IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v62y2023i3d10.1007_s10614-022-10280-4.html
   My bibliography  Save this article

Object Oriented (Dynamic) Programming: Closing the “Structural” Estimation Coding Gap

Author

Listed:
  • Christopher Ferrall

    (Queen’s University)

Abstract

This paper discusses how to design, solve and estimate dynamic programming models using the open source package niqlow. Reasons are given for why such a package has not appeared earlier and why the object-oriented approach followed by niqlow seems essential. An example is followed that starts with basic coding then expands the model and applies different solution methods to finally estimate parameters from data. The niqlow approach is used to organize the empirical DP literature differently from traditional surveys which may make it more accessible to new researchers. Features for efficiency and customization are also discussed.

Suggested Citation

  • Christopher Ferrall, 2023. "Object Oriented (Dynamic) Programming: Closing the “Structural” Estimation Coding Gap," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 761-816, October.
  • Handle: RePEc:kap:compec:v:62:y:2023:i:3:d:10.1007_s10614-022-10280-4
    DOI: 10.1007/s10614-022-10280-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-022-10280-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10614-022-10280-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    2. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    3. V. Joseph Hotz & Robert A. Miller, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 497-529.
    4. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    5. Hiroyuki Kasahara & Katsumi Shimotsu, 2012. "Sequential Estimation of Structural Models With a Fixed Point Constraint," Econometrica, Econometric Society, vol. 80(5), pages 2303-2319, September.
    6. Victor Aguirregabiria & Arvind Magesan, 2013. "Euler Equations for the Estimation of Dynamic Discrete Choice Structural Models," Advances in Econometrics, in: Structural Econometric Models, volume 31, pages 3-44, Emerald Group Publishing Limited.
    7. Susumu Imai & Neelam Jain & Andrew Ching, 2009. "Bayesian Estimation of Dynamic Discrete Choice Models," Econometrica, Econometric Society, vol. 77(6), pages 1865-1899, November.
    8. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-672, November.
    9. Aguirregabiria, Victor & Magesan, Arvind, 2013. "Euler Equations for the Estimation of Dynamic Discrete Choice Structural," MPRA Paper 46056, University Library of Munich, Germany.
    10. MaCurdy, Thomas E, 1981. "An Empirical Model of Labor Supply in a Life-Cycle Setting," Journal of Political Economy, University of Chicago Press, vol. 89(6), pages 1059-1085, December.
    11. Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
    12. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    13. Wolpin, Kenneth I, 1984. "An Estimable Dynamic Stochastic Model of Fertility and Child Mortality," Journal of Political Economy, University of Chicago Press, vol. 92(5), pages 852-874, October.
    14. Christopher Ferrall, 2005. "Solving Finite Mixture Models: Efficient Computation in Economics Under Serial and Parallel Execution," Computational Economics, Springer;Society for Computational Economics, vol. 25(4), pages 343-379, June.
    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. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    2. Christopher Ferrall, 2020. "Object Oriented (Dynamic) Programming: Replication, Innovation and "Structural" Estimation," Working Paper 1432, Economics Department, Queen's University.
    3. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    4. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    5. Keane, Michael P. & Todd, Petra E. & Wolpin, Kenneth I., 2011. "The Structural Estimation of Behavioral Models: Discrete Choice Dynamic Programming Methods and Applications," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 4, pages 331-461, Elsevier.
    6. Andriy Norets, 2010. "Continuity and differentiability of expected value functions in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 1(2), pages 305-322, November.
    7. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    8. Ji, Yongjie & Rabotyagov, Sergey & Kling, Catherine L., 2014. "Crop Choice and Rotational Effects: A Dynamic Model of Land Use in Iowa in Recent Years," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170366, Agricultural and Applied Economics Association.
    9. Hanming Fang & Yang Wang, 2015. "Estimating Dynamic Discrete Choice Models With Hyperbolic Discounting, With An Application To Mammography Decisions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(2), pages 565-596, May.
    10. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    11. Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.
    12. Michael P. Keane, 2011. "Labor Supply and Taxes: A Survey," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 961-1075, December.
    13. Blevins, Jason R. & Kim, Minhae, 2024. "Nested Pseudo likelihood estimation of continuous-time dynamic discrete games," Journal of Econometrics, Elsevier, vol. 238(2).
    14. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2021. "Linear IV regression estimators for structural dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 222(1), pages 778-804.
    15. Hu Yingyao & Shum Matthew & Tan Wei & Xiao Ruli, 2017. "A Simple Estimator for Dynamic Models with Serially Correlated Unobservables," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-16, January.
    16. Peter Arcidiacono & Paul B. Ellickson, 2011. "Practical Methods for Estimation of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 363-394, September.
    17. A. Norets & X. Tang, 2014. "Semiparametric Inference in Dynamic Binary Choice Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 1229-1262.
    18. Hancevic, Pedro Ignacio, 2017. "A dynamic approach to environmental compliance decisions in U.S. Electricity Market: The Acid Rain Program revisited," Energy Policy, Elsevier, vol. 106(C), pages 129-137.
    19. Otero, Karina V., 2016. "Nonparametric identification of dynamic multinomial choice games: unknown payoffs and shocks without interchangeability," MPRA Paper 86784, University Library of Munich, Germany.
    20. Yu Zheng & Juan Pantano, 2012. "Using Subjective Expectations Data to Allow for Unobserved Heterogeneity in Hotz-Miller Estimation Strategies," 2012 Meeting Papers 940, Society for Economic Dynamics.

    More about this item

    Keywords

    Dynamic programming; Computational methods;

    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:kap:compec:v:62:y:2023:i:3:d:10.1007_s10614-022-10280-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.