IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v116y2012i2p213-216.html
   My bibliography  Save this article

A test of the extreme value type I assumption in the bus engine replacement model

Author

Listed:
  • Larsen, Bradley J.
  • Oswald, Florian
  • Reich, Gregor
  • Wunderli, Dan

Abstract

This note tests the assumption of dynamic discrete choice models that underlying utility shocks have an extreme value type I distribution. We find that extreme value type I shocks cannot be rejected in most specifications of the Rust (1987) bus engine replacement model.

Suggested Citation

  • Larsen, Bradley J. & Oswald, Florian & Reich, Gregor & Wunderli, Dan, 2012. "A test of the extreme value type I assumption in the bus engine replacement model," Economics Letters, Elsevier, vol. 116(2), pages 213-216.
    • Handle: RePEc:eee:ecolet:v:116:y:2012:i:2:p:213-216
    DOI: 10.1016/j.econlet.2012.02.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512000870
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2012.02.031?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. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    3. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    4. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 69(2), pages 427-428, October.
    5. Theodossiou, Panayiotis & McDonald, James B. & Hansen, Christian B., 2007. "Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-20.
    6. James V. Hansen & James B. McDonald, 2002. "A Generalized Model for Predictive Data Mining," Information Systems Frontiers, Springer, vol. 4(2), pages 179-186, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christopher Ferrall, 2023. "Was Harold Zurcher myopic after all? Replicating Rust's engine replacement estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1093-1100, November.

    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. Victor Aguirregabiria & Cesar Alonso-Borrego, 2014. "Labor Contracts And Flexibility: Evidence From A Labor Market Reform In Spain," Economic Inquiry, Western Economic Association International, vol. 52(2), pages 930-957, April.
    2. Yusuke Hara & Eiji Hato, 2019. "Analysis of dynamic decision-making in a bicycle-sharing auction using a dynamic discrete choice model," Transportation, Springer, vol. 46(1), pages 147-173, February.
    3. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
    4. Norets, Andriy & Shimizu, Kenichi, 2024. "Semiparametric Bayesian estimation of dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 238(2).
    5. Andreas Lanz & Gregor Reich & Ole Wilms, 2022. "Adaptive grids for the estimation of dynamic models," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 179-238, June.
    6. BenSaïda, Ahmed & Slim, Skander, 2016. "Highly flexible distributions to fit multiple frequency financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 203-213.
    7. Sandeep Rath & Kumar Rajaram, 2022. "Staff Planning for Hospitals with Implicit Cost Estimation and Stochastic Optimization," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 1271-1289, March.
    8. Joao Macieira, 2010. "Oblivious Equilibrium in Dynamic Discrete Games," 2010 Meeting Papers 680, Society for Economic Dynamics.
    9. Yingyao Hu & Yi Xin, 2019. "Identi?cation and estimation of dynamic structural models with unobserved choices," CeMMAP working papers CWP35/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Artuc, Erhan, 2013. "PPML estimation of dynamic discrete choice models with aggregate shocks," Policy Research Working Paper Series 6480, The World Bank.
    11. Petra E. Todd & Kenneth I. Wolpin, 2010. "Structural Estimation and Policy Evaluation in Developing Countries," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 21-50, September.
    12. 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.
    13. Joe Hirschberg & Jenny Lye, 2021. "Estimating risk premiums for regulated firms when accounting for reference-day variation and high-order moments of return volatility," Environment Systems and Decisions, Springer, vol. 41(3), pages 455-467, September.
    14. Javier D. Donna, 2021. "Measuring long‐run gasoline price elasticities in urban travel demand," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 945-994, December.
    15. Peter Davis & Pasquale Schiraldi, 2014. "The flexible coefficient multinomial logit (FC-MNL) model of demand for differentiated products," RAND Journal of Economics, RAND Corporation, vol. 45(1), pages 32-63, March.
    16. 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.
    17. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    18. Arthur Charpentier & Romuald Élie & Carl Remlinger, 2023. "Reinforcement Learning in Economics and Finance," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 425-462, June.
    19. Andriy Norets, 2009. "Inference in Dynamic Discrete Choice Models With Serially orrelated Unobserved State Variables," Econometrica, Econometric Society, vol. 77(5), pages 1665-1682, September.
    20. Arcidiacono, Peter & Miller, Robert A., 2020. "Identifying dynamic discrete choice models off short panels," Journal of Econometrics, Elsevier, vol. 215(2), pages 473-485.

    More about this item

    Keywords

    Dynamic discrete choice; Extreme value type I; Numerical quadrature; Flexible distributions;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    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:eee:ecolet:v:116:y:2012:i:2:p:213-216. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.