Threshold mixed data sampling models with a covariate-dependent threshold

Abstract

ABSTRACT This paper introduces a threshold mixed data sampling model with a covariate-dependent threshold (TMIDAS-CDT), which allows for a threshold effect in the relationship between dependent and independent variables sampled at different frequencies, and allows for threshold regimes depending on a time-varying threshold being modelled as a linear function of informative covariates. We develop the estimation procedure for the model, and suggest test statistics for threshold effect, threshold constancy and the equal weighting scheme in aggregating high-frequency data. We conduct Monte Carlo simulations to investigate the performance of the estimation and testing procedures. The simulation results support that the estimation procedure works well in finite samples, and the test statistics have good size and power properties.