With the implementation of the “Going Out” policy and the “Belt and Road” initiative, Chinese outward foreign direct investment (OFDI) in the countries along the “Belt and Road” increased substantially in the past decade. This paper analyzes the impact of institutional distance on Chinese OFDI and whether Chinese OFDI exhibits institutional risk preferences, using data on Chinese OFDI in 41 countries along the “Belt and Road” for the period from 2003 to 2018. We find that political institutional distance and economic institutional distance are both positively related to China’s OFDI scale, while cultural distance has a negative impact on the investment scale. We also find that institutional distance has an asymmetric effect on China’s OFDI. In particular, the worse the host country’s political environment, the larger the Chinese OFDI, indicating that Chinese OFDI exhibits the political institutional risk preference. On the other hand, Chinese multinational enterprises are more willing to invest in host countries with high economic freedom. Culture institution environment of the host country has a positive but insignificant impact on the Chinese OFDI scale, indicating that Chinese OFDI shows the characteristics of cultural distance proximity.
With the continuous development and implementation of the “Going Out” policy, China’s outward foreign direct investment (OFDI) has risen rapidly in the past decade. In particular, with the advocacy of the “Belt and Road” initiative, China’s OFDI in countries along the “Belt and Road” has drastically increased in recent years. From 2014 to 2016, China’s investment in countries along the “Belt and Road” has accumulated more than $50 billion. Chinese multinational enterprises (MNEs) have built 56 economic and trade cooperation zones in more than 20 countries, creating nearly $1.1 billion in taxes and 180,000 jobs for these countries. In 2017, China’s outward foreign direct investment stock was US $1809.04 billion, the second highest level in history after the US $7797.59 billion reached in the United States (Statistical Bulletin of China’s OFDI in 2017). One of the salient features of China’s OFDI is that state-owned enterprises, as the main implementer of national policies, were the main subjects of China’s OFDI. In 2006, state-owned enterprises accounted for 81% of the OFDI stock. In recent years, with the diversified development of investment subjects, investment motivation, and investment industries, the proportion of state-owned enterprises in the OFDI stock has been decreasing. But in 2018, the proportion of state-owned enterprises was still as high as 48% (Statistical Bulletin of China’s OFDI in 2019). The dominant role of state-owned enterprises in China’s OFDI has not changed.
With the rise of transnational investment, the issue of political risks faced by Chinese enterprises’ outward direct investment has attracted wide attention. Ramasamy et al. [
As the largest developing country, China’s unique institutional characteristics in the transition period have become the focus of attention. The political attribute of state-owned enterprises makes China’s OFDI have strong institutional preference. In the twenty-first century, under the background of the new international trade and investment rules, the political risks and institutional preferences faced by Chinese state-owned enterprises have undergone structural changes. Using the panel dataset of China’s OFDI to 41 countries along the “Belt and Road” from 2003 to 2018, this paper analyzes the influence of the institutional quality of the host country and bilateral institutional distance between China and the host country on the location distribution and investment scale of China’s OFDI, which is of great significance for improving the institutional theory of OFDI. China provides an appropriate and unique setting for examining the influence of institutional factors on OFDI. At the same time, institutional characteristics of China’s OFDI can be used for reference for the healthy development of OFDI in other developing countries.
Mainstream investment theories stipulate that OFDI should be flowed into host countries with high institutional quality, especially low political risk [
Some prior research shows that Chinese MNEs appear to display a distinctive pattern to institutional risk, referred to as the puzzle of Chinese OFDI institutional risk preference. Buckley et al. [
When investing in foreign markets, MNEs must adapt their strategies to satisfy the requirements of local institutions, which may differ from the institutions of their home countries. Thus, institutional distance between home and host countries represents an important factor that influences MNEs’ OFDI. Firms perform better in foreign markets similar to their home markets than in markets that are dissimilar, as similarities are easier for firms to manage [
The costs of institutional distance may differ for firms from developed than those from developing countries. Firms from developed countries may have more experience and better networks than firms from developing countries, and this can help firms from developed countries better reduce the cost of institutional distance [
The existing literature and opinions can only explain outward foreign investment activities among developed countries and developing countries. Institutional distance well explains the outward foreign investment behavior of emerging economies and transition economies without competitive advantages. Different from western developed countries, the main object of China’s OFDI is state-owned enterprises (SOEs). The outward foreign investment behavior of state-owned enterprises is deeply affected by government participation and control. China’s institutional characteristics make it the most appropriate and unique setting for examining the influence of institutional factors on OFDI. We reconsider the relationship between institutional quality of the host country and China’s OFDI and examine the “China’s OFDI risk preference theory” proposed by previous studies. Given that the institutional environment of a country is a complex multidimensional construct, the impacts of institutional environment in different dimensions may differ from its overall effect. Thus, we consider the political institutional environment, the economic institutional environment, and the cultural institutional environment and examine the different impacts of each type of institution environment on China’s OFDI.
In contrast with prior studies in this area, this paper focuses on China’s OFDI in 41 countries along the “Belt and Road” from 2003 to 2018. Using the two-stage Heckman model with trade gravity, we find that large political distance reduces the willingness of Chinese MNEs to invest abroad, but once investment decision is made, the amount of Chinese OFDI is positively related to political distance. In addition, economic institutional distance has a significantly positive impact on the amount of Chinese OFDI. On the other hand, cultural distance has a significantly negative impact on the volume of Chinese OFDI. We further find that institutional distance has an asymmetric effect on the OFDI. The Chinese OFDI tends to flow into the host countries with a poorer political institutional environment, a better economic environment, and a similar cultural environment. Our results clearly show that Chinese OFDI presents political institutional risk preference and characteristics of cultural distance proximity.
The contributions of this paper to the literature are as follows. First, this paper divides the institutional environment of the host country into the political institutional environment, the economic institutional environment, and the cultural institutional environment and delves deeply into the characteristics of China’s OFDI preferences for various aspects of institutional environment. Thus, the analysis of this paper is more comprehensive, more specific, and more practically relevant. Second, this paper constructs a Heckman two-stage model with trade gravitation to analyze the impact of institutional environment of the host country and bilateral institutional distance on China’s OFDI. This model allows us to analyze how the host country’s institutional environment is related to both the willingness of China’s OFDI and the size of OFDI in the country, and our analysis is less subject to sample selection bias. Third, in addition to considering the size of the institutional distance, we also consider the direction of the institutional distance; that is, we analyze whether China’s OFDI outflows to the host country, whose institutional quality is better or worse than China’s, in order to clarify the puzzle of China’s OFDI institutional risk preference and examine the asymmetric effect of institutional distance.
The remainder of this paper is structured as follows: In Section
North [
Habib and Zurawicki [
Institutional diversification provides opportunities for MNEs to exploit differences between two institutional environments. From the perspective of institutional arbitrage, by implementing the OFDI strategy in developed economies, Chinese MNEs can not only avoid the institutional constraints in the domestic market, but also be integrated into the advanced economies to obtain the strategic assets and use the comparative institutional advantages to induce institutional changes and improve the long-term competitiveness of enterprises. Xu and Shenkar [
Based on institutional arbitrage, formal institutional distance may have a positive impact on Chinese OFDI.
The cultural differences between the home country and the host country determine the cultural barriers for MNEs to invest in the host country. When MNEs invest in the host country, they consider information flow, externality, information asymmetry, and adverse selection, among others. They also pay attention to the legitimacy of the market and thus obtain the recognition of suppliers, distributors, and consumers in the host country market, which is closely related to the cultural distance between the host country and the home country. If Chinese enterprises neglect local customs, cultural environment, labor rights, and interests, then it is hard for them to integrate into the local economic development environment in time and better realize the localized operation, leaving a bad impression on the host people, generating anti-Chinese sentiment, and disrupting the local investment and operation activities of enterprises. At the same time, the more Chinese people in the host country, the smaller the cultural difference between the host country and the home country, the lower the transaction cost of enterprises, and the easier it is to obtain a larger market share, which is more likely to drive the OFDI of overseas companies. In summary, we propose Hypothesis
The cultural distance between the host country and China is negatively related to Chinese OFDI.
Aleksynska and Havrylchyk [
The role of institutional distance on Chinese OFDI is asymmetric. Depending on investment motivation and type of institution, Chinese OFDI may flow into host countries with a worse institution environment, or flow into host countries with a better institution environment.
This paper uses the panel dataset of China’s OFDI in 41 countries along the “Belt and Road” from 2003 to 2018. The countries along the “Belt and Road” are listed in Table
Countries along the “Belt and Road.”
9 countries in ASEAN : |
Indonesia, Malaysia, Philippines, Singapore, Thailand, Brunei, Vietnam, Myanmar, Cambodia |
1 country in East Asia : Mongolia |
8 countries in West Asia: |
Iraq, Turkey, Jordan, Israel, Saudi Arabia, UAE, Greece, Cyprus |
5 countries in South Asia: |
India, Pakistan, Bangladesh, Afghanistan, Nepal |
7 countries in Commonwealth of Independent States (CIS): |
Russia, Ukraine, Belarus, Georgia, Azerbaijan, Armenia, Moldova |
11 countries in Central and Eastern Europe: |
Poland, Lithuania, Estonia, Latvia, Czech Republic, Hungary, Slovenia, Croatia, Serbia, Romania, Bulgaria |
The explained variable is the volume of China’s OFDI flows in the 41 countries along the “Belt and Road” and is expressed in the 2010 US constant price. The data is obtained from
The first explanatory variable is the informal institutional environment, which is the cultural distance between China and the host country (CD). It is measured by the six cultural dimensions given by Hofstede [
The second one is the political institutional environment (PI). This is measured by the six indicators given by the World Bank’s Global Governance Indicators, including Discourse Rights and Responsibilities (VA), Political Stability and Non-Violence (PS), Government Efficiency (GE), Regulatory Quality (RQ), Rule of Law (RL), and Corruption Control (CC). We use the average of these six indicators to represent the overall score of political institutional environment, which ranges from −2.5 to 2.5. The larger the value, the better the political institutional environment in the country. The data comes from the World Bank’s Global Governance Indicators database. The calculation method of the political distance between China and the
The third explanatory variable is the economic institutional environment (EI). This is measured by the economic freedom index released by
The above institutional distance measures solely the gap between the institutional environment of China and that of a host country and does not indicate whether the institution quality of the host country is better than China’s institution quality. Therefore, we take the average value of subindicators of the cultural, political, and economic environment to represent the comprehensive score of the cultural, political, and economic environment. The direction of the institutional distance is represented by whether the difference between institutional scores is greater than zero. We use dummy variables to indicate the direction of the institutional distance, denoted by
Anderson [
The motivations of China’s outward foreign direct investment can be divided into market-seeking, strategic asset-seeking, trade-seeking, and resource-seeking. In order to understand the investment motivation of China’s OFDI, this paper also considers the following control variables: (1) market potential (HAGDP), measured by the real GDP per capital (constant price in 2010 U. S. dollars), (2) technological development level (RD), which is measured by the number of patent applications in the countries along the “Belt and Road”, (3) degree of import dependence (EX), which is measured by the proportion of China’s exports to the host country to the total imports of the host country, and (4) natural resource intensity (Nature), which is measured by the proportion of fuel, ore and metal exports in total exports. The above data comes from
The descriptive statistics of the major variables are reported in Table
Variable definitions and descriptive statistics of variables.
Variable | Meaning | Unit | Max | Min | Average | Standard deviation |
---|---|---|---|---|---|---|
OFDI | China’s foreign investment flows | U.S. $10,000 | 1045248 | -45713 | 24891.31 | 74723.39 |
CD | Cultural distance | — | 7.72 | 0.55 | 2.88 | 1.82 |
PD | Political distance | — | 4.6 | 0.09 | 1.19 | 0.93 |
ED | Economic distance | — | 19.82 | 0.003 | 4.64 | 4.06 |
CGDP | China’s GDP | U.S.$1,000,000,000 | 94781.27 | 17989.83 | 50462.05 | 25475.03 |
HGDP | GDP of host country | U.S.$1,000,000,000 | 59163.17 | 8.251781 | 5135.098 | 11929.82 |
DIS | Geographic distance | Kilometers | 7722.64 | 1172.05 | 5568.86 | 1754.18 |
HAGDP | Per capita GDP of host country | U.S. $ | 60351.14 | 330.30 | 11112.38 | 12095.47 |
RD | R&D expenditure (% of GDP) | % | 63.58 | 0 | 22.84 | 15.67 |
IM | Degree of dependence on import trade | % | 73.02 | 0.16 | 10.99 | 11.03 |
Nature | Fuel, ore and metal exports (% of merchandise exports) | % | 99.79 | 0 | 24.42 | 27.29 |
The gravity model is the main empirical research tool in the field of international trade. GDP levels proxy for OFDI demand, geographical, and institutional distance proxy for trade friction and coordination costs, and these proxies enable us to construct a gravity model. Thus, this paper mainly analyzes the influence of bilateral economic scale, geographical distance, cultural distance, political distance, and economic distance on China’s outward foreign investment.
This paper uses China’s outward foreign direct investments in 41countries along the “Belt and Road” from 2003 to 2018 as a sample. We find that, in some years, China’s investment in certain countries was zero, and even negative. One possible reason for this is that the changes in the institutional environment of the host country lead to changes in China’s investment flows. Therefore, our sample is a self-selected sample rather than a random sample, meaning that there is a problem of sample selection bias. When some observations of sample are not exogenous and random, the estimated parameters will be biased. The Heckman model is to correct the estimation error caused by this bias [
The Heckman model allows for a two-stage decision process, in which MNEs first decide whether or not to outward invest (extensive margin) and then decide how much to invest (intensive margin). The Heckman model is in principle a suitable model if there is an exogenous variable that has a strong effect on the selection equation but has no effect on the level of OFDI (primary equation). In this paper, we use a Regional Trade Agreements dummy variable as the exogenous variable in the selection equation, but not in the primary equation. The signing of the agreements affects whether China makes the decision to outward invest in the host country, but it does not affect the level of outward foreign investment. China has signed Regional Trade Agreements (RTAs) with Mongolia, Turkey, Azerbaijan, Czech Republic, Georgia, Romania, Russia, Belarus, and Poland. For these countries, we set
The Heckman model with trade gravity is as follows.
The first stage is the selection equation (the Probit model):
The second stage is the primary equation:
In equation (
The empirical results of the Heckman model are reported in Table
Institutional distance and China’s OFDI.
Model variables | (4) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
First | Second | First | Second | First | Second | First | Second | First | Second | First | Second | |
ln (CGDP) | 0.288 | 2.711 | 0.384 | 2.859 | 0.414 | 2.949 | 0.478 | 2.612 | 0.350 | 3.018 | 0.406 | 2.934 |
ln (HGDP) | 0.329 | 0.058 | 0.401 | 0.266 | 0.410 | 0.355 | 0.505 | −0.091 | 0.398 | 0.368 | 0.495 | 0.135 |
ln (DIS) | 1.350 | −1.289 | −0.534 | −1.714 | −0.296 | −2.092 | −0.648 | −1.352 | −0.456 | −2.014 | −0.619 | −1.726 |
PD | −0.244 | 0.400 | −0.239 | 0.201 | −0.155 | 0.161 (0.83) | ||||||
ED | −0.136 | 0.449 | −0.077 | 0.382 | −0.075 | 0.389 | ||||||
CD | 0.148 | −0.252 | 0.138 | −0.182 | ||||||||
ln (HAGDP) | 0.146 | 0.112 | 0.008 | 0.199 | 0.023 | 0.325 | 0.151 | 0.109 | 0.109 | 0.127 | ||
RD | −0.016 | −0.034 | −0.012 | −0.048 | −0.022 | −0.020 | −0.011 | −0.049 | −0.017 | −0.042 | ||
EX | 0.015 | 0.006 | 0.020 | 0.004 | 0.011 | 0.003 | 0.022 | 0.002 | 0.018 | −0.004 | ||
Nature | −0.010 | 0.013 | −0.010 | 0.020 | −0.011 | 0.017 | −0.014 | 0.022 | −0.018 | 0.029 | ||
RTA | 0.179 | 0.267 | 0.347 | 0.265 | 0.347 | 0.335 | ||||||
Constant | 8.223 | −3.320 | −0.476 | −3.706 | −1.868 | −2.712 | −0.189 | −3.618 | −0.899 | −3.391 | −0.314 | −3.625 |
Mills | −3.77 | −3.19 | −1.49 | −3.41 | −1.45 | −2.17 | ||||||
LR | 20.70 | 160.85 | 299.84 | 78.32 | 311.49 | 269.79 | ||||||
N | 656 | 588 | 571 | 588 | 588 | 571 |
As can be seen in Table
Focusing on the OFDI motivation, we note that the per capita GDP and the degree of import dependence of the host country have no significant impact on China’s OFDI decisions and investment scale. The natural endowment of the host country has a significantly negative impact on China’s OFDI decisions, but it has a significantly positive impact on China’s outward investment scale. The technological level of the host country has a significantly negative impact on China’s OFDI decisions and investment scale. Because most of the countries along the “Belt and Road” are developing countries, and the market competitiveness of Chinese MNEs in technologically developed countries is not extremely strong, Chinese MNEs tend to invest in countries with abundant resources and low technological levels. That is, China’s investment in countries along the “Belt and Road” is not mainly driven by market-seeking, trade-seeking, or asset-seeking, but by resource-seeking.
The results in Table
We further find that economic distance deters China’s foreign direct investment decision, but it significantly promotes the scale of China’s foreign investment. The greater the economic distance, the greater the difference in the fiscal and trade environment between China and the host country, and the more obstacles Chinese MNEs face, resulting in lower willingness for Chinese MNEs to invest in the host country. But once Chinese MNEs enter the host country, they hope to reduce production costs, occupy a larger market share through larger investment scales, mitigate the risks brought by economic distance, and overcome the liability of foreignness. Collectively, large formal institutional distances, especially political distances, inhibit Chinese MNEs’ willingness to invest in countries along the “Belt and Road,” but once Chinese MNEs decide to invest in a country, larger institutional distances, especially economic distances, will promote Chinese MNEs reducing transaction costs and operating costs with a larger investment scale to reduce institutional risks. That is, formal institutional distance is positively related to China’s OFDI scale.
Cultural distance has a significantly positive impact on China’s foreign direct investment decisions, but it has a significantly negative impact on the scale of China’s foreign investment. China is a typical eastern country. The cultural traditions of countries along the Belt and Road are extremely different from China. In order to achieve communication and dissemination between different cultures, China is more inclined to invest in other countries different from China in customs, religions, and habits. However, the large cultural differences make it difficult for Chinese MNEs to be recognized by local residents and hinder the further expansion of the investment in countries along the “Belt and Road.” That is, China’s foreign direct investment shows the characteristics of cultural distance proximity.
The previous empirical analysis does not consider whether the host country’s institutional environment is better than that of China or worse than that of China. To examine the institutional preference of China’s OFDI, we add to our regressions dummy variables that indicate the direction of the institutional distance. The estimation results are reported in Table
Institutional preference.
Model variables | ||||||
---|---|---|---|---|---|---|
First | Second | First | Second | First | Second | |
ln (CGDP) | 0.392 | 2.862 | 0.543 | 3.166 | 0.460 | 2.848 |
ln (HGDP) | 0.41 | 0.325 | 0.517 | 0.476 | 0.627 | 0.157 |
ln (DIS) | −0.473 | −2.080 | 0.257 | −2.002 | −0.567 | −1.771 |
PD | −0.222 | 0.302 | ||||
PDD | 0.189 | −0.797 | ||||
ED | −0.066 | 0.574 | ||||
EDD | 0.453 | 0.209 | ||||
CD | 0.198 | −0.307 | ||||
CDD | 0.015 | 0.011 | ||||
ln (HAGDP) | 0.085 | 0.376 | 0.268 | 0.018 | −0.039 | 0.610 |
RD | −0.017 | −0.034 | −0.019 | −0.049 | −0.017 | −0.038 |
EX | 0.016 | 0.004 | 0.068 | 0.009 | 0.006 | 0.006 |
Nature | −0.009 | 0.007 | −0.015 | 0.024 | −0.013 | 0.027 |
RTA | 0.295 | 0.596 | 0.378 | |||
Constant | −0.766 | −2.519 | −6.274 | −5.155 | −1.082 | −4.181 |
Mills | −1.951 | −0.933 | −2.62 | |||
LR | 212.10 | 297.94 | 179.46 | |||
N | 588 | 478 | 536 |
The estimation results of Model (1) show that the political quality of the host country has no significant impact on China’s OFDI decisions, but it negatively impacts the scale of China’s OFDI. This suggests that the scale of Chinese OFDI is relatively large in the host country with a political environment poorer than China. In addition, the market potential of the host country also has a significant appeal to the scale of China’s OFDI. That is, China’s OFDI exhibits the characteristics of political risk preference, and the main investment motivation is to expand the domestic market and open business to foreign markets.
The host country’s economic environment has a significantly positive impact on China’s OFDI decisions and has a positive impact on the scale of China’s foreign investment, indicating that Chinese MNEs are more willing to invest in host countries with more economic freedom, and the scale of OFDI is directly proportional to the economic freedom of the host country. Moreover, China’s OFDI is mainly driven by natural-resource-seeking.
The host country’s cultural environment has a positive impact on China’s foreign investment decision-making process and the scale of investment, but not statistically significant. This shows that Chinese MNEs are more willing to invest in a host country with a better cultural environment than that of China. However, the excessive cultural distance inhibits the expansion of China’s OFDI. Therefore, Chinese MNEs invest in a host country with the similar cultural environment to China. Market-seeking and natural-resource-seeking are the main outward investment motivations.
Using the panel dataset of China’s OFDI in 41 countries along the “Belt and Road” from 2003 to 2018, this paper investigates the impacts of the host country’s institutional environment on China’s OFDI, as well as the institutional risk preference of China’s OFDI. To address the sample-selection bias and endogenous concerns, we adopt the two-stage Heckman model with trade gravity in our analysis.
First, we find that large political distance reduces the willingness of Chinese MNEs to invest abroad, but once the investment decision is made, the amount of Chinese OFDI is positively correlated with political distance. In addition, economic institutional distance has a significantly positive impact on the amount of Chinese OFDI. Overall, the large formal institutional distance (political and economic institutional distance) complements, rather than replaces, the formal institution environment of China. Chinese OFDI shows the characteristics of formal institution paradox, and the amount of Chinese OFDI is motived by formal institutional arbitrage.
Second, cultural distance has a significantly negative impact on the amount of Chinese OFDI. Thus, formal institutional distance and informal institutional distance have different impacts on Chinese OFDI. The large potential cultural difference inhibits the further expansion of overseas investment, meaning that Chinese OFDI shows the characteristics of cultural distance proximity.
Third, we find that institutional distance has an asymmetric effect on Chinese OFDI. More specifically, the worse the host country’s political environment, the larger the Chinese OFDI. That is, Chinese OFDI tends to flow into host countries with a worse political institutional environment. Chinese OFDI presents political institutional risk preference. On the contrary, the economic freedom of a host country has a positive impact on the level of Chinese OFDI. That is, Chinese OFDI tends to flow into host countries with a better economic institutional environment. Moreover, Chinese OFDI tends to flow into host countries with a better cultural institutional environment than China, but this effect is not statistically significant. Overall, Chinese OFDI tends to flow into host countries with a poorer political institutional environment, a better economic environment, and a similar cultural environment.
Our findings have important policy implications. First, it is important to establish an early warning system to reduce political risks. A considerable part of China’s investment in the countries along the “Belt and Road” is concentrated in countries with high political risks, and the host country’s political risk is an important factor affecting the risk and return of the investments of multinational enterprises. China should establish and improve the legal system and service system for OFDI and identify political risks in advance.
Second, it is also crucial to increase the operational autonomy of MNEs and create a relaxed economic environment. In particular, it is important to form a diversified development and flexible outward foreign investment pattern by establishing a new type of government-enterprise relationship that enables multinational corporations with conditions for foreign investment to enjoy foreign trade, financing and other financial management autonomy, simplifies foreign investment approval procedures, and encourages small- and medium-sized enterprises and private enterprises to invest abroad.
Third, it is also crucial to implement localized business strategies to encourage home country’s enterprises to be rooted in host countries. In order to alleviate and eliminate cultural conflicts, the parent company improves the company’s organizational structure and strengthens cross-cultural communication and management. On the other hand, it is recommended to appoint local senior management personnel in the host country’s subsidiaries, follow local cultural traditions, establish production systems and business models that are adapted to the local operating environment, and reduce the operating and management costs of multinational enterprises.
Fourth, it is important to promote a proactive foreign policy and establish good bilateral relationships between the home country and the host country. In particular, it is helpful to actively establish partnerships with host countries, form sister cities, and sign cooperation documents that are conducive to protect investment and trade, such as the bilateral investment protection agreements and the agreement to avoid double taxation. Finally, the home country should reduce its dependence on fossil energy imports, develop strategic asset-seeking outward direct investment, strengthen the absorption of OFDI reverse technology spillovers, and help host countries improve infrastructure, expand employment, and promote economic growth to form an optimal allocation of global resources and a win-win situation for cooperation.
China’s OFDI in the 41 countries along the “Belt and Road” is given by China Foreign Direct Investment Statistics Bulletin and is expressed in the 2010 US constant price. China’s GDP data comes from the China Statistical Yearbook. The total economic output of the host country is measured by real GDP of the host country, which is expressed in 2010 US constant prices. The data come from the United Nations account total database. Geographical distance (DIS) generally refers to the distance from the Chinese capital to the capital of the host country. The economic institutional environment (EI) is measured by the economic freedom index released by the “Wall Street Journal” and the Heritage Foundation, which includes five dimensions: business freedom, monetary freedom, trade freedom, investment freedom, and financial freedom. The political institutional environment (PI) is measured by the six indicators given by World Bank’s Global Governance Indicators. The cultural distance (CD) measured by the six cultural dimensions comes from the Hofstede personal database.
The authors declare that they have no conflicts of interest.
Y. W. designed the model, conducted empirical research, and wrote the manuscript. G. P. collected data and verified the analytical methods. All authors discussed the results and contributed to the final manuscript. All authors have read and agreed to the published version of the manuscript.
This work was supported by the National Natural Science Foundations of China (71763010 and 71773041) and Young Academic Talents Project of Jiangxi University of Finance and Economics.