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A machine learning approach to identifying different types of uncertainty

Bennett Saltzman and Julieta Yung ()

Economics Letters, 2018, vol. 171, issue C, 58-62

Abstract: We implement natural language processing techniques to extract uncertainty measures from Federal Reserve Beige Books between 1970 and 2018. Business and economic related uncertainty is associated with future weakness in output, higher unemployment, and elevated term premia. On the other hand, political and government uncertainty, while high during recent times, has no statistically significant impact on the economy.

Keywords: Natural language processing; VAR; Federal Reserve Beige Books (search for similar items in EconPapers)
JEL-codes: C8 E52 D80 (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:ecolet:v:171:y:2018:i:c:p:58-62