On business cycle forecasting

Frontiers of Business Research in China

Eric C. Y. Ng¹  Huiwen Lai² 

[1] Department of Economics, Hong Kong University of Science and Technology, Hong Kong, China;School of Accounting and Finance, Faculty of Business, Hong Kong Polytechnic University, Hong Kong, China;

关键词: Recession forecasting;    Business cycle;    Autoregressive Logit;    Dynamic factor;    Mixed data sampling (MIDAS) regression;   

DOI  :  10.1186/s11782-020-00085-3

来源: Springer

【 摘 要 】

We develop a recession forecasting framework using a less restrictive target variable and more flexible and inclusive specification than those used in the literature. The target variable captures the occurrence of a recession within a given future period rather than at a specific future point in time (widely used in the literature). The modeling specification combines an autoregressive Logit model capturing the autocorrelation of business cycles, a dynamic factor model encompassing many economic and financial variables, and a mixed data sampling regression incorporating common factors with mixed sampling frequencies. The model generates significantly more accurate forecasts for U.S. recessions with smaller forecast errors and stronger early signals for the turning points of business cycles than those generated by existing models.

【 授权许可】

CC BY