Nowcasting the output gap
提出基于混合频率贝叶斯VAR的贝弗里奇-尼尔森分解法直接即时预测美国产出缺口，发现月度信贷利差、消费者情绪和失业率指标对季度内预测特别有用，并在新冠疫情中成功提前预测了2020年第二季度-8.3%的巨大负缺口。
We propose a way to directly nowcast the output gap using the Beveridge–Nelson decomposition based on a mixed-frequency Bayesian VAR. The mixed-frequency approach produces similar but more timely estimates of the U.S. output gap compared to those based on a quarterly model, the CBO measure of potential, or the HP filter. We find that within-quarter nowcasts for the output gap are more reliable than for output growth, with monthly indicators for a credit risk spread, consumer sentiment, and the unemployment rate providing particularly useful new information about the final estimate of the output gap. An out-of-sample analysis of the COVID-19 crisis anticipates the exceptionally large negative output gap of -8.3% in 2020Q2 before the release of real GDP data for the quarter, with both conditional and scenario nowcasts tracking a dramatic decline in the output gap given the April data.