Adaptive learning and labor market dynamics

Federico Di Pace, Kaushik Mitra, Shoujian Zhang

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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.

Original languageEnglish
Pages (from-to)441-475
Number of pages35
JournalJournal of Money, Credit and Banking
Volume53
Issue number2-3
Early online date13 Jan 2021
DOIs
Publication statusPublished - Mar 2021

Bibliographical note

Publisher Copyright:
© 2021 The Ohio State University

Keywords

  • adaptive learning
  • bounded-rationality
  • search and matching frictions

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

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