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Diagnostic Analysis and Computational Strategies for Estimating Discrete Time Duration Models - A Monte Carlo Study
(with Barry Smith)
Journal of Econometrics , Volume 187, Issue 1, July 2015, pp. 275-292
Abstract: This paper uses Monte Carlo analysis to study important and contentious issues in estimating single-spell discrete time duration models. We find simulated annealing dominates gradient methods for recovering true models. We recommend a partially flexible step function for duration dependence combined with likelihood ratio tests for determining support points of unobserved heterogeneity. We find that ignoring time-changing features of explanatory variables introduces substantial biases in model coefficient and average partial effect estimates. These biases do not diminish as sample size increases.
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