Expectation and confusion: Evidence and theory
成果类型：
Article
署名作者：
Chen, Heng; Liu, Yicheng
署名单位：
University of Hong Kong; University of International Business & Economics
刊物名称：
JOURNAL OF ECONOMIC THEORY
ISSN/ISSBN：
0022-0531
DOI：
10.1016/j.jet.2026.106189
发表日期：
2026
关键词：
摘要：
In this paper, we characterize a forecasting model where forecasters cannot perfectly distinguish between the two persistent components (trends and cycles) in a dynamic setting. In this model, forecasters jointly update their beliefs about the two components: noisy information about one component is used to update beliefs about the other component. We present diagnostic empirical facts on forecasting behaviors and show that these facts are consistent with our model's predictions while contradicting those of existing models in the expectation formation literature. To validate our model, we exploit the Federal Reserve's 2012 adoption of explicit inflation targeting as a policy shock. Structural estimation reveals that this policy change altered the underlying data generation process, and the corresponding changes in forecasting behavior indeed align with our model's predictions. Finally, we revisit the standard Forecast Error-Forecast Revision regression approach in this literature. We examine its robustness within our enriched framework and reveal that trend-cycle confusion can interact with behavioral bias and generate horizon-dependent overreaction patterns documented in empirical studies.