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Moment Inequalities for Multinomial Choice with Fixed Effects

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  • Ariel Pakes
  • Jack Porter

Abstract

We propose a new approach to semiparametric analysis of multinomial choice models with fixed effects and a group (or panel) structure. A traditional random utility framework is employed, and the key assumption is a group homogeneity condition on the disturbances. This assumption places no restrictions on either the joint distribution of the disturbances across choices or within group (or across time) correlations. This work follows a substantial nonlinear panel literature (Manski 1987, Honore 1992, Abrevaya 1999, 2000) with the distinction that multiple covariate index functions now determine the outcome. A novel within-group comparison leads to a set of conditional moment inequalities that provide partial identifying information about the parameters of the observed covariate index functions, while avoiding the incidental parameter problem. We extend our framework to allow for: certain types of endogenous regressors (including lagged dependent variables and conditional heteroskedasticity), set-valued covariates, and parametric distributional information on disturbances.

Suggested Citation

  • Ariel Pakes & Jack Porter, 2016. "Moment Inequalities for Multinomial Choice with Fixed Effects," NBER Working Papers 21893, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21893
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    References listed on IDEAS

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    1. Kory Kroft & Fabian Lange & Matthew J. Notowidigdo, 2013. "Duration Dependence and Labor Market Conditions: Evidence from a Field Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 128(3), pages 1123-1167.
    2. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    3. Abrevaya, Jason, 1999. "Leapfrog estimation of a fixed-effects model with unknown transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 93(2), pages 203-228, December.
    4. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 225-238.
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    Citations

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    Cited by:

    1. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. 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.
    3. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2019. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," NBER Working Papers 25827, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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