IDEAS home Printed from https://ideas.repec.org/a/spr/comaot/v30y2024i4d10.1007_s10588-024-09391-0.html
   My bibliography  Save this article

Estimating dynamic logit models with unobserved individual heterogeneity and with application in household brand choices

Author

Listed:
  • Changbiao Liu

    (Guangxi University of Finance and Economics)

Abstract

In this paper, we propose a new method for dynamic discrete choice logit models with panel data, which capture both unobserved individual heterogeneities and the state dependence on purchase behaviors. The consistency and asymptotic normality of this estimators are studied in detail. Comparing with the estimators developed by Honore and Kyriazidou (Econometrica 68:839–874, 2000), the pseudo conditional likelihood estimators proposed by Bartolucci and Nigro (J Econom 170:102–116, 2012) and the modified profile likelihood estimators given by Bartolucci et al. (Economet Rev 35:1271–1289, 2016), simulations show the proposed estimators have some advantages on the mean bias and root mean squared error. As a byproduct, another estimator for static logit models is given and comparable with that developed by Chamberlain (in: Griliches Z, Intrilligator MD (eds), Handbook of econometrics, vol 2. North-Holland, Amsterdam, 1984). Last, the proposed approach is applied to the panel data on household detergent purchases and concludes that there exists significant dynamic relationship on household detergent purchases.

Suggested Citation

  • Changbiao Liu, 2024. "Estimating dynamic logit models with unobserved individual heterogeneity and with application in household brand choices," Computational and Mathematical Organization Theory, Springer, vol. 30(4), pages 321-349, December.
    • Handle: RePEc:spr:comaot:v:30:y:2024:i:4:d:10.1007_s10588-024-09391-0
    DOI: 10.1007/s10588-024-09391-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10588-024-09391-0
    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/s10588-024-09391-0?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. 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.
    2. Rishin Roy & Pradeep K. Chintagunta & Sudeep Haldar, 1996. "A Framework for Investigating Habits, “The Hand of the Past,” and Heterogeneity in Dynamic Brand Choice," Marketing Science, INFORMS, vol. 15(3), pages 280-299.
    3. Michael P. Keane & Robert M. Sauer, 2010. "A Computationally Practical Simulation Estimation Algorithm For Dynamic Panel Data Models With Unobserved Endogenous State Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(4), pages 925-958, November.
    4. Keane, Michael P, 1997. "Modeling Heterogeneity and State Dependence in Consumer Choice Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 310-327, July.
    5. Tata Subba Rao & Granville Tunnicliffe Wilson & Wei Gao & Wicher Bergsma & Qiwei Yao, 2017. "Estimation for Dynamic and Static Panel Probit Models with Large Individual Effects," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 266-284, March.
    6. 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.
    7. Jean‐Pierre Dubé & Günter J. Hitsch & Peter E. Rossi, 2010. "State dependence and alternative explanations for consumer inertia," RAND Journal of Economics, RAND Corporation, vol. 41(3), pages 417-445, September.
    8. Timothy J. Halliday, 2008. "Heterogeneity, state dependence and health," Econometrics Journal, Royal Economic Society, vol. 11(3), pages 499-516, November.
    9. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    10. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    11. 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.
    12. Elenna R. Dugundji & László Gulyás, 2013. "Structure and emergence in a nested logit model with social and spatial interactions," Computational and Mathematical Organization Theory, Springer, vol. 19(2), pages 151-203, June.
    13. Chintagunta, Pradeep & Kyriazidou, Ekaterini & Perktold, Josef, 2001. "Panel data analysis of household brand choices," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 111-153, July.
    14. Guo, Xu & Wong, Wing-Keung & Xu, Qunfang & Zhu, Xuehu, 2015. "Production and hedging decisions under regret aversion," Economic Modelling, Elsevier, vol. 51(C), pages 153-158.
    15. Francesco Bartolucci & Valentina Nigro & Claudia Pigini, 2018. "Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 61-88, January.
    16. Chamberlain, Gary, 2022. "Feedback in panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 4-20.
    17. 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.
    18. P. B. Seetharaman, 2004. "Modeling Multiple Sources of State Dependence in Random Utility Models: A Distributed Lag Approach," Marketing Science, INFORMS, vol. 23(2), pages 263-271, April.
    19. Chow, Sheung Chi & Vieito, João Paulo & Wong, Wing Keung, 2019. "Do both demand-following and supply-leading theories hold true in developing countries?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 536-554.
    20. 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.
    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. 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.
    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. 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.
    4. Francesco Bartolucci & Valentina Nigro & Claudia Pigini, 2018. "Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 61-88, January.
    5. Victor Aguirregabiria & Jesus Carro, 2021. "Identification of Average Marginal Effects in Fixed Effects Dynamic Discrete Choice Models," Working Papers tecipa-701, University of Toronto, Department of Economics.
    6. Francesco Bartolucci & Francesco Valentini & Claudia Pigini, 2023. "Recursive Computation of the Conditional Probability Function of the Quadratic Exponential Model for Binary Panel Data," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 529-557, February.
    7. Giulia Bettin & Riccardo Lucchetti, 2016. "Steady streams and sudden bursts: persistence patterns in remittance decisions," Journal of Population Economics, Springer;European Society for Population Economics, vol. 29(1), pages 263-292, January.
    8. Pauline Givord & Lionel Wilner, 2015. "When Does the Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work in Changing Economic Conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 787-805, August.
    9. 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.
    10. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Estimation of Dynamic Binary Choice Panel Data Models," ANU Working Papers in Economics and Econometrics 2020-671, Australian National University, College of Business and Economics, School of Economics.
    11. 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.
    12. Pigini, Claudia & Presbitero, Andrea F. & Zazzaro, Alberto, 2016. "State dependence in access to credit," Journal of Financial Stability, Elsevier, vol. 27(C), pages 17-34.
    13. Jia, Zhiyang & Vattø, Trine Engh, 2021. "Predicting the path of labor supply responses when state dependence matters," Labour Economics, Elsevier, vol. 71(C).
    14. Hong, Seung-Hyun & Rezende, Leonardo, 2012. "Lock-in and unobserved preferences in server operating systems: A case of Linux vs. Windows," Journal of Econometrics, Elsevier, vol. 167(2), pages 494-503.
    15. Bartolucci, Francesco & Nigro, Valentina & Pigini, Claudia, 2013. "Testing for state dependence in binary panel data with individual covariates," MPRA Paper 48233, University Library of Munich, Germany.
    16. Handel, Benjamin R. & Misra, Kanishka & Roberts, James W., 2013. "Robust firm pricing with panel data," Journal of Econometrics, Elsevier, vol. 174(2), pages 165-185.
    17. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Estimation of Dynamic Binary Choice Panel Data Models," Discussion Papers Series 626, School of Economics, University of Queensland, Australia.
    18. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    19. Okamura, Kazuaki & Islam, Nizamul, 2021. "Multinomial employment dynamics with state dependence and heterogeneity: Evidence from Japan," Economic Modelling, Elsevier, vol. 101(C).
    20. Fu Ouyang & Thomas Tao Yang, 2022. "Semiparametric Estimation of Dynamic Binary Choice Panel Data Models," Papers 2202.12062, arXiv.org, revised Feb 2024.

    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:spr:comaot:v:30:y:2024:i:4:d:10.1007_s10588-024-09391-0. 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.