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Non-parametric models in binary choice fixed effects panel data
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DOI：10.1111/j.1368-423X.2011.00343.x.png)
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Abstract
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In this paper we extend the fixed effects approach to deal with non-linear panel data with non-parametric components. Specifically, we propose a non-parametric procedure that generalizes the conditional logit approach. We develop an estimator based on non-linear stochastic integral equations and provide the asymptotic property of the estimator and an iterative algorithm to implement the estimator. We analyse the small sample behaviour of the estimator through a Monte Carlo study.
Keywords:
Binary choice
Panel data
Stochastic integral equation
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