Measuring business cycles: A temporal disaggregation model with regime switching

In this paper, we propose a temporal disaggregation model with regime switches to disaggregate U.S. quarterly GDP into monthly figures. Alternative to the existing literature, our model is able to capture the nonlinear behaviors of both aggregated and disaggregated output series as well as the asymmetric nature of business cycle phases. To demonstrate the applicability of the proposed model, we apply the model with a Markov trend component to U.S. quarterly real GDP. The results suggest that the combination of a temporal disaggregation model with Markov switches leads to a successful representation of the data relative to the existing literature. Also, the inferred probabilities of unobserved states are clearly in close agreement with the NBER reference cycle on a monthly basis, which highlights the importance of nonlinearities in business cycle.

► This paper proposes a temporal disaggregation model with regime switching. ► Our model describes the nonlinear behaviors of aggregated and disaggregated series. ► Our model can disaggregate the U.S. quarterly real GDP into monthly figures. ► Our model provides out-of-sample forecasts for the U.S. quarterly real GDP.