Predicting recessions with leading indicators: An application on the Icelandic economy
This paper focuses on the Stock and Watson methodology to fore- cast the future state of the business cycle in the Icelandic economy. By selecting variables available on a monthly basis that mimic the cyclical behaviour of the quarterly GDP, coincident and leading vari- ables are identi?ed. A factor model is then speci?ed based on the assumption that a single common unobservable element drives the cyclical evolution of many of the Icelandic macroeconomic variables. The model is cast into a state space form providing a simple frame- work both for estimation and for predicting the future recession and expansion patterns. Based on the bootstrap resampling technique, a simple approach to estimate recession and expansion probabilities is developed. This method is completely nonparametric compared to the semi-parametric approach used by Stock and Watson.
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