The impact of educational mismatch on returns to R&D: evidence from manufacturing in OECD countries
(2018) In Economics of Innovation and New Technology 28(5). p.435-464- Abstract
- This paper investigates the effect of educational mismatch of R&D workers on firm's returns to innovation. R&D labour mismatch emerges when R&D workers have competencies different from those required by their occupation providing a contribution to innovation lower than in the case of perfect educational matching. By estimating a knowledge production function on data for 13 manufacturing industries from 16 OECD countries between 2003 and 2011, we find that R&D labour mismatch may cause returns to R&D investment to be between 10 and 15% lower than estimated in the literature. These results are robust to controlling for institutional factors, simultaneity feedbacks and other mis-specification issues. The detrimental effect... (More)
- This paper investigates the effect of educational mismatch of R&D workers on firm's returns to innovation. R&D labour mismatch emerges when R&D workers have competencies different from those required by their occupation providing a contribution to innovation lower than in the case of perfect educational matching. By estimating a knowledge production function on data for 13 manufacturing industries from 16 OECD countries between 2003 and 2011, we find that R&D labour mismatch may cause returns to R&D investment to be between 10 and 15% lower than estimated in the literature. These results are robust to controlling for institutional factors, simultaneity feedbacks and other mis-specification issues. The detrimental effect of the misallocation of R&D labour is found to be stronger in those sectors where R&D activities have greater potential (returns), i.e. high-tech sectors. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/9db02fc7-c21a-4222-aa66-d7514b0f11cb
- author
- Igna, Ioana LU and Venturini, Francesco
- publishing date
- 2018-10-07
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- educational mismatch, returns to education in R&D, patents, R&D, OECD, manufacturing
- in
- Economics of Innovation and New Technology
- volume
- 28
- issue
- 5
- pages
- 30 pages
- publisher
- Taylor & Francis
- external identifiers
-
- scopus:85054583786
- ISSN
- 1043-8599
- DOI
- 10.1080/10438599.2018.1527548
- language
- English
- LU publication?
- no
- id
- 9db02fc7-c21a-4222-aa66-d7514b0f11cb
- date added to LUP
- 2021-02-16 10:41:56
- date last changed
- 2022-04-27 00:32:48
@article{9db02fc7-c21a-4222-aa66-d7514b0f11cb,
abstract = {{This paper investigates the effect of educational mismatch of R&D workers on firm's returns to innovation. R&D labour mismatch emerges when R&D workers have competencies different from those required by their occupation providing a contribution to innovation lower than in the case of perfect educational matching. By estimating a knowledge production function on data for 13 manufacturing industries from 16 OECD countries between 2003 and 2011, we find that R&D labour mismatch may cause returns to R&D investment to be between 10 and 15% lower than estimated in the literature. These results are robust to controlling for institutional factors, simultaneity feedbacks and other mis-specification issues. The detrimental effect of the misallocation of R&D labour is found to be stronger in those sectors where R&D activities have greater potential (returns), i.e. high-tech sectors.}},
author = {{Igna, Ioana and Venturini, Francesco}},
issn = {{1043-8599}},
keywords = {{educational mismatch; returns to education in R&D; patents; R&D; OECD; manufacturing}},
language = {{eng}},
month = {{10}},
number = {{5}},
pages = {{435--464}},
publisher = {{Taylor & Francis}},
series = {{Economics of Innovation and New Technology}},
title = {{The impact of educational mismatch on returns to R&D: evidence from manufacturing in OECD countries}},
url = {{http://dx.doi.org/10.1080/10438599.2018.1527548}},
doi = {{10.1080/10438599.2018.1527548}},
volume = {{28}},
year = {{2018}},
}