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Office of Survey Methods Research
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Published Year: 2018
Survey/Program(s): Office of Prices and Living Conditions
Catalog: Economic Working Paper
WP Number: WP-502
Publication Status / Disposition: Kwak, Do Won, Martin, Robert S. and Wooldridge, Jeffrey M.,"The Robustness of Conditional Logit for Binary Response Panel Data Models with Serial Correlation" Journal of Econometric Methods, vol. 12, no. 1, 2023, pp. 33-56. https://doi.org/10.1515/jem-2021-0005
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The Robustness of Conditional Logit for Binary Response Panel Data Models with Serial Correlation
Abstract
This paper examines the conditional logit estimator for binary panel data models with unobserved heterogeneity. A key assumption used to derive the conditional logit estimator is conditional serial independence (CI), which is problematic when the underlying innovations are serially correlated. A Monte Carlo experiment suggests that the conditional logit estimator is not robust to violation of the CI assumption. We find that higher persistence and smaller time dimension both increase the magnitude of the bias in slope parameter estimates. We also compare conditional logit to unconditional logit and pooled correlated random effects logit.