This paper uses several macroeconomic and financial indicators within a Markov Switching (MS) framework to predict the turning points of the business cycle. The presented model is applied to monthly German real-time data covering the recession and the recovery after the financial crisis. We show how to take advantage of combining single MS forecasts and of changing the number of regimes on the real-time path, where both leads to a higher forecast accuracy. Changing the number of regimes implies a distinction for recessions representing either a normal or an extraordinary one, which particularly means to determine as early as possible the point in time, from which the last recession structurally exceeded the previous ones. In fact it turns out that the Markov Switching model can signal quite early whether a conventional recession happens or whether an economic downturn will be more substantial.
Business Cycle Leading Indicators Macroeconomic Forecasting Markov Switching