Monitoring the world business cycle

- We propose a Markov-switching DFM to construct an index of global business cycle conditions in real time.
- Our model accounts for mixed frequencies, for asynchronous data publication and for leading financial indicators.
- We perform short-term forecasts of world GDP quarterly growth in real time and compute real-time business cycle probabilities.
- Pseudo real-time results show our approach provides reliable, timely inferences of world quarterly growth on a monthly basis.

We propose a Markov-switching dynamic factor model to construct an index of global business cycle conditions, to perform short-term forecasts of world GDP quarterly growth in real time and to compute real-time business cycle probabilities. To overcome the real-time forecasting challenges, the model accounts for mixed frequencies, for asynchronous data publication and for leading indicators. Our pseudo real-time results show that this approach provides reliable and timely inferences of the world quarterly growth and of the world state of the business cycle on a monthly basis.