Quantifying noise in survey expectations

Author:

Juodis Arturas12,Kucinskas Simas3

Affiliation:

1. Amsterdam School of Economics, University of Amsterdam

2. Tinbergen Institute

3. School of Business and Economics, Humboldt University of Berlin

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.

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Publisher

The Econometric Society

Subject

Economics and Econometrics

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Noise in Expectations: Evidence from Analyst Forecasts;The Review of Financial Studies;2023-12-07

2. Quantifying noise in survey expectations;Quantitative Economics;2023

3. Heterogeneous Expectations among Professional Forecasters;SSRN Electronic Journal;2023

4. Quantifying Sources of Forecaster Disagreement;SSRN Electronic Journal;2023

5. Heterogeneous Expectations among Professional Forecasters;SSRN Electronic Journal;2023

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