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Adaptive learning and labour market dynamics

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  • Di Pace, Frederico

    (Bank of England)

  • Mitra, Kaushik

    (University of Birmingham)

  • Zhang, Shoujian

    (Addiko Bank)

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 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.

Suggested Citation

  • Di Pace, Frederico & Mitra, Kaushik & Zhang, Shoujian, 2016. "Adaptive learning and labour market dynamics," Bank of England working papers 633, Bank of England.
    • Handle: RePEc:boe:boeewp:0633
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    5. Schaefer, Daniel & Singleton, Carl, 2018. "Unemployment and econometric learning," Research in Economics, Elsevier, vol. 72(2), pages 277-296.

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    More about this item

    Keywords

    Adaptive learning; bounded-rationality; search and matching frictions;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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