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Linear fixed-effects estimation with non-repeated outcomes

Author

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  • Farbmacher, Helmut
  • Tauchmann, Harald
Abstract
This paper demonstrates that popular linear fixed-effects panel-data estimators are biased and inconsistent when applied in a discrete-time hazard setting - that is, one in which the outcome variable is a binary dummy indicating an absorbing state, even if the data-generating process is fully consistent with the linear discrete-time hazard model. In addition to conventional survival bias, these estimators suffer from another source of - frequently severe - bias that originates from the data transformation itself and, unlike survival bias, is present even in the absence of any unobserved heterogeneity. We suggest an alternative estimation strategy, which is instrumental variables estimation using first-differences of the exogenous variables as instruments for their levels. Monte Carlo simulations and an empirical application substantiate our theoretical results.

Suggested Citation

  • Farbmacher, Helmut & Tauchmann, Harald, 2021. "Linear fixed-effects estimation with non-repeated outcomes," FAU Discussion Papers in Economics 03/2021, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2021.
    • Handle: RePEc:zbw:iwqwdp:032021
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    References listed on IDEAS

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    More about this item

    Keywords

    linear probability model; individual fixed effects; discrete-time hazard; absorbing state; survival bias; instrumental variables estimation;
    All these keywords.

    JEL classification:

    • 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
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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