This paper bridges the gap between two popular approaches to estimating the natural rate of unemployment, u*. The first approach uses detailed labor market indicators, such as labor market flows, cross-sectional data on unemployment and vacancies, or various measures of demographic changes. The second approach, which employs reduced-form models and DSGE models, relies on aggregate price and wage Phillips curve relationships. We combine the key features of these two approaches to estimate the natural rate of unemployment in the United States using both data on labor market flows and a forward-looking Phillips curve that links inflation to current and expected deviations of unemployment from its unobserved natural rate. We estimate that the natural rate of unemployment was around 4.0 percent toward the end of 2018 and that the unemployment gap was roughly closed. Identification of a secular downward trend in the unemployment rate, driven solely by the inflow rate, facilitates the estimation of u*. We identify the increase in labor force attachment of women, decline in job destruction and reallocation intensity, and dual aging of workers and firms as the main drivers of the secular downward trend in the inflow rate.

中文翻译：

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衡量u *的统一方法

本文弥合了两种用于估算自然失业率u *的流行方法之间的差距。第一种方法使用详细的劳动力市场指标，例如劳动力市场流量，有关失业和空缺的横断面数据，或各种人口变化衡量指标。第二种方法采用简化形式的模型和DSGE模型，它依赖于总价格和工资菲利普斯曲线关系。我们结合这两种方法的关键特征，使用劳动力市场流量数据和前瞻性菲利普斯曲线来估算美国的自然失业率，该曲线将通货膨胀与失业率与失业率与其未观察到的自然率的当前和预期偏差相关联。我们估计自然失业率约为4。到2018年底为0％，失业率差距已基本缩小。识别失业率的长期下降趋势，仅由流入率驱动，有助于对u *的估计。我们认为女性劳动力依恋的增加，工作破坏和重新分配强度的下降以及工人和公司的双重衰老是流入率长期下降趋势的主要驱动力。