In this paper we study, using the sup LR test, the possibility of discrimination between two classes of models: the Markov switching models of Hamilton (1989) and the Threshold Auto-Regressive Models (TAR) of Lim and Tong (1980). This work is motivated by the fact that generally practicians use,...

This paper uses three classes of univariate time series techniques (ARIMA type models, switching regression models, and state-space/structural time series models) to forecast, on an ex post basis, the downturn in U.S. housing prices starting around 2006. The performance of the techniques is...

This paper reconsiders the conventional use of econometric models, especially identified vector autoregressive models, in guiding monetary policy. The main question I explore is whether these models are seriously flawed because they ignore asymmetries in the business cycles. Toward that end,...

This paper focuses on the occupational mobility of temporary help agency workers by studying their job-to-job upgrading chances as opposed to those who have not been hired through these intermediaries. A screening approach to the role of those labor ‘brokers’ suggests that agency workers may...

In recent years two classes of switching models have been proposed, the Markov switching models, Hamilton (1989) and the Threshold Auto- Regressive Models (TAR), Lim and Tong (1980). These two models have the advantage of being able to modelize and capture asymmetry, sudden changes and...

This paper reconsiders the conventional use of econometric models, especially identified vector autoregressive models, in guiding monetary policy. The main question I explore is whether these models are seriously flawed because they ignore asymmetries in the business cycles. Toward that end,...

In this paper we propose a new parametrisation of transition probabilities that allows us to characterize and test Granger-causality in Markov switching models by means of an appropriate specification of the transition matrix. Test for independence are also provided. We illustrate our...