<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

Workforce Ageing and Labour Productivity Dynamics

Naše gospodarstvo/Our economy

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"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,...

Workforce Ageing and Labour Productivity Dynamics

Publié en ligne: 06 oct. 2020

Pages: 1 - 13

Reçu: 01 oct. 2019

Accepté: 01 juin 2020

DOI: https://doi.org/10.2478/ngoe-2020-0013

Mots clés
labour productivity, demographics, neoclassical production function, panel data

© 2020 Ana Milanez, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Workforce Ageing and Labour Productivity Dynamics

Publié en ligne: 06 oct. 2020

Pages: 1 - 13

Reçu: 01 oct. 2019

Accepté: 01 juin 2020

DOI: https://doi.org/10.2478/ngoe-2020-0013

Mots cléslabour productivity, demographics, neoclassical production function, panel data

© 2020 Ana Milanez, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
labour productivity, demographics, neoclassical production function, panel data