Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic
用大贝叶斯向量自回归的Beveridge-Nelson分解估算欧元区产出缺口，发现工作时长比失业率更能反映劳动力利用情况，尤其在新冠衰退期间。
We estimate the euro area output gap by applying the Beveridge-Nelson decomposition based on a large Bayesian vector autoregression. Our approach incorporates multivariate information through the inclusion of a wide range of variables in the analysis and addresses data issues associated with the COVID-19 pandemic. The estimated output gap lines up well with the CEPR chronology of the business cycle for the euro area and we find that hours worked, more than the unemployment rate, provides the key source of information about labor utilization in the economy, especially in pinning down the depth of the output gap during the COVID-19 recession when the unemployment rate rose only moderately. Our findings confirm that labor market adjustments to the business cycle in the euro area occur more through the intensive, rather than extensive, margin.