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News Shocks and Labor Market Dynamics in Matching Models

Author

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  • Konstantinos Theodoridis

    (Bank of England)

  • Francesco Zanetti

    (University of Oxford)

Abstract

We enrich a baseline RBC model with search and matching frictions on the labor market and real frictions that are helpful in accounting for the response of macroeconomic aggregates to shocks. The analysis allows shocks to have an unanticipated and a news (i.e. anticipated) component. The Bayesian estimation of the model reveals that the model which includes news shocks on macroeconomic aggregates produces a remarkable fit of the data. News shocks in stationary and non-stationary TFP, investment-specific productivity and preference shocks significantly affect labor market variables and explain a sizeable fraction of macroeconomic fluctuations at medium- and long-run horizons. Historically, news shocks have played a relevant role for output, but they have had a limited influence on unemployment.

Suggested Citation

  • Konstantinos Theodoridis & Francesco Zanetti, 2015. "News Shocks and Labor Market Dynamics in Matching Models," BCAM Working Papers 1501, Birkbeck Centre for Applied Macroeconomics.
    • Handle: RePEc:bbk:bbkcam:1501
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    Cited by:

    1. Christoph Görtz & John D. Tsoukalas & Francesco Zanetti, 2022. "News Shocks under Financial Frictions," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(4), pages 210-243, October.
    2. Luca Gambetti & Christoph Görtz & Dimitris Korobilis & John D. Tsoukalas & Francesco Zanetti, 2022. "The Effect of News Shocks and Monetary Policy," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 139-164, Emerald Group Publishing Limited.
    3. Renato Faccini & Leonardo Melosi, 2022. "Pigouvian Cycles," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(2), pages 281-318, April.
    4. Ryan Chahrour & Sanjay K. Chugh & Tristan Potter, 2023. "Anticipated productivity and the labor market," Quantitative Economics, Econometric Society, vol. 14(3), pages 897-934, July.
    5. Luca Gambetti & Dimitris Korobilis & John D. Tsoukalas & Francesco Zanetti, 2023. "Agreed and Disagreed Uncertainty," Working Paper series 23-01, Rimini Centre for Economic Analysis.
    6. Renato Faccini & Leonardo Melosi, 2018. "The Role of News about TFP in U.S. Recessions and Booms," Working Paper Series WP-2018-6, Federal Reserve Bank of Chicago.
    7. Schnattinger, Philip, 2023. "Beliefs- and fundamentals-driven job creation," Bank of England working papers 1040, Bank of England.

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    More about this item

    Keywords

    Anticipated productivity shocks; Bayesian SVAR methods; labor market search frictions.;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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