Quantifying noise in survey expectations

• 成果类型: Article
• 署名作者: Juodis, Arturas; Kucinskas, Simas
• 署名单位: University of Amsterdam; Tinbergen Institute; Humboldt University of Berlin
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE1633
• 发表日期: 2023
• 页码: 609-650
• 关键词: Expectation formation; factor models; measurement error; noise; panel data; subjective expectations; C53; D83; E70; G40

摘要

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.