Adaptive learning and labour market dynamics

Working papers set out research in progress by our staff, with the aim of encouraging comments and debate.
Published on 09 December 2016

Working Paper No. 633
By Federico Di Pace, Kaushik Mitra and Shoujian Zhang

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 it is unable to replicate: properties of survey forecasts of unemployment in the near term. We present a parsimonious model with adaptive learning and simple autoregressive forecasting rules which 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.

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