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The Nordhaus test with many zeros

Kajal Lahiri () and Yongchen Zhao

Economics Letters, 2020, vol. 193, issue C

Abstract: We reformulate the Nordhaus test as a friction model where the large number of zero revisions are treated as censored, i.e., unknown values inside a small region of “imperceptibility.” Using Blue Chip individual forecasts of U.S. real GDP growth, inflation, and unemployment over 1985–2020, we find pervasive over-reaction to news at most of the monthly forecast horizons from 24 to 1, but the degree of inefficiency is very small. The updaters, i.e., those who make non-zero revisions, are not found to perform better than their “inattentive” peers.

Keywords: Friction model; Expectations updating; Forecast efficiency; Fixed-event forecasts; Inattentive forecasters (search for similar items in EconPapers)
JEL-codes: C24 C53 E27 E37 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:193:y:2020:i:c:s0165176520302056

DOI: 10.1016/j.econlet.2020.109308

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