A Markov Switching Regime Model of the Brazilian Business Cycle

Previous studies have shown that linear models are incapable of capturing business cycle dynamics with accuracy. This has brought interest in non-linear models such as the Markov switching (MS) regime technique, which can distinguish business cycle recession and expansion phases, and is sufficiently flexible to allow different relationships to apply over these phases. This technique can be used to simultaneously estimate the data generating process of real GDP growth and classify each observation into one of two regimes (i.e. low-growth and high-growth regimes). In this study, we investigate the dynamics of the Brazilian business cycle using a Markov regime switching vector autoregressive model (MS-VAR). The study was developed using time-variable transition probabilities (TVTP) and for comparison and validation, fixed transition probabilities (FTP) between regimes. In order to capture cyclical fluctuations of the Brazilian GDP, we use the yield spread as a leading indicator. Most of the results obtained with the MS-VAR-TVTP are according to the expected. We show that the model is adequate to predict short-term cyclical fluctuations in the Brazilian economy. We also estimate an MS-VAR model with FTP in order to validate the TVTP model. We confirm the relevance of the yield spread in the estimation of the model parameters and the transition probabilities