IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2009.00085.html
   My bibliography  Save this paper

Identification of Semiparametric Panel Multinomial Choice Models with Infinite-Dimensional Fixed Effects

Author

Listed:
  • Wayne Yuan Gao
  • Ming Li

Abstract

This paper proposes a robust method for semiparametric identification and estimation in panel multinomial choice models, where we allow for infinite-dimensional fixed effects that enter into consumer utilities in an additively nonseparable way, thus incorporating rich forms of unobserved heterogeneity. Our identification strategy exploits multivariate monotonicity in parametric indexes, and uses the logical contraposition of an intertemporal inequality on choice probabilities to obtain identifying restrictions. We provide a consistent estimation procedure, and demonstrate the practical advantages of our method with Monte Carlo simulations and an empirical illustration on popcorn sales with the Nielsen data.

Suggested Citation

  • Wayne Yuan Gao & Ming Li, 2020. "Identification of Semiparametric Panel Multinomial Choice Models with Infinite-Dimensional Fixed Effects," Papers 2009.00085, arXiv.org, revised Nov 2024.
    • Handle: RePEc:arx:papers:2009.00085
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2009.00085
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Manski, Charles F. & Thompson, T. Scott, 1986. "Operational characteristics of maximum score estimation," Journal of Econometrics, Elsevier, vol. 32(1), pages 85-108, June.
    2. Ariel Pakes & Jack Porter, 2024. "Moment inequalities for multinomial choice with fixed effects," Quantitative Economics, Econometric Society, vol. 15(1), pages 1-25, January.
    3. Steven Berry & Amit Gandhi & Philip Haile, 2013. "Connected Substitutes and Invertibility of Demand," Econometrica, Econometric Society, vol. 81(5), pages 2087-2111, September.
    4. Jeremy T. Fox, 2007. "Semiparametric estimation of multinomial discrete-choice models using a subset of choices," RAND Journal of Economics, RAND Corporation, vol. 38(4), pages 1002-1019, December.
    5. Steven T. Berry & Philip A. Haile, 2014. "Identification in Differentiated Products Markets Using Market Level Data," Econometrica, Econometric Society, vol. 82, pages 1749-1797, September.
    6. Bo E. Honore & Arthur Lewbel, 2002. "Semiparametric Binary Choice Panel Data Models Without Strictly Exogeneous Regressors," Econometrica, Econometric Society, vol. 70(5), pages 2053-2063, September.
    7. Lee, Lung-fei, 1995. "Semiparametric maximum likelihood estimation of polychotomous and sequential choice models," Journal of Econometrics, Elsevier, vol. 65(2), pages 381-428, February.
    8. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    9. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    10. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    11. Gao, Wayne Yuan & Li, Ming & Xu, Sheng, 2023. "Logical differencing in dyadic network formation models with nontransferable utilities," Journal of Econometrics, Elsevier, vol. 235(1), pages 302-324.
    12. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
    13. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2019. "Inference on Semiparametric Multinomial Response Models," Boston College Working Papers in Economics 980, Boston College Department of Economics.
    14. Wayne Yuan Gao & Sheng Xu & Kan Xu, 2020. "Two-Stage Maximum Score Estimator," Papers 2009.02854, arXiv.org, revised Sep 2022.
    15. Victor Chernozhukov & Han Hong & Elie Tamer, 2007. "Estimation and Confidence Regions for Parameter Sets in Econometric Models," Econometrica, Econometric Society, vol. 75(5), pages 1243-1284, September.
    16. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
    17. Abrevaya, Jason, 2000. "Rank estimation of a generalized fixed-effects regression model," Journal of Econometrics, Elsevier, vol. 95(1), pages 1-23, March.
    18. Hyungtaik Ahn & Hidehiko Ichimura & James L. Powell & Paul A. Ruud, 2018. "Simple Estimators for Invertible Index Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 1-10, January.
    19. 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.
    20. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
    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. Rui Wang, 2023. "Testing and Identifying Substitution and Complementarity Patterns," Papers 2304.00678, arXiv.org.
    2. Wayne Yuan Gao & Sheng Xu & Kan Xu, 2020. "Two-Stage Maximum Score Estimator," Papers 2009.02854, arXiv.org, revised Sep 2022.
    3. Fu Ouyang & Thomas T. Yang, 2023. "Semiparametric Discrete Choice Models for Bundles," Papers 2306.04135, arXiv.org, revised Nov 2023.
    4. Andrew Chesher & Adam Rosen & Yuanqi Zhang, 2024. "Robust analysis of short panels," IFS Working Papers WCWP01/24, Institute for Fiscal Studies.
    5. Wayne Yuan Gao & Rui Wang, 2023. "Identification of Nonlinear Dynamic Panels under Partial Stationarity," Papers 2401.00264, arXiv.org, revised May 2024.
    6. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Other publications TiSEM 7899deb9-0eda-47e6-a3b8-2, Tilburg University, School of Economics and Management.
    7. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2021. "Inference on semiparametric multinomial response models," Quantitative Economics, Econometric Society, vol. 12(3), pages 743-777, July.

    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. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Discrete Choice Models for Bundles," Discussion Papers Series 625, School of Economics, University of Queensland, Australia.
    2. Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008. "Evaluating wireless carrier consolidation using semiparametric demand estimation," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 299-338, December.
    3. Jeremy T. Fox, 2018. "Estimating matching games with transfers," Quantitative Economics, Econometric Society, vol. 9(1), pages 1-38, March.
    4. Khai Xiang Chiong & Matthew Shum, 2019. "Random Projection Estimation of Discrete-Choice Models with Large Choice Sets," Management Science, INFORMS, vol. 65(1), pages 256-271, January.
    5. Jiarui Liu, 2021. "Sequential Search Models: A Pairwise Maximum Rank Approach," Papers 2104.13865, arXiv.org, revised Nov 2021.
    6. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    7. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    8. Chen, Le-Yu & Lee, Sokbae, 2019. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," Journal of Econometrics, Elsevier, vol. 210(2), pages 482-497.
    9. Shakeeb Khan & Xiaoying Lan & Elie Tamer & Qingsong Yao, 2021. "Estimating High Dimensional Monotone Index Models by Iterative Convex Optimization1," Papers 2110.04388, arXiv.org, revised Feb 2023.
    10. Wayne Yuan Gao & Sheng Xu & Kan Xu, 2020. "Two-Stage Maximum Score Estimator," Papers 2009.02854, arXiv.org, revised Sep 2022.
    11. Fu Ouyang & Thomas T. Yang, 2023. "Semiparametric Discrete Choice Models for Bundles," Papers 2306.04135, arXiv.org, revised Nov 2023.
    12. Ariel Pakes & Jack Porter, 2024. "Moment inequalities for multinomial choice with fixed effects," Quantitative Economics, Econometric Society, vol. 15(1), pages 1-25, January.
    13. repec:hal:wpspec:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
    14. Jochmans, Koen, 2015. "Multiplicative-error models with sample selection," Journal of Econometrics, Elsevier, vol. 184(2), pages 315-327.
    15. repec:hal:spmain:info:hdl:2441/3vl5fe4i569nbr005tctlc8ll5 is not listed on IDEAS
    16. Shakeeb Khan & Fu Ouyang & Elie Tamer, 2019. "Inference on Semiparametric Multinomial Response Models," Boston College Working Papers in Economics 980, Boston College Department of Economics.
    17. 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.
    18. Komarova, Tatiana, 2013. "Binary choice models with discrete regressors: Identification and misspecification," Journal of Econometrics, Elsevier, vol. 177(1), pages 14-33.
    19. Yan, Jin & Yoo, Hong Il, 2019. "Semiparametric estimation of the random utility model with rank-ordered choice data," Journal of Econometrics, Elsevier, vol. 211(2), pages 414-438.
    20. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    21. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    22. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2023. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," Econometrica, Econometric Society, vol. 91(1), pages 107-146, January.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2009.00085. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.