This paper intends to harmonize two different approaches to the analysis of the business cycle and in doing so it retrieves the stylized facts of the business cycle in Europe. We start with the ‘classical’ approach proposed in Burns and Mitchell (1946) of dating and analyzing the business cycle; we then adopt the ‘modern’ alternative: the Markov-switching time series model proposed in Hamilton ...

We derive forecasts for Markov switching models that are optimal in the MSFE sense by means of weighting observations. We provide analytic expressions of the weights conditional on the Markov states and conditional on state probabilities. This allows us to study the e↵ect of uncertainty around states on forecasts. It emerges that, even in large samples, forecasting performance increases substan...

We examine the determinants of low income transitions using first-order Markov models that control for initial conditions effects (those found to be poor in the base year may be a nonrandom sample) and for attrition (panel retention may also be non-random). Our econometric model is a form of endogeneous switching regression, and is fitted using simulated maximum likelihood methods. The estimate...

This paper offers new insights into the nature of exchange rate pass through modelling in the context of a Markov regime-switching environment. Using New Zealand data, the results indicate that pass through to import prices resulting from fluctuations in the exchange rate or exporter costs can be characterised as regime-specific. Furthermore, there is evidence that the probability of switching ...

We introduce the Multivariate Autoregressive Conditional Double Poisson model to deal with discreteness, overdispersion and both auto and cross-correlation, arising with multivariate counts. We model counts with a double Poisson and assume that conditionally on past observations the means follow a Vector Autoregression. We resort to copulas to introduce contemporaneous correlation. We apply it ...

Commodity price always related to the movement of stock market index. However real economic time series data always exhibit nonlinear properties such as structural change, jumps or break in the series through time. Therefore, linear time series models are no longer suitable and Markov Switching Vector Autoregressive models which able to study the asymmetry and regime switching behavior of the d...

in a finite stationary markov chain, transition probabilities may depend on some explanatoryvariables. a similar problem has been considered here. the corresponding posteriors are derived andinferences are done using these posteriors. finally, the procedure is illustrated with a real example.