SSOAR Logo
    • Deutsch
    • English
  • Deutsch 
    • Deutsch
    • English
  • Einloggen
SSOAR ▼
  • Home
  • Über SSOAR
  • Leitlinien
  • Veröffentlichen auf SSOAR
  • Kooperieren mit SSOAR
    • Kooperationsmodelle
    • Ablieferungswege und Formate
    • Projekte
  • Kooperationspartner
    • Informationen zu Kooperationspartnern
  • Informationen
    • Möglichkeiten für den Grünen Weg
    • Vergabe von Nutzungslizenzen
    • Informationsmaterial zum Download
  • Betriebskonzept
Browsen und suchen Dokument hinzufügen OAI-PMH-Schnittstelle
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Volltext herunterladen

(743.9 KB)

Zitationshinweis

Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):
https://nbn-resolving.org/urn:nbn:de:0168-ssoar-84505-2

Export für Ihre Literaturverwaltung

Bibtex-Export
Endnote-Export

Statistiken anzeigen
Weiterempfehlen
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

Do job vacancies variations anticipate employment variations by sector? Some preliminary evidence from Italy

[Zeitschriftenartikel]

Lovaglio, Pietro Giorgio

Abstract

Government policy has placed increasing emphasis on the need for robust labour market projections. The job vacancy rate is a key indicator of the state of the economy underpinning most monetary policy decisions. However, its variation over time is rarely studied in relation to employment variations,... mehr

Government policy has placed increasing emphasis on the need for robust labour market projections. The job vacancy rate is a key indicator of the state of the economy underpinning most monetary policy decisions. However, its variation over time is rarely studied in relation to employment variations, especially at the sectoral level. The present paper assesses whether changes in the number of vacancies from quarter to quarter are a leading anticipator of employment variation in certain economic sectors over the previous decade in Italy, using multivariate time-series tools (the vector autoregressive and error correction models) with Eurostat data. As robustness checks for integration order and cointegration, we compare traditional critical values with those provided by response surface models. To the best of our knowledge, no previous study has evaluated this relationship using Italian data over the last decade. The results demonstrate that percentage changes in numbers employed (occupied persons) react to percentage changes in vacancies (one-quarter lagged), but not vice versa, indicating that variations of vacancies are weakly exogenous. The fastest short-term adjustment from disequilibrium is seen in the construction industry, whereas the manufacturing and the information and communication technology sectors demonstrate the strongest long-run relationships among variations. This suggests that the matching rates - the likelihood that a vacancy is filled - are higher for these than for other sectors, as a result of developments in recruitment technology for professional figures of such industries.... weniger

Thesaurusschlagwörter
Italien; Stellenangebot; Beschäftigung; Arbeitsnachfrage; Arbeitsmarkt; Wirtschaftssektor; offene Stellen

Klassifikation
Arbeitsmarktforschung

Freie Schlagwörter
EU-LFS 2011-2018; cointegration; job vacancy rate; long-run equilibrium

Sprache Dokument
Englisch

Publikationsjahr
2022

Seitenangabe
S. 71-93

Zeitschriftentitel
LABOUR, 36 (2022) 1

DOI
https://doi.org/10.1111/labr.12213

ISSN
1121-7081

Status
Veröffentlichungsversion; begutachtet (peer reviewed)

Lizenz
Creative Commons - Namensnennung, Nicht-kommerz. 4.0


GESIS LogoDFG LogoOpen Access Logo
Home  |  Impressum  |  Betriebskonzept  |  Datenschutzerklärung
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Impressum  |  Betriebskonzept  |  Datenschutzerklärung
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.