Technology and skill upgrading: Results from linked worker-plant data for Finnish manufacturing
Vainiomäki, Jari (2013)
Vainiomäki, Jari
Tampereen yliopisto
2013
Johtamiskorkeakoulu - School of Management
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https://urn.fi/URN:ISBN:978-951-44-9083-5
https://urn.fi/URN:ISBN:978-951-44-9083-5
Tiivistelmä
In this paper we use both the standard Census of Manufacturing data and new linked
information on worker characteristics for the Finnish manufacturing plants to examine the skilled/unskilled relative demand and its correlation with technology and demand factors.
The linked worker-plant data are produced by matching workers in the Employment
Statistics database to the plants in the Census of Manufacturing. The employment statistics database is utilised to procure an alternative measure for the skill composition of plants’ work force based on education and to obtain average wages for these educational skill groups. We are therefore able to analyse skill upgrading and relative wages using the standard non-production/production breakdown as well as a skill-grouping based on the workers’ education. We apply decomposition techniques and regression analysis to study possible explanations for the changes in the share of skilled workers. In order to analyse the effects of technology on skill demand we introduce plant level technology indicators from the R&D Survey and a Manufacturing Technology Survey. Our main findings are that skill upgrading is mostly the results of increasing shares of more skilled workers within plants, but also that plant entry and exit effects have become more important. This within-plant skill upgrading correlates positively with the plant level R&D intensity which provides evidence for skill-biased technological change. We also find that the effect of increased demand for skilled workers has mainly increased their employment rather than their wages.
information on worker characteristics for the Finnish manufacturing plants to examine the skilled/unskilled relative demand and its correlation with technology and demand factors.
The linked worker-plant data are produced by matching workers in the Employment
Statistics database to the plants in the Census of Manufacturing. The employment statistics database is utilised to procure an alternative measure for the skill composition of plants’ work force based on education and to obtain average wages for these educational skill groups. We are therefore able to analyse skill upgrading and relative wages using the standard non-production/production breakdown as well as a skill-grouping based on the workers’ education. We apply decomposition techniques and regression analysis to study possible explanations for the changes in the share of skilled workers. In order to analyse the effects of technology on skill demand we introduce plant level technology indicators from the R&D Survey and a Manufacturing Technology Survey. Our main findings are that skill upgrading is mostly the results of increasing shares of more skilled workers within plants, but also that plant entry and exit effects have become more important. This within-plant skill upgrading correlates positively with the plant level R&D intensity which provides evidence for skill-biased technological change. We also find that the effect of increased demand for skilled workers has mainly increased their employment rather than their wages.