Capital Flight for Family? Exploring the Moderating Effects of Social Connections on Capital Outflow of Family Business

Abstract

Capital flight amounts to a substantial proportion of outward capital flow in emerging markets. This study, using a large sample of 2711 Chinese private firms, examines the relationship between family involvement and capital flight of family businesses. The results show that family involvement is positively associated with capital flight. And political connection weakens the positive effect of family involvement on capital flight. Further, our study investigates the moderating effects of political connection and local connection and their context-dependence on business environment. Generally, political connection weakens the positive effect of family involvement on capital flight. And such moderating effect of political connection is significantly negative in high-quality business environments and insignificant in low-quality business environments. More interestingly, moderating effect of local connection that is significantly negative in high-quality business environments turns into significantly positive in low-quality business environments. The effect of family involvement on OFDI and similar moderating effects of political connection and local connection are examined as comparisons. There are divergences of such effects in the case of OFDI and capital flight.

Full text

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Capital Flight for Family?
Exploring the Moderating Effects of Social Connections on Capital
Outflow of Family Business
Bao WU1*, Qi WANG1, Chevy-Hanqing FANG2, Fu-Sheng Tsai3,4, Yuanze XIA1
1* School of Management, Zhejiang University of Technology, Hangzhou, P.R.China, 310012,
2 School of Business and Information Technology, Missouri University of Science and Technology, Rolla,
MO, 65409
3 North China University of Water Resources and Electric Power, China
4 Cheng Shiu University, Taiwan
Corresponding to Prof. Bao WU at School of Management, Zhejiang University of Technology,
wubao@zjut.edu.cn
This study was funded by Major project of Zhejiang Provincial Philosophy and Social Sciences Research
Planning Project [20YSXK02ZD]. And the author thanks the supports from the National Social Science
Fund of China (20VYJ073), Basic Scientific Research Expenses Projects of Zhejiang University of
Technology (GB201903002).

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Capital Flight for Family?
Exploring the Moderating Effects of Social Connections on Capital
Outflow of Family Business
Abstract: Capital flight amounts to a substantial proportion of outward capital flow in emerging markets.
This study, using a large sample of 2711 Chinese private firms, examines the relationship between family
involvement and capital flight of family businesses. The results show that family involvement is positively
associated with capital flight. And political connection weakens the positive effect of family involvement
on capital flight. Further, our study investigates the moderating effects of political connection and local
connection and their context-dependence on business environment. Generally, political connection
weakens the positive effect of family involvement on capital flight. And such moderating effect of political
connection is significantly negative in high-quality business environments and insignificant in low-quality
business environments. More interestingly, moderating effect of local connection that is significantly
negative in high-quality business environments turns into significantly positive in low-quality business
environments. The effect of family involvement on OFDI and similar moderating effects of political
connection and local connection are examined as comparisons. There are divergences of such effects in the
case of OFDI and capital flight.
Keywords: capital flight, family firm, local connection, political connection, business environment

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1. Introduction
Unlike usual forms of internationalization of family businesses, such as M&A, FDI, international joint
venture etc., which provoke fevered debates in previous literature (Arregle et al., 2016; Kontinen and Ojala,
2010; Pukall and Calabrò, 2014), less discussed is capital flight of family businesses from emerging
markets in the last decades (Cheung et al., 2016; Gunter, 2017, 2004; Ljungwall and Wang, 2008).
Empirical studies show that capital flight is a substantial impediment to national solvency and economic
growth (Hermes and Lensink, 2001; Steiner et al., 2019; Varman-Schneider and Benu, 1991). Previous
studies have devoted extensive efforts to estimating the sizes of capital flight and their growth in emerging
markets (Asongu and Amankwah-Amoah, 2018; Gunter, 2017, 2004) identifying determinants underlying
capital flight (Collier et al., 2001; Geda and Yimer, 2016; Hermes and Lensink, 1992; Lensink et al., 2000;
Ramiandrisoa and Rakotomanana, 2016) and exploring its impacts on macroeconomics (Dachraoui et al.,
2020; Ndikumana, 2014; Steiner et al., 2019). Though capital flight has been extensively examined at
macro-level, investigations about capital flight at firm-level, particularly about family firms, is less
discussed among this stream of burgeoning literature. To the best of our knowledge, this study is one of the
very few, if not the first, to empirically investigate the hidden association between family involvement and
capital flight at firm-level. Capital flight in family businesses is an important issue. First, family businesses
play a substantial role in capital flight, particularly in emerging economies. A survey found that about 60%
of rich Chinese, whose family assets are worth more than $9.4 million, intended to migrate from China
mostly to the United States or Canada while these Chinese have already moved an estimated 20% of their
total assets out of China (Shi and Ran, 2011). Therefore, exploring the relationship between family
involvement and capital flight in family firms offers a good chance to build better micro-foundations for

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explaining capital flight in emerging markets. Second, capital flight is one of critical concerns for the
sustainability of family businesses in emerging markets. It is argued that the acceleration of capital flight in
China over recent decades is at least partially motivated by a desire to migrate among family businesses
(Gunter, 2017). The capital flight of family businesses, as well as the flight of family entrepreneurs
through emigration, has cost a huge capital outflow of trillions in US dollars and a serious brain drain in
China (Hess, 2016). In the conception framework proposed by Hirschman (1970), in response to adverse
economic, societal, and political uncertainties, family businesses have two primary alternative modes of
action including exit and voice. Surely, capital flight is one step of move their family out the business
community that they formerly rooted in for a long time. Such choice undermines their business linkage
with their motherland and brings negative impact at least to their domestic business running. Differing
from business internationalization, such capital flight has exposed a significant threat to sustainable
operation and intra-generational succession of family businesses in emerging markets. Our study may
enrich existing literature about the internationalization of family businesses and offer more insights about
their internationalization motivation.
It is found that organizational behaviors of family businesses may differ from other firms with
different ownership structures because social connection is usually a particularly important feature of
family firms (Baù et al., 2018; Bird and Wennberg, 2014). Family firms‟ higher social connection is
associated with owning families‟ noneconomic goals, such as organizational longevity, intra-generational
succession and socioemotional wealth (Chrisman et al., 2012). The achievement of these goals often
related to the preservation of durable relationships with local stakeholders (e.g., Miller et al., 2009; Pittino
et al., 2016). „„Family businesses are more embedded within the regional community than their non-family

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counterparts‟‟ (Bird and Wennberg, 2014: 424). Prior family business literature points to important
differences in international investment between family and nonfamily firms (Casillas and
Moreno-Menéndez, 2017; Gallo and Garcia Pont, 1996; Pukall and Calabrò, 2014). The majority of
literature on family firms‟ international investment suggests that family firms often take social connection
and socioemotional wealth (SEW) into account in their decision process on international investment
(Berrone et al., 2012; Gomez-Mejia et al., 2011, 2010, 2007). The capital flight phenomenon is ignored in
this research stream. The existing wisdoms about social connection can be helpful to explain the
relationship between family involvement and capital flight in family firms.
Our study advances theoretically and empirically the understanding about capital flight of family
firms from the perspective of social connection. Particularly, our study contributes to the literature in three
ways. First, we attempt to empirically investigate the association between family involvement and capital
flight in family firms, offering firm-level insights for capital flight in the context of family businesses. To
the best of our knowledge and the literature in hand, this study is one of very few, if not the first, to explore
the hidden association between family involvement and capital flight in family businesses. In this study,
we document strong evidence to show that family involvement is positively associated with capital flight,
which differs from the picture about the generally negative relationship between family involvement and
OFDI. Considering the important portion of family businesses in global economies, the study offers an
interesting and insightful perspective to explain the capital flight phenomenon at firm level. Second, our
study offers insights about the moderating effect of social connection in capital flight of family firms. This
study classifies the various ways in which political connection and local connection may influence the
relationships between family involvement and capital flight. Third, we find the moderating effects of local

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connection and political connection are context-dependent on the business environment. The negative
moderating effect of political connection on the relationship between family involvement and capital flight
is significant only in high-quality business environments. Furthermore, the negative moderating effect of
local connection in high-quality business environments may turn positive in low-quality business
environments. Hence, our study offers insights about how to understand the relationship between family
involvement and capital flight in family firms and contributes to internationalization and family business,
social connection literatures.
In the remainder of this study, we review the literature and development hypotheses, describe our
research design and empirical results, and finally discuss their theoretical implications and the limitations
of this study.
2. Theory and hypotheses
2.1 Family involvement and capital flight of family business
The major distinction between family firms and non-family firms is that the owning family of family firms
may intend to run their business in a way that allows creating and preserving of socioemotional wealth
(SEW) even at the expense of financial gains (Chrisman et al., 2007; Chrisman and Patel, 2012). The
family involvement that family business should be controlled or at least influenced by family members is
the psychological sources of SEW (Gomez-Mejia et al., 2007) and their motivations for pursuing
family-centered non-financial goals. The ideological connection between family and family businesses is
the core sources of familiness (Habbershon and Williams, 1999) and SEW (Gomez-Mejia et al., 2007), and
offers a fundamental perspective to better understand goals, behaviors and performance of family

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businesses (Pearson et al., 2008). The family involvement and its related conception of familiness and
SEW defines the distinctive qualities of family businesses. Strong family involvement may enhance the
involvement of family members in family businesses and may influence decision-making in family firms
so that family-centered affective values may be highly recognized and well maintained in business
operations. This stream of literature documents these traditional non-financial goals of family firms
including enjoyment of personal control, ability to exercise authority, need for identification, perpetuation
of a positive family image and reputation, sense of belonging, and an active role in the family dynasty (e.g.,
Berrone et al., 2012; Gomez-Mejia et al., 2010; Hauck et al., 2016). In this way, family involvement may
shape the thinking model of the owning family about their business strategy, including capital flight.
The perspective of SEW offers insights explaining the linkage between family involvement and
capital flight in family firms. The motivations behind capital flight include inflation, overvaluation,
differential yields, policy instability and political uncertainty at macro-level (Pastor, 1990; Pradhan and
Hiremath, 2020) and finance migration, corruption, transaction cost and even anxiety about children‟s
education and family business succession at micro-level (Browne, 2014; Gunter, 2017; Hess, 2016).
Usually, capital flight at macro-level can be explained by the investment-climate approach and the
discriminatory treatment approach (Lessard and Williamson, 1987). Capital flight is one defensive way for
family businesses to save their SEW endowment in adversely turbulent environments (Dou et al., 2019;
Gomez-Mejia et al., 2007; Gunter, 2017).
In one aspect, capital flight can be achieved at a lower cost against adverse domestic investment
climate that caused failure of family businesses and associated potential loss of SEW. The essence of
capital flight is that family businesses can place their assets beyond the reach of domestic regulation as a

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response to political risks and economic uncertainties (Pradhan and Hiremath, 2020). Capital flight is
appealing in reducing adverse impact of domestic uncertainties for family businesses (Hess, 2016). In
other aspects, capital flight from emerging markets offers an opportunity for international portfolios of
financial assets, which can lead to risk reduction for family businesses. In past decades, China experienced
improved economic and political stability, higher return of investment and yet capital flight accelerated
(Gunter, 2017). Explanations lie in the unusual pattern of transaction costs, particularly the high level of
financial transaction costs in China‟s financial markets, and long-term discrimination in favor of foreign
investors (Sicular, 1998). It is highly possible that family firms would take capital flight as a defensive
approach against domestic adverse investment climate or discriminatory treatment. Furthermore,
emigration motivated by the desire to secure better educational opportunities and offer high-quality life in
western countries for the next generations is another important reason for capital flight of family
businesses. China has experienced a large and growing population of young students studying abroad in
past decades. Family-centered long-term orientation is a primary reference point in decision making in
family businesses (Liang et al., 2014). Family firms usually pursue family-centered goals and apply
family-based resources in their strategic initiatives to achieve such goals in comparison to nonfamily firms
(Bennedsen et al., 2010; Chua et al., 1999; Fang et al., 2018). Family involvement in business may
encourage the desire to preserve long-term SEW, such as passing the business to the next generation to
attain lasting prosperity of the family (Liang et al., 2014). From this perspective, firms with highly family
involvement would have a higher tendency to capital flight to support their family members‟ emigration or
overseas education.

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In traditional wisdom, family businesses will establish the long-lasting prosperity of their family
based on long-term success of the family business, while in some cases family prosperity is separated from
the continuity of family business. Family may have to place the continuity of the family higher than the
success of the family business where private property is not well protected by the institutional system.
Capital flight is part of the long-term effort to move “their children, their money and themselves” out of
China for many Chinese families (Browne, 2014; Gunter, 2017; Shi and Ran, 2011). Among these rich
owning families, the achievement of safety of family wealth and intergenerational prosperity by way of
migration and capital flight coincide with their desire to preserve SEW. In such cases, capital flight may be
perceived as a useful strategy for preserving long-term family prosperity. Therefore, it is hypothesized as
follows:
Hypothesis 1: There is a positive relationship between family involvement and capital flight.
2.2 The moderating effect of local connection
Following Hirschman‟s conceptional framework (Hirschman, 1970), as a response to adverse
investment climate or discriminatory treatment, family business can choose to exit from their homeland or
apply voice tactics to feed back and support changes in some desired way (Hess, 2016). First, an aggrieved
owning family may choose to exit a negative situation in the form of capital flight. The exit approach could
result in loss of business opportunities in domestic markets and loss of SEW associated with their local
reputation and social networks. Alternatively, an owning family business can express their worries,
dissatisfaction, and proposals to change adverse investment climate and unfair treatment. Such expression
of voice is usually an attempt to compel local government to improve investment climate and solve

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internal discontent (Hess, 2016). The costs of exit and possibility of voice expression are determinants in
the owning family‟s choice between the exit approach and the voice approach.
Local connection, which is the involvement of an economic actor in a geographically bonded social
network (Baù et al., 2018), plays a crucial role in family firms‟ behavior (Bird and Wennberg, 2014;
Zellweger et al., 2013). The majority of this stream of literature argues that a firm highly embedded in
local social networks and local communities is more likely to preserve durable local relationships and
motivate their local capital investment (Le Breton-Miller and Miller, 2009; Pittino et al., 2016). The local
connection is particular important for family businesses because it largely shapes the institutional setting in
which family businesses operate (Granovetter, 1973; Hess, 2004) and provides fundamental support for
their productivity and competitiveness (Cooke, 2007; Davidsson and Wiklund, 2006). Those family
businesses with higher local connection are more likely to maintain a good relationship with local
customers and suppliers (e.g., Cooke, 2007) and facilitate access to localized knowledge and other
productive resources rooted in local social networks and local community (Baù et al., 2018). And local
institutions and linkages may favor the establishment of legitimacy and capabilities (Baù et al., 2018).
Traditional wisdom argues that increasing local connections should motivate family businesses to be more
sensitive to the preservation of family SEW, while the pursuit of SEW should lead family businesses to
future-oriented financial strategies and the focus on businesses‟ long-term continuity in the community
(Baù et al., 2018; Le Breton-Miller and Miller, 2009; Zahra et al., 2004). Various affective utilities rooted
in local social networks, including perpetuation of a positive family image and reputation, have been
mentioned as content of SEW (e.g., Berrone et al., 2012; Gomez-Mejia et al., 2010). Such external sources
of SEW, such as family reputation, are well associated with the owning family‟s local connection. High

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level of local connection may increase the cost of capital flight. After all, such SEW rooted in local social
networks should not be easily preserved if the owning family has shifted the majority of their family
business abroad or even emigrated from their homeland.
So, in this context, family businesses would be less likely to capital flight to foreign countries. As
such, based on traditional wisdom and previous literature, we contend that as local connections increase,
the positive association between family involvement and capital flight of family businesses should be
weakened. Formally:
Hypothesis 2: Local connection weakens the positive association between family involvement and
capital flight in family firms.
2.3 The moderating effect of political connection
The influence of political connection on business strategy is prevalent worldwide in emerging
countries and developed countries (Ding et al., 2014; Faccio, 2006; Wu et al., 2018). Less is known about
the effect of political connection on the relationship between family involvement and capital flight in
family firms, which remain underexplored in existing literature.
Owing to the dominance of government in resource allocation and the imperfections of price
mechanisms, the legal environment, and the credit system etc., interpersonal relationships with local
government and local officials are critical social capital for owning family in emerging markets. In the
opening and reforming process, successful owning family develop dense personal connections to local
officials and further are politically absorbed in the local political system, such as the Chinese People‟s
Congress (CPC) system and the Chinese People's Political Consultative Conference (CPPCC) system.
Political connection offers them privileged access to public resources and protection from official scrutiny

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(Hess, 2016). Thus, politically connected family businesses will be less affected by negative sides of
domestic investment climate and are less likely to be discriminatorily treated. In addition, political
reputation is a core part of intangible property for the lasting prosperity of family businesses. The damage
to political connection may impede political legitimacy of family businesses in the local community and
finally hurt their SEW. The perspective of government about capital flight is almost totally negative. The
involvement, at least in public, in capital flight may bring potential threats to the image of a family
business. Thus, political connection increases the opportunity cost of the exit approach in the form of
capital flight. The substantial losses in financial benefits and family SEW that increased by the existence of
political connection should convince an owning family to consider the alternative voice approach (Hess,
2016). The needs of aversion to potential loss of SEW may let a family business to refrain from capital
flight.
In another aspect, political connection offers more chance for an owning family to engage in the voice
approach rather than the exit approach in the form of capital flight. The information transfer effects of
political connections on mitigating policy uncertainty (Liu et al., 2021) would alleviate a family business‟s
worries about policy adjustment and uncertainty and let them to refrain from capital flight. The previous
literature on the determinants of capital flight shows that policy uncertainty, along with macroeconomic
instability, is one of the most important determining factors of capital flight (Lensink, 2001; Lensink et al.,
2000). Facing serious policy uncertainty, a family will be uncertain about the safety of their business in the
future. Such uncertainty will stimulate them to withdraw their domestic investment and leading to capital
outflow from homeland (Lensink, 2001; Lensink et al., 2000). Political connection helps family businesses
to get policy information before their enforcement, particularly details about timing and specific details of

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policy adjustment (Liu et al., 2021). Then such an information transfer effect will largely eliminate the
negative impact of policy uncertainty. Furthermore, a politically connected family business is more likely
to participate in the process of shaping policy adjustment (Liu et al., 2021). These politically connected
family businesses have the chance to communicate face-to-face with policymakers (Hojnacki and Kimball,
2001) and convey their own ideas for policy adjustment. Their advantage of being familiar with
policymakers‟ preferences (Austen-Smith, 1995) also helps them to judge and predict adjustment details.
In this way, political connection can largely mitigate the negative impact of policy uncertainty in emerging
markets, which is one of the most important determinants of capital flight. Thus, it is hypothesized that:
Hypothesis 3: Political connection weakens the positive effect of family involvement and capital
flight in family firms.
2.4 The macro business environment and context-dependence of moderating effects
Following the idea of Hirschman (1970), the sense of loyalty can significantly raise the perceived cost
of the exit approach and lead family businesses to the choice of the voice approach against adverse
economic, political uncertainties (Hess, 2016). The loyalty of family businesses to their homeland largely
lies in their faith in the domestic business environment, economic prosperity, and political stability etc. The
macro business environment, referring to the combination of institutions and factors that influence
business operational situations, offers a general context for strategic decisions of family firms. Clean,
efficient and stable public governance should be a necessary element of the high-quality business
environment (Baliamoune-Lutz and Ndikumana, 2008). Such a high-quality business environment should
be tightly associated with political stability and political efficacy, which should enhance the loyalty of
family businesses to the local community and the local political system. That is, a high-quality business

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environment may enhance the loyalty of family firms and in turn encourage economic actors more deeply
embedded into the local political system, particularly if local government is open to feedback from private
sectors and willing to reform in some desired way. Thus, the moderating effect of social connection, either
local connection or political connection, on the relationship between family involvement and capital flight
should be largely determined by the loyalty of family businesses to the domestic business environment.
The strategic thinking and motivation of capital flight at firm level is usually influenced by the macro
business environment. That is, the moderating effect of social connections should be context-dependent on
the macro business environment.
The implications of local connection for capital flight also vary according to the environmental
context in which a family business is located. Baù et al. (2018) discussed the context-dependence of local
embeddedness and argued that the moderating effect of local embeddedness on the relationship between
family involvement and economic growth is dependent on rural or urban contexts. That is, local connection
does not necessarily lead family businesses to lock-in local community. The premise of the traditional
argument that the increasing of local connection should motivate family businesses to seek future-oriented
business growth in the local community is that the owning family will lay their long-lasting prosperity,
which is a core part of family SEW, on long-term success of the family business in domestic. This is the
case in high-quality business environments, if a family firm largely depends on what the local community
offers in terms of business opportunities and business convenience (Dicken and Malmberg, 2001), local
connection should be helpful to prevent capital flight. In high-quality business environments, local
connection provides more competitive advantages in supplier chains, localized knowledge, and local
resources for the family business. The relatively higher return of investment in high-quality business

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environments will encourage the family business to maintain their loyalty and keep their capital in the
local business system. Then the peer effect or network effect based on local social networks would, in turn,
enhance individuals‟ loyalty and inhibit the inclination of capital flight in family firms. The involvement in
capital flight may cause higher cost of SEW when the popular attitude of members of the local community
is negative regarding capital flight from high-quality business environments.
In comparison, low-quality business environments may lead to deterioration of the loyalty of family
businesses and finally lead to family firms‟ capital flight from emerging markets. Family businesses should
struggle with opaque and even unfair institutional environments and deal with risks originating from
political and policy uncertainties. Osei-Assibey et al. (2018) confirmed the effect of corruption and
institutional governance indicators on capital flight in Sub-Saharan Africa. In such cases where owning
family‟s continuity is no longer dependent on the longevity of their family business rooted in local
communities, local connection should not necessarily weaken motivations for capital flight. Then, owning
family may have to take capital flight as a strategy for continuity of family success. Local connections,
along with the support of informal and trust-based interactions sustained by family members‟ personal
commitment and personalized business relationships (Baù et al., 2018; Carney, 2005; Carney and
Gedajlovic, 2010), may foster capital flight of family businesses in such contexts.
One important feature of local connection, its peer effect rooted in local network interactions, is
usually ignored when discussing the effect of local connection on the relationship between family
involvement and capital flight in family firms. Hiwatari (2016) revealed that the peer effect originating
from local social networks positively influences household migration decisions. In emerging markets, such
as China, capital flight of family businesses is more or less linked with immigration intention (Gunter,

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2017). The increasing literature of migration networks suggests linkage with migration networks are
expected to increase migration likelihood and lower the cost and risks of movement (Massey et al., 1993;
Mckenzie and Rapoport, 2007; Munshi, 2003). Family-based and community-based networks are
important factors in the migration decision (Angelucci et al., 2009; Winters et al., 2001). The direction of
the peer effect on the relationship between family involvement and capital flight is largely dependent on
the attitude of the majority of local networks or the local community. Peer experience about capital flight
can offer valuable information for following peers about the economic opportunities abroad and the
operating references. Then a more context-dependent picture about how local connection influences the
relationship between family involvement and capital flight may emerge if we carefully explore local
attitudes to capital flight. In some cases, capital flight is perceived as a useful method of portfolio
diversification (Le and Zak, 2006). China‟s mainland is the third immigration exporting country in the
world, according to Annual Report on Chinese International Migration (2020). Then both migration and
capital flight are not always bad choices for local business owners under low-quality business
environments. In such contexts, it is reasonable for those business families and their stakeholders
struggling with negative institutions to move part of their capital abroad to preserve family capital for
following generations or to offer intergenerational career success abroad for children. Then the
involvement in capital flight may be acceptable and would not damage their SEW and connection with the
local community. Actually, family-based and community-based networks may provide some assistance for
migration and capital flight (Angelucci et al., 2009; Hiwatari, 2016; Winters et al., 2001). Accordingly, it is
hypothesized that:

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Hypothesis 4: Local connection may enhance the positive relationship between family involvement
and capital flight in low-quality business environments and weaken such relationships between family
involvement and capital flight in high-quality business environments.
Political connection is one of the most important types of social capital for family businesses in
emerging markets. And its function in high-quality business environments and low-quality business
environments is differentiated. In high-quality business environments, political connection offers more
chances for family businesses to engage in local policy-making processes. One important feature of
high-quality business environments is transparent and inclusive policy-making processes. Local
government should be open to listening to feedback from family businesses and show their willingness and
determination to solve repairable lapses by performing reforms to improve the business environment. Thus,
family businesses are inclined to engage in the local political agenda and to try to feed back their
complaints on some undesirable parts of the business environment, rather than confronting it. Intimate
interaction between family businesses and the local political system facilitates the voice approach for
family businesses when they are facing adverse impact of some industrial policy. Then, the choice of the
exit approach, especially in terms of capital flight, is not so appealing in high-quality business
environments. The moderating effect of political connection on the relationship between family
involvement and capital flight should be enhanced under high-quality business environments.
On the other hand, low-quality business environments are usually associated with political instability
and political risk. A transparent and inclusive policy-making process does not necessarily exist or work
well in low-quality business environments. The feasibility of shaping policymaking through formal
political procedures or clear political agendas for politically connected family businesses is relatively low

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compared with the situation in high-quality business environments. Family businesses may enhance their
connections with local officials to secure their benefits, which may partly enhance rent-seeking activities.
The potential involvement in rent-seeking activities increases political risks for family businesses. It is
documented that corruption and relevant activities is one of the important causes of capital flight in China
(Gunter, 2017). Thus the function of political connection in encouraging family businesses to take the
voice approach against adverse political instability or economic uncertainties is undermined in low-quality
business environments and increase, in turn, the likelihood of capital flight. In addition, negative business
performance and inadequate business opportunity will weaken the loyalty of family businesses to local
communities and may lead them to decouple from the local business system. Then the importance of
political connection may not be so pronounced. Then the moderating effect of political connection should
not be so pronounced in low-quality environments than in high-quality environments. Accordingly, it is
hypothesized that:
Hypothesis 5: The weakening effect of political connection on the positive relationship between
family involvement and capital flight is more pronounced in high-quality business environments.
3. Research design
3.1 Samples
The data used in this study are based on the 12th China Private Enterprise Survey (CPES) in 2016, which
is a part of nationwide serial surveys on Chinese private entrepreneurs jointly conducted by the All-China
Federation of Industry and Commerce (ACFIC), the State Administration for Industry and Commerce
(SAIC) and the Chinese Academy of Social Science (CASS) since the beginning of the 1990s. Each wave

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of surveys covers about 0.055% of private firms on the Chinese mainland and 31 provincial regions,
including 22 provinces, 4 municipalities directly under the supervision of the central government and 5
minority autonomous regions.
The majority of private firms in China are characterized by their family ownership and their nature as
small businesses. In the 12th CPES , the average employee size of sampled enterprises is about 215
persons, and the annual revenue of these enterprises is only about 140.19 million RMB. The average share
of family ownership is 79.9%, and about 58.4% of sampled firms are entirely held by an owning family,
while 95.8% of sampled firms are controlled by over 50% family ownership. It is well accepted that the
agency problem of corporate management is not a prominent issue in these family-owned small businesses
(Du et al., 2015). Hence, our focus on family-controlled small businesses allows us to intensively explore
the effect of SEWs to foreign investment of family businesses by controlling the disturbs of agency
problem. The survey contains 8111 initial observations. After deleting those observations with missing data,
this study obtains the final sample of 2711 observations.
3.2 Variables
Capital flight: The measuring of capital flight is usually discussed at macro-level, mainly including
the residual method (World Bank, 1985), the trade misinvoicing method (Bhagwati et al., 1974), the
Dooley method (Dooley, 1986) and the hot money method (Cuddington, 1987, 1986). This study is
designed to explore the relationship between family involvement and capital flight in family firms, while
the measurement of capital flight is measured at firm level. Although capital flight is complexity and
concealment (Goldsmith, 2020; Wong, 2021), previous studies have revealed that important channels for
capital flight involve participation in immigrant investor programs (Gunter, 2017; Hess, 2016), purchasing

20
real estate abroad (Alstadsaeter et al., 2018; Ndiaye and Siri, 2016), sending children abroad
(Colic-Peisker and Deng, 2019; Gunter, 2017) and so on. Considering that household financial outflows
are hard to quantify (Wong, 2021), thus we restrict our attention to the important channels for capital flight:
immigration and foreign real estate. In CPES, family business owners were asked to report the volume of
their foreign investment in 2015 and illustrate the usage destination of their foreign investments in this
survey. The classification of usage destination of foreign investments in the surveys is as follows: (1)
building overseas plants; (2) establishing overseas marketing branches; (3) merger, acquisition or
investment in foreign enterprises; (4) investing in real estate property in foreign countries; (5) purchasing
overseas natural resources, energy resources and land; (6) establishing overseas research and development
branches; (7) investment immigration for business owner or family members; (8) others. OFDI and capital
flight are identified by their distinction of investment purposes. The dummy variable of capital flight is
constructed and takes the value 1 if the usage destination of foreign investment belongs to (4) investing in
real estate property in foreign countries or (7) investment immigration for business owner or family
members, and is equal to 0 otherwise. Another dummy variable of OFDI is constructed and takes the value
1 if the usage destination of foreign investment belongs to (1), (2), (3), (5), (6), (8), and is equal to 0
otherwise.
Family involvement: Measuring the influence of the owning family on a family business is always
an important task in family business research (Chrisman et al., 2010). Family involvement, particularly the
owning family‟s intention of being involved in the family business, is a source of familiness (Barros et al.,
2017; Frank et al., 2010; Habbershon and Williams, 1999) and SEW (Berrone et al., 2012; Gomez-Mejia et
al., 2011). Based on CPES, this measurement of family involvement about involvement in family

21
businesses is constructed on the basis of the following three items: (1) the owning family should retain
over 50% ownership of the family firm; (2) the strategic decisions of family businesses should be made by
family members; (3) the key positions should be occupied by family members. All items are measured by a
5-point Likert scale anchored between “strongly disagree” and “strongly agree”.
Local connection: This variable is measured by counting the number of local associations
participated in by the firm or the private owner. Such local associations include Local/Region based
associations, Private Shareholder Associations, MBA and other alumni Associations, Charity Associations,
Interest-Based Group/Associations etc. A cardinal variable is therefore constructed.
Political connection: In CPES, business owners are asked to report (1) whether he/she currently
serves or formerly served as a member of the Chinese People‟s Congress (CPC), and the highest ranks of
CPC that he/she served (national, provincial, prefectural, county); (2) whether he/she currently serves or
formerly served as a member of the Chinese People‟s Political Consultative Conference (CPPCC), and the
highest ranks of CPPCC that he/she served (national, provincial, prefectural, county). An ordinal variable
is constructed based on the highest rank of CPC and CPPCC the family business owner served.
Business environment: In the survey, the domestic business environment is evaluated by 14 question
items covering administrative approval, honesty and efficiency of public officials, fair enforcement of laws,
intellectual property protection, personal security, protection of property, infrastructure, business service in
markets, interference from local government, financing from banks and private sources, availability of
skilled workers. All items are measured by a 5-point Likert scale anchored between “strongly dissatisfied”
and “strongly satisfied”. The mean of these 14 question items is used to measure family business owners‟

22
perception of the domestic environment. We construct two subsamples with high-quality and low-quality
business environments based on the sample mean of business environment.
Control variables:
This study used a number of control variables of firm characteristics. It is reasonable to assume that
domestic investment is tightly connected with capital flight at firm-level investment strategy. So, domestic
investment, in the term of the logarithm of domestic investment in 2015, is controlled in this study. And
family influence and control over family businesses, along with structure of SEW, may vary with firm size
(Gomez-Mejia et al., 2011; Pukall and Calabrò, 2014). So, this study also controlled for firm size,
measured by the logarithm of employee number (Cesinger et al., 2016). Profitable family firms may
exhibit higher inclination for internationalization (Acedo and Casillas, 2005). Outward foreign investment
is tightly connected with financial status, such as its profitability. Consistent with the literature, this study
adopts the logarithm of profit as a control variable. The industry effect of internationalization, particularly
between the manufacturing sector and other sectors, is often mentioned in previous research (e.g.,
Carpenter and Fredrickson, 2001; Yang et al., 2018). This study used a dummy variable to control for
industry effect of manufacturing. Regional heterogeneity is considered as previous research, dummy
variables are constructed to control regional effect of central (Regional Dummy 1), and western China
(Regional Dummy 2), with eastern China as the default. In analyses not reported here, this study used more
fine-grained industry controls and region controls, which did not affect the results and were omitted for
parsimony (Bernerth and Aguinis, 2016; Yang et al., 2018).
3.3 Empirical method

23
To investigate the hypotheses proposed, our analysis compares the probability of capital flight varying
different levels of family involvement under varying moderating contexts and macro business contexts.
Considering the dependent variable capital flight is measured by the dummy variable, Probit model is used
to test basic effects of family involvement and moderating effects of local connection and political
connection based on a cross-sectional dataset of CPES 2016. Our detailed models are as follows:
    
       
Here, CF and FI represent the dependent and independent variable of capital flight and family
involvement, respectively. INT represents the moderating variables such as local connection and political
connection, which are used one at a time in the Eq. (2) to assess their moderating effects. Controls
represents a set of control variables, including firm profitability, domestic investment, firm size, regional
dummies, and manufacturer dummy. i indexes firms and  is an error term. Eq. (1) is the baseline model
and explores the relationship between family involvement and capital flight (H1), and Eq. (2) examines the
potential moderating effect of social connections (H2 and H3). To test H4 and H5, we repeat our regression
analysis of models (1) to (2) based on sub-samples divided according to the quality of the macro business
environment.
In robustness tests, Propensity Score Matching (PSM) analysis is used to confirm the validity of basic
effects and moderating effects after controlling the potential self-selection problem and endogeneity. As a
comparison, this study parallelly test the effect of family involvement on OFDI and such moderating
effects on the relationship between family involvement and OFDI using the same empirical methods. Then

24
this study can explore more insights about capital flight in family firms, taking their effect on OFDI as a
reference point.
4. Empirical results
Table 1 reports descriptive statistics and their correlations for the variables of interest. About 3% of firms
self-reported their foreign investment is involved with activities of capital flight, and about 5% of firms
reported their OFDI in 2015. It appears that the mean scores of family involvement (5-point Likert scale) is
3.39 with standard deviation of 1.16; the family intention of being involved in the family business is
relatively high.
[Insert Table 1 about here]
Table 2 reports the basic results about the relationship between family involvement and capital flight
that test H1. As shown in Table 2, in support of H1, family involvement has a positive effect on capital
flight (Model 1, B=0.14, p<0.01). Table 2 also reports the moderating effect of local connection and
political connection that test H2 and H3. As shown in Table 2, the moderating effect of local connection is
insignificant. So our H2 is not supported here. Our further studies in Tables 3 and 4 suggest that such
moderating effect should be context-dependent on the business environment (see more details in Table 3).
Supporting our H3, our result shows that political connection negatively moderates the relationship
between family involvement and capital flight (Model 3, B=-0.26, p<0.01). Specifically, the interaction
term that tests H3 is depicted in Fig. 1.

25
[Insert Table 2 about here]
[Insert Fig. 1 about here]
Table 3 relatively reports the moderating effect of social connections on the relationship between
family involvement and capital flight in high-quality and low-quality business environments. As shown in
Model 5, the effect of family involvement is not significant in high-quality business environments and its
effect in low-quality business environments turns out to be significantly positive as shown in Model 6
(B=0.23, p<0.01). That is, macro business environments may directly moderate the effect of family
involvement on capital flight. More interestingly, the interaction item between family involvement and
local connection is significantly negative (Model 7, B=-0.25, p<0.01) in high-quality business
environments, and such an interaction item turns out to be significantly positive in low-quality business
environments (Model 8, B=0.19, p<0.05). The results of Model 7 and Model 8, supporting our H4, confirm
that the moderating effect of local connection is context-dependent on the macro business environment
(see Fig. 2A and Fig. 2B).
[Insert Fig. 2A and Fig. 2B about here]
Models 9 and 10 examine whether the moderating effect of political connection is context-dependent
on the macro business environment. In high-quality business environments, the interaction item between
family involvement and political connection is negative and significant (Model 9, B=-0.50, p<0.001; also
see Fig. 3) and such an interaction item is not significant in low-quality business environments (Model 10,

26
B=-0.15, p>0.1). These results support our H5 predicting the moderating effect of political connection is
context-dependent on the macro business environment. Accordingly, our arguments about the moderating
effects of both local connection and political connection on the relationship between family involvement
and capital flight are context-dependent on the macro business environment.
[Insert Table 3 about here]
[Insert Fig. 3 about here]
5. Robustness test and comparison with family business internationalization
First, we test the robustness of measurement of the independent variable. The family involvement actually
reflects the intention of the owning family to be involved in the family business. Table 4 reports the basic
effect of family control and capital flight. Here, family control is measured by a dummy variable that is
coded as 1 if the family member controls at least a 50% share and makes the major decisions in the family
business, otherwise 0. The results in Table 5 show the direct effect of family control is significantly
positive (Model 13, B=0.25, p<0.05), the moderating effect of local connection is insignificant (Model 14,
p>0.10), and the moderating effect of political connection is significantly negative (Model 15, B=-0.68,
p<0.05). These results are consistent with Table 2, indicating our empirical is robust.
[Insert Table 4 about here]

27
Second, we examine the robustness of the moderating effect of social connections after controlling
sample selection bias. This study might be vulnerable to selection bias of social selections. Indeed, the
sample group with a high extent of social connections may have very different characteristics in terms of
firm size, revenue, diversification, geographic distribution, and other unobservable characteristics,
compared to the sample group with a low extent of social connections. Our study adopts Propensity Score
Matching method (PSM) to control sample bias. To begin, we apply a self-selection model in which certain
variables such as profitability, firm size, and education level are used to predict the probability of whether
a family firm is sufficiently connected with a local community or government (dummy variable is coded 1).
We then calculate the propensity value of either local connection or political connection and distinguish
treatment and control groups with the nearest neighbor matching method. Tables 5 and 6 report the balance
diagnostics results for controlling selection bias of political connection and local connection, respectively.
Both tables show that the biases for all covariates have actually reduced to 6% or below after matching and
the means of all covariates between the treatment group and the control group in the matched sample are
not statistically significant, indicating that the PSM effect is applicable. As shown in Table 7, the effect of
family involvement on capital flight is significantly positive (Model 20, B=0.27, p<0.05) only in the
control group (political connection=0) after controlling selection bias. The effect of family involvement on
capital flight is not significant both in the treatment group (local connection=1) and the control group
(local connection=0). These results are also consistent with those in Table 2.
[Insert Tables 5, 6 and 7 about here]

28
Third, we further examine the context-dependence of moderating effects of political connection and
local connection. Table 8 confirms the existence of context-dependence of these moderating effects.
Models 21 and 22 show the moderating effect of local connection is significantly positive in low-quality
business environments (B=0.20, p<0.05) and significantly negative in high-quality business environments
(B=-0.22, p<0.05) after control sample bias of local connection. Models 23 and 24 show the moderating
effect of political connection is significantly negative in high-quality business environments (B= -0.51,
p<0.01) and insignificant in low-quality business environments after control sample bias of political
connection. These results are also consistent with those of Table 3. Overall, based on PSM analysis, we
confirm that our empirical results are robust even after controlling for selection biases.
[Insert Table 8 about here]
As a comparison, we further explore more insights about family business internationalization by
examining the effect of family involvement on OFDI. Table 9 shows a significant and negative effect of
family involvement on OFDI at firm level (Model 25, B=-0.20, p<0.001). These results together support
our argument that the owning family may hold divergent attitudes to capital flight and OFDI. Our result is
aligned with the view in previous literature that family firms are often risk-averse and reluctant to expand
beyond domestic boundaries (Banalieva and Eddleston, 2011; Boellis et al., 2016; Gomez-Mejia et al.,
2010), and contribute to the literature by providing insight that family firms may be interested in capital
flight and taking it as a preventative way to preserve SEW.

29
Table 9 also reports the moderating effect of local connection and political connection. Interestingly,
our result confirms local connection should enhance the negative effect of family involvement on OFDI
(Model 26, B=-0.08, p<0.05). This may be because those family businesses with higher local connection
can obtain more business opportunities and are more willing to invest in their familiar domestic markets.
In addition, the moderating effect of political connection is not so significant (Model 27, B=-0.10, p<0.1)
in the case of the relationship between family involvement and OFDI.
[Insert Table 9 about here]
Table 10 reports the moderating effect of social connections on the relationship between family
involvement and OFDI in high-quality and low-quality business environments. The interaction item
between family involvement and local connection is insignificant (Model 31, B=-0.07, p>0.1) in
high-quality business environments, and such an interaction item turns out to be significantly negative in
low-quality business environments (Model 32, B=-0.15, p<0.01). Models 31 and 32 show that the
enhancing effect of the local connection on the relationship between family involvement and OFDI is more
pronounced in low-quality business environments. On the one hand, poor business environments will
undermine the willingness of family businesses to continue operations. To avoid the loss of SEW, family
business owners will adopt a wait-and-see attitude towards foreign investment strategies against political
and economic uncertainties in the domestic market, and are more likely to resort to capital flight. On the
other hand, in low-quality business environments, the government usually directly and indirectly imposes
institutional constraints on OFDI (Luo et al., 2019; Witt and Lewin, 2007) and encourages companies to

30
invest in the domestic market. Such a macro business environment not only reduces the local network‟s
support for internationalization but may also intensify the lock-in effect of local connection, which means
family firms with high local connection are more likely to be locked into the focal region. From the above
perspective, local connection may enhance the negative relationship between family involvement and
OFDI in low-quality business environments. In addition, the results of Model 21 and Model 22 confirm
there is no significant difference on the moderating effect of political connection under high-quality and
low-quality business environments. In our empirical results, the context-dependence of political
connection on business environment is not found.
[Insert Table 10 about here]
6. Further discussion
Our study contributes to existing literature by offering three insights about capital flight in family
businesses. First, our study explores the relationship between family involvement and capital flight at firm
level and contributes to the literature about capital flight and internationalization of family businesses. To
the best of our knowledge and the literature in hand, this study is one of very few, if not the first, to explore
the relationship between family involvement and capital flight at firm level. Most previous studies about
the capital flight phenomenon are conducted at macro level (Cheung et al., 2016; Gunter, 2017; Gunter,
2004; Ljungwall and Wang, 2008) and focus on issues about the sizes of capital flight and their growth in a
specific country (Asongu and Amankwah-Amoah, 2018; Fedderke and Liu, 2002; Gunter, 2017, 2004),
determinants at national level (Collier et al., 2001; Geda and Yimer, 2016; Hermes and Lensink, 1992;

31
Lensink et al., 2000; Ramiandrisoa and Rakotomanana, 2016), and their impact on macroeconomics
(Dachraoui et al., 2020; Ndikumana, 2015; Steiner et al., 2019). Our study provides quite detailed and
insightful micro foundations for explaining capital flight at firm level in the context of family businesses.
The picture at macro level and micro level about capital flight is interestingly divergent in many aspects.
For example, previous studies at macro level usually attribute the flow of capital flight to political
instability and political risk (Le and Zak, 2006; Lensink et al., 2000), while our study finds that political
connection in general is helpful to inhibit family business to engage in capital flight at firm level. More
detailed and context-relevant studies at micro level may substantially contribute to the stream of literature
about capital flight at macro level. In addition, our study enriches the stream of literature about
internationalization of family businesses. Traditional wisdoms about the internationalization of family
business intend to suggest that family firms are usually risk-averse and family involvement is negatively
associated with internationalization (Banalieva and Eddleston, 2011; Boellis et al., 2016; Gomez-Mejia et
al., 2010). However, when they are talking about internationalization, they usually talk about OFDI. Our
study suggests that owning families may hold divergent attitudes to OFDI and capital flight from the
perspective of SEW. We confirm that family involvement is positively associated with capital flight and
negatively associated with OFDI. Such divergence in family business is reasonable in the framework of
SEW. Being reluctant to be involved in international business expansion can be explained as preserving
SEW from partial loss of family control in the internationalization process. And capital flight is usually
associated with migration of family members and international assets allocation, which is helpful to
keeping family prosperity and then preserving the owning family‟s SEW.

32
Second, our study explores the moderating effect of local connection and political connection on the
relationship between family involvement and capital flight. Previous literature studies the effect of political
connection or local connection on OFDI or international business expansion (Gomez-Mejia et al., 2011,
2010). The existing studies generally intend to suggest positive effect of political connection on OFDI and
negative effect of local connection on OFDI. Our empirical results are aligned with these traditional
wisdoms. Less discussed in previous studies is their moderating effect on the relationship between family
involvement and capital flight from the perspective of SEW in the context of family business. Our study
finds a different picture about their effect on capital flight. The political connection negatively moderates
the positive relationship between family involvement and their direct effect on capital flight is also
negative. Our results, to a certain extent, coincide with common sense, after all capital flight, particularly
in the public view, is negative and usually associated with speculation, hot money and even illegal money
(Cheung et al., 2020; Gunter, 2017). Government should hold different attitudes to normal OFDI and
capital flight. And this study also finds that local connection does not significantly moderate the
relationship between family involvement and capital flight. Actually, such a moderating effect of local
connection is dependent on context, which we will discuss following. Our study about such moderating
effects contributes insights for the streams of literature about internationalization of family business and
capital flight.
Third, more interestingly, we find that the moderating effects of local connection and political
connection are context-dependent on the business environment. Social embeddedness should, at least in
part, be dependent on the institutional system at a higher level. Sociological studies suggest that there is
the possibility for economic actors to decouple with their existing institutional system or social network

33
and escape to another new system and social network. Our study finds the moderating effect of political
connection is negative and significant in high-quality business environments, and such moderating effect is
not significant in low-quality business environments. And our results also confirm that the moderating
effect of local connections is context-dependent on the macro business environment. In high-quality
business environments, the interaction item between family involvement and local connection is
significantly negative and such an interaction item is significantly positive in low-quality business
environments. In general, local connection is positive to capital flight in low-quality business
environments and negative in high-quality business environments. The context-dependence of such
moderating effects is full of implications for government. Generally speaking, it is important for
governments, particularly in emerging markets, to foster a better business environment for the sake of
preventing large scale capital flight.
This study is not without limitations. First, given the complexity of capital flight of family businesses,
this study is still an exploratory effort at firm-level. More efforts are required to shed light on the black box
of SEWs and their effects on capital flight of family businesses including mediating factors and
moderating effects. Second, this study focuses on a single country (China) and might reflect some
peculiarities of the national economic and social context. Generalization of the results of this study should
be cautious because the status of Chinese small family businesses may differ from that of family
businesses in western countries. Therefore, we suggest further studies to detect similarities and disparities
with family businesses from different cultural and economic contexts, and to explore cross-country
comparisons. We also propose to explore the intra-China heterogeneity on this issue in the future.

34
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45
Table 1. Summary Statistics and Pearson Correlation Matrix
Variables
Mean
SD
1
2
3
4
5
6
7
8
10
1.Capital Flight
0.03
0.18
1.00
2.OFDI
0.05
0.22
0.27*
1.00
3.Family Involvement
3.39
1.16
0.07*
-0.13*
1.00
4.Political Connection
0.39
0.57
-0.09*
0.11*
-0.12*
1.00
5.Local Connection
0.93
0.97
-0.02
0.08*
-0.13*
0.16*
1.00
6.Firm Profitability
3.89
2.68
-0.03
0.12*
-0.05*
0.32*
0.21*
1.00
7.Domestic Investment
3.92
3.05
-0.03
0.13*
-0.13*
0.32*
0.25*
0.52*
1.00
8.Firm Size
3.91
1.80
-0.09*
0.10*
-0.14*
0.45*
0.27*
0.62*
0.60*
1.00
9.Manufacturer
0.38
0.49
-0.09*
0.05*
0.01
0.10*
0.03
0.22*
0.22*
0.34*
1.00
Note. * p<0.05. Region here is treated as ordinal variable as east (=1), central (=2), western (=3), and they are treated as dummies in following
regressions.

46
Table 2. Basic Regression Results about Direct Effect and Moderating Effect of Political
Connection and Local Connection on Capital Flight
DV
Capital Flight
Model 1
Model 2
Model 3
Model 4
Family Involvement
0.14**
0.15**
0.09+
0.09+
(0.05)
(0.05)
(0.05)
(0.05)
Political Connection
-0.60***
-0.59***
-0.64***
-0.63***
(0.14)
(0.15)
(0.13)
(0.13)
Local Connection
-0.01
-0.04
-0.01
-0.04
(0.06)
(0.06)
(0.06)
(0.06)
Firm Profitability
0.04
0.04
0.04
0.04
(0.03)
(0.03)
(0.03)
(0.03)
Domestic Investment
0.04+
0.05+
0.05*
0.05*
(0.02)
(0.02)
(0.02)
(0.02)
Firm Size
-0.10*
-0.10*
-0.10*
-0.11*
(0.05)
(0.05)
(0.05)
(0.05)
Regional Dummy 1
-0.45***
-0.45***
-0.46***
-0.45***
(0.13)
(0.13)
(0.13)
(0.13)
Regional Dummy 2
-0.14
-0.15
-0.16
-0.17
(0.13)
(0.13)
(0.13)
(0.13)
Manufacturer
-0.62***
-0.63***
-0.61***
-0.62***
(0.14)
(0.14)
(0.14)
(0.14)
Family Involvement *
Local Connection (H2)
0.08
0.09
(0.06)
(0.06)
Family Involvement *
Political Connection (H3)
-0.26**
-0.29**
(0.09)
(0.09)
Constant
-1.84***
-1.84***
-1.67***
-1.65***
(0.24)
(0.23)
(0.24)
(0.23)
N
2711
2711
2711
2711
Chi2
50.346***
49.896***
61.566***
60.952***
Pseudo.R-Square
0.107
0.111
0.113
0.118
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001.

47
Table 3. The Context-dependence of Moderating Effects on the Macro Business Environment (Capital Flight)
DV
Capital Flight
Model 5
Model 6
Model 7
Model 8
Model 9
Model 10
Model 11
Model 12
HQBC
LQBC
HQBC
LQBC
HQBC
LQBC
HQBC
LQBC
Family Involvement
0.00
0.23**
-0.13
0.22**
-0.13*
0.20**
-0.22**
0.19*
(0.07)
(0.07)
(0.08)
(0.07)
(0.06)
(0.08)
(0.08)
(0.08)
Political Connection
-0.48+
-0.73***
-0.51+
-0.70***
-0.88**
-0.70***
-0.87**
-0.66***
(0.26)
(0.19)
(0.27)
(0.19)
(0.28)
(0.18)
(0.29)
(0.18)
Local Connection
-0.37**
0.10
-0.49***
0.02
-0.38**
0.10
-0.50***
0.02
(0.12)
(0.07)
(0.13)
(0.08)
(0.12)
(0.07)
(0.13)
(0.08)
Firm Profitability
0.01
0.08+
0.02
0.08+
0.01
0.08+
0.02
0.08+
(0.04)
(0.05)
(0.04)
(0.05)
(0.04)
(0.05)
(0.04)
(0.05)
Domestic Investment
-0.05
0.13***
-0.05
0.13***
-0.05
0.13***
-0.05
0.13***
(0.03)
(0.04)
(0.03)
(0.04)
(0.03)
(0.04)
(0.03)
(0.04)
Firm Size
0.05
-0.26***
0.05
-0.27***
0.06
-0.26***
0.06
-0.27***
(0.06)
(0.08)
(0.06)
(0.08)
(0.07)
(0.08)
(0.07)
(0.08)
Regional Dummy 1
-0.25
-0.72***
-0.28
-0.71**
-0.26
-0.72***
-0.28
-0.71**
(0.18)
(0.21)
(0.18)
(0.22)
(0.18)
(0.22)
(0.18)
(0.22)
Regional Dummy 2
-0.30
-0.11
-0.32
-0.14
-0.32
-0.12
-0.34
-0.15
(0.25)
(0.17)
(0.25)
(0.17)
(0.25)
(0.17)
(0.26)
(0.17)
Manufacturer
-0.70**
-0.56***
-0.69**
-0.58***
-0.71**
-0.56***
-0.69**
-0.58***
(0.25)
(0.17)
(0.25)
(0.17)
(0.27)
(0.17)
(0.26)
(0.17)
Family Involvement *
Local Connection (H2)
-0.25**
0.19*
-0.21*
0.20**
(0.08)
(0.07)
(0.08)
(0.07)
Family Involvement *
Political Connection (H3)
-0.50***
-0.15
-0.41***
-0.20
(0.11)
(0.17)
(0.11)
(0.16)
Constant
-1.36***
-2.18***
-0.94**
-2.05***
-0.93**
-2.10***
-0.63+
-1.94***
(0.31)
(0.36)
(0.35)
(0.33)
(0.30)
(0.36)
(0.36)
(0.34)
N
1300
1411
1300
1411
1300
1411
1300
1411
Chi2
33.481***
46.674***
48.967***
52.142***
45.256***
52.335***
53.954***
59.479***
Pseudo.R-Square
0.122
0.199
0.143
0.216
0.140
0.200
0.155
0.219
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001, HQBC : High-Quality Business Environments, LQBC : Low-Quality Business Environments.

48
Table 4. Robustness Test: Family Control and Capital Flight
DV
Capital Flight
Model 13
Model 14
Model 15
Model 16
Family Control
0.25*
0.24*
0.09
0.09
(0.10)
(0.11)
(0.13)
(0.13)
Political Connection
-0.61***
-0.61***
-0.68***
-0.68***
(0.14)
(0.14)
(0.14)
(0.14)
Local Connection
-0.01
-0.01
-0.01
-0.01
(0.06)
(0.06)
(0.06)
(0.06)
Firm Profitability
0.04
0.04
0.04
0.04
(0.03)
(0.03)
(0.03)
(0.03)
Domestic Investment
0.05*
0.05*
0.05*
0.05*
(0.02)
(0.02)
(0.02)
(0.02)
Firm Size
-0.10*
-0.10*
-0.10*
-0.10*
(0.05)
(0.05)
(0.05)
(0.05)
Regional Dummy 1
-0.46***
-0.47***
-0.47***
-0.47***
(0.13)
(0.13)
(0.13)
(0.13)
Regional Dummy 2
-0.17
-0.17
-0.19
-0.18
(0.13)
(0.13)
(0.13)
(0.13)
Manufacturer
-0.60***
-0.60***
-0.60***
-0.60***
(0.14)
(0.14)
(0.14)
(0.14)
Family Control*
Local Connection (H2)
-0.11
-0.09
(0.12)
(0.12)
Family Control*
Political Connection (H3)
-0.68*
-0.64*
(0.31)
(0.31)
Constant
-1.49***
-1.50***
-1.44***
-1.45***
(0.15)
(0.15)
(0.15)
(0.16)
N
2711
2711
2711
2711
Chi2
49.765***
54.458***
58.033***
61.340***
Pseudo.R-Square
0.102
0.104
0.108
0.108
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001.

49
Table 5. Balance Test of Controlling Selection Bias of Political Connection
Variable
Sample
Treated
Control
%bias
%reduct
t-test
Firm Profitability
Unmatched
4.86
3.15
67.2
97.5
17.07***
Matched
4.86
4.82
1.7
0.39
Domestic Investment
Unmatched
5.10
2.99
73.7
99.7
18.74***
Matched
5.10
5.11
-0.2
-0.06
Firm Size
Unmatched
4.87
3.18
107.1
97.3
26.78***
Matched
4.87
4.92
-2.9
-0.77
Political Status
Unmatched
6.02
4.36
84.7
95.3
21.27***
Matched
6.02
5.94
4.0
1.01
Economic Status
Unmatched
6.23
5.12
62.8
99.6
15.84***
Matched
6.23
6.23
-0.3
-0.06
Social Status
Unmatched
6.34
5.16
67.8
92.6
17.05***
Matched
6.34
6.25
5.0
1.26
Education
Unmatched
2.07
1.96
23.4
88.2
5.98***
Matched
2.07
2.08
-2.8
-0.63
Note. * p<0.05 ** p<0.01 *** p<0.001; %bia: the standardized percentage bias, %reduct: the
achieved percentage reduction in abs(bias).
Table 6. Balance Test of Controlling Selection Bias of Local Connection
Variable
Sample
Treated
Control
%bias
%reduct
t-test
Firm Profitability
Unmatched
4.36
3.12
47.3
87.4
11.86***
Matched
4.36
4.51
-6.0
-1.68
Domestic Investment
Unmatched
4.50
2.91
53.4
97.3
13.4***
Matched
4.50
4.54
-1.4
-0.41
Firm Size
Unmatched
4.33
3.21
63.9
90.7
16.22***
Matched
4.33
4.44
-6.0
-1.79
Political Status
Unmatched
5.32
4.66
31.0
93.1
7.75***
Matched
5.32
5.37
-2.1
-0.62
Economic Status
Unmatched
5.90
5.10
43.9
92.0
11.04***
Matched
5.90
5.96
-3.5
-1.05
Social Status
Unmatched
5.96
5.19
42.3
97.8
10.64***
Matched
5.96
5.94
0.9
0.28
Education
Unmatched
2.04
1.95
21.2
91.5
5.25***
Matched
2.04
2.03
1.8
0.51
Note. * p<0.05 ** p<0.01 *** p<0.001; %bia: the standardized percentage bias, %reduct: the
achieved percentage reduction in abs(bias).

50
Table 7. Robustness Test: Moderating Effect After Controlling Selection Bias of Political
Connection and Local Connection by PSM
DV
Capital Flight
Controlling Selection Bias of
Local Connection
Controlling Selection Bias of
Political Connection
Model 17
Model 18
Model 19
Model 20
LC=1
LC=0
PC=1
PC=0
Family Involvement
0.09
0.24+
0.05
0.27*
(0.07)
(0.14)
(0.09)
(0.12)
Political Connection
-0.45**
-0.69**
(0.14)
(0.23)
Local Connection
0.02
-0.16
(0.10)
(0.10)
Firm Profitability
0.06+
0.02
0.03
0.11+
(0.03)
(0.08)
(0.05)
(0.06)
Domestic Investment
0.05+
0.04
0.01
0.01
(0.03)
(0.07)
(0.04)
(0.05)
Firm Size
-0.08
-0.07
0.06
-0.18
(0.06)
(0.11)
(0.08)
(0.11)
Regional Dummy 1
-0.71**
-0.57+
-0.24
-0.52+
(0.24)
(0.31)
(0.27)
(0.28)
Regional Dummy 2
-0.07
-0.32
0.16
-0.35
(0.17)
(0.32)
(0.21)
(0.30)
Manufacturer
-0.67***
-0.32
-0.43*
-0.90**
(0.19)
(0.21)
(0.19)
(0.32)
Constant
-1.99***
-2.45***
-2.70***
-2.08***
(0.35)
(0.62)
(0.54)
(0.58)
N
1635
587
1132
555
Chi2
34.479***
24.733**
8.948
33.480***
Pseudo.R-Square
0.107
0.110
0.043
0.165
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001; PC : 1 represent high Political connection and 0 otherwise. LC :
1 represent high local connection and 0 otherwise.

51
Table 8. Robustness Test: The Context-dependence of Moderating Effects on the Macro
Business Environment after Controlling Selection Bias of Political Connection and Local
Connection by PSM
DV
Capital Flight
Controlling Selection Bias of
Local Connection
Controlling Selection Bias of
Political Connection
Model 21
Model 22
Model 23
Model 24
HQBC
LQBC
HQBC
LQBC
Family Involvement
-0.11
0.18*
-0.13
0.21*
(0.10)
(0.08)
(0.10)
(0.10)
Political Connection
-0.25
-0.63***
-0.79**
-0.69***
(0.22)
(0.17)
(0.28)
(0.18)
Local Connection
-0.33*
0.05
-0.35**
0.01
(0.13)
(0.09)
(0.12)
(0.09)
Firm Profitability
0.03
0.07
0.02
0.08
(0.06)
(0.05)
(0.07)
(0.06)
Domestic Investment
-0.06
0.11**
-0.08
0.08+
(0.04)
(0.04)
(0.05)
(0.04)
Firm Size
0.04
-0.19*
0.11
-0.09
(0.08)
(0.08)
(0.11)
(0.10)
Regional Dummy 1
-0.51+
-0.76**
0.10
-0.62*
(0.31)
(0.25)
(0.32)
(0.30)
Regional Dummy 2
-0.30
-0.11
0.04
-0.13
(0.30)
(0.19)
(0.37)
(0.23)
Manufacturer
-0.70*
-0.53**
-1.05**
-0.54**
(0.30)
(0.18)
(0.37)
(0.21)
Family Involvement *
Local Connection (H2)
-0.22*
0.20*
(0.09)
(0.08)
Family Involvement *
Political Connection (H3)
-0.51**
-0.17
(0.16)
(0.17)
Constant
-1.21**
-2.18***
-1.28*
-2.59***
(0.43)
(0.40)
(0.57)
(0.60)
N
1013
1209
726
961
Chi2
41.080***
48.343***
44.928***
38.696***
Pseudo.R-Square
0.125
0.205
0.207
0.163
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001; HQBC: High-Quality Business Environments, LQBC:
Low-Quality Business Environments.

52
Table 9. Basic Regression Results about Direct Effect and Moderating Effect of Political
connection and Local Connection on OFDI
DV
OFDI
Model 25
Model 26
Model 27
Model 28
Family Involvement
-0.20***
-0.19***
-0.19***
-0.18***
(0.04)
(0.04)
(0.04)
(0.04)
Political Connection
0.15*
0.14+
0.09
0.09
(0.07)
(0.08)
(0.09)
(0.09)
Local Connection
0.06
0.02
0.06
0.02
(0.04)
(0.05)
(0.04)
(0.05)
Firm Profitability
0.05*
0.05*
0.05*
0.05*
(0.02)
(0.02)
(0.02)
(0.02)
Domestic Investment
0.07***
0.07***
0.07***
0.07***
(0.02)
(0.02)
(0.02)
(0.02)
Firm Size
-0.06
-0.06
-0.06
-0.06
(0.04)
(0.04)
(0.04)
(0.04)
Regional Dummy 1
-0.16
-0.17
-0.16
-0.17
(0.11)
(0.11)
(0.11)
(0.11)
Regional Dummy 2
-0.33*
-0.32*
-0.33*
-0.32*
(0.13)
(0.13)
(0.13)
(0.13)
Manufacturer
0.04
0.05
0.04
0.05
(0.09)
(0.09)
(0.09)
(0.09)
Family Involvement *
Local Connection (H2)
-0.08*
-0.07*
(0.04)
(0.04)
Family Involvement *
Political Connection (H3)
-0.10+
-0.08
(0.06)
(0.06)
Constant
-1.32***
-1.34***
-1.35***
-1.37***
(0.17)
(0.18)
(0.18)
(0.19)
N
2711
2711
2711
2711
Chi2
80.502***
99.253***
94.007***
107.460***
Pseudo.R-Square
0.094
0.099
0.097
0.101
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001.

53
Table 10. The Context-dependence of Moderating Effects on the Macro Business Environment (OFDI)
DV
OFDI
Model 29
Model 30
Model 31
Model 32
Model 33
Model 34
Model 35
Model 36
HQBC
LQBC
HQBC
LQBC
HQBC
LQBC
HQBC
LQBC
Family Involvement
-0.28***
-0.13**
-0.29***
-0.09
-0.28***
-0.11*
-0.29***
-0.06
(0.05)
(0.05)
(0.05)
(0.05)
(0.05)
(0.05)
(0.05)
(0.06)
Political Connection
-0.06
0.30**
-0.07
0.30**
-0.15
0.23*
-0.15
0.23*
(0.13)
(0.10)
(0.13)
(0.10)
(0.16)
(0.11)
(0.16)
(0.11)
Local Connection
-0.13+
0.18**
-0.18*
0.12*
-0.13+
0.18**
-0.18*
0.13*
(0.07)
(0.06)
(0.09)
(0.06)
(0.07)
(0.06)
(0.09)
(0.06)
Firm Profitability
0.06+
0.05+
0.06+
0.05+
0.06+
0.05+
0.06+
0.05+
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
(0.03)
Domestic Investment
0.05+
0.09***
0.05+
0.09***
0.05+
0.09***
0.05+
0.09***
(0.03)
(0.02)
(0.03)
(0.03)
(0.03)
(0.02)
(0.03)
(0.02)
Firm Size
-0.00
-0.11*
-0.00
-0.11*
-0.00
-0.11*
-0.00
-0.11*
(0.06)
(0.05)
(0.06)
(0.06)
(0.06)
(0.05)
(0.06)
(0.06)
Regional Dummy 1
0.12
-0.45**
0.11
-0.46**
0.12
-0.44**
0.11
-0.45**
(0.15)
(0.16)
(0.15)
(0.17)
(0.15)
(0.16)
(0.15)
(0.17)
Regional Dummy 2
-0.23
-0.41*
-0.23
-0.37*
-0.22
-0.41*
-0.23
-0.38*
(0.22)
(0.17)
(0.22)
(0.17)
(0.22)
(0.17)
(0.22)
(0.17)
Manufacturer
0.07
0.00
0.09
0.02
0.07
0.00
0.08
0.01
(0.14)
(0.12)
(0.14)
(0.13)
(0.14)
(0.12)
(0.14)
(0.12)
Family Involvement *
Local Connection (H2)
-0.07
-0.15**
-0.06
-0.15**
(0.05)
(0.05)
(0.05)
(0.05)
Family Involvement *
Political Connection (H3)
-0.11
-0.13
-0.09
-0.12
(0.09)
(0.08)
(0.09)
(0.08)
Constant
-1.11***
-1.56***
-1.05***
-1.74***
-1.09***
-1.65***
-1.04***
-1.84***
(0.24)
(0.26)
(0.25)
(0.29)
(0.25)
(0.27)
(0.25)
(0.30)
N
1300
1411
1300
1411
1300
1411
1300
1411
Chi2
48.554***
77.648***
53.437***
100.783***
56.540***
89.445***
59.318***
108.738***
Pseudo.R-Square
0.116
0.127
0.118
0.143
0.118
0.132
0.120
0.148
Note. + p<0.10 * p<0.05 ** p<0.01 *** p<0.001; HQBC : High-Quality Business Environments, LQBC : Low-Quality Business Environments