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  4. Yesterday's Model for Tomorrow's Economy? The Effect of Dual VET on Wage Inequality in the Knowledge Economy
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Yesterday's Model for Tomorrow's Economy? The Effect of Dual VET on Wage Inequality in the Knowledge Economy

Type
conference paper
Date Issued
2023-09-08
Author(s)
Patrick Emmenegger  
;
Matthias Haslberger  
Abstract
Dual vocational education and training (VET) systems are said to have positive economic effects, such as reducing wage inequality. However, recent contributions suggest that the rise of the knowledge economy undermines these positive effects. Most notably, employment in routine task-intensive occupations is declining, while technological change is increasing demand for non-routine cognitive tasks. For such high-end jobs, university-educated workers are argued to be better suited. This paper provides the first evidence on the effect of dual VET on wage inequality in mature knowledge economies. We have assembled a new panel data set for 37 advanced economies from 1996 to 2020. We find that dual VET remains associated with lower levels of wage inequality throughout the entire period. The rise of the knowledge economy is positively associated with wage inequality at low levels of dual VET. However, where the dual VET share is high, the rise of the knowledge economy further reduces wage inequality. Our paper significantly extends existing research on the effects of dual VET by explicitly theorizing and modelling its interaction with the knowledge economy. Contrary to the fears often espoused in the literature, we find no evidence that the knowledge economy undermines the positive effects of dual VET.
HSG Classification
contribution to scientific community
Refereed
No
Event Title
RC28 Summer Meeting
Event Location
University of Michigan, Ann Arbor, USA
Event Date
15.08.2023
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/118548
Subject(s)

political science

Division(s)

SEPS - School of Econ...

File(s)
Thumbnail Image
Name

Yesterdays Model RC28 PP.pdf

Size

337.05 KB

Format

Adobe PDF

Checksum (MD5)

793d13287214b02568d7536c9507449b

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