This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications by applying...

This paper explores the forecasting abilities of Markov-Switching models. Although MS models generally display a superior in-sample fit relative to linear models, the gain in prediction remains small. We confirm this result using simulated data for a wide range of specifications by applying...

Progresses in fiscal consolidation programs are often expressed in cyclically-adjusted terms, meaning that business cycles have to be accurately estimated. In this paper, we put forward a parametric framework enabling to assess business cycles, especially at the end of recession periods by...

This paper proposes a two-regime Bounce-Back Function augmented Self-Exciting Threshold AutoRegression (SETAR) model which allows for various shapes of recoveries from the recession regime. It relies on the bounce-back effects which were first analyzed in a Markov-Switching setup by Kim, Morley,...

In recent years, central banks and international organisations have been making ever greater use of factor models to forecast macroeconomic variables. We examine the performance of these models in forecasting French GDP growth over short horizons. The factors are extracted from a large data set...

In this paper, we investigate the interactions between public debt and transfer policies in a framework based on Floden [2001], that we extend to allow for transitional dynamics between steady states. First, we show that, starting from a high level of public debt, it is possible to implement a...