Standard models of information frictions explain sluggishness in forecasts but struggle to account for excessive sensitivity. I argue that this gap reflects a narrow definition of information frictions: these models constrain the processing of new information while assuming agents can access and use previously acquired information without error. I propose a broader framework with two constraints: attention frictions introduce errors in how agents use new information, and memory frictions introduce errors in how they use previously acquired information. This unified model better matches observed forecast biases and jointly identifies attention and memory frictions using survey forecasts.
Suggested citation:
Sung, Yeji. 2026. “Macroeconomic Expectations and Cognitive Noise.” Federal Reserve Bank of San Francisco Working Paper 2024-19. https://doi.org/10.24148/wp2024-19