IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v43y2014i4p395-409.html
   My bibliography  Save this article

Simulation Estimation of Dynamic Panel Discrete Choice Models Using the $$t$$ t Distributions

Author

Listed:
  • Sheng-Kai Chang

Abstract

In this paper a practical robust simulation estimator is proposed for the dynamic panel data discrete choice models using the $$t$$ t distribution. The maximum simulated likelihood estimators are obtained through a recursive algorithm formulated by Geweke–Hajivassiliou–Keane simulators. Monte Carlo experiments indicate that the proposed robust simulation estimators perform well under the errors with longer than normal tails for a small simulation size, even with the initial conditions problem. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Sheng-Kai Chang, 2014. "Simulation Estimation of Dynamic Panel Discrete Choice Models Using the $$t$$ t Distributions," Computational Economics, Springer;Society for Computational Economics, vol. 43(4), pages 395-409, April.
    • Handle: RePEc:kap:compec:v:43:y:2014:i:4:p:395-409
    DOI: 10.1007/s10614-014-9425-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-014-9425-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-014-9425-z?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. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    2. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    3. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    4. Hahn, Jinyong, 2001. "The Information Bound Of A Dynamic Panel Logit Model With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 17(5), pages 913-932, October.
    5. Sheng‐Kai Chang, 2011. "Simulation estimation of two‐tiered dynamic panel Tobit models with an application to the labor supply of married women," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(5), pages 854-871, August.
    6. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    7. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 19-40, Suppl. De.
    8. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    9. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
    10. Sheng-Kai Chang, 2012. "State dependence, serial correlation and heterogeneity in the union membership dynamics," Applied Economics, Taylor & Francis Journals, vol. 44(26), pages 3453-3460, September.
    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. Shiu, Ji-Liang & Hu, Yingyao, 2013. "Identification and estimation of nonlinear dynamic panel data models with unobserved covariates," Journal of Econometrics, Elsevier, vol. 175(2), pages 116-131.
    2. Lucchetti, Riccardo & Pigini, Claudia, 2017. "DPB: Dynamic Panel Binary Data Models in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i08).
    3. Akay, Alpaslan, 2007. "Monte Carlo Investigation of the Initial Values Problem in Censored Dynamic Random-Effects Panel Data Models," Working Papers in Economics 278, University of Gothenburg, Department of Economics.
    4. Chang Sheng-Kai, 2011. "A Computationally Practical Robust Simulation Estimator for Dynamic Panel Tobit Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-21, September.
    5. Thierry Kamionka & Guy Lacroix, 2018. "Homeownership, Labour Market Transitions and Earnings," CIRANO Working Papers 2018s-35, CIRANO.
    6. Geert Dhaene & Koen Jochmans, 2015. "Split-panel Jackknife Estimation of Fixed-effect Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 991-1030.
    7. Peter Haan, 2005. "State Dependence and Female Labor Supply in Germany: The Extensive and the Intensive Margin," Discussion Papers of DIW Berlin 538, DIW Berlin, German Institute for Economic Research.
    8. Breitung, Jörg & Lechner, Michael, 1998. "Alternative GMM methods for nonlinear panel data models," SFB 373 Discussion Papers 1998,81, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
    10. Francesco Bartolucci & Claudia Pigini, 2017. "Granger causality in dynamic binary short panel data models," Working Papers 421, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    11. Prowse, Victoria L., 2005. "State Dependence in a Multi-State Model of Employment Dynamics," IZA Discussion Papers 1623, Institute of Labor Economics (IZA).
    12. M. P. Keane & R. M. Sauer, 2008. "Implications of Classification Error for the Dynamics of Female Labor Supply," CHILD Working Papers wp13_08, CHILD - Centre for Household, Income, Labour and Demographic economics - ITALY.
    13. Sheng-Kai Chang, 2012. "State dependence, serial correlation and heterogeneity in the union membership dynamics," Applied Economics, Taylor & Francis Journals, vol. 44(26), pages 3453-3460, September.
    14. Inkmann, Joachim, 2000. "Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators," Journal of Econometrics, Elsevier, vol. 97(2), pages 227-259, August.
    15. Thierry Kamionka & Cyriaque Edon, 2007. "Modélisation dynamique de la participation au marché du travail des femmes en couple," Annals of Economics and Statistics, GENES, issue 86, pages 77-108.
    16. Mark B. Stewart, 2007. "The interrelated dynamics of unemployment and low-wage employment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 511-531.
    17. Manudeep Bhuller & Christian N. Brinch & Sebastian Königs, 2017. "Time Aggregation and State Dependence in Welfare Receipt," Economic Journal, Royal Economic Society, vol. 127(604), pages 1833-1873, September.
    18. Michael P. Keane & Robert M. Sauer, 2009. "Classification Error in Dynamic Discrete Choice Models: Implications for Female Labor Supply Behavior," Econometrica, Econometric Society, vol. 77(3), pages 975-991, May.
    19. Andreas Ziegler, 2007. "Simulated classical tests in multinomial probit models," Statistical Papers, Springer, vol. 48(4), pages 655-681, October.
    20. Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2023. "Conditional inference and bias reduction for partial effects estimation of fixed-effects logit models," Empirical Economics, Springer, vol. 64(5), pages 2257-2290, May.

    More about this item

    Keywords

    Dynamic panel discrete choice models; Robust simulation estimation; GHK simulator; Initial conditions problem; C15; C23; C24;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

    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:43:y:2014:i:4:p:395-409. 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.