We conduct Monte Carlo simulations to investigate the effects of outlier observations on the properties of linearity tests against threshold autoregressive (TAR) processes. By considering different specifications and levels of persistence of the data generating processes, we find that outliers...

We propose an improved method for constructing likelihood-ratio-based confidence intervals for threshold parameters in threshold regressions. Related methods have been extensively developed in the literature and are asymptotically valid. However, their performance in finite samples is not...

A threshold vector autoregression (TVAR) is estimated to study the effects of oil price shocks on Canadian output and price level. While much of the literature has investigated potential asymmetric effects of positive and negative oil price shocks, we extend the analysis to consider asymmetries...

Despite a low unemployment rate, wage growth in the U.S. was negligible during the 2013-2015 period. Conventional linear models of the relationship between wages and unemployment, the so- called wage Phillips curve (WPC), and previous models of the WPC that rely on regime-switching driven only...

Within the context of threshold regressions, we show that asymptotically-valid likelihood-ratio-based confidence intervals for threshold parameters perform poorly in finite samples when the threshold effect is large. A large threshold effect leads to a poor approximation of the profile...

We estimate a Bayesian threshold vector autoregression (TVAR) to study the relationship between exchange rate pass-through and economic activity in Canada and Mexico. Both the model comparison and the analysis of impulse-response functions provide strong evidence of a nonlinear relationship and...