Misclassification errors in labor force statuses and the early identification of economic recessions

Abstract

Accurate identification of economic recessions in a timely fashion is a major macroeconomic challenge. The so-called Sahm recession indicator (Sahm, 2019), one of the most reliable early detectors of the U.S. recessions, relies on changes in unemployment rates, and is thus subject to misclassification errors in labor force statuses based on survey data. We propose a novel misclassification-errors correction to improve the predictive timeliness and provide a proper threshold value. Using historical data, we show that the adjusted unemployment-based recession indicator offers earlier identification of economic recessions.