Adaptive Learning and Labor Market Dynamics

B-Tier
Journal: Journal of Money, Credit, and Banking
Year: 2021
Volume: 53
Issue: 2-3
Pages: 441-475

Authors (3)

F. DI PACE (not in RePEc) K. MITRA (University of Birmingham) S. ZHANG (not in RePEc)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

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

Abstract

The standard search and matching model with rational expectations is well known to be unable to generate amplification in unemployment and vacancies. We document a new feature that cannot be replicated: properties of wage forecasts published by institutions in the near term. A parsimonious model with adaptive learning can provide a solution to both of these problems. Firms choose vacancies by forecasting wages using simple autoregressive models; they have greater incentive to post vacancies at the time of a positive productivity shock because of overoptimism about the discounted value of expected profits.

Technical Details

RePEc Handle
repec:wly:jmoncb:v:53:y:2021:i:2-3:p:441-475
Journal Field
Macro
Author Count
3
Added to Database
2026-01-25