Does Social Capital Have an Effect on Industry Production in G7 Countries? Causality Analysis *

Abstract

The relationship between social capital and economic growth has become an attractive research area in the literature recently. In this context, this paper examines the relationship between social capital indicators and industry production in the period of 2006-2014 with monthly data for the G7 countries. For empirical analysis, panel causality analysis method developed by Dumitrescu & Hurlin (2012) was used. Results indicate that there is a bidirectional relationship between social capital indicators and industry production. These findings support feedback hypothesis in the context of social capital and economic growth in the G7 countries.

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Journal of Economics Library
www.kspjournals.org
Volume 4 March 2017 Issue 1
Does Social Capital Have an Effect on Industry Production in
G7 Countries? Causality Analysis *
By
Oktay KIZILKAYA a Murat ÇETİNKAYA b
& Emrah SOFUOĞLUac†
Abstract. The relationship between social capital and economic growth has become an
attractive research area in the literature recently. In this context, this paper examines the
relationship between social capital indicators and industry production in the period of 2006-
2014 with monthly data for the G7 countries. For empirical analysis, panel causality
analysis method developed by Dumitrescu & Hurlin (2012) was used. Results indicate that
there is a bidirectional relationship between social capital indicators and industry
production. These findings support feedback hypothesis in the context of social capital and
economic growth in the G7 countries.
Keywords. Social capital, Industry production, Economic growth, Panel causality, G7
Countries.
JEL. F63, J24, O47.
1. Introduction
ecently, the impact of social capital on economic growth has been an
important topic of discussion. The majority of studies analyzing relationship
between social capital and economic growth disagree with the opinion that
economic growth is determined by traditional factors such as capital, labor force
and national resources. This debate ensues from the study titled “Making
Democracy Work” conducted by Putnam
et al.
in (1993). It is the first paper
focusing on relationship between social capital and economic growth. Putnam
et
al.
(1993) compare social capital and economic development by dividing Italy into
two regions and point out that the region with higher social capital grows faster
economically. Putnam
et al.
(1993) define social capital as social union
characteristics such as norms, networks and trust that increase social efficiency by
facilitating cooperation activities. James Coleman is another researcher who has
contributed to the concept of social capital. Coleman (1988, 1990) defines social
capital as institutional relationships between the people and evolution that
facilitates certain activities of individuals in social structure and institutional actors.
aa Ahi Evran University, Faculty of Economics and Administrative Sciences, Department of
Economics, Kırşehir, Turkey.
. +90 (386) 280 49 19
. okizilkaya@ahievran.edu.tr
b Gazi University, School of Banking and Insurance, Department of Banking, Ankara, Turkey.
. +90 (312) 5821145
. mcetinkaya@gazi.edu.tr
c† Ahi Evran University, Faculty of Economics and Administrative Sciences, Department of
Economics, Kırşehir, Turkey.
. +90 (386) 280 49 46
. emrahsofuoglu@gmail.com
* This study was presented at International Humanities and Social Science Conference in 2016
(Budapest/Hungary) and then revised. This study was supported by the Ahi Evran University
Scientific Research Projects Coordination Unit. Project number: PYO-İKT.4001.15.001.
R

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Whiteley (2000) describes social capital as people who want to rely on their family
members, citizens and other individuals, Woolcock & Narayan (2002) as norms
and networks that enable people to act together, Putnam (2001), as evolution that
constitutes values for individuals and provides positive externalities, and finally
Sciarrone (2002), describes social capital as all of resources resulting from social
relationship that occur due to the individual’s position in networks.
On the other hand, Fukuyama (1995a, 1999, 2002), describes social capital as
individuals’ ability to act together in groups for their common purpose, norms
provide interindividual cooperation or informal set of values. World Bank (1998)
states that social capital includes institutes that rule interactions between the
individuals in the society, relationships, behaviors and values. The report also
explains that social capital is a contributory factor for economic and social
development. OECD (2001) determines social capital as trust, norm and
communication network that increase social productivity and facilitate coordination
activities between community members, civil society organizations and public
institutions. In economic sense, OECD (2001) accepts social capital as a
confidential relation between people and institutions which reflects economic
efficiency and production.
In terms of social capital; trust and organizational efficiency variables are often
used as an indicator in the literature. These indicators are generally obtained from
World Values Surveys and utilized for micro social capital indicators (La Porta
et
al.
1997; Knack & Keefer 1997). While micro social capital represents social
capital forming in a society, macro social capital represents social capital occurring
in public sphere. Democratic accountability, democratic participation, superiority
of law, rule of law, applicability of agreements, regimes, government stability,
political, economic and financial risk assessments, quality of institutions are
considered as macro social capital indicators (Knack & Keefer 1995, 1997; Akçay,
2005). Other indicators in the literature accepted as social capital indicators are
safety laws, corruption, transparency, effectiveness of the management system,
adequacy and credibility of governments.
The study focuses on institutional indicators compiled by the International
Country Risk Guide (ICRG) that provides private international risk service. The
study uses ICRG data accepted as social capital indicators by Mauro (1995), Knack
& Keefer (1995). These ratios are accepted as government social capital and macro
social capital in the literature (Mauro 1995; Knack & Keefer 1995; Kormendi &
Meguire 1985).
Fukuyama (1995a) argues that generalized trust factor has a positive impact on
economic performance in developed countries. This study aims to contribute to the
literature by analyzing this thesis of Fukuyama. From this point of view, the
relationship between economic growth and social capital is tested in some
developed countries. In this context, the concept of social capital is discussed in
introduction. In the first part, theoretical relationship between social capital and
economic growth is demonstrated. In the second part, empirical studies analyzing
the relationship between social capital and economic growth are categorized into
two according to positive and negative results. In the third part, the relation
between social capital and economic growth is analyzed for the period of 2006-
2014 for G7 countries. In conclusion, empirical findings are evaluated and some
policy recommendations are suggested.
2. Theoretical Background
Economists admit that social capital is an important explanatory variable for
economic development along with the macroeconomic variables. Fukuyama
(1995a) and Putnam
et al.
(1993) stress that social capital has a positive impact on
economic growth. Fukuyama (1995a) considers social capital as generalized trust
for successful economic performance in developed countries and underlines that
social capital is a key factor for economic development. While Putnam
et al.
(1993)
refer to norms and networks for social capital, Fukuyama (1995a) has a high

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opinion of the role of trust. There are some studies in the literature in the field of
social capital. However, it is seen that there are not sufficient empirical studies that
analyze the positive impact of social capital on economic performance as both
Putnam
et al.
(1993) and Fukuyama (1995a, 1995b) come up with their studies
(Paldam & Svendsen, 2000; Beugelsdijk & Schaik 2005). Measuring social capital
empirically is complicated and this is the main reason for this issue (Salahuddin
et
al.,
2015).
According to Fukuyama (1995a), generalized trust is required for successful
economic performance in developed countries. Trust enables cooperation without
direct effect of power and market. Therefore, trust not only serves as an alternative
in legal system, but also facilitates complex transactions even in a well-functioning
institutional system. In other words, even in the presence of a well-functioning
institutional system, some transactions might be almost impossible in the absence
of trust. According to this idea, in societies with high trust level, new technologies
can be applied more effectively and in this way productivity can be enhanced.
Knack (1999) asserts that social capital affects economic performance through
two channels as micro and macroeconomicpolicies. At micro level, social ties and
interindividual trust decrease transaction costs, ensures the applicability of the
contracts and facilitates loans for the individual investors. At macro level, social
adaptation and civil consensus empower democratic management (Almond &
Verba, 1963), social capital can improve the public administration efficiency and
qualification (Putnam
et al.,
1993), and it enhances the quality of economic policies
(Easterly & Levine, 1997). Helliwell & Putnam (1995) emphasize the effects of
intuitional performance on economic growth and suggest alternative components
such as civil society and citizen satisfaction to measure this performance. Zak &
Knack (2001) propound that in societies with high trust level investment and
economic growth can be high and income equality can raise social trust.
3. Empirical Literature
The first empirical study on the relationship between social capital and
economic growth was conducted by Kormendi & Meguire in 1985. Kormendi &
Meguire (1985) investigated the relationship between government social capital
and economic performance with a statistical approach in 47 countries. Civil
freedom is an important indicator for social capital in the study and it is found to be
a key factor to explain the share of investment in GDP. Besides, high civil freedom
increases the share of investment in GDP by %5.
Other empirical studies in the literature in the field of social capital focus on
some different indicators to explain social capital such as trust, norms, networks,
organizational effectiveness (Putnam
et al.,
1993), and trust (Knack & Keefer,
1997). Putnam
et al.
(1993) employed group membership in their model as a social
capital indicator and found that North Italy has developed faster than South Italy
due to its high social capital level. According to Putnam et al., regional differential
in terms of economic and institutional performance makes a major contribution to
development of social capital. Knack & Keefer (1997) have no proof about group
membership to government agency; however, they found a strong relationship
among trust, civil norms and income. There is a relationship between economic
growth performance and trust as well. Besides, Knack & Keefer (1997) state that
countries in which agreements and intellectual property rights are protected by
governmental agencies, trust factor and civil norms are more effective. According
to Knack (2002) social ties and trust provided in the society are associated with
property and agreement rights which are in force in the country. Like property and
agreement rights, trust factor decreases uncertainty in the market and transaction
costs.
Apart from the studies which have found negative or positive relationship
between social capital and economic growth, there are some studies finding no
relationship between the variables. Most of those studies conclude that social
capital contributes to economic growth and development of the countries (Putnam

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et al.,
1993, Knack & Keefer, 1997, Hjerppe, 1998, La Porta
et al.,
1999, Zak &
Knack, 2001, Beugelsdijk & Schaik, 2005). However, some studies purports a
negative relationship between social capital and economic growth (Helliwell, 1996,
Raiser
et al.
, 2001, Roth, 2006). Literature related to this issue is summarized in
two different categories.
Table 1.
Studies Based on Positive Relationship Between Economic Growth and Social Capital
Author
Country/
Region
Period
Method
Variables
Conclusion
Knack &
Keefer
(1997)
29 Market
Economies
1981-
1991
OLS
Social Capital
Economic Growth
There is a strong and significant
relationship between social capital and
economic growth.
Hjerppe
(1998)
Selected 27
Countries
1990-
1993
OLS
Trust, Participation
in Civil
Organizations, GDP
There is a positive relationship between
trust level and economic growth.
Temple &
Johnson
(1998)
74
Developing
Countries
1957-
1962
Robustn
essTest
Social Capital
Economic Growth
Social capital has a positive impact on
economic growth.
La Porta
et
al.
(1999)
39 Countries
1970-
1993
OLS
Trust (Institutions)
and Economic
Growth
Trust accelerates economic growth.
Whiteley
(2000)
34 Countries
1970-
1992
OLS
Interindividual
Trust and Economic
Growth
Trust has a strong impact on economic
growth.
Zak & Knack
(2001)
37 Countries
1970-
1992
OLS
Trust Level and
Economic Growth
Countries with higher trust have higher
economic growth rates.
Karagül &
Akçay (2002)
36 Countries
1960-
1995/198
0-1995
Time
Series
Analysis
Social Capital
Economic Growth
There is a positive relationship between
social capital and economic growth.
Beugelsdijk
& Schaik
(2005)
54 EU
Regions
1950-
1998
Robustn
ess Test
Social Capital
Economic Growth
Regional growth differentials in Europe are
related to the social capital level.
Baliamonue
(2005)
39 Africa
Countries
1975-
2000
Unbalan
ced
Panel
Data
Analysis
Social Capital
Economic
Development
Social capital has a strong impact on
income growth.
Rupasingha
et al.
(2006)
Some States
in the USA
1980-
1997
OLS
Social Capital
Economic Growth
There is a positive relationship between
social capital and economic growth.
Dinçer &
Uslaner
(2007)
43 bordering
province. in
the USA
1990-
2000
OLS
Trust and
Economic Growth
There is a positive relationship between
trust level and economic growth.
Dinda (2008)
63 Countries
1990-
2000
Time
Series
Analysis
Social Capital,
Human Capital
Economic Growth
Social capital has an indirect effect on
economic growth through human capital.
Dearmon &
Grier (2009)
51 Countries
1981-
2004Q4
Unbalan
ced
Panel
Data
Analysis
Trust and
Economic Growth
Trust affects economic growth indirectly.
Feki &
Chtouro
(2014)
Developed
and
Developing
Countries
1990-
2004
Static
and
Unbalan
ced
Panel
Data
Analysis
Social Capital
Economic Growth
With the high trust level, interindividual
communication have a positive impact on
economic growth.
Ponzetto &
Troiano
(2014)
Developing
countries
1981-
2008
Dynamic
Equilibri
um
Social Capital,
Human Capital
Public Investment
and Economic
Growth
Social capital affect economic growth
positively through productive public
investment which promotes human capital.
Aguilera
(2016)
North and
South
America
Countries
1994-
2014
Panel
Data
Analysis
Social Capital
Economic Growth
There is a positive relationship between
social capital and economic growth.

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Table 2.
Studies Based on Negative or No Relationship Between Economic Growth and
Social Capital
Author
Country/
Region
Period
Methodology
Variables
Conclusion
Helliwell
(1996)
Asian
Countries
1987-
1994
OLS
Social Capital,
Intuitional Quality
and Economic
Growth
Social capital and institutional quality
have no explanatory capacity on
economic growth.
Raiser
et
al.
(2001)
Central and
Eastern
Transition
Countries of
the Soviet
Union
1990-
1995
OLS
Social Capital,
Economic Growth
There is no positive relationship
between social capital and economic
growth.
Iyer
et al.
(2005)
9 Region in US
2000
Ordered Logit
Regression
Model
Social Capital,
Regional
Development and
Economic Growth
Although it is not strong, there is a
positive relationship between
development and social capital.
Sabatini
(2006)
Italy
1998-
2002
Time Series
Analysis
Social Capital,
Economic
Development
No relationship is found between
social capital and economic growth,
on the contrary, weak ties between
the individual could provide a
positive contribution to economic
growth.
Neira
et al.
(2008)
14 Developed
OECD
Countries
1980-
2000
Panel Data
Analysis
Social Capital,
Human Capital
Economic Growth
It is stated that social capital is
important for economic growth,
however it cannot accelerate
economic growth singly.
Neira
et al.
(2010)
EU-15
Countries and
Eastern EU
Countries
2002-
2008
Cross Section
Analysis
Social Capital,
Human Capital
Economic Growth
No certain relationship is found
between social capital and economic
growth.
Pfister
(2010)
116 Countries
1950-
2005
Panel Data
Analysis
Social Trust,
Economic Growth
It is precipitated that impact of social
trust on economic growth fluctuates
according to the development level of
the country.
Salahuddin
et al.
(2015)
Australia
1985-
2013
Time Series
Analysis
Social Capital,
Internet Usage
Economic Growth
No relationship is found between
social capital and economic both
short and long term.
Palamino
(2016)
237 Regions in
Europe
1995-
2007
Non-Parametric
Regression
Model
Social Capital,
Economic Growth
It is found that relationship between
social capital and economic growth is
not linear.
4. Econometric Analysis
4.1. Data
This study analyzes the impact of social capital on economic growth by
causality analysis for G7 countries (America, Japan, Canada, Germany, France,
Italy, and the United Kingdom) over the period of 2006-2014 with annual data. 7
indicators that represent social capital are utilized in the study. These indicators are
democratic accountability (DA), contract viability (CONT), law and order (LO),
economic risk assessment (ER), financial risk assessment (FR), political risk
assessment (PR) and government stability (GOV) respectively. The data of
Industry Production Index (IP) representing economic growth pertain to the
International Financial Statistics published by International Monetary Fund. All
data used in the analysis are seasonally adjusted.
According to the ICRG Guide to Data Variables (PRS Group, 2016), some
explanations related to the data and ICRG methodology are given below:
Democratic Accountability:
A measure of, not just whether there are free and
fair elections, but how responsive government is to its people. The less responsive
it is, the more likely it will fall. Even democratically elected governments can
delude themselves into thinking they know what is best for the people, regardless
of clear indications to the contrary from the people.
Contract Viability:
The risk of unilateral contract modification or cancellation
and, at worst, outright expropriation of foreign owned assets.
Law and Order:
Two measures comprising one risk component. Each
subcomponent equals half of the total. The "law" sub-component assesses the
strength and impartiality of the legal system, and the "order" sub-component
assesses popular observance of the law.

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Economic Risk:
A means of assessing a country's current economic strengths
and weaknesses. In general, where strengths outweigh weaknesses, a country will
show low risk and where weaknesses outweigh strengths, the economic risk will be
high. To ensure comparability between countries, risk components are based on
accepted ratios between the measured data within the national economic/financial
structure, and then the ratios are compared, not the data.
Political Risk:
A means of assessing the political stability of a country on a
comparable basis with other countries by assessing risk points for each of the
component factors of government stability, socioeconomic conditions, investment
profile, internal conflict, external conflict, corruption, military in politics, religious
tensions, law and order, ethnic tensions, democratic accountability, and
bureaucracy quality.
Financial Risk:
A means of assessing a country's ability to pay its way by
financing its official, commercial and trade debt obligations. To ensure
comparability between countries, risk components are based on accepted ratios
between the measured data within the national economic/financial structure, and
then the ratios are compared, not the data.
Government Stability:
A measure of the government's ability to stay in office
and carry out its declared program(s), depending upon such factors as the type of
governance, cohesion of the government and governing parties, approach of an
election, and command of the legislature.
Table 3 indicates explanatory statistics and correlation matrix based on the data
utilized in the analysis. According to this, all statistics belong to IP variable are
greater than the statistics belong to other variables. Correlation matrix shows that
there is a positive correlation between Ip variable and social capital indicators.
These findings present some preliminary information. However, in the next phase,
unit root and causality tests will be utilized to reach more effective information for
the relationship between the variables.
Table 3.
Explanatory Statistics and Correlation Matrix
Explanatory Statistics
DA
CONT
LO
ER
FR
PR
GOV
IP
Mean
5.766
3.645
4.992
37.914
38.551
80.474
7.540
103.106
Median
6.000
4.000
5.000
38.250
39.000
80.500
7.500
101.630
Min.
6.000
4.000
6.000
47.500
46.500
88.500
11.000
122.370
Max.
4.500
2.000
4.000
29.000
30.000
68.000
3.500
76.590
Std. Error
0.369
0.525
0.490
3.335
3.570
4.585
1.415
7.451
Obs. Number
756
756
756
756
756
756
756
756
Correlation Matrix
DA
1
CONT
-0.051
1
LO
0.325
0.329
1
ER
-0.025
0.481
0.276
1
FR
-0.432
0.324
0.326
0.385
1
PR
0.115
0.695
0,525
0.432
0.366
1
GOV
0.221
0.366
0.139
0.021
0.037
0.648
1
IP
0.075
0.424
0.049
0.453
0.030
0.149
0,097
1
4.2. Method
In this study relationship between social capital and economic growth is
analyzed with panel causality test developed by Dumitrescu and Hurlin in 2012.
For causality test, integration levels of series should be determined first. At the first
step of the empirical analysis, stationarity of series will be tested with panel unit
root test developed by Levin
et al.
(2012, LLC) and Im
et al.
(2003, IPS). For LLC
panel unit root test, the model below should be estimated:
Δyit = µi + ρyit-1 + αj∆yit-j
m
j=1 + δit + θt + εit (1)
In Equation (1), Δ represents the first difference operator, m represents lag
length, µi and θt are entity-specific fixed and time effects. ρ = 0 null hypothesis is

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tested against ρ < 0 hypothesis for all i values. Rejection of null hypothesis means
series are stationary.
IPS test developed by Im et al. (2003) calculates each section in the panel and
average them by modifying LLC test. This test allows a variety of ρ values for each
unit to form the panel. If Equation (1) is written again:
Δyit = µi + ρyit-1 + αj∆yit-j
m
j=1 + δit + θt + εit (2)
For IPS test, null hypothesis is tested for all i values against ρ = 0, at least one i
value against ρ < 0 alternative hypothesis. Rejection of null hypothesis stands for
that series are stationary.
The causality test developed by Dumitrescu & Hurlin (2012) and based on
Wald statistics considers heterogeneity and dependence between countries. This
case increases the reliability of test results. As for this test, null hypothesis “there is
no causality relation for all sections” is examined against alternative hypothesis
“there is a causality relation for some sections” by Wald test. Wald statistics is
calculated as follows:
WN,T
Hnc= 1
NWi,T
N
i=1 (3)
In Equation (3), N and T represent section and time dimensions, respectively.
Dumitrescu & Hurlin (2012) suggest using ZN,T
Hnc test statistics when time dimension
(T) is greater than section dimension (T>N). In this study, T> N and so ZN,T
Hnc test
statistics are used. After analysis, test statistics related to causality are indicated in
Equation (4) by calculating test statistics and probability values belonging to these
statistics.
ZN,T
Hnc = N
2K WN,T
Hnc-K → N(0,1) (4)
4.3. Empirical Findings
Results of panel unit test are shown in Table 4. According to the those results,
series employed for the analysis are not stationary at level values. The series are
found to be stationary at the first difference, however. Therefore, integration level
of series is I(1).
Table 4.
Panel Unit Root Test Results
Variables
LLC
IPS
DA
0.046
-0.198
CONT
-0.674
-2.582a
LO
0.164
0.532
ER
-1.397b
-0.898
FR
-3.037a
-0.847
PR
-0.611
-0.746
GOV
-0.369
-0.601
IP
0,640
0.069
∆DA
-8.375a
-7.445a
∆CONT
-18.671a
-19.703a
∆LO
-19.902a
-18.183a
∆ER
-24.076a
-24.639a
∆FR
-22.174a
-25.037a
∆PR
-26.172a
-23.765a
∆GOV
-19.605a
-22.324a
∆IP
-31.538a
-26.658a
Note: a and b illustrates 1%and 5% significance level respectively.
In Table 5, Dumitrescu & Hurlin (2012) panel causality test results are reported.
For the test, integration level of series I(1) are used. According to the findings,

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there is a direct causality relationship between industrial production and democratic
accountability (DA), contract viability (CONT), law and order (LO), financial risk
assessment (FR), and government stability (GOV). Thus, there is a feedback
relation between industrial production and five indicators representing social
capital. In addition, there is a unidirectional causality relation from economic risk
and political risk to industrial production. Therefore, both economic and political
risks affect industrial production. However, industrial production does not affect
economic and political risk. These findings imply that social capital indicators have
a significant impact on industrial production.
Table 5.
Dumitrescu & Hurlin (2012) Panel Causality Test Results
Causality
Wald ist.
Causality
Wald ist.
DA→IP
3.602a
(0.00)
IP→DA
4.971a
(0.00)
CONT→IP
4.685a
(0.00)
IP→CONT
11.083a
(0.00)
LO→IP
1.919c
(0.08)
IP→LO
2.174b
(0.04)
ER→IP
8.98a
(0.00)
IP→ER
1.240
(0.18)
FR→IP
3.777a
(0.00)
IP→FR
4.362a
(0.00)
PR→IP
2.048b
(0.04)
IP→PR
1.535
(0.12)
GOV→IP
3.579a
(0.00)
IP→GOV
3.506a
(0.00)
Note: a, illustrates 1% significance level; b, illustrates 5% significance level; c, illustrates 10%
significance level.
5. Conclusion
In this study, the relationship between social capital indicators and industry
production is examined in the period of 2006-2014 with monthly data for the G7
countries (America, Japan, Canada, Germany, France, Italy, United Kingdom).
Democratic accountability (DA), contract viability (CONT), law and order (LO),
economic risk assessment (ER), financial risk assessment (FR), political risk
assessment (PR) and government stability (GOV) represent social capital, and
industrial production (IP) represents economic growth in the study. The causality
between social capital indicators and industrial production was estimated via
Dumitrescu and Hurlin (2012) panel causality test method. According to the
findings, there is a direct causality relationship between industrial production and
democratic accountability (DA), contract viability (CONT), law and order (LO),
financial risk assessment (FR), and government stability (GOV). Hence, there is a
feedback relation between industrial production and five indicators stand for social
capital. Furthermore, there is a unidirectional causality relation from economic risk
and political risk to industrial production. Therefore, both economic and political
risks have impacts on industrial production. However, industrial production has no
impact on economic and political risk. These findings suggest that social capital
indicators have a significant impact on industrial production.
Empirical results indicate that governments should focus on factors such as
social capital indicators in addition to labor force, capital, natural resources and
technology for economic growth policies. Since social capital represents trust
factor, it might be considered that rise in social capital decreases uncertainty in the
market. In addition, developing relationships between individuals and institutions
based on trust factor has a significant impact on economic performance.
Development of trust, communication and harmony between individuals and
institutions may contribute to economic productivity through political, social and
economic policies.

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