The effect of formal and informal institution on outward foreign direct investment : does conventional theory hold for emering economies.

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1

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2 Acknowledgements

I would like to thank my supervisor dr. Ilir Haxhi for the pleasant corporation during the process of writing my thesis. I wish to thank Erik Dirksen for reading and grading my thesis together with Dr. Ilir Haxhi. Further, I would like to thank my family and friends for their support throughout my studies. Finally, I want to thank the University of Amsterdam for providing excellent study facilities in the past years.

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3 Abstract

While the financial crisis negatively affected the amount of Outward Foreign Direct Investment (OFDI) from developing countries, OFDI from emerging countries kept on rising in the past 5 years and became more important within the global economy. The Chinese OFDI rose from US $23 million in 2007 to US $52 million at the end of 2008 (UNCTAD, 2013), indicating a doubling of Chinese OFDI flows during the global financial crisis. Existing literature shows that developed countries are associated with certain institutional determinants of OFDI. It is however questionable to what extent these findings are applicable to predict the OFDI activities of emerging economies, and this has been given limited exposure in the existing literature so far. This thesis addresses this issue by comparing results of the conventional OFDI theory with new findings regarding the effects of institutional determinants on OFDI of an emerging economy. In particular, we will exemplify emerging economies with Chinese OFDI and developed economies with U.S.A. OFDI. This thesis aims to provide a comprehensive framework in which the relationships between institutional determinants and OFDI of both emerging economies (China) and developed economies (U.S.A.) are identified and explained. Furthermore, this thesis attempts to clarify whether, and which, institutional determinants of emerging economies are significantly different from those of developed economies. Findings show that Chinese OFDI is negatively influenced by cultural distance, institutional quality and uncertainty avoidance. It appeared for China that greater cultural distance will strengthen the negative effect of institutional quality on Chinese OFDI, and that China is attracted by host countries with a low score on voice and accountability. For the U.S.A., only the effect of market size on OFDI was found to be significant. Contributing to the existing literature, this thesis found that the OFDI of emerging economies is associated with similar culture, high trust and poor institutions, while the OFDI of developed economies is attracted purely by market size. From a managerial perspective, this research suggests that host country governments, which desire to receive FDI inflows from emerging economies such as China, should optimize their policy and institutional environment from an emerging economy (Chinese) perspective.

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4

List of abbreviations

BEA = Bureau of Economic Analysis FDI = Foreign Direct Investment

FGLS = Feasible Generalized Least Squares GDP = Gross Domestic Product

IMF = International Monetary Fund MNE = Multinational Enterprise

MOFCOM = Ministry of commerce of the people republic of China OECD = Organization for Economic Co-operation and Development OFDI = Outward Foreign Direct Investment

OLI = Ownership, Location, Internalization OLS = Ordinary Least Squares

SOE = State-Owned Enterprise

UNCTAD = United Nations Conference on Trade and Development U.S.A. = United States of America

VIF = Variance Inflating Factor

WGI = Worldwide Governance Indicator

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1. Introduction

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2. Literature review

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2.1 FDI theory

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2.2 FDI motives

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2.3 Institutions

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2.4 Determinants of FDI

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2.5 Institutional determinants

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3 Hypothesis development

This section is devoted to the formation of the hypotheses in this thesis. Relevant literature, theories and variables are reviewed, merged and transformed into hypotheses, which will address the relevant issues regarding this WKHVLV¶ topic.

General FDI theory and institutional determinants of OFDI are dominated by the perspective of developed economies (Morck et al, 2008; Filatotchev, Strange, Piesse, & Lien, 2007); it is questionable whether these results are applicable for developing economies as well. Conventional OFDI theory claims that OFDI is associated with host countries with high quality formal institutions (Globerman & Shapiro, 2002; Asiedu, 2006; Seyoum, 2009; Stein and Daude, 2001). Strong institutions reduce risk and the cost of doing business, and increase productivity and thus attract more FDI inflow. Blonigen (2005) states that OFDI activity is OHVVDWWUDFWLYHLQFDVHDFRXQWU\¶VSRRUOHJDOV\VWHPZLOOQRWSURSHUO\SURWHFWDILUP¶VDVVHWV and thus will increase the chance of expropriation.

This thesis tests whether the conventional theory regarding institutional determinants of OFDI will hold for emerging economies as well. We exemplify developed countries by using the U.S.A and emerging economies by using China. The U.S.A. symbolizes the classical example of capitalism and economic prosperity, while China is an emerging economy that still exhibits signs of communism. Although Chinese government involvement within economic policy is diminishing, nowadays they provide more leniency in an attempt to substantiate a competitive market rather than a politically driven economy (Child & Rodrigues, 2005). However, economic and OFDI activities still suffer from the communistic history (Aggerwal & Agmon, 1990). Where developing economies prefer to invest in countries with strong institutions, the 2007 United Nations report shows that China is a major capital provider for African countries (UNCTAD, 2007; Cheung et al, 2010). Africa is the third largest recipient of Chinese OFDI. These facts indicate that Chinese OFDI is associated with host countries which possess a weak institutional framework.

In the existing literature it is found that Chinese OFDI is attracted by political risk (Buckley et al, 2007). Kolstad & Wig (2012) claim that Chinese OFDI is attracted by natural resources in host countries with low quality institutions. Cheung et al (2010) found that law and order risk and corruption risk factors attract Chinese OFDI, while other risk factors deter Chinese investment. Cheung et al (2010) IXUWKHU GLVFXVV &KLQD¶V QRQ-interference policy, which separates business from politics. This Chinese policy is often criticized, as China

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sometimes enjoys economic benefits at the expense of human rights and democracy. Furthermore, Chinese OFDI is often influenced by political motives, whereas almost 70% of Chinese OFDI is from SOEs (Hurst, 2011). The SOEs have corporate management structures where the board of directors are members of the ruling party. Therefore, Chinese foreign direct investment decisions are influenced by governmental institutional pressures and objectives (Wang et al, 2012). Due to market imperfections Chinese SOEs were provided with access to funds below market rates, allowing them to invest in riskier and less institutional developed host countries (Ramasamy et al, 2012). Based on these findings, this thesis aims to research whether Chinese OFDI is associated with less qualitative formal institutions, rather than being associated with high qualitative formal institutional predicted by conventional theory. Institutional quality is represented by the average of six formal institutional indicators based on the findings of Kaufmann et al. (2004). We expect that conventional theory of OFDI will not hold for China, and that Chinese OFDI is associated with host countries with a qualitative weak formal institutional framework. Therefore, we propose:

Hypothesis 1: As opposed to conventional O F DI theory, the O F DI of emerging economies, exemplified by China, is associated with host countries having low quality institutions rather than high quality institutions.

Johanson and Vahlne (1977) found that firms gradually expand from familiar domestic markets to foreign markets that are more culturally and/or geographically distant. Conventional OFDI theory claims that cultural distance has a negative effect on OFDI flows (Dunning, 2008). Barkema et al (1996), Barkema & Vermeulen (1997) Brown et al (1989) and Tang (2012) claim that cultural distance increases FDI costs and thus reduces OFDI flows. They further state that cultural distance creates ambiguities in relationships that threaten the existence and performance of international joint ventures. Tihany et al (2005) state that cultural distance affects the ease of doing business. It causes misunderstandings and ambiguity when firms invest abroad. Cultural proximity reduces transaction costs and cause network effects and appears to be a significant factor in attracting FDI flows (Buckley et al, 2007).

Informal institutions comprise the unwritten rules that govern life, such as expected behavior, culture and code of conduct (North, 1991). These informal institutions affect OFDI

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flows. Chinese OFDI is associated with host countries which house more Chinese inhabitants and is influenced by the extent to which guanxi determines the way of doing business in a host country (Tong, 2003). Guanxi refers to informal relationships based on trust. This thesis aims to research whether Chinese OFDI is associated with host countries with similar informal institutions, rather than being associated with host countries with dissimilar informal institutions. We expect that China, in line with conventional theory, prefers to invest in host countries with similar informal institutions. We expect that China invests in countries with a small cultural distance. Therefore, we propose:

Hypothesis 2: In line with conventional theory we expect that the O F DI of emerging economies, exemplified by China, is associated with host countries with a small cultural distance, rather than countries with a large cultural distance to China.

China is lacking a developed legal system, but is still able to attract a lot of FDI. Informal institutions complement and compensate for the weak Chinese legal system. Networks of personal connections and interpersonal trust (guanxi) play a major role in facilitating FDI flows into China (Wang, 2000). Guanxi is a personal reciprocal relationship based on trust. Ramasamy et al (2012) claim that guanxi, trust and personal connections are not only strongly used in domestic markets, but also in international markets. In this thesis, aside from cultural distance, interpersonal trust is considered an important element of informal institutions. We assume that interpersonal trust is an important element of informal institution, ZKLFKLVQRWFRYHUHGE\WKHGRPDLQRIFXOWXUDOGLVWDQFHPHDVXUHGE\+RIVWHGH¶V dimensions. In this thesis we therefore test for both cultural distance and interpersonal trust, as they are complementary elements of informal institutions.

We interpretet interpersonal trust as an indicator of high and low context cultures, where high interpersonal trust indicates a high context culture and low interpersonal trust indicates a low context culture. This hypothesis is derived from the concept of high versus low FRQWH[WFXOWXUHV+DOOZKLFKUHIHUVWRDFXOWXUH¶VWHQGHQF\WRXVHHLWKHUPDLQO\ high context or low context communication. China has a high context culture and Chinese business networks are based on intensely personal connections and trust (Wang, 2000). Buckley et al (2007) claim that Chinese firms prefer to invest in countries with a large population of ethnic Chinese in order to benefit from the presence of guanxi networks. China lacks a developed legal system and therefore business is done based on informal institutions,

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in particular based on interpersonal trust (guanxi). According to Filatotchev, Strange, Piesse, & Lien (2007) diverging FDI strategies between firms from developed and emerging economies are explained by the fact that firms from developing countries are often controlled by founding families or governments. These firms rely heavily on interpersonal trust and network linkages when developing their strategies (Hsing, 1996). China has lots of these kind of firms that rely on trust and network linkages (Chen and Chen, 1998). We expect that Chinese OFDI is associated with host countries were high interpersonal trust prevails, aligning with the Chinese high context culture (Kim et al. 1998). Therefore, we propose:

Hypothesis 3: We expect that the O F DI of emerging economies, exemplified by China, is associated with host countries where high interpersonal trust prevails among the population.

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Hypothesis 4a: Cultural similarity weakens the relationship between formal institutions and the O F DI of an emerging economy, exemplified by China.

Hypothesis 4b: Interpersonal trust weakens the relationship between formal institutions and the O F DI of an emerging economy, exemplified by China.

An overview of the hypotheses and the model is shown in picture 1. In the discussion chapter we provide an adjusted model, which exhibits whether the hypotheses are supported or rejected.

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4. Data and method

This section provides an overview of the empirical research method of this thesis. We explain the data collection and the selected variables. Furthermore, the model specification is presented and explained.

4.1 Data collection

The data required to research the impact of formal and informal institutions on the amount of OFDI that flows from China and the U.S.A towards host countries was obtained from several secondary sources. These secondary sources were found on the internet. The bilateral FDI flows were obtained from the Bureau of Economic Analysis (BEA, 2013) and the Ministry of commerce of the people republic of China (MOFCOM, 2010). The BEA is a trustworthy governmental online financial database of the U.S.A. The MOFCOM is the Chinese counterpart. It is expected that the Chinese data is less accurate and reliable because compilation methods are not totally congruent with the standards of the OECD and IMF. However, MOFCOM is the only database providing Chinese OFDI data and thus used in this thesis. Market size and market growth data were found in the :RUOG%DQN¶V (2013) reputable database. The Hofstede Centre (2013) provided this thesis with the indexes RI +RIVWHGH¶V individual cultural dimensions, which made it possible to compute the cultural distance values (Kogut and Sing 1998). The corporate governance data was obtained from the Worldwide Governance Indicators (WGI) project of the World Bank (2013). The interpersonal trust index data has been collected from the ASEP/JDS databank (2013); a reliable database that provides researchers statistical data and survey data files. All currency variables in this research are expressed in US$ dollars.

4.2 Sample

The self-constructed dataset contains data of 67 selected countries throughout the whole world. After correcting for missing data, we eventually had complete data for 61 countries. The dataset comprises the period from 2004 until 2010, and thus offers a large set of observations for this research. Finally, we had 429 observations were The overview of these selected countries can be found in appendix A. The chosen countries are selected on the availability of the relevant data required for this research.

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4.3 Dependent variable

In order to test whether the conventional institutional determinants of OFDI hold for emerging economies, institutional determinants of Chinese and U.S.A are compared. The dependent variable in this research is the FDI flow from China and the U.S.A towards the selected host countries (BEA 2013; MOFCOM, 2010). First, the composed models are executed with Chinese OFDI as the dependent variable and secondly with the U.S.A. OFDI as dependent variable. FDI is described by the World Bank (2013) as the net inflows of investment to acquire a lasting management interest, which is at least 10 percentage of voting stock, in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments.

4.4 Control variables

Derived from earlier research, and based on the availability, reliability and completeness of data we selected three general, non-institutional variables to function as control variables in this research. These independent control variables are market size, physical distance and market growth.

Market size (GDP): In the existing literature (Blonigen, 2005) market size has shown to be an important and significant determinant of FDI. Market size is measured by the size of GDP of a host country. GDP is the market value of all officially recognized final goods and services produced within a country in a given period of time. The size of a market indicates the attractiveness of a host country when an MNE is searching to produce and sell in that market within the host country (Chakrabarti, 2001). A large market size is important for the efficient utilization of resources and for the exploitation of economies of scale. The GDP has been collected from the World Bank (2013) online database.

Distance (DISTANCE): In the literature physical distance has shown to be an important and significant determinant of FDI (Chakrabarti, 2001). Distance is measured as the physical distance between the capital of the host country and the capital of the country of origin. The existing literature explains that increased physical distance is associated with more uncertainty (Du et al, 2009). Thus greater physical distance between host and home country is expected to have a negative effect on FDI flows, due to the fact that there are increased costs associated with shipping, moving, travelling, and other logistical costs.

Market potential (GDP growth): The market potential of a host country is estimated by the annual growth rate of the GDP of a country (Busse and Hefeker, 2005). A growing

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GDP presumably results in higher purchasing power of the population of a country, which is expected to have a positive effect on FDI inflows. High growth rates could indicate high return on investments, and thus may attract more FDI (Busse and Hefeker, 2005). The GDP growth has been collected from the World Bank (2013) online database.

4.5 Institutional variables

Based on empirical findings from earlier research, and based on the availability, reliability and completeness of data, formal and informal institutional variables have been selected as independent variables within this research. The model tests informal institutions by using cultural distance and interpersonal trust. Furthermore, we measure the individual effect of the four individual cultural dimensions of Hofstede (1980) on the OFDI of China and the U.S.A. The formal institutions are represented by the institutional quality of the host country. Institutional quality is represented by the calculated average of the individual Worldwide Governance Indicators (WGIs). Furthermore, we measure the individual effect of the six WGIs. We expect that the WGIs strongly correlate, thus we test the individual WGIs in separate models in order to prevent multicollinaerity.

Formal institutions (INSTQ): This variable has been composed by calculating an average index number based on WKH KRVW FRXQWU\¶V VFRUH RQ WKH :RUOGZLGH *RYHUQDQFH Indicators (WGI) project. The project of the World Bank (2011) reports aggregate and individual governance indicators for 215 economies over the period 1996±2011. This is done for six dimensions of governance: voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption. Countries have been given an index score on a scale from -2.5 to + 2.5. A high positive score indicates high quality institutions. A high negative score indicates low quality institutions. The six governance indicators of Kaufman et al (2010, p. 223) will be further explained: Voice and Accountability (VA): This variable concerns the extent to which the population of a country is able to participate in electing their government, as well the freedom of association, freedom of expression and free media.

Political Stability and Absence of Violence (PS): This variable concerns the extent to which it is likely that the government of a country will be overthrown or destabilized by violent or unconstitutional means. Terrorism and politically-motivated violence are also included in this variable.

Government Effectiveness (GE): This variable concerns the quality of public services, civil services and the extent to which they are independent from political pressures. Further it

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captures the quality of policy formulation and implementation, the commitment and credibiliW\RIDFRXQWU\¶VJRYHUQPHQW

Regulatory Quality (RQ): 7KLVYDULDEOHFDSWXUHVSHUFHSWLRQVRIWKHJRYHUQPHQW¶VDELOLW\WR formulate and implement sound policies and regulations in order to promote private sector GHYHORSPHQWDQGPDNHDFRXQWU\¶VLQYHVWPHQWFlimate more attractive.

Rule of Law (RL): This variable measures the extent to which actors have confidence in the rules of society, and the extent to which they abide these rules. The rules of society are property right protection, quality of contract enforcement, the legal system and the probability of crime and violence.

Control of Corruption (CC): This variable measures the extent to which public power is exercised for private gain. All forms of benefits that are paid to the government are taken into account through this variable.

Due to expected high correlation coefficients between the six indicators, it is not allowed to include them as separate variables in one model. Thus a computed average of institutional quality will be calculated. The indicators will individually be tested in separate models as well. The formula for institutional quality is:

ܫܳூ ൌ ଵ_଺ σ଺௄ୀଵܫ௞௜

Informal institutions. We measure informal institutions by calculating the cultural distance (HOFCD) index, based on the scores on the cultural dimensions of Hofstede (1980). We chose Hofstede, based on a few reasons mentioned by Haxhi and Van Ees (2010, p. 712). )LUVW +RIVWHGH¶V YDOXHV DUH WKH PRVW ZLGHO\ XVHG values as the measurement of national culture, which helps to develop commonly acceptable, well-defined and empirically based terminology to characterize culture and facilitate systematic comparison. Second, the size of +RIVWHGH¶VGDWDVHWDOORZVXVWRFUHDWHDODUJHVDPSOHRIFRXQWULHVWRLQFOXGHLQWKLVUHVHDUFK. FLQDOO\+RIVWHGH¶VGLPHQVLRQVDUHEDVHGRQQDWLRQDOPHDQVZKLFKPDWFKHVWKHFRXQWU\OHYHO analysis of this research. Hofstede has created a dataset which contains the scores of a large amount of countries on five cultural dimensions. The dimensions of Hofstede that we use in this thesis are power distance (PDI), uncertainty avoidance (UA), individualism versus collectivism and masculinity (MAS).

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- 8QFHUWDLQW\ DYRLGDQFH µ7KH GHJUHH WR ZKLFK WKH PHPEHUV RI D VRFLHW\ IHHO XQFRPIRUWDEOHZLWKXQFHUWDLQW\DQGDPELJXLW\¶

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Cultural distance, a constructed measure derived from the four cultural dimensions of Hofstede (1980), is computed by using the formula of Kogut and Singh (1988). Criticism by Haxhi and Van Ees (2010) is that not all cultural dimensions are of equal importance in their influence on certain issues. However, this method is still considered valuable and is widely used by academics. In this thesis we will calculate the cultural distance between the host countries and China and the U.S.A. The individual dimensions are tested in separate models as well in order to clarify their significance. The formula is as follows:

ܥܦ_௜௝ ൌ ଵ_ସσସ ሺܥ_௖௜െ ܥ_௜௝ሻଶ

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We think interpersonal trust (TRUST) is an important informal institution which is QRWFRYHUHGE\WKHGRPDLQRIFXOWXUDOGLVWDQFHPHDVXUHGE\+RIVWHGH¶VGLPHQVLRQVWe think that cultural distance and interpersonal trust are complementary elements of informal institutions. Therefore, the final informal institutional variable is interpersonal trust. Interpersonal trust is linked to the concept of high versus low context cultures (ASEP/JDS, 2013). In high context culture countries, business is conducted based on cultural practices, customs and norms (Hall, 1976). High context cultures are built on trust. Therefore we use the interpersonal trust index as an indicator of informal institutions. When interpersonal trust is high, the need for rules and regulations might be less important because informal institutions can reduce uncertainty.

4.6 Interaction variables

We composed interaction variables in order to research the effect of informal institutions on the effect of institutional quality on OFDI. The interaction variables are HOFCD*INSTQ and TRUST*INSTQ. This thesis aims to measure whether cultural distance and interpersonal trust have a moderating effect on the relationship between institutional quality and OFDI (Baron & Kenny, 1986). More specific, when a country has a less distant culture this might strengthen or weaken the effect of formal institutions on FDI flows.

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Furthermore, when in a host country high interpersonal trust prevails, this might strengthen or weaken the effect of formal institutions on FDI flows.

4.7 Model specification

In order to research the effect of institutions on the OFDI of developing and emerging economies, this thesis makes use of panel data. Hsiao (2003, p. 3) defines SDQHOGDWDDVµD longitudinal data set that follows a given sample of individuals over time, and thus provides multiple observations RQHDFKLQGLYLGXDOLQWKHVDPSOH¶An advantage of panel data is that over a given period of time, the development of each cross-sectional unit can be analyzed. Furthermore, another significant advantage of panel data is that panel data sets provide large amount of data points, and thus increases the degrees of freedom and reduces multicollinearity among explanatory variables (Hsiao, 2003; Wooldridge, 2006). This improves the efficiency of the econometric estimates.

This thesis makes use of the gravity equation of international trade. This log-linear equation specifies the FDI flows from a home to a host country, which are explained by economic determinants in the home and host country. The model controls for economic size and geographical distance (Bergstrand, 1985). In the existing literature this model often has been used to analyze international trade patterns and it has proven to yield statistical significant results (Frankel, 1997). In order to identify the relationship between OFDI flows and institutional determinants, the model is extended with formal and informal institutional variables. Finally, the interaction effects within this model are tested. This might identify potential interaction effects within the model.

The data is panel-level heteroskedastic. Using a pooled Ordinary Least Square (OLS) regression model such as Buckley et al (2007) did, violates the assumption of independence. This is the case because this method does not correct for dependencies within country observations. OLS estimations could possibly be statistically inefficient and even might give misleading inferences. The consecutive years presumably cause serial autocorrelations and it does not take into account the possibility of different serial autocorrelation within countries. In order to conduct this research with a valid research method, this thesis uses a cross-sectional time-series FGLS regression model. This has been done with the aid of the xtgls command in the statistical software program STATA. Testing the model with the FGLS method provides the most efficient estimates. Since the data collected is panel type data, the