we propose a Bayesian Logistic Smooth Transition Autoregressive (LSTAR) model with stochastic volatility (SV) to inflation dynamics in nonlinear fashion. Inflationary regimes are determined by smoothed money growth which serves as transition variable that governs the between regimes. We apply this approach quarterly data from US, UK and Canada able identify well-known, high periods samples. Mor...

Although linear autoregressive models are useful to practitioners in different fields, often a nonlinear specification would be more appropriate time series analysis. In general, there many alternative approaches nonlinearity modelling, one consists assuming multiple regimes. Among the possible specifications that account for regime changes multivariate framework, smooth transition most since t...

This article examines the null limit distribution of quasi-likelihood ratio (QLR) statistic for testing linearity condition against smooth transition autoregressive (STAR) model. We explicitly show that QLR test weakly converges to a functional multivariate Gaussian process under linearity, which is done by resolving issue identification problem arises in two different ways null. In contrast wi...

Since the late nineties, both theoretical and empirical analysis devoted to the real exchange rate suggest that their dynamics might be well approximated by nonlinear models. This paper examines this possibility for post-1970 monthly ASEAN-5 data, extending the existing research in two directions. First, we use recently developed unit root tests which allow for more flexible nonlinear stationar...

The universal method for testing linearity against smooth transition autoregressive (STAR) alternatives is the linearization of the STAR model around the null nuisance parameter value, and performing F-tests on polynomial regressions in the spirit of the RESET test. Polynomial regressors, however, are poor proxies for the nonlinearity associated with STAR processes, and are not consistent (asym...