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Macroeconomic determinants of labour costs in the EU: a comprehensive panel and cluster analysis

Author

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  • Cristescu Amalia

    (National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania)

  • Stănilă Larisa

    (National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania)

  • Vasilescu Maria Denisa

    (National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania)

  • Munteanu Andreea Monica

    (National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania)

Abstract

Labour costs are a fundamental component of production expenses, significantly impacting both the quantity and quality of output. This study explores the determinants of labour costs within EU member states that have implemented minimum wage policies over the past two decades. The research technique includes a comprehensive panel analysis of EU member states to identify significant variables influencing labour costs, as well as cluster analysis to discover underlying patterns across the nations under examination. Our findings reveal that higher minimum wage levels, higher employment rates, increased labour productivity, and greater trade openness are positively correlated with higher labour costs. Specifically, increases in these variables lead to higher wages and a broader tax base, while greater trade openness results in elevated labour costs due to expanded market opportunities. Conversely, gross fixed capital formation negatively affects labour costs, as investments in production assets tend to reduce labour requirements or hours worked. The cluster analysis led to the identification of three distinct groups. The first cluster consists of well-developed economies with modest labour cost increases and average minimum wages. The second cluster includes countries with substantial labour cost increases, low minimum wages, and significant productivity gains. The third cluster features nations with high minimum wages and high employment rates. This paper contributes to the field by highlighting the complex interplay between labour costs and economic factors, offering insights for decision-makers to tailor macroeconomic and company-level strategies to specific local conditions. The findings emphasise the importance of balancing wage policies with sustainable economic development to enhance competitiveness while ensuring fair labour conditions.

Suggested Citation

  • Cristescu Amalia & Stănilă Larisa & Vasilescu Maria Denisa & Munteanu Andreea Monica, 2024. "Macroeconomic determinants of labour costs in the EU: a comprehensive panel and cluster analysis," Management & Marketing, Sciendo, vol. 19(3), pages 538-554.
  • Handle: RePEc:vrs:manmar:v:19:y:2024:i:3:p:538-554:n:1008
    DOI: 10.2478/mmcks-2024-0024
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    References listed on IDEAS

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    1. Destefanis, Sergio & Rehman, Naqeeb Ur, 2023. "Investment, innovation activities and employment across European regions," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 474-490.
    2. Van Reenen, John & Bloom, Nicholas & Sadun, Raffaella, 2016. "Management as a Technology," CEPR Discussion Papers 11312, C.E.P.R. Discussion Papers.
    3. Bogliacino, Francesco & Pianta, Mario, 2010. "Innovation and Employment: a Reinvestigation using Revised Pavitt classes," Research Policy, Elsevier, vol. 39(6), pages 799-809, July.
    4. Dosi, G. & Piva, M. & Virgillito, M.E. & Vivarelli, M., 2021. "Embodied and disembodied technological change: The sectoral patterns of job-creation and job-destruction," Research Policy, Elsevier, vol. 50(4).
    5. repec:bbp:journl:y:2014:p:3 is not listed on IDEAS
    6. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
    7. Alina Mihaela Dima & Mihail Busu & Vanesa Madalina Vargas, 2022. "The mediating role of students’ ability to adapt to online activities on the relationship between perceived university culture and academic performance," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1253-1281, December.
    8. Christopher F Baum, 2001. "Residual diagnostics for cross-section time series regression models," Stata Journal, StataCorp LLC, vol. 1(1), pages 101-104, November.
    9. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
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