This document analyzes the relationship between sectoral cognitive skills, research and development (R&D), and productivity across countries. It finds that cognitive skills and R&D are strongly positively related to productivity, while years of schooling is not. The relationship between R&D and skills and their complementary impact on productivity requires more longitudinal data analysis. High-tech sectors like chemicals have much higher cognitive skills and productivity than low-tech sectors like textiles. Countries also vary widely in average cognitive skills, with Japan, Belgium, and Netherlands highest and Poland, Italy, and Spain lowest.

1. SECTORAL COGNITIVE SKILLS,
R&D AND PRODUCTIVITY
A cross-country analysis
SIMONE SASSO, JO RITZEN
MODEL 1 MODEL 2 MODEL 3 MODEL 4 MODEL 5 MODEL 6 MODEL 7
log (labour) 0.058*** -0.077*** 0.0655** 0.044* 0.053** 0.058*** 0.062**
log (capital per worker) 0.418*** 0.324*** 0.546*** 0.441*** 0.431*** 0.417*** 0.535***
log (R&D per worker) 0.123*** 0.030 0.163*** 0.126*** 0.123*** 0.383 0.158***
log PIAAC numeracy 1.240** 2.879*** 0.203 1.059* 1.237** -1.619
log (avg years school) 0.499 0.076
log (R&D) x log (PIAAC) -0.0462
% PIAAC num. lev. 3 0.004
% PIAAC num. lev. 4 0.015*
industry dummies YES YES
Country dummies YES
Constant -5.054* -13.050*** -0.042 0.599 -4.273 -5.031 9.926
N. Obs. 204 204 204 187 187 204 204
R2 0.690 0.849 0.836 0.687 0.691 0.690 0.839
CONCEPTUAL FRAMEWORK
• Productivity growth is ultimately determined by technological progress (Solow, 1957)
• Education, by equipping individuals with knowledge and skills, enables them to generate new
ideas, to stimulate innovation and to increase the economic output (e.g. Lucas, 1988; Romer, 1986).
• R&D, by aiming at increasing the stock of knowledge and finding new innovative solutions, boosts
the economic output (e.g. Romer, 1990; Grossman and Helpman, 1991)
• Complementarities between skills and R&D
· R&D ➝ Innovation ➝ Skills : Skilled-biased technological change (e.g. Accemoglu, 2002)
· Skills ➝ R&D ➝ Innovation : Induced skilled-biased technological change (e.g. Piva and Vivarelli, 2015)
STATE OF THE ART
• Returns to education: most studies based on input-variables (i.e. school attainment e.g. Barro and Lee,
2010) with contrasting results (e.g. Mankiw, Romer and Weil, 1992 vs. Prichett, 2001)
• Returns to R&D: fewer studies at the sectoral level (e.g. Bartelsman , 1990; Ortega-Argilés et al., 2015), mainly
focusing on manufacturing and not on services (e.g. Verspagen, 1995)
We analyse the skills - R&D - productivity relationship and
the possible complementarities across countries and sectors. Low-tech sector (Textiles) High-tech sector (Chemicals and pharmaceuticals)
METHOD
• We compute a measure of average sectoral cognitive skills across 12 countries and 17 industries
both in manufacturing and services
• We use econometrics in order to investigate the relationship between cognitive skills, R&D and
productivity and their possible complementarities
Table 1. Log-log regressions of labour productivity on skills and R&D investments across sector-country combinations.
***, ** and * indicate significance at the 1, 5 and 10 percent levels respectively.
COGNITIVE SKILLS BY SECTOR
Cognitive skills by sector
294.5
287.7
283.4
279.6 279.5 279.4
275.1 274.6
269.1 268.5 267.3 266.7 266.4
262.7 261.5 259.4 259.0
260
280
300
320
220
240
Average numeracy skills by sector (with sectoral min and max values). Source: own calculations based on OECD PIAAC database
COGNITIVE SKILLS BY COUNTRY
Cognitive skills by country
293.4
289.8
287.2
277.3 277.3
271.7
267.9
265.2 263.6 261.7 259.9
280
300
320
263.6 261.7 259.9
256.4
220
240
260
JPN BEL NLD CZE DEU UK POL FRA KOR USA ESP ITA
Average numeracy skills by country (with sectoral min and max values). Source: own calculations based on OECD PIAAC database
COGNITIVE SKILLS & PRODUCTIVITY :
HIGH-TECH VS. LOW-TECH SECTORS
Skills and productivity: hi-tech vs. low tech
France
NetherlandsJapan
Belgium
Germany
United States
Korea
200300
Labourproductivity
France
United Kingdom
BelgiumNetherlands
Japan
Czech Republic
Czech Republic
Poland
Poland
Italy
Spain
United Kingdom
Italy
Germany
United States
Korea
Spain
0100
Labourproductivity
220 240 260 280 300 320
Cognitive skills (numeracy)
FINDINGS
• High heterogeneity of cognitive skills across sectors and countries
• Strong positive relationship between skills and productivity and not between schooling and
productivity
• Complementarity between R&D and skills remains an open question
• Longitudinal data on cognitive skills are necessary to investigate the causality of the
skills-R&D-productivity relationship
Are you interested in this research?
Contact the authors!
Simone Sasso
sasso@merit.unu.edu
Jo Ritzen
j.ritzen@maastrichtuniversity.nl
ln = ln A+ +
Q C RD
L ij
ij
L Lij
ij
ij
ij ij
ij
ln ln ln SKILLS ln +εα2
+ α4
+ −1)(α1
+ α2
+ α3
α3
Lij
WIOD
• Gross value added, capital stocks
and labour stocks
1995-2011, 2 digit ISIC Rev. 3.1 (35 sectors)
OECD ANBERD
• R&D expenditures
1995-2013, 1 and 2 digit ISIC Rev. 3 or ISIC Rev. 4
OECD PIAAC
• Test scores measuring adult
cognitive skills
(numeracy, literacy,
problem solving)
2011-2012, 2 digit ISIC Rev. 4
DATA
• We match data coming from 3 databases:
Average numeracy skills by country (mean, min and max values on a scale 0-500). Source: own calculations based on OECD PIAAC data.
Average numeracy skills by sector (mean, min and max values on a scale 0-500). Source: own calculations based on OECD PIAAC data.
Average sectoral numeracy skills (on a scale 0-500) and average sectoral labour productivity (in thousand USD at constant 1995 prices).
Source: own calculations based on WIOD and OECD PIAAC data.
RANKING OF LABOUR PRODUCTIVITYRANKING OF LABOUR PRODUCTIVITY
0 20 40 60 80 100 120 140 160
Japan
Belgium
United States
Netherlands
France
Germany
KoreaKorea
United Kindgom
Italy
Spain
Czech Republic
Poland
Explained by Labour
Explained by Capital
Explained by R&D
Explained by Skills
Constant and residual