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Panel conditional and multinomial logit with time-varying parameters

Author

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  • Lee Myoung-jae

    (Department of Economics, Korea University, Seoul 136-701, South Korea)

Abstract

Panel conditional logit estimators (PCLE) in the literature use mostly time-constant parameters. If the panel periods are volatile or long, however, the model parameters can change much. Hence this paper generalizes PCLE with time-constant parameters to PCLE with time-varying parameters; both static and dynamic PCLE are considered for this. The main finding is that time-varying parameters are fully allowed for static PCLE and the dynamic “pseudo” PCLE of [Bartolucci, F. and V. Nigro. 2010. “A Dynamic Model for Binary Panel Data with Unobserved Heterogeneity Admitting a n$\sqrt n$-Consistent Conditional Estimator.” Econometrica 78: 719–733] that are thus recommended to practitioners. As a further generalization, static “panel conditional multinomial logit estimator (PML)” with time-varying parameters is also examined. As it turns out, time-varying parameters are also fully allowed for PML. With no error term serial correlation allowed in PCLE and dynamic PCLE’s being restrictive in their assumptions, time-varying parameters provide an alternative avenue to inject dynamics and flexibility into PCLE and PML. Since PCLE and PML converge straightforwardly in computation, allowing time-varying parameters in PCLE and PML is “computationally free.” A simulation study is also provided.

Suggested Citation

  • Lee Myoung-jae, 2015. "Panel conditional and multinomial logit with time-varying parameters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(3), pages 317-337, June.
    • Handle: RePEc:bpj:sndecm:v:19:y:2015:i:3:p:317-337:n:4
    DOI: 10.1515/snde-2014-0003
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    References listed on IDEAS

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    1. Francesco Bartolucci & Valentina Nigro, 2010. "A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a √n-Consistent Conditional Estimator," Econometrica, Econometric Society, vol. 78(2), pages 719-733, March.
    2. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318, Elsevier.
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    4. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
    5. Bartolucci, Francesco & Nigro, Valentina, 2012. "Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data," Journal of Econometrics, Elsevier, vol. 170(1), pages 102-116.
    6. Lee, Myoung-jae & Kim, Young-sook, 2007. "Multinomial choice and nonparametric average derivatives," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 63-81, January.
    7. Colin O. Wu & Kai F. Yu, 2002. "Nonparametric Varying-Coefficient Models for the Analysis of Longitudinal Data," International Statistical Review, International Statistical Institute, vol. 70(3), pages 373-393, December.
    8. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
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    Cited by:

    1. Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.

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    More about this item

    Keywords

    binary choice; conditional logit; multinomial choice; panel data; time-varying parameters;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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