Search Frictions and Evolving Labour Market Dynamics

Michael Ellington, Christopher Martin, Bingsong Wang

Research output: Contribution to journalArticlepeer-review

2 Citations (SciVal)
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Abstract

This paper puts Search Frictions models under novel empirical scrutiny. To capture changing dynamics, we fit a Bayesian time-varying parameter VAR to US labour market data from 1965–2016. Using a DSGE model with Search Frictions, we identify several structural shocks, including a shock to worker bargaining power that we name a wage shock. We argue that the wage shock is a key driver of cyclical variation, explaining a higher proportion of the variation of these variables than productivity, demand or job separation shocks. We also document stark differences between empirical and theoretical impulse response functions that cast doubt on the core transmission mechanism of search and matching models.

Original languageEnglish
Article number104104
Number of pages26
JournalJournal of Economic Dynamics and Control
Volume127
Early online date21 Apr 2021
DOIs
Publication statusPublished - 30 Jun 2021

Funding

We would like to thank the editor, Thomas Lubik, an anonymous associate editor and two anonymous referees for providing insightful comments that have increased the quality of our work. We also thank Luca Benati, Franceso Zanetti, Haroon Mumtaz, Gary Koop and Marco Fogoni for their comments, discussions, and sharing computer code. Finally, we are grateful to seminar participants at: The University of Bath; Brunel University; Durham University; The University of Strathclyde; the 12th International Conference on Computational and Financial Econometrics held at the University of Pisa in December 2018; and the Spanish Association of International Economics and Finance meeting held in Granada in June 2019.

FundersFunder number
Brunel University
Spanish Association of International Economics and Finance
University of Strathclyde
Durham University

    Keywords

    • real wages
    • search frictions
    • time-varying parameter model

    ASJC Scopus subject areas

    • Control and Optimization
    • Applied Mathematics
    • Economics and Econometrics

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