Artikel

Workforce ageing and labour productivity dynamics

This paper adopts a neoclassical framework to study the effect of age composition of the working-age population on labour productivity and its determinants, based on an unbalanced panel of 64 non-oil-producing countries, over the period 1950-2017. Our first contribution comes from testing whether a shock in age structure has the ability to permanently shift labour productivity dynamics. From methodological standpoint, we try to reduce the risk of model mispecification in the existing literature, that has often overlooked the possibility of cross-sectional dependence in the data and heterogeneity in slope coefficients. We also note the importance of time series properties of the data for valid statistical inference. Our results indicate, that ageing of the working-age population depresses labour productivity growth; negative impact of individuals aged between 55 and 64 on total factor productivity growth is only partially offset by its positive impact on human and physical capital accumulation. For sustaining the current level of living standards, adoption of policies, which forestall the negative impact of older workers on innovation process and promote their positive impact on the supply of production factors, is of crucial importance. We do not find evidence, that higher public spending on education in% of GDP has such an effect.

Sprache
Englisch

Erschienen in
Journal: Naše gospodarstvo / Our Economy ; ISSN: 2385-8052 ; Volume: 66 ; Year: 2020 ; Issue: 3 ; Pages: 1-13

Klassifikation
Wirtschaft
Economics of the Elderly; Economics of the Handicapped; Non-labor Market Discrimination
Human Capital; Skills; Occupational Choice; Labor Productivity
General Aggregative Models: Neoclassical
Thema
labour productivity
demographics
neoclassical production function
panel data

Ereignis
Geistige Schöpfung
(wer)
Milanez, Ana
Ereignis
Veröffentlichung
(wer)
Sciendo
(wo)
Warsaw
(wann)
2020

DOI
doi:10.2478/ngoe-2020-0013
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

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Objekttyp

  • Artikel

Beteiligte

  • Milanez, Ana
  • Sciendo

Entstanden

  • 2020

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