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Honoré, Bo E.; Kesina, Michaela

Estimation of Some Nonlinear Panel Data Models With Both Time-Varying and Time-Invariant Explanatory Variables

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  • Medientyp: E-Artikel
  • Titel: Estimation of Some Nonlinear Panel Data Models With Both Time-Varying and Time-Invariant Explanatory Variables
  • Beteiligte: Honoré, Bo E.; Kesina, Michaela
  • Erschienen: American Statistical Association, 2017
  • Erschienen in: Journal of Business & Economic Statistics
  • Sprache: Englisch
  • ISSN: 0735-0015
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <p>The so-called "fixed effects" approach to the estimation of panel data models suffers from the limitation that it is not possible to estimate the coefficients on explanatory variables that are time-invariant. This is in contrast to a "random effects" approach, which achieves this by making much stronger assumptions on the relationship between the explanatory variables and the individual-specific effect. In a linear model, it is possible to obtain the best of both worlds by making random effects-type assumptions on the time-invariant explanatory variables while maintaining the flexibility of a fixed effects approach when it comes to the time-varying covariates. This article attempts to do the same for some popular nonlinear models.</p>