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Indirect Inference for Nonlinear Panel Models with Fixed Effects by Chen, Shuowen is a scholarly article available to read on EtoBox.

What is Indirect Inference for Nonlinear Panel Models with Fixed Effects about?

Fixed effect estimators of nonlinear panel data models suffer from the incidental parameter problem. This leads to two undesirable consequences in applied research: (1) point estimates are subject to large biases, and (2) confidence intervals have incorrect coverages. This paper proposes a simulation-based method for bias reduction. The method simulates data using the model with estimated individual effects, and finds values of parameters by equating fixed effect estimates obtained from observed and simulated data. The asymptotic framework provides consistency, bias correction, and asymptotic normality results. An application and simulations to female labor force participation illustrates the finite-sample performance of the method.

Author

Chen, Shuowen

Published

2022

Language

EN