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Likelihood corrections for two-way models

Author

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  • Koen Jochmans
  • Taisuke Otsu

Abstract

The use of two-way fixed-effect models is widespread. The presence of incidental parameter bias, however, invalidates statistical inference based on the likelihood. In this paper we consider modifications to the (profile) likelihood that yield asymptotically unbiased estimators as well as likelihood-ratio and score tests with correct size. The modifications are widely applicable and easy to implement. Our examples illustrate that the modifications can lead to dramatic improvements relative to the maximum likelihood method both in terms of point estimation and inference.

Suggested Citation

  • Koen Jochmans & Taisuke Otsu, 2018. "Likelihood corrections for two-way models," STICERD - Econometrics Paper Series 598, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:598
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    Cited by:

    1. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased inference for dynamic nonlinear models with two-way fixed effects," Papers 2305.03134, arXiv.org, revised Oct 2023.
    2. Bartolucci, Francesco & Pigini, Claudia & Valentini, Francesco, 2021. "MCMC Conditional Maximum Likelihood for the two-way fixed-effects logit," MPRA Paper 110034, University Library of Munich, Germany.

    More about this item

    Keywords

    asymptotic bias; bias correction; fixed effects; information bias; modified profile likelihood; panel data; MCMC; penalization; rectangular-array asymptotics;
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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