Partial effects estimation for fixed-effects logit panel data models

Bartolucci, Francesco and Pigini, Claudia (2019): Partial effects estimation for fixed-effects logit panel data models.

Abstract

We propose a multiple step procedure to estimate Average Partial Effects (APE) in fixed-effects panel logit models. Because the incidental parameters problem plagues the APEs via both the inconsistent estimates of the slope and individual parameters, we reduce the bias by evaluating the APEs at a fixed-T consistent estimator for the slope coefficients and at a bias corrected estimator for the unobserved heterogeneity. The proposed estimator has bias of order O(T −2 ) as n → ∞ and performs well in finite sample, even when n is much larger than T . We provide a real data application based on the labor supply of married women.

• Item Type: MPRA Paper
• Language: English
• Keywords: Average partial effects, Bias reduction, Binary panel data, Conditional Maximum Likelihood
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C25 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions ; Probabilities

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