Evaluating currency crises: A Bayesian Markov switching approach

In this paper we examine the nature of a currency crisis. We do so by employing an out-of-sample forecasting exercise to analyse the Mexican crisis in 1994. Forecast evaluation was based on modern econometric techniques concerning the shape of forecaster's loss function. We also extend the empirical framework suggested by Jeanne and Masson [Jeanne, O., Masson, P., 2000. Currency crises and Markov-switching regimes. Journal of International Economics 50, 327-350] to test for the hypothesis that the currency crisis was driven by sunspots. To this end we contribute to the existing literature by comparing Markov regime switching model with a time-varying transition probabilities with two alternative models. The first is a Markov regime switching model with constant transition probabilities. The second is a linear benchmark model. Empirical results show that the proxy for the probability of devaluation is an important factor explaining the nature of currency crisis. More concretely, when the expectation market pressure was used as a proxy of probability of devaluation, forecast evaluation supports the view that currency crisis was driven by market expectation unrelated to fundamentals. Alternatively, when interest rate differential is used as a proxy for probability of devaluation, currency crisis was due to predictable deterioration of fundamentals.