Quantifying noise in survey expectations

Artūras Juodis and Simas Kučinskas

Quantitative Economics, 2023, vol. 14, issue 2, 609-650

Abstract: Expectations affect economic decisions, and inaccurate expectations are costly. Expectations can be wrong due to either bias (systematic mistakes) or noise (unsystematic mistakes). We develop a framework for quantifying the level of noise in survey expectations. The method is based on the insight that theoretical models of expectation formation predict a factor structure for individual expectations. Using data from professional forecasters, we find that the magnitude of noise is large (10%–30% of forecast MSE) and comparable to bias. We illustrate how our estimates can be applied to calibrate models with incomplete information and bound the effects of measurement error.

Date: 2023
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https://doi.org/10.3982/QE1633

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Persistent link: https://EconPapers.repec.org/RePEc:wly:quante:v:14:y:2023:i:2:p:609-650

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