The COVID-19 recession that started in March 2020 led to an unprecedented decline in economic activity across the globe. To fight this recession, policy makers in central banks engaged in expansionary monetary policy. This paper asks whether the measures adopted by the US Federal Reserve (Fed) have been effective in boosting real activity and calming financial markets. To measure these effects at high frequencies, we propose a novel mixed frequency vector autoregressive (MF-VAR) model. This model allows us to combine weekly and monthly information within a unified framework. Our model combines a set of macroeconomic aggregates such as industrial production, unemployment rates, and inflation with high-frequency information from financial markets such as stock prices, interest rate spreads, and weekly information on the Fed's balance sheet size. The latter set of high-frequency time series is used to dynamically interpolate the monthly time series to obtain weekly macroeconomic measures. We use this setup to simulate counterfactuals in absence of monetary stimulus. The results show that the monetary expansion caused higher output growth and stock market returns, more favorable long-term financing conditions and a depreciation of the US dollar compared with a no-policy benchmark scenario.

中文翻译：

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在 COVID-19 衰退期间衡量美国货币政策的有效性

2020 年 3 月开始的 COVID-19 衰退导致全球经济活动出现前所未有的下滑。为了应对这场衰退，中央银行的政策制定者实施了扩张性货币政策。本文询问美联储（Fed）采取的措施是否有效促进了实体活动和稳定金融市场。为了在高频下测量这些影响，我们提出了一种新的混合频率向量自回归 (MF-VAR) 模型。这个模型允许我们在一个统一的框架内结合每周和每月的信息。我们的模型将一组宏观经济总量（如工业生产、失业率和通货膨胀）与来自金融市场的高频信息（如股票价格、利差和美联储资产负债表规模的每周信息）相结合。后一组高频时间序列用于动态插值月时间序列以获得每周宏观经济指标。在没有货币刺激的情况下，我们使用此设置来模拟反事实。结果表明，与无政策基准情景相比，货币扩张导致更高的产出增长和股市回报、更有利的长期融资条件以及美元贬值。