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Global Value Chains, National Innovation Systems and Economic Development

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Abstract

The purpose of this paper is to examine the hypothesis that increased participation in global value chains (GVCs), such as assembly of imported parts for exports, leads to higher economic growth. The focus is particularly on the extent to which this holds for low-income countries, and the role that capability-building, i.e. development of the national innovation system, plays in the possibility of benefitting from GVCs. The analysis is based on evidence from 125 countries over the period 1997–2013. To analyse the issue, a comprehensive framework that allows for inclusion of a range of relevant factors, including GVC participation (measured by the foreign value added embodied in a country’s exports), is applied. The results suggest that countries that increase GVC participation do not grow faster than other countries, when other relevant factors are controlled for. Small countries, and countries with low capabilities, appear to be particularly disadvantaged.

Le but de cet article est d’examiner l’hypothèse selon laquelle une participation accrue aux chaînes de valeur mondiales (CVM), telle que l’assemblage de parties importées dans le but de les exporter, conduit à une croissance économique plus élevée. L’accent est mis surtout sur la pertinence de cet hypothèse pour les pays en développement. L’analyse est fondée sur des données probantes provenant de 125 pays, dont de nombreux pays à faible revenu, sur la période 1997–2013. Pour analyser la question, un cadre global qui permet d’inclure une série de facteurs pertinents, y compris la valeur ajoutée étrangère dans les exportations d’un pays (importations CVM), est appliqué. Les résultats présentés dans l’article suggèrent que les pays qui augmentent les importations de la chaîne de valeur mondiale ne connaissent pas une croissance plus rapide que d’autres pays, lorsque d’autres facteurs sont contrôlés. Les petits pays, et les pays à faible capacité, semblent particulièrement désavantagés.

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Figure 1
Figure 2
Figure 3

Note: The baseline is the estimated beta coefficient of Δ GVC imports. Interaction is the estimated coefficient of an interaction term between Δ GVC imports and a dummy variable for countries with capabilities exceeding a certain threshold level. Total is the sum of the baseline coefficient and the interaction term. All other variables remain the same as in the third column of Table 1. Smoothed values (the lines) are derived from kernel-weighted local polynomial smoothing (using Epanechnikov kernel function).

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Acknowledgements

Financial support from the VINNOVA Core Funding of Centers for Innovation Systems Research project 2010-01370 on “Transformation and Growth in Innovation Systems: Innovation Policy for Global Competitiveness of SMEs and R&I Milieus” and the Czech Science Foundation (GAČR) project 17-09628S on “Innovation activities in global production networks: Evidence from Czech business enterprises” is gratefully acknowledged. Earlier versions of the paper were presented at the 2016 OBEL Symposium on Innovation Systems, Globalization and Development, May 10–12, 2016, Aalborg, Denmark, the 14th Globelics International Conference, October 12–14, 2016, Bandung, Indonesia and the workshop on “Innovation Systems in the era of Global Value Chains”, April 24–25, 2017, Copenhagen, Denmark. We thank participants at these events, especially John Humphrey, Ned Lorenz and Bart Verspagen, and reviewers and editors of the journal for useful comments and suggestions. All usual caveats apply.

Author information

Authors and Affiliations

  1. Center for Technology, Innovation and Culture (TIK), University of Oslo, Oslo, Norway

    Jan Fagerberg

  2. IKE, Department of Business and Management, Aalborg University, Aalborg, Denmark

    Jan Fagerberg & Bengt-Åke Lundvall

  3. Center for Economic Research and Graduate Education-Economics Institute (CERGE-EI), a joint workplace of Charles University and the Economics Institute of the Czech Academy of Sciences, Politickych veznu 7, 111 21 Prague, Czechia

    Martin Srholec

  4. Centre for Innovation, Research and Competence in the Learning Economy (CIRCLE), Lund University, Lund, Sweden

    Martin Srholec

Authors
  1. Jan Fagerberg
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Correspondence to Martin Srholec.

Appendices

Appendix A1: Definitions and Sources of the Variables

Indicator and definition

Scaling

Source

Estimated observations

GDP per capita Gross domestic product converted to constant 2011 international dollars using purchasing power parity rates

USD per capita

World Bank (2016)

0

Scientific and engineering articles Counts of citable documents recorded in SCImago Journal and Country Rank (based on information contained in the Scopus database)

Per mil. people

SCImago (2016)

0

USPTO patent applications Counts of applications for utility patents filed in the US Patent and Trademark Office (USPTO) classified by country of residence of the first named inventor

Per mil. people

USPTO (2016)

0

R&D expenditures Intramural expenditure on research and experimental development (R&D) performed on the national territory

% of GDP

UNESCO (2016), OECD (2016), Castellacci and Natera (2011) and national sources

39

Trademark applications Counts of applications for registration of trademarks filed by residents directly and via the Madrid system

Per mil. people

WIPO (2016)

43

ISO 9001 certifications Counts of ISO 9001 management system standard certifications

Per mil. people

ISO (2014)

0

Internet users Internet users are individuals who have used the Internet (from any location) in the last 12 months

Per 100 people

World Bank (2016)

0

Mean years of schooling Average number of years of education received by people aged 25 years and older, converted from education attainment levels using official durations of each level

Years

UNDP (2016)

0

Adult literacy People aged 15 years and over who can read, understand and write a short, simple statement on their everyday life

% of adult population

UNDP (2016) and World Bank (2016)

2

Bureaucracy quality An assessment of the institutional strength and quality of the bureaucracy, which represents a shock absorber that tends to limit revisions of policy when governments change

Index

PRS Group (2014)

10

GVC imports Imported inputs (produced in other countries) accounted in the gross exports of a country derived from input–output tables

% of GDP

UNCTAD/Eora (2016)

0

Capital goods imports Imports of capital goods (BEC, rev. 3 categories 41, 51 and 52) derived from trade in goods statistics

% of GDP

UN (2016)

7

FDI inward The value of capital and reserves (including retained profits) attributable to foreign parent enterprises with lasting management interest, plus the net indebtedness of foreign affiliates to the parent enterprises

% of GDP

UNCTAD (2016)

0

Outbound mobility of tertiary students Gross outbound tertiary enrolment ratio given by the number of tertiary students from a given country studying in North America and Western Europe expressed as the percentage of the population of tertiary age in that country

Gross enrolment in  %

UNCTAD (2016)

8

Size (population) All residents regardless of legal status or citizenship (except for refugees not permanently settled in the country of asylum) who are generally considered part of the population of their country of origin

People

World Bank (2016)

0

Agriculture Agriculture corresponds to ISIC divisions 1-5 and includes forestry, hunting and fishing, as well as cultivation of crops and livestock production

% of GDP

World Bank (2016)

0

Natural resources rents The sum of oil rents, natural gas rents, coal rents (hard and soft), mineral rents and forest rents

% of GDP

World Bank (2016)

0

Tropics Proportion of land area in Köppen–Geiger tropics

Share

Gallup et al (1999)

0

Malaria ecology Stability of malaria transmission given by biologic characteristics of vector mosquitoes

Index

Kiszewski et al (2004)

0

Appendix A2: Capabilities: Results of the Factor Analysis

 

Factor loadings

Scientific and engineering articles (per capita)

0.94

USPTO patent applications (per capita)

0.87

R&D expenditures (% of GDP)

0.79

Trademark applications (per capita)

0.76

ISO 9001 certifications (per capita)

0.91

Internet users (per capita)

0.70

Years of schooling (years)

0.80

Adult literacy (% of adult population)

0.68

Bureaucracy quality (index)

0.76

  1. The extraction method is principal factors; based on pooled data in 125 countries in 1997 and 2013, hence 250 observations in total; only one factor with eigenvalue > 1.00 was detected; 0.65 proportion of eigenvalues accounted for by the first factor using the trace of the correlation matrix as the divisor.

Appendix A3: Descriptive Statistics

 

Mean

SD

Min.

Max.

Δ GDP per capita

0.024

0.020

−0.036

0.097

GDP per capita

9.071

1.243

6.195

11.609

Capabilities

−0.286

0.950

−2.222

1.520

Δ capabilities

0.036

0.014

0.009

0.081

GVC imports

1.657

0.872

0.284

3.967

Δ GVC imports

0.024

0.023

−0.039

0.089

Capital goods imports

1.955

0.457

0.701

3.280

Δ capital goods imports

0.003

0.025

−0.072

0.076

FDI inward

2.665

0.834

0.486

5.128

Δ FDI inward

0.061

0.054

−0.069

0.272

Outbound mobility of tertiary students

0.542

0.594

0.019

3.294

Δ outbound mobility of tertiary students

0.010

0.018

−0.020

0.088

Size (population)

16.217

1.559

12.510

20.930

Agriculture

2.318

0.975

0.086

4.073

Natural resources rents

1.506

1.129

0.000

3.807

Tropics

1.566

2.020

0.000

4.615

Malaria

0.684

1.016

0.000

3.483

  1. All variables are in logs, Δ refers to log difference divided by the number of years (a log approximation of the annual growth rate).

Appendix A4: List of Countries (Alphabetical)

Albania

Croatia

Iran

Morocco

Slovenia

Algeria

Cyprus

Ireland

Mozambique

South Africa

Argentina

Czech Rep.

Israel

Namibia

Spain

Armenia

Denmark

Italy

Netherlands

Sri Lanka

Australia

Dominican Rep.

Jamaica

New Zealand

Sweden

Austria

Ecuador

Japan

Nicaragua

Switzerland

Azerbaijan

Egypt

Jordan

Niger

Taiwan

Bahrain

El Salvador

Kazakhstan

Nigeria

Tajikistan

Bangladesh

Estonia

Kenya

Norway

Tanzania

Belarus

Ethiopia

Korea

Oman

Thailand

Belgium

Finland

Kuwait

Pakistan

Togo

Bolivia

France

Kyrgyzstan

Panama

Trinidad and Tobago

Botswana

Gabon

Latvia

Papua New Guinea

Tunisia

Brazil

Georgia

Lebanon

Paraguay

Turkey

Brunei Darussalam

Germany

Lithuania

Peru

Uganda

Bulgaria

Ghana

Luxembourg

Philippines

Ukraine

Burkina Faso

Greece

Macedonia

Poland

United Arab Emirates

Cambodia

Guatemala

Madagascar

Portugal

United Kingdom

Cameroon

Guinea

Malawi

Qatar

United States

Canada

Honduras

Malaysia

Romania

Uruguay

Chile

Hong Kong

Mali

Russia

Venezuela

China

Hungary

Malta

Saudi Arabia

Vietnam

Colombia

Iceland

Mexico

Senegal

Yemen

Costa Rica

India

Moldova

Singapore

Zambia

Côte d’Ivoire

Indonesia

Mongolia

Slovakia

Zimbabwe

Appendix A5: Correlation Table

 

Δ GDP per capita

GDP per capita

Capabilities

Δ capabilities

GVC imports

Δ GVC imports

Capital goods imports

Δ capital goods imports

Δ GDP per capita

1.00

       

GDP per capita

−0.37

1.00

      

Capabilities

−0.16

0.83

1.00

     

Δ capabilities

0.34

0.05

−0.15

1.00

    

GVC imports

0.06

0.50

0.63

0.08

1.00

   

Δ GVC imports

−0.13

0.06

0.14

0.00

−0.02

1.00

  

Capital goods imports

−0.02

0.28

0.26

0.00

0.63

0.00

1.00

 

Δ capital goods imports

0.08

−0.36

−0.28

−0.03

−0.27

0.30

−0.42

1.00

FDI inward

0.05

0.16

0.16

−0.09

0.39

−0.04

0.47

−0.20

Δ FDI inward

−0.02

0.04

0.10

0.16

0.10

0.25

0.06

0.09

Outbound mobility of tertiary students

−0.28

0.64

0.56

0.03

0.43

0.13

0.41

−0.45

Δ outbound mobility of tertiary students

0.36

0.03

0.04

0.40

0.19

0.11

0.10

0.08

Size (population)

0.18

−0.25

−0.11

0.06

−0.25

−0.08

−0.59

0.21

Agriculture

0.36

−0.92

−0.79

0.04

−0.49

−0.08

−0.30

0.31

Natural resources rents

−0.06

−0.27

−0.57

0.05

−0.42

−0.34

−0.11

0.09

Tropics

−0.01

−0.42

−0.48

−0.11

−0.26

−0.15

0.00

−0.09

Malaria

−0.13

−0.59

−0.61

−0.26

−0.37

−0.05

−0.05

0.16

 

FDI inward

Δ FDI inward

Outbound mobility of tertiary students

Δ outbound mobility of tertiary students

Size (population)

Agriculture

Natural resources rents

Tropics

Malaria

Δ GDP per capita

         

GDP per capita

         

Capabilities

         

Δ capabilities

         

GVC imports

         

Δ GVC imports

         

Capital goods imports

         

Δ capital goods imports

         

FDI inward

1.00

        

Δ FDI inward

−0.47

1.00

       

Outbound mobility of tertiary students

0.22

0.22

1.00

      

Δ outbound mobility of tertiary students

−0.04

0.24

0.02

1.00

     

Size (population)

−0.24

−0.25

−0.52

−0.17

1.00

    

Agriculture

−0.23

−0.03

−0.60

0.03

0.22

1.00

   

Natural resources rents

−0.03

−0.28

−0.31

−0.07

0.01

0.30

1.00

  

Tropics

0.02

−0.16

−0.29

−0.21

0.14

0.38

0.32

1.00

 

Malaria

0.05

−0.14

−0.28

−0.22

0.08

0.46

0.39

0.59

1.00

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Fagerberg, J., Lundvall, BÅ. & Srholec, M. Global Value Chains, National Innovation Systems and Economic Development. Eur J Dev Res 30, 533–556 (2018). https://doi.org/10.1057/s41287-018-0147-2

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