Panel Threshold Mixed Data Sampling Models With a Covariate-Dependent Threshold

Abstract

This paper introduces a panel threshold mixed data sampling model with a covariate-dependent threshold and unobserved individual-specific threshold effects (PTMIDAS-CDT), in which we allow for a covariate-dependent threshold effect in the relationship between dependent and independent variables sampled at different frequencies, and allow for unobserved individual-specific threshold effects. Based on the Chamberlain–Mundlak correlated random effects (CRE) device and Markov chain Monte Carlo (MCMC) technique, we develop the estimator of model parameters and suggest test statistics for threshold effect, threshold constancy, the equal weighting scheme, and unobserved individual-specific threshold effects. We establish the asymptotic properties of the proposed estimator in the small-threshold-effect framework and derive the limiting distributions of the suggested test statistics. Monte Carlo simulations are conducted to examine the performance properties of the estimation and testing procedures. The simulation results point out that the estimation procedure works well in finite samples, and the test statistics have good size and power properties. The model is illustrated with an application to the nexus between climate change and economic growth.