Misclassification-Errors-Adjusted Sahm Rule for Early Identification of Economic Recession

Shuaizhang Feng () and Jiandong Sun ()
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Shuaizhang Feng: Shanghai University of Finance and Economics
Jiandong Sun: Jinan University

No 13168, IZA Discussion Papers from IZA Network @ LISER

Abstract: Accurate identification of economic recessions in a timely fashion is a major macroeconomic challenge. The most successful early detector of recessions, the Sahm rule, relies on changes in unemployment rates, and is thus subject to measurement errors in the U.S. labor force statuses based on survey data. We propose a novel misclassification-error-adjusted Sahm recession indicator and provide empirically-based optimal threshold values. Using historical data, we show that the adjusted Sahm rule offers earlier identification of economic recessions. Based on the newly released U.S. unemployment rate in March 2020, our adjusted Sahm rule diagnoses the U.S. economy is already in recession, while the original Sahm rule does not.

Keywords: misclassification errors; Sahm rule; economic recession; unemployment rate (search for similar items in EconPapers)
JEL-codes: E32 J64 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2020-04
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (3)

Published - published in: Journal of Asian Economics, 2021, 75, 101319

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