Forecasting the state of the Finnish business cycle

Abstract

We employ probit models to study the predictability of recession periods in Finland using a set of commonly used variables based on previous literature. The findings point out that individual predictors, including the term spread and the real housing prices from the capital area, are useful predictors of recession periods. However, the best in-sample fit is found using combinations of variables. The pseudo out-of-sample forecasting results are generally in line with the in-sample results, and suggest that in the one-quarter ahead forecasts a model combining the term spread, the unemployment expectation component of the consumer confidence index, and the real housing price index performs the best based on the area under the receiver operating characteristic curve. Autoregressive probit models yield higher in-sample fits compared to the static probit models, and the best pseudo out-of-sample forecasts for longer forecasting horizons are given by an autoregressive model.