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Estimating Fixed Effects Logit Models with Large Panel Data

Author

Listed:
  • Stammann, Amrei
  • Heiß, Florian
  • McFadden, Daniel
Abstract
For the parametric estimation of logit models with individual time-invariant effects the conditional and unconditional fixed effects maximum likelihood estimators exist. The conditional fixed effects logit (CL) estimator is consistent but it has the drawback that it does not deliver estimates of the fixed effects or marginal effects. It is also computationally costly if the number of observations per individual T is large. The unconditional fixed effects logit estimator (UCL) can be estimated by including a dummy variable for each individual (DVL). It suffers from the incidental parameters problem which causes severe biases for small T. Another problem is that with a large number of individuals N, the computational costs of the DVL estimator can be prohibitive. We suggest a pseudo-demeaning algorithm in spirit of Greene (2004) and Chamberlain (1980) that delivers the identical results as the DVL estimator without its computational burden for large N. We also discuss how to correct for the incidental parameters bias of parameters and marginal effects. Monte-Carlo evidence suggests that the bias-corrected estimator has similar properties as the CL estimator in terms of parameter estimation. Its computational burden is much lower than the CL or the DVL estimators, especially with large N and/or T.

Suggested Citation

  • Stammann, Amrei & Heiß, Florian & McFadden, Daniel, 2016. "Estimating Fixed Effects Logit Models with Large Panel Data," VfS Annual Conference 2016 (Augsburg): Demographic Change 145837, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc16:145837
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    File URL: https://www.econstor.eu/bitstream/10419/145837/1/VfS_2016_pid_6909.pdf
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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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