Output Collapse, Growth and Volatility in Sub-Saharan Africa: A Regime-Switching Approach

Abstract

A Markov-switching model with time-varying transition probabilities is applied to sub- Saharan African data to examine the link between output collapses and growth. In the model, the growth rate moves discretely between two regimes; one characterised by a stable positive average growth rate, and a collapse regime characterised by negative and volatile growth rate. The aim is to derive plausible estimates of the transition probabilities for the Markov chain component. These estimates are then included in a vector of time-varying country-specific variables for the Markov-switching estimation. The results show that the probability of an economy remaining in a stable growth regime increases with institutional quality, education, improving terms of trade and increased concentration on manufacturing industries. The analysis takes into account the fact that the dynamics of output following a large collapse differs significantly from the dynamics of output during more stable time periods by taking a non-linear approach.