Dynamic information aggregation: Learning from the past

A-Tier
Journal: Journal of Monetary Economics
Year: 2023
Volume: 136
Issue: C
Pages: 107-124

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

With dispersed information, how much can agents learn from past endogenous aggregates such as prices or output? In a rational-expectations equilibrium, if general equilibrium effects are strong enough, aggregates no longer perfectly reveal underlying fundamentals. In this confounding regime, the effects of informational frictions are persistent over time, and the aggregate outcome displays an initial under-reaction followed by a delayed over-reaction relative to its perfect-information counterpart. In a standard New Keynesian model, we show that endogenous information aggregation helps bring the model predictions on aggregate forecasts closer to the data.

Technical Details

RePEc Handle
repec:eee:moneco:v:136:y:2023:i:c:p:107-124
Journal Field
Macro
Author Count
2
Added to Database
2026-01-29