Panel threshold models with interactive fixed effects
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This paper studies estimation and inference in a panel threshold model in the presence of interactive fixed effects. We study the asymptotic properties of the least squares estimators of the regression parameters in the shrinking-threshold-effect framework. We find that under some regularity conditions, the threshold parameter estimator possesses super-consistency in the sense that its estimation error has an asymptotically negligible effect on the asymptotic properties of the slope coefficients. The inference on the threshold parameter can be conducted based on a likelihood ratio test statistic as in the cross-sectional or time series setup. We also propose a test for the presence of the threshold effect. Monte Carlo simulations suggest that our estimators and test statistics perform well in finite samples. We apply our method to study the effect of financial development on economic growth and find that there is indeed a turning point in the effect for all three measures of financial development when the cross-sectional dependence is properly accounted for.