New technology and old institutions: An empirical analysis of the skill-biased demand for older workers in Europe

Fei Peng; Sajid Anwar; Lili Kang

doi:10.1016/j.econmod.2017.03.004

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New technology and old institutions: An empirical analysis of the skill-biased demand for older workers in Europe

Journal article

Open access

Peer reviewed

New technology and old institutions: An empirical analysis of the skill-biased demand for older workers in Europe

Fei Peng, Sajid Anwar and Lili Kang

Economic Modelling, Vol.64, pp.1-19

2017

DOI: https://doi.org/10.1016/j.econmod.2017.03.004

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Abstract

earnings

older workers

information and communication technology

labour market institutions

Using panel data from nine European countries over the period 1970 to 2007, we examine the impact of information and communication technology (ICT) on the demand for older workers (aged 50 and over). We find evidence of a decrease in demand for older workers in the 1970s and 1980s. It can be argued that the impact of ICT on demand for older workers is skill-biased. However, the skill-biased demand for older workers is mainly reflected in the skill-biased changes in employment shares rather than relative wages. There is some evidence of a gradual deskilling of older workers. We find that labour market institutions such as the national minimum wage, social pacts on wage issues and union density mostly benefit skilled older workers, while coordination of wage setting, extension of collective agreements, social pacts on pensions and centralisation of wage bargaining can alleviate the adverse effects of skill-biased technological change.

Details

Title: New technology and old institutions: An empirical analysis of the skill-biased demand for older workers in Europe
Authors: Fei Peng (Author) - Shanghai Lixin University of Accounting and Finance, China
Sajid Anwar (Author) - University of the Sunshine Coast - Faculty of Arts, Business and Law
Lili Kang (Author) - Shanghai Lixin University of Accounting and Finance, China
Publication details: Economic Modelling, Vol.64, pp.1-19
Publisher: Elsevier BV
Date published: 2017
DOI: 10.1016/j.econmod.2017.03.004
ISSN: 0264-9993
Organisation Unit: School of Business and Creative Industries; Indigenous and Transcultural Research Centre; University of the Sunshine Coast, Queensland; USC Business School - Legacy
Language: English
Record Identifier: 99450935702621
Output Type: Journal article

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