Utilizing an outward foreign direct investment (ODI) data sample of 48 countries and districts from the year 2003 to 2010, and based on institutional distance theory, a resource-based view, an institutional-based view and political risk management theory, this paper applies multiple regression equations to explore the linkages between China’s ODI motivations, political risk, institutional distance and location choice. We obtain the following conclusions: 1) there are three different motivations affecting China’s ODI location choice, namely, resource-seeking, strategic asset-seeking and market-seeking motivations; 2) generally, China’s multinational enterprises are inclined to invest ODI in countries with high political risk and short institutional distance; and 3) multinational enterprises with different ODI motivations have diverse location choices. For resource-seeking foreign investment, Chinese multinational enterprises tend to invest in countries with high political risk and short institutional distance. For strategic asset-seeking foreign investment, Chinese multinational enterprises tend to avoid countries with high political risk and short institutional distance. For market-seeking foreign investment, multinational enterprises of China tend to avoid countries with high political risk and short institutional distance.
China is a developing country with an emerging economy, and its outward foreign direct investment (ODI) preferences and behaviors have been the subject of research. In recent years, China’s outward foreign direct investment shows a trend of accelerated development. By the end of 2012, the value of China’s foreign direct investment ranked third worldwide and first among developing countries. However, while Chinese multinational enterprises (MNEs) engaging in ODI are making prominent achievements, they are suffering from the significant political risks of host countries. This study explores how political risk affects ODI made by Chinese MNEs and is of great practical significance. In contrast to the rapid development of ODI in emerging economies, traditional ODI theory for developed and developing countries progresses slowly and may not suitably explain the level of ODI from emerging economies. China is a major emerging economies. And in the course of its rapid ODI development, China’s ODI shows many features that traditional theory cannot explain. One example is that traditional ODI theory emphasizes that MNEs could be internationalized under the conditions of their own competitive advantages. However, Chinese MNEs actively invest abroad with great success without ODI advantages. Another example is that the effects caused by host-country institutional factors for China’s ODI MNEs are inconsistent with the expectations of traditional theories. Compared with the ODI of developed countries, China’s ODI shows preferences for high political risk in location choice.
Location choice, an important strategic decision for ODI, determines the success and risk of a firm’s investment [
It can be useful to explain the behaviors of foreign direct investment in developing countries from an institutional distance perspective [
Political risk is another important factor for ODI location choice [
According to prior research, the exchange rate has some effect on foreign direct investment [
Most of the existing research assumes that either motivation of ODI or institutional factors between China and host countries are homogeneous, which ignores the different ODI effects caused by target resources or institutional factors. To facilitate a better understanding of how the resources factors and institutional factors jointly affect China’s ODI, this paper decomposes the above two factors (institution factors include institutional distance and political risk; resources factors include natural resources motivation, strategic asset motivation, and market motivation) and studies the ODI location choice affected by the resources factors and institutional factors simultaneously. In this study, we establish an analytical framework for China’s foreign direct investment motivation, political risk, institutional distance and ODI location choice to analyze their relationships within the context of China’s ODI.
We hypothesize the following:
First, both institutional factors and resources factors have some effect on the local choice of China’s ODI.
Second, there are some interactions between institutional factors and resources factors with regards to ODI.
where IF is short for institutional factors, RF is short for resources factors.
According to the principle of availability and consistency of data, this paper selects forty-eight countries and districts as a sample of host countries for China’s ODI, which that represents a huge amount of China’s ODI. The forty-eight countries and districts are as follows: Austria, Switzerland, Australia, Mexico, Belgium, Poland, Denmark, Germany, France, Finland, Korea, the Netherlands, Canada, Czech Republic, Romania, the United States, Norway, Japan, Sweden, Turkey, Spain, Greece, New Zealand, Hungary, Israel, Italy, the United Kingdom, Chile, Morocco, Argentina, Pakistan, Brazil, Russia, Ecuador, the Philippines, Colombia, Malaysia, Peru, South Africa, Saudi Arabia, Thailand, Singapore, Iran, India, Indonesia, Jordan, Hong Kong, and Vietnam. This paper uses different sources to avoid deviations due to single data source. The definitions of variables and data sources are shown in
To test the hypotheses, this paper suggests the following multiple regression equation:
. Definitions of variables and data sources.
Variable | Operational Definition or Proxy Variable | Data source | |
---|---|---|---|
Explained variables | Location Choice | ODI: The stock amount of China’s ODI in host countries | 2010 Statistical Bulletin of China’s Outward Foreign Direct Investment |
Control variables (CV) | Exchange Rate | Exch: The host-country’s official annual average exchange rate against RMB | World Bank Development Indicator |
Attitude on ODI | Op: Openness to ODI | UNCTAD ODI database | |
Geographic Distance | Dis: The geographic distance between the host and home countries | http://www.cepii.fr/welcome.asp | |
Infrastructure Construction | Mob: The number of fixed-telephones in the host-country | World Bank Development Indicator | |
Economic Risk | Inf: The host-country’s inflation rate | World Economic Outlook Database | |
Cluster | Reg: Dummy variable | World Economic Outlook Database | |
Explanatory variables Resources factors (Types of motivation, MOT for short) | ResourceSeeking Motivation | Ore: the ratio of the host country’s ore and metal exports to its merchandise exports | World Bank Development Indicator |
Strategic Asset Motivation | Pat: The host country’s total (resident plus non-resident) annual patent registrations | World Bank Development Indicator | |
Market Seeking Motivation | Gdp: The host-country’s GDP | World Bank Development Indicator | |
Moderating variables Institutional factors | Political Risk | Pr: The host country’s political risk indicator | International Country Risk Guide (ICRG) |
Institutional Distance | Id: The institutional distance between the host and home countries | World Bank Development Indicator |
where ODI denotes the stock amount of China’s ODI in host countries; MOT denotes the types of motivation of China’s ODI; CV denotes control variables, including Exch, Op, Mob, Dis, and Inf; i denotes country; t denotes time; and
Using panel data, we employ Eviews 6.0 to make the estimation regression of all variables. The descriptive statistics and correlation matrix of variables are shown in
We use the above-mentioned multiple regression equations to analyze the effects of China’s ODI motivations, political risk and institutional distance on location choices, as shown in Tables 3-5.
As shown in the tables below, we obtain several findings. First, China’s ODI MNEs tend to invest in countries with high political risk. Second, China’s ODI MNEs tend to invest in countries with short institutional distances.
. Correlation matrix of variables and VIF test.
Variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 lnODI | 1 | |||||||||||
2 Op | 0.056 | 1 | ||||||||||
3 Ore | 0.056 | 0.241 | 1 | |||||||||
4 Inf | −0.044 | 0.082 | 0.082 | 1 | ||||||||
5 Reg | −0.071 | 0.271 | 0.271 | −0.099 | 1 | |||||||
6 lnGdp | 0.345 | −0.15 | −0.15 | −0.228 | 0.219 | 1 | ||||||
7 lnPat | 0.225 | −0.216 | −0.216 | −0.226 | 0.13 | 0.84 | 1 | |||||
8 lnPr | 0.068 | 0.035 | 0.035 | 0.415 | −0.381 | −0.249 | −0.387 | 1 | ||||
9 lnMob | 0.179 | −0.048 | −0.048 | −0.332 | 0.187 | 0.251 | 0.237 | −0.439 | 1 | |||
10 lnDis | −0.294 | 0.392 | 0.392 | 0.132 | 0.686 | −0.051 | −0.233 | −0.011 | 0.056 | 1 | ||
11 lnExch | 0.125 | 0.055 | 0.055 | 0.292 | −0.367 | −0.206 | −0.105 | 0.403 | −0.407 | −0.375 | 1 | |
12 lnId | 0.113 | 0.094 | 0.094 | −0.548 | 0.241 | 0.192 | 0.254 | −0.615 | 0.414 | −0.016 | −0.299 | 1 |
Minimum | 1.946 | 0.084 | 0.001 | −0.219 | 1 | 9.23 | 1.386 | 1.846 | 0.693 | 6.863 | −0.694 | −2.303 |
Maximum | 16.807 | 1.930 | 0.648 | 0.24 | 6 | 16.496 | 12.817 | 4.02 | 5.278 | 9.867 | 9.832 | 3.664 |
Mean | 8.878 | 0.383 | 0.068 | 0.049 | 2.646 | 12.786 | 7.189 | 3.155 | 4.295 | 8.858 | 2.161 | 2.266 |
VIN | 1.338 | 1.583 | 1.597 | 2.833 | 4.158 | 4.692 | 2.445 | 1.432 | 3.213 | 1.761 | 2.06 |
. China’s ODI motivations and location choice (explained variable: ODI).
Variable | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
---|---|---|---|---|---|
Motivations | |||||
Ore | 2.361*** | 4.971*** | |||
(4.533) | (5.281) | ||||
Pat | 0.198*** | 0.432*** | |||
(3.462) | (4.735) | ||||
Gdp | 0.787*** | 1.595*** | |||
(3.652) | (11.144) | ||||
Control variables | |||||
Mob | 0.686*** | 0.146 | −0.001 | −0.182 | 0.342** |
(0.190) | (0.954) | (−0.004) | (−1.279) | (2.099) | |
Op | 1.647*** | −0.006 | 0.716* | 1.646*** | 3.325*** |
(0.410) | (−0.019) | (1.875) | (4.813) | (8.378) | |
Dis | −1.533*** | −0.711*** | −0.010 | 0.303 | −1.418*** |
(0.283) | (−2.929) | (−0.038) | (1.360) | (−4.952) | |
Exch | 0.133*** | −0.010 | 0.039 | 0.087** | 0.171*** |
(0.051) | (−0.243) | (0.939) | (2.288) | (3.861) | |
Inf | 4.629*** | 5.019*** | 5.367*** | 6.812*** | 7.957*** |
(2.492) | (2.489) | (2.674) | (3.722) | (3.829) | |
Reg | 0.523*** | −0.430*** | −0.521*** | −0.601*** | 0.355*** |
(0.121) | (−4.408) | (−5.154) | (−6.678) | (3.398) | |
R2 | 0.198 | 0.404 | 0.216 | 0.352 | 0.455 |
Adjusted R2 | 0.185 | 0.391 | 0.201 | 0.341 | 0.442 |
N | 384 | 384 | 384 | 384 | 384 |
***, ** and * indicate that the coefficient is significant at the 0.01, 0.05 and 0.1 levels, respectively.
. Political risk, institutional distance and China’s ODI location choice (explained variable: ODI).
Variable | Model 1 | Model 2 | Model 3 |
---|---|---|---|
Pr | 1.423*** | 1.481*** | |
(5.078) | (4.933) | ||
Id | −0.155** | −0.071** | |
(−2.265) | (−2.345) | ||
Ore | 5.243*** | 5.241*** | 5.133*** |
(5.741) | (5.434) | (5.484) | |
Pat | 0.255*** | 0.404*** | 0.26*** |
(2.687) | (4.312) | (2.725) | |
Gdp | 1.373*** | 1.576*** | 1.372*** |
(9.442) | (10.953) | (9.431) | |
Control Variables | |||
Mob | 3.546*** | 0.371** | 0.500*** |
(9.167) | (2.256) | (3.095) | |
Op | 3.546*** | 3.492*** | 3.48*** |
(9.167) | (8.357) | (8.586) | |
Dis | −1.698*** | −1.425*** | −1.707*** |
(−6.005) | (−4.979) | (−6.02) | |
Exch | 0.113** | 0.168*** | 0.112*** |
(2.535) | (3.774) | (2.514) | |
Inf | 5.841*** | 6.768*** | 6.286*** |
(2.842) | (2.97) | (2.84) | |
Reg | 0.581*** | 0.382*** | 0.578*** |
(5.254) | (3.587) | (5.215) | |
R2 | 0.491 | 0.458 | 0.491 |
Adjusted R2 | 0.477 | 0.443 | 0.476 |
N | 384 | 384 | 384 |
. China’s ODI motivations, political risk, institutional distance and location choice (explained variable: ODI).
Variable | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 |
---|---|---|---|---|---|---|---|
Pr | 1.167*** | 4.442*** | 11.763*** | 0.939*** | |||
(3.782) | (4.229) | (4.207) | (4.293) | ||||
Id | 0.044*** | −0.109** | −0.35*** | 0.307 | |||
(2.421) | (−2.394) | (−3.141) | (1.509) | ||||
Ore | −10.368 | 5.531*** | 5.316*** | 11.816*** | 5.500*** | 5.290*** | 17.450* |
(−1.278) | (6.086) | (5.920) | (5.506) | (5.448) | (5.369) | (1.857) | |
Pat | 0.262*** | 1.199** | 0.212** | 0.461*** | 0.61*** | 0.414*** | 1.151** |
(2.774) | (2.414) | (2.256) | (5.018) | (5.631) | (4.46) | (2.214) | |
GDP | 1.38*** | 1.284*** | 3.921*** | 1.584*** | 1.55*** | 1.148*** | 3.712*** |
(9.521) | (8.744) | (5.600) | (11.242) | (10.866) | (5.873) | (4.336) | |
ORE × Pr | 4.786* | −0.087 | |||||
(1.937) | (−0.427) | ||||||
Pat × Pr | −0.422*** | −0.027** | |||||
(−2.98) | (−2.183) | ||||||
GDP × Pr | −0.822*** | −0.083*** | |||||
(−3.717) | (−3.660) | ||||||
ORE × Id | −0.403*** | −0.574** | |||||
(−3.693) | (−2.570) | ||||||
Pat × Id | 0.016*** | 0.014 | |||||
(2.875) | (0.961) | ||||||
GDP × Id | 0.028*** | −0.024 | |||||
(3.295) | (−1.095) | ||||||
Control variables | |||||||
Mob | 3.557*** | 0.579*** | 0.631*** | 0.383** | 0.396** | 0.432*** | 0.803*** |
(9.229) | (3.592) | (3.902) | (2.373) | (2.422) | (2.630) | (5.074) | |
Op | 3.557*** | 3.924*** | 3.703*** | 2.955*** | 3.610*** | 3.353*** | 2.931*** |
(9.229) | (9.73) | (9.677) | (6.248) | (7.143) | (7.007) | (6.007) | |
Dis | −1.755*** | −1.529*** | −1.605*** | −1.462*** | −1.363*** | −1.367*** | −1.708*** |
(−6.197) | (−5.357) | (−5.750) | (−5.145) | (−4.77) | (−4.805) | (−6.026) | |
Exch | 0.127*** | 0.123*** | 0.134*** | 0.213*** | 0.176*** | 0.183*** | 0.180*** |
(2.831) | (2.79) | (3.026) | (4.728) | (3.984) | (4.149) | (4.075) | |
Inf | 6.303*** | 6.995*** | 6.931*** | 9.345*** | 8.777*** | 8.366*** | 9.558*** |
(3.057) | (3.379) | (3.394) | (4.296) | (4.024) | (3.850) | (4.589) | |
Reg | 0.626*** | 0.528*** | 0.546*** | 0.367*** | 0.298*** | 0.286*** | 0.550*** |
(5.56) | (4.763) | (5.005) | (3.231) | (2.618) | (2.518) | (4.803) | |
R2 | 0.496 | 0.503 | 0.509 | 0.476 | 0.468 | 0.472 | 0.558 |
Adjusted R2 | 0.481 | 0.488 | 0.494 | 0.461 | 0.453 | 0.456 | 0.538 |
N | 384 | 384 | 384 | 384 | 384 | 384 | 384 |
Third, the motivations of China’s ODI MNEs include market-seeking, strategic asset-seeking and resource- seeking; resource-seeking investment is the strongest motivation. Fourth, for Chinese resource-seeking foreign investment, MNEs tend to invest in countries with high political risk and short institutional distance. For strategic asset-seeking foreign investment, MNEs tend to avoid countries with high political risk and short institutional distance. For market-seeking foreign investment, MNEs tend to avoid countries with high political risk and short institutional distance.
According to Model 1 in
According to Model 2 and 5 in
According to Model 3 in
Since reforms opened up China’s economy, exports and foreign direct investment, as two main patterns of internationalization, have promoted economic growth China and increased per capita income. The official “Go Global” policy was announced in 1999, and overseas investment was officially described as one of the Five- Year Plan’s main objectives in 2001. Since then, China has integrated rapidly with the world economy by increasing its foreign investment linkages with other countries. In 2012, China was the third largest investor among all countries, up from fifth in 2011, with 179 countries and districts receiving China’s ODI. Thus, ODI is crucial to the health of the Chinese economy.
This paper analyzes the effects of resources factors and institutional factors on China’s ODI and establishes an analytic framework for the study of the interaction effects of location choice, foreign investment motivations, political risk, and institutional distance. This paper contributes to the development and improvement of the institution-based and resource-based FDI theory and enriches the background theory for Chinese foreign investment.
With a sample of ODI data for 48 countries and districts from the year 2003 to 2010, this paper applies multiple regression equations to develop an analysis of the effect of China’s ODI motivations, political risk and institutional distance on location choice. First, both political risk and institutional distance exert significant influence on China’s ODI. Generally, China’s ODI MNEs are inclined to invest in countries with high political risk and short institutional distance. Second, we find that there are various motivations for China’s ODI location choice, namely, resource-seeking, strategic asset-seeking and market-seeking motivations. Third, multinational enterprises with different ODI motivations exhibit diverse location choices. For resource-seeking foreign investment, MNEs tend to invest in countries with high political risk and short institutional distance; for strategic asset-seeking foreign investment, MNEs tend to avoid countries with high political risk and short institutional distance; and for market-seeking foreign investment, MNEs tend to avoid countries with high political risk and short institutional distance.