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Hysteresis and sources of aggregate employment inertia

  • Paulo R. Mota EMAIL logo and Paulo B. Vasconcelos
Published/Copyright: November 27, 2020
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Studies in Nonlinear Dynamics & Econometrics
From the journal Studies in Nonlinear Dynamics & Econometrics Volume 26 Issue 1

Abstract

It is widely recognized that aggregate employment dynamics is characterized by hysteresis. In the presence of hysteresis, the long run level of employment instead of being unique and history-independent, depends on the adjustment path that is taken, which includes the monetary and fiscal measures. It is thus important to study the presence of hysteresis in the macrodynamics of employment to understand whether the recession followed 2007s financial crisis will have permanent effects, and prospectively to conduct fiscal and monetary policies. The main contribution of this paper is to analyse the relative impact of the main sources hysteresis (non-convex adjustment costs, uncertainty and the flexibility of working time arrangements) to the width of the employment band of inaction. For that purpose, a switching employment equation was estimated from a computational implementation of the linear play model of hysteresis. From our results we found significant hysteresis effects in the aggregate employment dynamics caused by the presence of non-convex adjustment costs as uncertainty. We also found that the flexibility firms may have to adjust labour input by varying the number of hours of work per employee helps to mitigate the effect of uncertainty upon the band of inaction.

Keywords: adjustment costs; employment; hours of work; hysteresis; uncertainty
JEL Classification: E24; J23
Corresponding author: Paulo R. Mota, Faculdade de Economia do Porto, School of Economics and Business and CEF.UP, University of Porto, Rua Dr. Roberto Frias, 4200 Porto, Portugal, E-mail:

Funding source: FCT – Fundação para a Ciência e a Tecnologia, I.P

Award Identifier / Grant number: UIDB/04105/2020

Award Identifier / Grant number: UIDB/00144/2020 

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This research has been financed by Portuguese public funds through FCT - Fundação para a Ciência e a Tecnologia, I.P., in the framework of the project with reference UIDB/04105/2020. The second author acknowledges the support from CMUP (UID/MAT/00144/2019), which is funded by FCT with national (MCTES) and European structural funds through the programs FEDER, under the partnership agreement PT2020.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

Appendix

GMM Estimation Results.

Independent variables Dependent variable
Aggregate employment in industry (N t ) Total hours of work in industry (H t )
C 1.6131*** (11.966) 1.713*** (12.031)
Y t 0.198** (2.052) 0.142 (1.2828)
SPURT Nt 1.825*** (13.202) –
SPURT Ht – 1.865*** (14.106)
W t −0.285*** (−4.289) −0.286 (−3.953)
R 2 0.944 0.940

  1. Wald test statistics are in parentheses. ***, **,* Significant at 1, 5, and 10% respectively.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/snde-2019-0135).

Received: 2019-11-05
Accepted: 2020-10-30
Published Online: 2020-11-27

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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  2. Research Articles
  3. Testing constant cross-sectional dependence with time-varying marginal distributions in parametric models
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https://doi.org/10.1515/snde-2019-0135
Keywords for this article
adjustment costs; employment; hours of work; hysteresis; uncertainty

Articles in the same Issue

  1. Frontmatter
  2. Research Articles
  3. Testing constant cross-sectional dependence with time-varying marginal distributions in parametric models
  4. Bayesian inference for unit root in smooth transition autoregressive models and its application to OECD countries
  5. Openness-inflation Nexus in alternative monetary regimes
  6. Bayesian bandwidth estimation for local linear fitting in nonparametric regression models
  7. Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data
  8. Choosing between identification schemes in noisy-news models
  9. Hysteresis and sources of aggregate employment inertia
  10. Asymmetric dynamics between uncertainty and unemployment flows in the United States
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