Social Capital and Innovation in East Asia
Seo-Young Cho∗
This paper investigates the relationship between social capital and innovation in
high-performing East Asian economies. Rapid economic growth and innovation
in these economies contradicts the presumed positive link between social
trust and innovation suggested in the literature, as these economies are often
characterized as low-trust societies. The results of the multilevel analyses
conducted in this paper show that social trust among individuals is not a
driving force of innovation in East Asia. Stattdessen, other elements of social
capital—shared social norms of supporting collective developmental goals and
trust in formal institutions—are more important determinants of innovation.
This finding reveals the region-specific developmental path of East Asia—states
set innovation and growth as common goals for society and played an active role
in initiating and coordinating efforts to achieve them.
Schlüsselwörter: High-performing East Asian economies, Innovation, institutions,
social capital
JEL-Codes: L26, N15, O31, O43
ICH. Einführung
According to Coase (1960), social trust—generalized trust or trusting broad
ranges of other people—can promote innovation because it reduces transaction
costs among economic players. This argument is further elaborated by the school
of social capital (Putnam 2000, Fukuyama 1995). In explaining the role of social
trust, Fukuyama (1995) introduced the concept of high- and low-trust societies,
distinguished by the extent of trust clusters. In high-trust environments, trust-based
relationships exist between a large number of social actors so that individuals with
a broad spectrum of backgrounds can socialize and cooperate with one another.
Andererseits, in low-trust milieus, trust remains in families and friends
and therefore interactions and cooperation with unrelated people are limited. Als
generalized trust with strangers (high-trust cluster, d.h., social trust) can facilitate
sharing valuable information and knowledge with a wide range of entrepreneurs
and economic actors, it plays an important role in innovation through learning
∗Seo-Young Cho: Free University of Berlin, Institute of Korean Studies, Deutschland. Email: sc2242@columbia.edu.
I thank the managing editor and the anonymous referees for helpful comments and suggestions. The Asian
Development Bank (ADB) recognizes “China” as the People’s Republic of China. The usual ADB disclaimer applies.
Asiatischer Entwicklungsbericht, Bd. 38, NEIN. 1, S. 207–238
https://doi.org/10.1162/adev_a_00163
© 2021 Asian Development Bank and
Asian Development Bank Institute.
Veröffentlicht unter Creative Commons
Namensnennung 3.0 International (CC BY 3.0) Lizenz.
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208 Asiatischer Entwicklungsbericht
spillovers in society (Welter 2012). daher, high-trust economies are likely to
foster innovative entrepreneurship and economic growth.
Jedoch, when one considers high-performing East Asian economies, Das
presumed link between social trust and innovation becomes puzzling. East Asian
economies—especially the People’s Republic of China (VR China); Taipeh,China; Und
Hongkong, China; as well as Singapore, which has an ethnic Chinese majority,
but also the Republic of Korea to some degree—are often defined as having
low-trust societies because personal ties based on family values tend to overshadow
broader social networks and generalized trust (Fukuyama 1995). In spite of
Das, East Asian economies have achieved a high level of innovation which
has contributed to their rapid growth in the last several decades. Zum Beispiel,
the Global Innovation Index (GII) (Cornell University, INSEAD, and WIPO
2014–2018), which evaluates inputs and outputs of innovation of countries and
economies worldwide, ranks East Asian economies ahead of most others in terms
of innovation in technological and knowledge development. Singapore was ranked
5th; the Republic of Korea 12th; Hongkong, China 14th; and the PRC 17th out of
126 economies evaluated in 2018 (in addition, Japan was ranked 13th). Darüber hinaus,
these economies are characterized as early adopters of innovation outcomes such as
information technologies, online games, and new medical treatments.
This puzzle exhibited by these East Asian economies provides the motivation
to reevaluate the relationship between social trust and innovation. The central
question here is how the presumably low-trust East Asian economies have
played lead roles in building innovation economies. One potential answer to this
conundrum is that the relationship between social trust and innovation differs in
East Asia compared to others, with social trust not necessarily playing an important
role in innovation in the East Asian context.
Let us consider the East Asian economies’ development paths, Wo
innovation was led by the states during the period of fast economic growth.
The state played the role of an entrepreneur and participated in markets as the
main actor (Gulati 1992, Moon and Prasad 1994). The state’s role contrasts with
the industrialization path taken by Western economies that was mainly led by
individual entrepreneurs. Under the collective leadership of the state, the role
of social trust in innovation can be different from the one observed in Western
economies. Because of state-mediated cooperation among individual entrepreneurs
and knowledge and technology spillovers in East Asia, the level of trust between
individual entrepreneurs may not be as important as in Western economies. Stattdessen,
social norms and values can be more crucial determinants of innovation, wie zum Beispiel
the degree to which individual entrepreneurs share collective goals of development
and accept the modes of development proposed by the state. Likewise, trust in
institutions that set up common goals and coordinate economic activities can
be an equally important factor in encouraging individual stakeholders to support
Innovation.
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Social Capital and Innovation in East Asia 209
In this regard, shared social norms and institutional trust are proposed as the
elements of social capital that play the key role of contributors to innovation in East
Asia instead of social trust. With this proposition, this paper aims to empirically
examine how social norms and institutional trust promote innovation in East Asia
by borrowing concepts from social capital theory and disentangling dimensions of
social capital to ascertain their roles in innovation. To do so, the study conducts
multilevel analyses through which the relationships between different components
of social capital and innovation are identified in the six high-performing East
Asian economies (Hongkong, China; Japan;1 die VR China;2 the Republic of Korea;
Singapur;3 and Taipei,China). The findings of this paper suggest that social trust
is not an important determinant of innovation in East Asia, while its positive effect
on innovation is generally supported in other parts of the world. Instead of social
trust, the findings highlight the importance of social norms and institutional trust,
as hypothesized above. Insbesondere, social norms that endorse the shared societal
goal of growth primacy and competition- and performance-based incentives are the
prime drivers of innovation in East Asia. These results contribute a new piece of
evidence in explaining East Asian development by emphasizing competition-based
Innovation (instead of innovation based on cooperation as proxied by social trust).
The paper is organized as follows. Section II provides a literature review
and presents testable hypotheses. In section III, social capital is decomposed
into different dimensions and each component is explained. In section IV, Die
hypotheses are tested across the economies, followed by an analysis at the individual
level presented and discussed in section V. Section VI recaptures the main findings
and concludes the paper.
II. Literature Review and Articulation of Hypotheses
In the social capital literature, many studies emphasize social trust as an
important determinant of innovation and growth (Akcomak and ter Weel 2009;
1Japan has been a developed country since the early 20th century, which is significantly earlier than
its neighboring newly industrialized economies—Hong Kong, China; the Republic of Korea; Singapur; Und
Taipeh,China. Trotzdem, Japan is included in the analyses because it was the lead economy engineering East Asian
Wachstum, followed by the newly industrialized economies and the PRC (“flying geese model”). Auch, comparative
analyses between Japan and the other economies presented in section V provide interesting findings that reveal
similarities and differences in the effects of social capital between them.
2Measuring social trust in the PRC is a particularly challenging task because the World Values Survey data
reveal various levels of social trust in the country depending on the survey year and types of questions. Steinhart
(2012) defines the PRC as an outlier in terms of social trust because of this problem and suggests two plausible
explanations for this: (fluctuating) spillover effects of institutional confidence in answering questions on generalized
trust and problems in measurement validity (d.h., culturally induced response biases).
3Strictly speaking, Singapore is located in Southeast Asia. But this country is integrated in the analyses of this
paper because it shares developmental and cultural characteristics with the East Asian economies to a considerable
Grad: being one of the four tiger economies or newly industrialized economies and having an ethnic Chinese
majority (76% der Gesamtbevölkerung).
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210 Asiatischer Entwicklungsbericht
Beugelsdijk and van Schaik 2005; Dakhli and De Clercq 2004; Hauser, Tappeiner,
and Walde 2007; Horvath 2013; Knack and Keefer 1997; La Porta et al. 1997;
Paldam and Svendsen 2000; and Zak and Knack 2001).4
dennoch, the East Asian experience presents an interesting case with
counterevidence to the presumed positive relationship between social trust and
Innovation, as their economies grew fast despite lower levels of social trust. Das
observation offers an alternative view on the role of social capital. Insbesondere,
social trust may not always be the necessary condition to achieve innovation,
but other types of social capital may emerge as more important and take over
the role of social trust when social trust endowments are not readily available in
society (Horvath 2013). Tatsächlich, substantial empirical evidence is provided in the
literature that supports the role of other types of social capital in innovation. In einem
cross-country study, Doh and Acs (2010) show that civic norms and institutional
trust promote associated entrepreneurial activities. In another study on firm-level
behaviors, Landry, Amara, and Lamari (2002) propose stakeholders’ participation
and reciprocal norms as crucial social capital assets that determine firms’ decision
to innovate. Zusätzlich, Yoon et al. (2015) suggest shared norms as a type of
cognitive social capital that vitalized entrepreneurial efforts in the Republic of
Korea and Taipei,China. Another study on Spain by Molina-Morales and Martínez-
Fernández (2010) also endorses the importance of shared orientations in shaping
policy makers’ and entrepreneurs’ perceptions toward innovation.
As summarized above, the literature gives a special emphasis on social norms
because innovation can be facilitated when society shares supportive norms and
Werte. Such social norms are probably more important in East Asian economies,
considering that they have upgraded their economic structures from agriculture-
based economies to high technology-based innovation economies within only a
few decades under the leadership of the states. Compared to private-led Western
industrialization where trust between individual entrepreneurs and investors were
an important determinant in forming a cooperation for innovation, the essential
elements that supported public-led innovation in East Asia are arguably different.
For economic players in East Asia, it is more crucial to share goals set by the
state and demonstrate collective will toward the goals in order to participate in
entrepreneurial projects sponsored by the state. Somit, social norms of embracing
developmental goals can play a deciding role in stimulating innovation. Ähnlich,
state-led innovation requires citizens to endorse and support the legitimacy and
leadership of the state as the main economic stakeholder, and therefore the
importance of trust in formal institutions overshadows that of social trust among
individuals in the East Asian economies.
4Several other studies suggest a more complex relationship between social capital and innovation. Echebarria
and Barrutia (2013) show an inverted U-shape in the effect of social ties on innovation. Pérez-Luño et al. (2011)
propose an interactive effect that social and human capital jointly generate to enhance innovation.
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Social Capital and Innovation in East Asia 211
With these arguments in mind, social norms and institutional trust that reflect
societal recognition of state leadership and common goals are hypothesized as
essential elements of social capital that drive innovation in East Asia. Entsprechend,
this paper proposes and empirically tests the following hypotheses:
Hypothesis 1. In high-performing East Asian economies, social trust has no
positive effect on innovation.
Hypothesis 2. In high-performing East Asian economies, social norms that support
the shared goal of development have a positive effect on innovation.
Hypothesis 3. In high-performing East Asian economies, trust in formal institutions
has a positive effect on innovation.
III. Decomposition of Social Capital
To test for the hypotheses articulated above, social capital is decomposed
into different dimensions, distinguishing between social trust, norms, institutional
trust, and others, so that the net effect of each element can be identified. Das
paper follows the measurement approach suggested by Scrivens and Smith (2013)
in a study done for the Organisation for Economic Co-operation and Development
(OECD). According to Scrivens and Smith (2013), social capital consists of four
essential dimensions: trust, personal and social networks, cooperative norms and
Werte, and civic engagement. This classification seizes the concept of social capital
defined by Putnam (1993) and Coleman (1990) who proposed social networks
and shared norms as underlying values of creating social trust and citizens’
participation. Adopted by these two representative scholars of the social capital
Schule, this concept is widely recognized and used in empirical studies on social
capital.
With this in mind, the empirical model of this paper is designed to account
for each effect of social norms, civil participation, trust, and networks by employing
data from the 4th–6th waves of the World Values Survey (World Values Survey
Association 2005–2014). A special emphasis is placed on social and civic norms
shared by members of society that support collective goals and values toward
Entwicklung, as hypothesized above. Entsprechend, the following questions in the
survey are selected to measure such norms: (ich) whether one supports the shared
societal goal of economic growth (growth primacy, answered on a scale of 0 Zu 1);
(ii) how much one embraces the values of competition and incentive orientation
as modes of achieving goals (competition orientation and acceptance of inequality,
jeweils; scale of 1 Zu 10); (iii) reciprocity for others in society (scale of 1 Zu 6);
Und (iv) tolerance toward social minorities (scale of 1 Zu 10). Components (ich) Und
(ii) represent social norms, while (iii) Und (iv) reflect civic-mindedness.
Trust, another important dimension of social capital, is further subdivided
into social, personal, and institutional trust. In this analysis, institutional trust is
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212 Asiatischer Entwicklungsbericht
hypothesized as a crucial determinant of innovation in East Asia because it can be
more relevant for state-led innovation than trust among individuals. Institutional
trust is measured by degrees of trusting various types of formal institutions that
were asked in the World Values Survey: (ich) trust in courts (answered on a scale
von 1 Zu 4); (ii) trust in parliaments (scale of 1 Zu 4); Und (iii) trust in fairness of
the rules (scale of 1 Zu 10). Distinguished from institutional trust, social trust is
measured by using the question on how much one trusts other people in general
(scale of 1 Zu 4). This question captures the level of trust in broadly defined groups
of people. This type of trust can be an asset in forming cooperation with many other
individuals for economic and entrepreneurial activities. Im Gegensatz, personal trust
is evaluated through a question on how much one trusts family members, close
friends, and relatives (scale of 1 Zu 4). Personal trust refers to a limited cluster
of people who can be available for cooperation, which is different from social
trust.
The other decomposed dimension of social capital is networks, welche
accounts for the scope of connectivity among individuals. Networks can function
as a tool of imposing informal sanctions and encouraging members to participate
in common activities. Similar to distinguishing social and personal trust, Netzwerke
are also separated based on their extent, with each network’s outreach involving
different people and participatory causes: social networks for civil participation
(humanitarian networks) and personal networks for private interests (hobby
Netzwerke). The degree of one’s participation in each type of network is measured
by the frequency of participation in the respective network on a 3-point scale from
0 (no participation) Zu 2 (very frequent participation).
In Summe, social capital is decomposed into 12 different dimensions. Der
binary correlations across the different elements of social capital are all positive
varying from 0.07 Zu 0.68 (see Appendix 2). These results show that
Die
decomposed elements of social capital share the same direction, but each variable
includes an independent component to a considerable degree (zwischen 0.32 Und
0.93). This finding verifies the empirical justification of distinguishing different
dimensions of social capital and identifying each effect. The descriptive statistics
of the social capital variables can be found in Appendix 1, and the utilization of the
variables in the empirical model is discussed in more detail in section V.
IV. Economywide Aggregate Analysis
Before closely examining the relationship between social capital and
innovation in East Asia at the individual level, an aggregate analysis is conducted
at the level of each national economy to show whether the effects of social capital
are different between East Asia and other parts of the world. Wenn ja, the evidence
can be used to support a specific role of social capital in East Asian economic
Entwicklung.
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Social Capital and Innovation in East Asia 213
Tisch 1. Aggregate Analysis: The Effects of Social Capital on Innovation
(Cross-economy panel, linear estimation model)
Global Sample (excluding East Asia)
Ostasien
(log) Patent
Global Innovation Index
(log) Patent
(1)
(2)
(3)
(4)
0.052
(0.010)***
2.091
(0.541)***
3.668
(1.039)***
Fixed
Wirkung
Ja
0.021
(0.011)*
−0.068
(0.023)***
−0.003
(0.007)
−0.005
(0.009)
0.002
(0.005)
0.786
(0.379)**
2.579
(0.942)***
Fixed
Wirkung
Ja
0.215
(0.051)***
6.098
(0.631)***
0.836
(0.511)
Random
Wirkung
Ja
0.178
(0.056)***
−0.249
(0.212)
0.055
(0.046)
−0.038
(0.086)
0.059
(0.042)
5.776
(0.663)***
0.740
(0.538)
Random
Wirkung
Ja
(5)
0.029
(0.031)
2.433
(0.288)***
5.959
(2.917)
Fixed
Wirkung
Ja
(6)
−0.031
(0.013)*
0.164
(0.025)***
0.157
(0.023)***
0.090
(0.013)***
0.054
(0.007)***
3.766
(0.253)***
3.901
(1.172)**
Fixed
Wirkung
Ja
2005–2014
2014–2017
2005–2014
897
83
0.45
401
78
0.20
264
54
0.35
254
52
0.35
91
6
40
6
0.97
0.98
Social trust
Social networks
Institutional trust
Growth primacy
Tolerance
(log) GDP per
capita
(log) Bevölkerung
Economywide
fixed effects
Time effects
Period
Beobachtungen
Number of
economies
R2 (innerhalb)
BIP = Bruttoinlandsprodukt.
Notes: Numbers in parentheses are robust standard errors clustered at the economy level. *P < .10, **p < .05, ***p <
.001.
Source: Author’s estimates.
Table 1 provides the results of the aggregate analysis using panel data from
the GII (Cornell University, INSEAD, and WIPO 2014–2018) and the number
of patents (taken from the World Bank Database) as innovation outputs at the
economy level. The World Values Survey was utilized to measure the aggregate
levels of social capital in each economy. The empirical model used for this analysis
is presented below.
Innovationit = β1social trustit + β2social networksit + β3institutional trustit
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+ β4growth primacyit
+ β7populationit
+ αi + γt + uit
+ β5toleranceit + β6GDP pcit
(1)
The aggregate analysis employs a reduced form of using one representative
measurement for each dimension of social capital so that links between social
capital and innovation can be presented without multicollinearity. Accordingly,
214 Asian Development Review
the following variables are encompassed in the model: social trust (trust in other
people in general), social networks (participation in humanitarian organizations),
institutional trust (trust in the parliament), the shared norm of growth primacy
(endorsing growth as the most important societal goal), and tolerance toward
minorities (accepting homosexuals as neighbors). The decomposition analysis
model in section V includes the full set of 12 social capital variables in order to
disentangle the net effect of each element on innovation.
Besides social capital variables, income (gross domestic product per capita)
and population variables enter the model as control variables as they represent
important conditions in each economy that influence innovation. In addition,
time-invariant unobserved heterogeneity in each economy (denoted as αi) is
accounted for in this model (fixed effects are applied when the dependent variable
is the logarithmic (log) number of patents and random effects when the GII is used
as the dependent variable due to limited variations in the GII scores). The rest of the
unobserved effects is addressed as an error term (uit), and time effects are controlled
for by using year dummies (t).
As for the dependent variables, two innovation measurements are used in
this model. The first is the (log) number of patent applications of an economy
in a given year. Patents are considered an important indicator of innovation
outputs, and the number of patents is the most frequently used measurement of
innovation in the literature (Knack and Keefer 1997, Zak and Knack 2001). Second,
the knowledge and technology outputs of the GII are taken as an alternative
measurement. This index evaluates multifaceted dimensions of knowledge and
technology including knowledge creation (e.g., patent applications); impact (e.g.,
high technology outputs); and diffusion (e.g., intellectual property receipts). This
measurement is chosen because it focuses on outputs of high technology-based
innovation that are relevant for the scope of this paper.
The period of investigation is 2005–2017 when the dependent variable is
(log) patent applications, because data on social capital variables are available in
the World Values Survey for this period. When the GII serves as the dependent
variable, the analysis includes the period 2014–2017 due to the availability of the
index. The model is estimated using a linear estimation technique.
In Table 1, the results are presented separately for the global sample of
countries (up to 83 countries that were surveyed in the World Values Survey,
excluding the six East Asian economies) and six East Asian high-performing
economies (Hong Kong, China; Japan; the PRC; the Republic of Korea; Singapore;
and Taipei,China). The comparison between the global and East Asian samples
enables us to identify whether the effect of social trust differs in East Asia and
whether social norms and institutional trust play an important role in promoting
innovation.
First, in the global sample, it is evident that social trust has a positive
effect on innovation (both patent applications and the GII). Without considering
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Social Capital and Innovation in East Asia 215
the other components of social capital (columns 1 and 3), increasing social trust by
1 percentage point increases the number of patent applications by 5.2% and the GII
score by 0.2 percentage point. When social networks, institutional trust, the norm
of growth primacy, and tolerance are all included in the model (columns 2 and
4), the effect of social trust decreases but remains positive and significant. Given
that accounting for other compounding effects of social capital reduces the effect
of social trust by 17%–60%, 40%–83% of the total effect of social capital can be
attributed to social trust in the global sample.
However, when the sample is limited to the six East Asian economies, the
results show quite a different outlook. Without controlling for the other components
of social capital, social trust has no effect on innovation (column 5), in contrast to
social trust’s positive effect in the global sample.5 Moreover, its effect on East Asian
innovation becomes negative—although marginally significant at the 10% level—
after accounting for the effects of the other social capital components (column 6).
Instead, social and civic norms, networks, and institutional trust promote innovation
in East Asia, as all of these effects become positive and significant.
This comparison suggests that, as expected, the role of social trust is different
in the East Asian economies than in the rest of the world. The findings presented
in Table 1 support hypotheses 1, 2, and 3 in that the role of social norms and
institutional trust dominates that of social trust in this region. In the following
section, these hypotheses are further investigated by using decomposed data at the
individual level in the six East Asian economies.
V. Decomposition Analysis at the Individual Level
A. Model
In this section, the relationships between innovation and social capital in
the East Asian economies are further disentangled by employing the full set
of social capital variables. To this end, a decomposition analysis that exploits
individual variations of the variables is conducted for two reasons. First, this
analysis can reveal how individual endowments of social capital influence one’s
attitudes toward innovation, with the evidence contributing to explanations of
behavioral consequences of social capital. Second, the application of individual
data enables the use of finer sets of social capital and innovation measurements
so that a more precise link between each element of social capital and innovation
can be established. In this decomposition analysis, the 6th wave of the World Values
Survey 2010–2014 is used because it provides the largest set of social capital and
innovation measurements.
5In the East Asian sample, the number of patent applications is employed as the sole dependent variable
because the GII has too few observations.
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216 Asian Development Review
Accordingly, 12 variables which mirror various aspects of social capital
are incorporated in the model (instead of the five variables that appeared in the
parsimonious model in the aggregate analysis). As presented in section III, the 12
social capital variables represent social, personal, and institutional trust, social and
civic norms, and social and personal networks. The vector of social capital consists
of the following variables:
Social Capital = {social trust (scale 1–4), personal trust (scale 1–4),
social networks (scale 0–2), personal networks (scale 0–2), trust in
parliaments (scale 1–4), trust in courts (scale 1–4), trust in the fairness
of the rules (scale 1–10), growth primacy (scale 0–1), competition
orientation (scale 1–10), acceptance of economic inequality (scale
1–10), reciprocity (scale 1–6), tolerance (scale 1–10)}
In this model,
individual attitudes toward innovation are used as the
dependent variables. These variables reveal
to which individuals
the extent
value innovation. Six measurements that evaluate the degree of importance and
acceptance of the particular aspects of innovation are selected to compose the set of
dependent variables as presented below:
Innovation = {importance of new ideas and creativity (scale 1–6),
importance of technological development (scale 1–3), importance of
science and technology today (scale 1–10), importance of science and
technology in the future (scale 1–10), acceptance of the statement
“science makes the world better” (scale 1–10), acceptance of the
statement “we depend too much on science” (an antagonistic attitude
toward innovation, scale 1–10)}
Additionally,
individuals’ demographic characteristics are included as
control variables in the model following the selection of personal trait variables
suggested in the literature that
investigates individual attitudes reflected in
the World Values Survey (Eichhorn 2012; Kistler, Thöni, and Welzel 2015).
They include gender (being a female), age and age2, marital status, income
level, employment status (self-employed and unemployed), education (university
degree), and an individual’s preference for risk taking. Particularly, an individual’s
preference for risk taking is chosen as a control variable because innovation
involves risky initiatives, therefore such a preference can influence one’s attitudes
toward innovation. Regarding the choice of employment variables, those who are
self-employed are expected to be more willing to recognize innovation, while the
opposite could be true for the unemployed. Additionally, a dummy variable for each
economy is added in the model to account for shared cultural and cognitive frames
(same language, rules, history, collective experience, etc.) among individuals from
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Social Capital and Innovation in East Asia 217
the same economy. Accordingly, the model of the decomposition analysis takes the
form below:
(cid:2)
(cid:2)
(cid:2)
Innovationi = α +
β (cid:3)
ksocial capitalki
+
ϕ jx ji +
λ(cid:3)
meconomymi
+ ui
(2)
k
j
m
In equation 2, k denotes each of the 12 social capital variables, j is each
of the nine demographic variables (x), m is each of the six economy dummies,
and i represents each individual (up to 7,462 in total). This model is estimated by
using two regression methods: ordered probit, given the ordered structures of the
dependent variables; and ordinary least squares (OLS) to compute marginal effects.
The results of the linear and nonlinear estimations are presented and compared in
Table 2.
Furthermore, an additional analysis is conducted by exploiting individual
variations within each economy in order to identify economy-specific effects of
social capital and compare their differences across the six economies. In this
within-economy analysis, economywide fixed effects are naturally excluded from
the model, leading the equation to be modified as follows:6
(cid:2)
(cid:2)
Innovationi = α +
β (cid:3)
ksocial capitalki
+
ϕ jx ji + ui
(3)
k
j
In addition, the potential endogeneity of the model is addressed by using
an instrumental variable (IV) approach, for which the instrument for each social
capital variable is the average value of the respective social capital variable of the
same demographic group that shares the same gender and age cohort with individual
i in the same economy (naturally excluding individual i in computing the average
value of the group). The exclusion criteria of the chosen instruments are tested by
two-stage least squares estimations and the results are presented in Appendix 3 (the
first-stage results for the explanatory power of the instruments and the Hansen tests
for the exogeneity of the instruments). The IV estimations produce results that are
qualitatively similar to those of the OLS and ordered probit methods presented in
Table 2. Hence, I will focus on the findings in Table 2 in the following section.
B.
Findings
The results presented in Table 2 show the effects of the 12 social capital
variables in the six East Asian economies. The table highlights the importance of
shared social norms and institutional trust over social trust. Note that when the
dependent variable is “too much dependence on science,” the effects are expected
6The OLS and ordered probit estimations of equation (2) produce qualitatively identical results (see Table 2).
Thus, a linear method is applied to estimate equation (3) so that the coefficients can be interpreted in a straightforward
way.
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218 Asian Development Review
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222 Asian Development Review
to stand in opposition to those in the other models because this variable reflects
negative attitudes toward innovation.
First, the decomposition analysis shows no positive effect of social trust
on innovation in general. It even constrains individuals from having positive
attitudes toward technology and science. The only exception is its positive effect
on promoting new and creative ideas. Instead of social trust, personal trust plays
a more positive role in innovation, improving one’s support for technology and
science. However, personal trust negatively affects one’s attitudes toward new ideas
and creativity, which is exactly the opposite effect of social trust. This finding infers
a region-specific aspect of East Asian development, in that innovation has been
facilitated through cooperation between personally connected individuals and thus
personal connectivity is an important driving force. However, personal trust can
also be a hindrance to new ideas and creativity, while social trust is their promoter.
These mixed findings complicate the role of individual trust in East Asia.
In contrast to the mixed results of trust in individuals, trust in formal
institutions has a more robustly positive effect on innovation. All of the three
types of trust in formal institutions stimulate individuals’ positive attitudes toward
innovation—the effects of trust in courts and fairness of the rules are significant in
four out of the six models and the effect of trust in parliaments is significant in three
models. A 10 percentage point increase in trust in courts, parliaments, and fairness
of the rules boosts one’s support for innovation by 9–19.2 percentage points,
12.7–21.4 percentage points, and 2.8–8.8 percentage points, respectively.
More importantly, shared social norms and values produce the most
prominent effects of determining one’s attitudes toward innovation. Particularly,
the norms of growth primacy and competition orientation have robustly positive,
significant effects in all models. Agreeing that economic growth is the main goal
of the economy (growth primacy) increases the level of positive attitudes on
innovation by 1.5–2.4 percentage points and reduces negative perceptions by 1
percentage point. Increasing the degree of accepting the norm of competition by
10 percentage points enhances one’s innovative attitudes by 3.7–14.5 percentage
points. In addition, the acceptance of economic inequality has a positive effect
in five out of the six models—increasing the acceptance level of this norm by 10
percentage points improves one’s supportive attitudes toward innovation by 3.1–7.2
percentage points.
These findings disclose the importance of the shared norm of stimulating
growth through competition and individual efforts in East Asia. The role of social
norms is further evident in the positive effect of reciprocity, which is significant in
four of the six models. Increasing the degree of reciprocity for others in society
by 10 percentage points raises one’s positive attitudes toward innovation by 5–34.2
percentage points. The positive role of social norms found in this analysis provides
an indication that East Asian innovation and growth have been achieved through the
collective will of the society and shared norms toward development. On the other
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Social Capital and Innovation in East Asia 223
hand, the role of networks is limited in explaining innovation in this region. The
effects of social and personal networks are either insignificant or negative. The only
exception is the positive effect of social networks on new ideas and creativity—a
10 percentage point increase in social network participation increases one’s support
for new ideas and creativity by 11.2 percentage points.
Regarding the effects of individual traits, gender is an important determinant
that shapes one’s attitudes toward innovation. Women tend to support innovation
less than men, and this negative effect remains significant with a gender gap
of 0.5–2 percentage points against women after controlling for other individual
differences in characteristics. This gender difference in attitudes toward innovation
may be explained by the limited role women could play in phases of economic
development, which results in fewer opportunities to contribute to innovation (this
is probably true not only in East Asia but also worldwide). In contrast to the
gender effect, the effects of income and education are generally insignificant in
most specifications. Nonetheless, there is some evidence that higher income levels
and university education enhance individuals’ support for new ideas and creativity
and for science and technology. This finding implies that innovation is an outcome
of resourceful environments.
C.
Analysis and Comparisons across the Six East Asian Economies
The results above highlight shared social norms and institutional trust as
crucial determinants of innovation in East Asia. This common finding in the six
economies is further disentangled in this section by identifying economy-specific
heterogeneity in the effects of social capital. Accordingly, the sample is divided
by economy in order to implement within-economy analyses. Table 3 presents the
results estimated by OLS. Overall, there is considerable heterogeneity across the
six economies in the effects of the different types of social norms and institutional
trust.
1.
The People’s Republic of China and Hong Kong, China
Results for the PRC and Hong Kong, China are shown in Table 3.1. In the
PRC, the importance of shared social norms is largely established. However, the
specific types of social norms that are important in the PRC are different from the
common findings in the six economies presented in section V.B. The most crucial
component of social norms that determine attitudes of individuals toward innovation
in the PRC is reciprocity. The effect of reciprocity is significant in all six innovation
models. Increasing the level of reciprocity by 10 percentage points increases
positive attitudes toward innovation by 9.8–49.7 percentage points and decreases
negative perceptions of innovation by 15.7 percentage points. Moreover, the value
of accepting competition as a means to stimulate individual efforts has a generally
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224 Asian Development Review
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230 Asian Development Review
positive effect on innovation (significant in five of the six models). Increasing
the acceptance level of competition by 10 percentage points strengthens one’s
supportive attitudes for innovation by 4.8–11.1 percentage points. These findings
are puzzling because they suggest that innovation in the PRC is the outcome
of both mutual assistance and individual competition, which are two potentially
conflicting values. It mirrors the complex path of the PRC’s fast development, in
which both traditional (reciprocity) and individual (competition) values coexist and
concur.
On the other hand, the shared norm of growth primacy plays a minimal
role in promoting innovation in the PRC. The effect is either insignificant or
sometimes even negative, contrary to the positive effect at the aggregate level of
the six economies as shown in Table 2. In addition, the effect of trust in other
individuals—both social and personal trust—is largely trivial, as is the limited
role of networks. Instead, trust in formal institutions is important in promoting
innovation. In particular, increasing the level of trust in parliaments and in the
fairness of the rules by 10 percentage points improves one’s support for innovation
by 23.8–34.8 percentage points and 8.6–12.3 percentage points, respectively.
In Hong Kong, China the results demonstrate both similarities and
differences with the PRC. First, similar to the PRC, the shared norm of growth
primacy does not play a meaningful role in Hong Kong, China. The important
component of social norms for Hong Kong, China is the value of accepting
competition. This norm has a significant, positive effect in five of the six models
in Hong Kong, China, a finding similar to the PRC with somewhat larger effects.
Increasing the level of acceptance of competition by 10 percentage points improves
one’s attitudes toward innovation by 6.2–11.1 percentage points in Hong Kong,
China compared to 4.8–11.1 percentage points in the PRC. Trust in formal
institutions is also important in Hong Kong, China. Trust in courts and parliaments
as well as the fairness of the rules all have significant effects in three of the six
innovation models—an increase in institutional trust by 10 percentage points results
in increasing innovation by 10.7–34.8 percentage points.
On the other hand, despite their shared ethnic backgrounds and Chinese
tradition, several differences between the PRC and Hong Kong, China are observed.
The effect of reciprocity is significant in only two out of the six models in Hong
Kong, China. This finding suggests that reciprocity is less important in Hong Kong,
China than in the PRC. Moreover, social trust discourages innovative attitudes in
Hong Kong, China, which is similar to the overall results for the six economies
but different from the insignificant effect in the PRC. All in all, contemporary
individualist values (e.g., competition) overshadow traditional norms (reciprocity)
in determining innovation in Hong Kong, China, while both types of norms coexist
in the PRC. This might be explained by the different economic and institutional
developmental paths the PRC and Hong Kong, China have taken in recent history.
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Social Capital and Innovation in East Asia 231
2.
The Republic of Korea and Japan
The role of social capital is similar in the Republic of Korea and Japan
to a substantial extent (see Table 3.2). In both countries, the effect of individual
trust is considerably limited in explaining innovative attitudes, as both social and
personal trust have almost no effect. In addition, social and personal networks are
not important determinants of promoting innovation—there is (almost) no effect
in Japan and either insignificant or negative effects in the Republic of Korea
(except for a positive effect on new ideas and creativity). These findings provide
counterevidence to the argument by Fukuyama (1995) who hypothesized Japan as a
high-trust society (therefore relying on generalized social networks for economic
cooperation and innovation) and the Republic of Korea as a low-trust society
(therefore relying on personal networks). Instead of social and personal trust and
networks, two other components of social capital play a meaningful role in these
two countries: (i) trust in formal institutions, particularly justice (trust in courts in
both countries and trust in the fairness of the rules in the Republic of Korea); and
(ii) social norms that support growth primacy as a societal goal and competition as
a mode of stimulating individual efforts.
In both countries, trust in courts has a significant, positive effect in five of
the six innovation models. The size of the effect is comparable between the two
countries: increasing trust in courts by 10 percentage points increases positive
attitudes toward innovation by 16.7–29.3 percentage points in Japan and 15.7–29
percentage points in the Republic of Korea. Additionally, in the Republic of Korea,
trust in the fairness of the rules has a significant effect in four of the six models,
with an increase in this type of trust by 10 percentage points resulting in promoting
innovative attitudes by 7.1–10 percentage points.
Among the different types of social norms, growth primacy plays a somewhat
more significant role in Japan than in the Republic of Korea—the effect is
significant in five models in Japan and four models in the Republic of Korea.
However, the size of the effect is 20%–40% larger in the Republic of Korea
when it is significant (except for Tech. Dev., i.e., the importance of technological
development). Both the Republic of Korea and Japan tend to accept the norm
of competition as a mode of fostering efforts, with the significance of the effect
appearing in three models out of six. The effect is significantly greater in the
Republic of Korea than in Japan (14.7–20.1 percentage points versus 7.8–9.5
percentage points), implying that the Republic of Korea tends to have a competition-
oriented society.
However, the two countries differ in endorsing the norm of performance-
based incentives (economic inequality). In Japan, the acceptance of economic
inequality has a generally positive effect. A 10 percentage point increase in the level
of accepting this norm increases innovative attitudes by 9.3–10.5 percentage points
in four of the six models. The effect is more mixed in the Republic of Korea where
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232 Asian Development Review
accepting inequality increases positive attitudes toward the importance of science
and technology only in the present but not in the future. The positive effects on
Sci. & Tech. (importance of science and technology today) and World (agreeing
that science makes the world better) have a magnitude of 7.3–11.5 percentage
points. However, accepting inequality negatively affects Future (attitudes toward the
importance of science and technology in the future)—a 10 percentage point increase
in the level of accepting inequality results in constraining one’s support for this type
of innovation by 10.6 percentage points. This difference suggests that Koreans tend
to accept economic inequality as a currently valid norm for development but not
for the future, whereas the Japanese are more inclined to embrace such economic
incentives in general.
While both countries generally support the social norms of competition- and
incentive-based growth, the Republic of Korea and Japan place different emphases
on the norms of social inclusion. In the Republic of Korea, the reciprocity of
broad social groups plays an important role in innovation, while tolerance toward
minorities fills this role in Japan. Increasing the level of reciprocity by 10 percentage
points in the Republic of Korea enhances one’s support for innovation by 9–18.16
percentage points, but tolerance has no effect. In Japan, increasing tolerance by the
same margin results in stimulating one’s innovative attitudes by 3.9–7.8 percentage
points, but the effect of reciprocity is minimal.
Moreover, the gender effect is different between the Republic of Korea and
Japan. Women’s support toward innovation is generally lower in Japan—25.4%–
29.8% lower than men’s in four of the six models. On the contrary, in the Republic of
Korea, women are as innovative as men, as the gender effect is largely insignificant.
This result is similar to that in Hong Kong, China where there is also almost no
gender difference in individuals’ innovative attitudes.
3.
Singapore and Taipei,China
Singapore shows generally similar results to those of the other East Asian
economies (see Table 3.3). In Singapore, social trust has either a negative or
insignificant effect. However, the effect of personal trust is more mixed—positive,
negative, or insignificant—depending on the innovation measure. Also, the effects
of both social and personal networks are insignificant or negative. Similar to the
other East Asian economies, there is no evidence to support the positive role
of trust in individuals or networks in explaining Singaporeans’ attitudes toward
innovation.
Instead, it is the shared social norms that stimulate innovative attitudes in
Singapore, similar to the other East Asian economies. The value of accepting
competition is the most robust determinant—increasing the level of endorsing
this value by 10 percentage points raises one’s innovative attitudes by 3.3–16
percentage points in four of the six models. Reciprocity, growth primacy, and
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Social Capital and Innovation in East Asia 233
acceptance of inequality also form a group of important social norms, as they
foster attitudes toward innovation in three of the six models. Increasing the level
of reciprocity and acceptance of inequality improves one’s support for innovation
by 5.1–29.8 percentage points and 4–6.6 percentage points, respectively, and
agreeing with growth primacy as the main goal of the economy strengthens
innovative attitudes by 3.2–3.6 percentage points. This finding contributes to the
argument that innovation is an outcome of competition-based activities rather than
cooperation-based activities in East Asia. Additionally, trust in the fairness of the
rules is an important institutional determinant in Singapore. Increasing this type of
institutional trust by 10 percentage points boosts the degree of supportive attitudes
toward innovation by 2.9–4.2 percentage points.
The findings for Taipei,China (also in Table 3.3) are similar to those for
Singapore to a great extent, supporting the important role of shared social norms.
Increasing the degree of accepting competition by 10 percentage points raises
positive attitudes toward innovation by 5.3–11.3 percentage points in four of the
six models. The effect of reciprocity is significant in three out of the six models. A
10 percentage point increase in the level of accepting this norm creates a positive
effect of 15.3–40 percentage points on innovative attitudes. Growth primacy and
acceptance of inequality also have positive effects of 5.4–32.8 percentage points
and 5.2–7.3 percentage points, respectively, but they are significant in only two
models. In addition, trust in formal institutions is also important in Taipei,China. In
particular, increasing the level of fairness of the rules and trust in parliaments by 10
percentage points improves one’s innovative attitudes by 10–12.2 percentage points
and 22.2–27.3 percentage points, respectively.
the effects of trust
In contrast to the significant role of social norms and trust in formal
institutions,
in individuals and networks are limited in
boosting innovation in Taipei,China. The effect of social trust is either negative
or insignificant (except for the modestly positive effect on New Idea), while
personal trust has no effect on innovation. Also, social networks generally do not
have significant effects. Personal-interest-driven networks have a positive effect of
stimulating innovative attitudes to some degree, albeit the effect is significant in
only two models. This positive (although limited) effect of personal networks may
be explained by the industrial structures of Taipei,China as a small economy that
depends on many small and medium-sized, family-owned enterprises.
Overall, the effects of trust in individuals tend to be negative in smaller
economies (Hong Kong, China; Singapore; and Taipei,China) and insignificant
in larger ones (Japan,
the PRC, and the Republic of Korea). In any case,
social
trust plays no positive role in shaping innovative attitudes. Instead,
institutional trust and shared social norms such as growth primacy, acceptance
of competition- and performance-based economic incentives, and reciprocity are
important determinants of innovation in East Asia. This analysis renders social
norms as the driving force of innovation in this region while questioning the role of
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234 Asian Development Review
social trust. While social norms are important in all six East Asian economies, the
specific components of social norms that have more significant effects differ among
them. This requires a future study that can address heterogeneity across economies
in the role of social norms.
VI. Conclusion
The findings of this study recapture the important role of social capital in
achieving innovation and economic development. Nevertheless, the types of social
capital that are essential for innovation in East Asia are different from the emphasis
given on social trust in the literature. Shared social norms and values are the prime
drivers of innovation in the high-performing East Asian economies. In addition,
trust in formal institutions plays a crucial role. These results indicate how the East
Asian economies realized their development: by supporting societal goals that were
collectively set by citizens and led by the states.
While the East Asian economies share the importance of social norms, the
types of social norms and values that are particularly key to innovation differ
across economies—for example, reciprocity plays a pronounced role in the PRC,
in contrast to Japan and the Republic of Korea where growth primacy is more
important. Further studies are encouraged to investigate how each economy’s social
conditions and contexts contribute toward shaping economy-specific roles of social
norms as a promoter of innovation.
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Appendix 1. Descriptive Statistics of Social Capital Variables
Variables
Observations Mean Minimum Maximum
Social trust
Personal trust
Social networks
Personal networks
Trust in courts
Trust in parliaments
Trust in fairness
Reciprocity
Growth primacy
Competition orientation
Tolerance
Acceptance of inequality
7,446
7,117
7,446
7,117
7,446
7,117
7,117
7,117
7,446
7,117
7,446
7,117
2.32
2.45
1.21
1.33
2.74
2.01
2.55
3.89
0.68
0.71
4.59
5.97
1
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Source: Author’s estimates using data from the World Values Survey (2005–2014).
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Social Capital and Innovation in East Asia 237
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Appendix 3. Instrumental Variable Approach, Two-Stage Least Squares
1st Stage
Average value
(Instrument)
F–statistics
Controls
Observations
1st Stage
Average value
(Instrument)
F–statistics
Controls
Observations
2nd Stage
Variablesa
Social trust
Personal trust
Social networks
Personal networks
Trust in courts
Trust in parliaments
Trust in fairness
Reciprocity
Growth primacy
Competition
orientation
Tolerance
Acceptance of
inequality
Controls
Economywide fixed
(1)
Social
Trust
0.14***
(0.05)
31.71***
Yes
7,117
(7)
Trust in
Fairness
0.78***
(0.33)
29.01***
Yes
7,117
(2)
Personal
Trust
0.07**
(0.03)
28.9***
Yes
7,117
(3)
Social
Networks
0.06**
(0.03)
36.78***
Yes
7,117
(9)
(8)
Growth
Primacy Competition
0.05***
(0.02)
37.10***
Yes
7,117
0.51***
(0.24)
16.42***
Yes
7,117
(1)
(2)
New Idea Tech. Dev. Sci. & Tech.
(3)
0.056
(0.032)*
−0.055
(0.045)
0.069
(0.036)*
0.041
(0.033)
−0.012
(0.013)
0.001
(0.003)
0.015
(0.007)**
0.121
(0.061)**
0.091
(0.032)***
0.032
(0.016)**
0.020
(0.016)
0.045
(0.016)***
Yes
Yes
−0.121
(0.059)**
0.011
(0.032)
−0.053
(0.044)
0.031
(0.065)
0.096
(0.045)**
0.085
(0.043)**
−0.010
(0.053)
0.076
(0.034)***
0.095
(0.051)**
0.054
(0.017)***
−0.037
(0.020)*
0.025
(0.011)***
Yes
Yes
−0.104
(0.065)*
0.081
(0.049)*
−0.076
(0.101)
−0.043
(0.026)*
0.197
(0.081)***
0.051
(0.048)
0.093
(0.044)***
0.009
(0.052)
0.095
(0.050)**
0.109
(0.057)**
0.071
(0.041)*
0.098
(0.043)***
Yes
Yes
(4)
Personal
Networks
0.02**
(0.01)
18.78***
Yes
7,117
(5)
Trust in
Courts
0.12***
(0.05)
24.62***
Yes
7,117
(10)
Acceptance
Inequality Reciprocity
(11)
0.69**
(0.37)
27.28***
Yes
7,117
(4)
Future
−0.105
(0.077)
0.092
(0.084)
−0.054
(0.095)
−0.042
(0.055)
0.174
(0.091)**
0.066
(0.040)*
0.097
(0.051)**
0.006
(0.021)
0.113
(0.054)***
0.195
(0.095)**
−0.001
(0.011)
0.074
(0.039)**
Yes
Yes
0.15**
(0.08)
19.50***
Yes
7,117
(5)
Too Much
−0.039
(0.072)
−0.022
(0.091)
0.105
(0.099)
0.035
(0.048)
−0.032
(0.044)
−0.051
(0.071)
0.011
(0.021)
−0.075
(0.044)*
−0.111
(0.061)**
−0.065
(0.031)***
0.002
(0.015)
0.010
(0.039)
Yes
Yes
(6)
Trust in
Parliaments
0.16**
(0.07)
34.48***
Yes
7,117
(12)
Tolerance
0.33*
(0.20)
23.32***
Yes
7,117
(6)
World
−0.099
(0.059)*
0.109
(0.061)*
−0.055
(0.030)**
−0.012
(0.031)
0.156
(0.071)***
0.199
(0.099)**
0.071
(0.033)***
0.100
(0.051)**
0.198
(0.079)***
0.123
(0.065)**
0.009
(0.011)
0.040
(0.020)***
Yes
Yes
7,117
6
0.35
7,117
6
0.33
effects
Observations
Countries
Hansen test (p-value)
Notes: aNew Idea: importance of new ideas and creativity; Tech. Dev.: importance of technological development; Sci.
& Tech.: importance of science and technology today; Future: importance of science and technology in the future; Too
Much: acceptance of the statement “we depend too much on science;” World: acceptance of the statement “science
makes the world better.” Numbers in parentheses are robust standard errors clustered at the individual level. *p < .10,
**p < .05, ***p < .001. The coefficients of the control variables are not presented here to save space.
Source: Author’s estimates.
7,108
6
0.38
7,117
6
0.42
7,117
6
0.30
7,117
6
0.29
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