Real Time Measurement of the Business Cycle Using Mixed Frequency Data

Real-time, daily measurements of the state of the economy are important for economic agents, including financial market participants.To measure the state of the economy in real time, this paper estimates the unobservable state of the economy using a dynamic factor model with mixed frequency data, which simultaneously examines an economic time series using daily, monthly, and quarterly observation periods.Specifically, a real-time economic index using daily term premia, monthly employment and industrial production index growth rates, and quarterly real GDP growth rates were estimated.The estimation results show that the parameter are statistically significant, and the estimated index is able to describe the past economic upturns and downturns and has some similarity with the quarterly real GDP time series.This suggests that the estimation methodology of this paper and the resulting estimated economic index have some relevance.Furthermore, this study's contribution to the Korean economy is somewhat limited when it comes to applying the economic index construction method developed in earlier studies, but its significance lies in its confirmation of the method's potential for use in future economic analyses in Korea.In other words, the methodology of this study can be applied to the existing monthly economic coincidence index at the national level, and it can also be used to create economic indexes for local economies that lack monthly time series.