We present non-linear models to capture the turning points in global economic activity as well as in advanced and emerging economies from 1980 to 2017. We first estimate Markov Switching models within a univariate framework. These models support the relevance of three business cycle regimes...

This paper reconciles two widely used trend-cycle decompositions of GDP that give markedly different estimates: the correlated unobserved components model yields output gaps that are small in amplitude, whereas the Hodrick-Prescott (HP) filter generates large and persistent cycles. By embedding...

In this paper, we examine the results of GDP trend-cycle decompositions from the estimation of bivariate unobserved components models that allow for correlated trend and cycle innovations. Three competing variables are considered in the bivariate setup along with GDP: the unemployment rate, the...

This paper analyzes the evolution of the Lebanese GDP growth rate over the period 1970- 2019 by estimating two kinds of switching models: The Smooth Transition Autoregressive (STAR) model and the model of the Markov process. These models show, on the one hand, asymmetries in the evolution of GDP...