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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