle: RePEc:ebl:ecbull:eb-22-00646
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2022/Volume42/EB-22-V42-I4-P179.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter Arcidiacono & Patrick Bayer & Jason R. Blevins & Paul B. Ellickson, 2016. "Estimation of Dynamic Discrete Choice Models in Continuous Time with an Application to Retail Competition," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(3), pages 889-931.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2013. "Testing for Equilibrium Multiplicity in Dynamic Markov Games," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 423, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    2. Haoying Wang & Guohui Wu, 2022. "Modeling discrete choices with large fine-scale spatial data: opportunities and challenges," Journal of Geographical Systems, Springer, vol. 24(3), pages 325-351, July.
    3. Pesendorfer, Martin & Takahashi, Yuya & Otsu, Taisuke, 2014. "Testing Equilibrium Multiplicity in Dynamic Games," CEPR Discussion Papers 10111, C.E.P.R. Discussion Papers.
    4. Dominic Smith & Sergio Ocampo, 2020. "The Evolution of U.S. Retail Concentration," Economic Working Papers 526, Bureau of Labor Statistics.
    5. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo Somaini & Daniel Waldinger, 2021. "Equilibrium Allocations Under Alternative Waitlist Designs: Evidence From Deceased Donor Kidneys," Econometrica, Econometric Society, vol. 89(1), pages 37-76, January.
    6. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," NBER Working Papers 29291, National Bureau of Economic Research, Inc.
    7. Blevins, Jason R. & Kim, Minhae, 2024. "Nested Pseudo likelihood estimation of continuous-time dynamic discrete games," Journal of Econometrics, Elsevier, vol. 238(2).
    8. Attila Gyetvai & Peter Arcidiacono, 2022. "Identification and Estimation of Continuous-Time Job Search Models with Preference Shocks," Working Papers w202215, Banco de Portugal, Economics and Research Department.
    9. Doraszelski, Ulrich & Escobar, Juan F., 2019. "Protocol invariance and the timing of decisions in dynamic games," Theoretical Economics, Econometric Society, vol. 14(2), May.
    10. B Glumac & Q Han & W Schaefer, 2018. "A negotiation decision model for public–private partnerships in brownfield redevelopment," Environment and Planning B, , vol. 45(1), pages 145-160, January.
    11. Sofia Moroni, 2020. "Existence of Trembling hand perfect and sequential equilibrium in Stochastic Games," Working Paper 6837, Department of Economics, University of Pittsburgh.
    12. Taisuke Otsu & Martin Pesendorfer, 2021. "Equilibrium multiplicity in dynamic games: testing and estimation," STICERD - Econometrics Paper Series 618, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    13. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo J. Somaini & Daniel C. Waldinger, 2019. "Equilibrium Allocations under Alternative Waitlist Designs: Evidence from Deceased Donor Kidneys," NBER Working Papers 25607, National Bureau of Economic Research, Inc.
    14. Andrew Sweeting, 2015. "A Model of Non-Stationary Dynamic Price Competition with an Application to Platform Design," Working Papers 15-03, NET Institute.
    15. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Adam Dearing & Jason R. Blevins, 2019. "Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games," Papers 1912.10488, arXiv.org, revised Apr 2024.
    17. Lauren Chenarides & Metin Çakır & Timothy J. Richards, 2024. "Dynamic model of entry: Dollar stores," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 852-882, March.
    18. Koster, Hans R.A. & Pasidis, Ilias & van Ommeren, Jos, 2019. "Shopping externalities and retail concentration: Evidence from dutch shopping streets," Journal of Urban Economics, Elsevier, vol. 114(C).
    19. Ulrich Doraszelski & Kenneth L. Judd, 2019. "Dynamic stochastic games with random moves," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 59-79, March.
    20. Sordi, Serena & Dávila-Fernández, Marwil J., 2023. "The green-MKS system: A baseline environmental macro-dynamic model," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 1056-1085.

    More about this item

    Keywords

    Sparse; Discretization;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-22-00646. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.