Extracting a robust US business cycle using a time‐varying multivariate model‐based bandpass filter
开发了一个灵活的商业周期指标，基于多变量趋势周期分解模型，从美国宏观经济时间序列中提取共同周期，并考虑了时变性和异方差性，预测结果显示未来可能出现衰退。
Abstract We develop a flexible business cycle indicator that accounts for potential time variation in macroeconomic variables. The coincident economic indicator is based on a multivariate trend cycle decomposition model and is constructed from a moderate set of US macroeconomic time series. In particular, we consider an unobserved components time series model with a common cycle that is shared across different time series but adjusted for phase shift and amplitude. The extracted cycle can be interpreted as a model‐based bandpass filter and is designed to emphasize the business cycle frequencies that are of interest to applied researchers and policymakers. Stochastic volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to account for the heteroskedasticity present in the data. Forecasting results are presented for a set of different specifications. Point forecasts from the preferred model indicate a future recession with the uncertainty over the business cycle growing quickly as the forecast horizon increases. Copyright © 2010 John Wiley & Sons, Ltd.