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摘要：外商直接投资已经被视作企业在全球扩张中的一种典型方式。通过吸收国外资金，技术或者管理经验，外商直接投资已经成为所在国家经济发展的潜在催化剂。与此同时，外国公司和他们的公司所属国也将会从外商直接投资中获得更大的利益，更低的成本等等。所以，这就不难看出外商直接投资已经日益成为一种对两国经济发展双赢的投资方式。然而，在对外投资的过程中，外国企业以及公司所属国家不得不面对一些问题，那就是如何将风险最小化。事实上，在这个过程中，风险是多种多样的，例如，政治风险，经济风险，汇率风险以及法律风险，所有的这些都将会影响外商直接投资的方向因为它将会导致企业的盈利能力下降。通过基于于1984年至2007年间，美国企业对全球43个发展中国家投资的固定样本数据作为参考，本文的实证结果能够统计地证实风险与外商直接投资流存在反向关系。
关键词：风险 外商直接投资 美国数据
Abstract：Foreign direct investment is now perceived as a classic form of business across the world. By transferring foreign capitals， technologies or managerial expertise， FDI has the potential to be a catalyst of host countries’ economic development. Meanwhile， foreign firms and their home countries could also benefit from FDI by enjoying profits， low-cost products， etc. As the result， there is no wonder why FDI has been increasingly recognized as a win-win choice of both home and host countries. However， in making or attracting overseas investment， foreign firms and host countries both face a same issue： how to minimize risks. Indeed， various risks， such as political， economic， exchange rate and legal risks， all may affect the direction of FDI because its adverse impact on firms’ profitability. By using panel data estimation based on the dataset of flows of U.S. FDI to 43 developing countries during the period of 1984 to 2007， the empirical results of this paper statistically confirmed the negative relationship between risk and flows of FDI.
Key words：Risk FDI Panel dataset
▲▲Introduction
Although tracing back to its exact origin is practically impossible， foreign direct investment （FDI） is now perceived as a classic form of business across the world. By definition， FDI refers to “an investment made to acquire lasting interest in enterprises operating outside of the economy of the investor” （International Monetary Fund， IMF， 1993）.
By receiving capital， technologies or managerial expertise， developing countries like China and India have benefited from FDI greatly， while at the same time low-cost products have entered advanced economies from developing economies， profiting both Western enterprises and consumers. Therefore， it is widely accepted that FDI is a win-win choice of both home and host countries and “a major catalyst to development” （Organization for Economic Co-operation and Development， OECD， 2002）.
Considering the following two questions， the first being how nations attract FDI and the second being how MNEs decide where to invest， there exists a short answer for both questions： to minimize risks. Indeed， given their influences in affecting firms’ profitability， various risks， such as a sudden political upheaval， a huge fluctuation in exchange rate， or an unfavourable amendment of legal provisions， etc.， are primary concerns for investors. Those risks， in particular， are more striking and common in developing countries， as those countries typically have weak and fragile political， economic and legal frameworks. Thus， minimizing risks is a key to success for both nations seeking capitals and MNEs creating FDI. ▲▲Section 1 Literature Review
1.1 A Brief Review of the History and Phenomenon of FDI
Foreign direct investment is a major form of international capital flows. It involves a physical investment by a company from one country to another （Sullivan and Sheffrin， 2003）. Foreign direct investment distinguishes itself from international portfolio investment by the degree of control of a foreign affiliate （IMF， 1993）. According to the IMF’s definition， when an investment into a foreign company is worth more than 10% of the voting power of the company， the investment is defined as a foreign direct investment. In calculation， FDI is commonly divided into three parts： equity capital， reinvested earnings and intra-company loans. However， UNCTAD （2009） pointed out that countries do not always compile with those three categories when collecting and allocating data.
To understand the incentives behind the decisions of firms in undertaking investments abroad， Seyf （2001） identified the following motivations： to explore new markets； to acquire new technologies； to overcome tariff and other protective restrictions； to enhance efficiency of servicing a foreign market by localizing production； to reduce risk by diversifying market as well as product； to be able to combat the threat of rivals in the international marketplace and so on.
1.2 Theoretical Analysis of Risks Associated with FDI
As noted at the beginning of this paper， given MNEs’ ultimate goal of maximizing profits， various risks which directly affect profitability are the primary concerns of firms who seek offshore investments. Many scholars pointed out that investing aboard carries additional risks compared with investing domestically （Lessard， 1996； Musonera， 2008）. Those additional risks which were frequently mentioned in previous studies include political risk， economic risk， exchange rate risk， legal risk， sovereign risk， and so on.
Political Risk
One common concept given to political risk is known as “the actions of national governments which interfere with or prevent business transactions， or change the terms of agreements， or cause the confiscation of wholly or partially foreign owned business property” （Weston and Sorge， 1972）. In this context， political risk partially represents the concept of legal risk. Especially， in many developing countries， administrative authorities hold tremendous influences over the operation of the judicial systems， which means that some judicial actions against foreign firms may be reflections of political decisions. However， Robock （1971） criticized the opinion by pointing out that “political fluctuations which do not change the business environment significantly do not represent risk for international business”. Economic Risk
Economic risk of host countries ranks high in the list of risks associated with FDI， as Musonera （2008） claimed that “the level of economic activity of a country sets the stage for business operations.” Meldrum （2000） defined economic risk as a significant change in the economic structure or growth rate that produces a major change in the expected return of an investment. This definition makes it clear that FDI are subject to the economic factors of host countries， as it affects the profitability of MNEs.
Exchange Rate Risk
Exchange rate risk has become an increasingly highlighted risk since the collapse of the Bretton Woods system in the early 1970s which marked the end of fixed exchange rates regime among world’s major economies （Schmidt and Broll， 2008）. In general， exchange rate risk refers to “the effect that unanticipated exchange rate changes have on the value of the firm” （Giddy and Dufey， 1997）. More specifically， it is a risk stemming from changes in the exchange rates for different currencies and affecting investments and business operations of companies undertaking international business （BNET， 2007）.
Legal risk
A sound legal environment is considered to be crucial to investors， especially foreign investors， in operating their businesses. Perry-Kessaris （2003） pointed out that it is common to argue that the direction of FDI to some extent depends on the effectiveness of destination countries’ legal systems. Contrary to such a sound legal environment which possesses characteristics including transparency， certainty， accountability， and consistency， etc.， legal risk arises from uncertainty due to “legal actions or uncertainty in the applicability or interpretation of contracts， laws or regulations” （Riskglossary.com， 2004）.
1.3 Previous Empirical Studies on the Relationship between Risks and FDI
Ramcharran （1999） pointed out that there are two types of empirical studies – “survey method” and “statistical analysis” in analyzing the correlation between country risk and FDI. In using the survey method， researchers typically request a large number of executives from different multinational firms to rank or list risks which may affect their overseas investment decisions. By employing this method， Basi （1963）， Aharoni （1966）， and Agodo （1978） among others found that the risk mangers concern the most is political risk. Obviously， a common criticism regarding the survey method is solely dependent on respondents’ subjectivity （Kobrin， 1979； Brewer， 1981）. The statistical analysis requires the use of econometric techniques. Ordinary least square estimation is a fundamental technique applied by researchers when studying the relationship between country risk and FDI. Also， panel data is often employed and fixed or random effect can be applied depending on the current circumstances.
▲▲2 Empirical Studies
2.1 Methodology
This paper studies the relationship between risks and FDI focusing on the U.S. outward FDI flows in 43 developing countries during the period of 1984 to 2007. The choice of this period allows the empirical analysis of this paper to be based on a more recent time spam than most of previous studies. In analyzing the impact of various risks on FDI flows， panel dataset is employed in this paper. As Hsiao （2003） and Baltagi （2005） identified， applying panel data analysis has the following advantages. Firstly， panel data analysis controls individual heterogeneity in the way illustrated later. Secondly， effects that are not detectable in cross-sectional or time-series dataset will be captured by panel data analysis. Thirdly， more complicated behavioural models are able to be constructed and tested in panel data analysis. Finally， panel data analysis offers more variability， reduces collinearity among variables， and enhances degrees of freedom and efficiency.
The regression model applied in the estimation is stated as follow：
（1）
where ， and .
In the model， is the amount of U.S. outward FDI to country at time ， is a vector of variables including controls as well as key variables that are under primary interest. is the time invariant country specific characteristics and is the error term that varies both across time and countries.
By using panel dataset， this paper applies “fixed effect” in estimating the regression equation above. It is assumed the country specific effect is correlated with the explanatory variables. One of the major advantages of using fixed effect is that this econometric technique eliminates the country specific characteristics before estimation. If such characteristics exist， the regression results are likely to be biased. For example， a MNE’s decision to invest into a particular country may be based on that country’s specific location and culture. However， those country specific features may well correlate with variables that are included in the regression equation， making the estimation results biased because some of the effects of time invariant variables that are not included in the equation have been absorbed by variables that are included in the equation. The following steps illustrate how the within estimation solves this potential problem. Firstly， by taking the equation above and average across time we obtain （2）
where .
Secondly， by subtracting （2） from （1） we have
（3）
It can be seen from （3） that the country specific characteristic is eliminated. Therefore， （3） is the final equation to be estimated and the technique is referred as fixed， or within estimation. Furthermore， robust standard error is applied through the Fixed Effect estimations.
Based on the above model and the availability of data， the general form of the estimation equation can be written as below：
FDI = FDI （economic risk， political risk， control variables）
where economic risk is measured by inflation rates of host countries， political risk is measured by the indices of bureaucracy quality and democratic accountability of host countries， both issued in the International Country Risk Guide （ICRG）. Control variables include gross domestic product （GDP） per capita and exchange rates of host countries.
It is important and necessary to include variables which also affect flows of U.S. outward FDI along with various risk factors in the regression estimation. This is because if those variables are excluded， their effects on the flows of U.S. outward FDI will be captured by the error term. Given the potential correlation between those variables and various types of risks， the error term in the regression equation will be correlated with the key risk variables that are under primary interest. As a result， it leads to the violation of Gauss-Markov conditions which biases the estimation results.
The reason why exchange rates act as a control variable here rather than a measure of exchange rates risk results from the unavailability of daily， monthly or quarterly exchange rates between the U.S. and host countries， which restricts the calculation of volatilities of exchange rates used to measure exchange rates risk.
According to above analysis， an appropriate empirical model for analyzing the relationship between flows of the U.S. outward FDI and political and economic risks can be given in the following linear form.
where ， and .
In the equation， denotes flows of U.S. outward FDI into country i in year t ； denotes inflation rate of country i in year t ； denotes bureaucracy quality of country i in year t ； denotes democratic accountability of country i in year t ； denotes average official exchange rate in a year between the U.S. and country i in year t ； country i in year t ； country i in year t ； denotes GDP per capita of country i in year t . Besides， β0 is a constant； βs are estimated coefficients of each variable； εis an error term with a zero conditional mean. The justification of all independent variables is shown as follows：
1. Inflation rate. Acting as a proxy of economic risk， inflation rate is expected to have a negative correlation with flows of U.S. outward FDI. That is， other things being equal， when a country’s inflation rate increases， especially when it increases sharply， U.S. outward FDI to that country is expect to decrease， because a higher inflation rate indicates lower macroeconomic stability and higher risk， vice versa.
2. Bureaucracy quality. Bureaucracy quality is an indicator of political risk. According to the PRS Group （2009） who is responsible for the conducting of ICRG， bureaucracy quality measures “the institutional strength and quality of the bureaucracy”. It is rated between 0 and 4 with 0 indicating the lowest bureaucracy quality and the highest political risk because of drastic changes in policy or interruptions in government services （ICRG， 2009） and 4 indicating the highest bureaucracy quality and the lowest political risk. Thus， it is expected to have a negative correlation between bureaucracy quality and FDI. That is， other things being equal， when a country is assigned a low rating of bureaucracy quality， suggesting the country has high political risk， flows of U.S. outward FDI to that country is expected to be low， vice versa.
3. Democratic accountability. Democratic accountability is another proxy of political risk. It measures the responsiveness of a government to its citizens such that the irresponsiveness may cause the failure of the government （ICRG， 2009）. Countries are rated between 0 and 6 in terms of their democratic accountabilities. The higher a country is rated， the lower the political risk of that country possesses and vice versa. Hence， a negative correlation between democratic accountability and flows of U.S. outward FDI is expected.
4. GDP per capita. GDP per capita represents the size of a country’s economy. One of the main incentives for MNEs to invest abroad directly is to gain access to foreign market. As a result， countries with higher GDP per capita are likely to attract more FDI from the U.S.， ceteris paribus. To analyse the effects of different risks on U.S. FDI outflow， it is necessary to control for GDP per capita of the host countries， otherwise， estimated coefficients may be biased as different forms of risks of a country is likely to be correlated with its level of GDP per capita.
5. Exchange rate. Exchange rate is measured in terms of local currency units per U.S. dollar， so that an increase in exchange rate indicates a depreciation of a host country’s currency. As explained earlier， exchange rate is a control variable in the regression， which means that it acts as a general determinant of the flows of U.S. outward FDI. Thus， exchange rate is expected to positively correlate with the flows of U.S. outward FDI， ceteris paribus. The rationale behind this expected relationship is that when a country’s currency depreciates， foreign firms homed in another country with a relatively stronger currency would have their production costs reduced and profitability increased. 2.2 Data Sources
The flows of U.S. outward FDI are obtained from the website of the Bureau of Economic Analysis （BEA） of the U.S. Department of Commerce. The data have been adjusted into constant 2000 U.S. dollars in the unit of million.
Variables including inflation rate， GDP per capita and exchange rate come from the World Development Indicators （WDI） in the version of June， 2009. WDI is conducted by the World Bank and published on the Bank’s website. In the empirical studies， inflation rates of individual countries are given in decimal. Data of GDP per capita are in constant 2000 U.S. dollars. Exchange rates are real exchange rates derived from official ones. The reason of using official exchange rates is that although they may undervalue or overvalue domestic currencies， given MNEs have to transfer funds through legal channels in most cases， it is these rates concerning MNEs.
As noted previously， two risk measures of bureaucracy quality and democratic accountability are conducted by the International Country Risk Guide， a product of the PRS Group.
2.3 Data Description
Table 1 illustrates the statistics of variables contained in the regression which shows numbers of observations， means， standard deviations， minimums and maximums of both dependent variable and independent variables. While the dependent variable of the flows of U.S. outward FDI and three independent variables of GDP per capita， inflation rate， and exchange rate has substantial variation， the other two independent variables， namely bureaucracy quality and democratic accountability， only have very small variations because of their rating-based characteristic.
Table 2 presents the correlation matrix of independent variables included in the regression equation. The correlation coefficients among those independent variables are in the range of -0.0815 to 0.3337， indicating it is unlikely to have the problem of severe multicollinearity.
2.4 Empirical Results
Table 3 Regression estimates of each independent variables
Independent Variables Coefficients Robust Standard Errors P-values
GDPPC 3.015874 .6543028 0.000***
INFL -1.124499 .6546437 0.086*
EXRATE .0483234 .0288662 0.094*
BQ 859.2279 283.2691 0.002***
DA 399.4627 161.8561 0.014**
*** Statistical significance at 1% level； ** Statistical significance at 5% level； * Statistical significance at 10% level
Table 3 displays the parameter estimates of both risk factors and control variables by using fixed-effect. Satisfactorily， coefficients of all variables have the signs as theories suggest and are statistically significant 10% significant level with bureaucracy quality and GDP per capita being significant at 5% and 1% levels respectively. Looking separately， inflation rate， which acts as a measure of economic risk， indicates that higher economic risk of a country tends to reduce flows of FDI from the U.S. to that country， ceteris paribus. As two political risk indicators， the coefficients of bureaucracy quality and democratic accountability suggest that U.S. investors are very concerned by a foreign country’s political risk. In other words， when a country’s political risk level is lifted by a professional institution， such as the PGS group in this case， flows of U.S. outward FDI to that country tend to decrease substantially. This finding is consistent with the results of recent empirical studies that political risk and flows of U.S. outward FDI are positively correlated with each other. In terms of control variables， GDP per capita indicates that when a country’s market gets bigger， U.S. investors will make more investment to that country， in part to serve the purpose of exploring a new market or better serving a foreign market. The coefficient of exchange rate demonstrates that exchange rate does not affect flows of U.S. outward FDI strongly. One reason may be U.S. firms’ capacities to use hedging instruments against some unfavourable exchange rate movements.
▲▲3. Conclusion
3.1 Evaluation
Admittedly， although the results of empirical studies are rather reasonable and satisfactory， there exist several drawbacks in the paper. One major shortcoming， as mentioned in the section of introduction， is the severe data limitation which prevents the paper from studying more risks together and comprehensively. Exchange rate risk and legal risk were not included in the empirical studies， instead， they were analyzed theoretically in the section of literature review.
Moreover， as shown in table 2， the independent variables of bureaucracy quality and democratic accountability are measured at a limited scale and thus have very small variations as a result of their rating-based characteristic， therefore the variables are not as informative as otherwise they would be， causing the regression results less precise. However， if measurements of the two variables were rated at a larger scale， they would be more informative and the preciseness of the regression’s estimates can be improved.
3.2 End Remarks
It has been widely recognized that FDI benefits both enterprises who operating business abroad and countries who receive foreign capitals. However， a common issue that draws attentions from firms and countries is the various risks associated with FDI. Indeed， empirical results of this paper demonstrate that when risks of a country undermine the profitability of foreign firms， it also means that the attractiveness of the country to foreign firms falls. Furthermore， the results show that political risk has substantial influence on the direction of a foreign firm’s overseas investment， regardless how political risk is measured. Besides， although economic risk is measured by inflation rate only， the result still highlights the adverse impact of economic risk on the flows of U.S. outward FDI. There is no doubt that political risk and economic risk are not the only risks concerning a foreign investor. Subject to the severe limitation of data， this paper fails to empirically assess other risks associated with FDI. However， the paper does not arbitrarily lead to the conclusion that other risks have no effect on FDI. To the contrary， given the feature that political risk overlaps with legal risk to some extent， together with the fact that this overlapping is more striking in developing countries who are also the subject of this paper， it can be argued that the high coefficients of two political risk factors hint the possible existence of the effect of legal risk on FDI.
References：
[1]Busse， Matthias and Carsten Hefeker， 2005. “Political Risk， Institutions and Foreign Direct Investment”， HWWA Discussion Paper 315.
[2]Fitzpatrick， Mark， 1983. “The Definition and Assessment of Political Risk in International Business： A Review of the Literature”， Academy of Management Review， 1983， Vol. 8， No.2， pp. 249-254.
[3]Goldberg， Linda S.， 1993. “Exchange Rates and Investment in United States Industry”， The Review of Economics and Statistics， Vol. LXXV， No.4.
[4]Korbin， Stephen J.， 1981. “Political assessment by international firms – Models or Methodologies”， Journal of Policy Modeling， 1983， Vol. 3， Issue 2， pp. 251-270.
【作者简介】姓名：王博 出生年月：1988年4月16日 性别：男 民族：汉 籍贯：北京 学历：硕士 研究方向：金融
（责任编辑：罗亦成）
关键词：风险 外商直接投资 美国数据
Abstract：Foreign direct investment is now perceived as a classic form of business across the world. By transferring foreign capitals， technologies or managerial expertise， FDI has the potential to be a catalyst of host countries’ economic development. Meanwhile， foreign firms and their home countries could also benefit from FDI by enjoying profits， low-cost products， etc. As the result， there is no wonder why FDI has been increasingly recognized as a win-win choice of both home and host countries. However， in making or attracting overseas investment， foreign firms and host countries both face a same issue： how to minimize risks. Indeed， various risks， such as political， economic， exchange rate and legal risks， all may affect the direction of FDI because its adverse impact on firms’ profitability. By using panel data estimation based on the dataset of flows of U.S. FDI to 43 developing countries during the period of 1984 to 2007， the empirical results of this paper statistically confirmed the negative relationship between risk and flows of FDI.
Key words：Risk FDI Panel dataset
▲▲Introduction
Although tracing back to its exact origin is practically impossible， foreign direct investment （FDI） is now perceived as a classic form of business across the world. By definition， FDI refers to “an investment made to acquire lasting interest in enterprises operating outside of the economy of the investor” （International Monetary Fund， IMF， 1993）.
By receiving capital， technologies or managerial expertise， developing countries like China and India have benefited from FDI greatly， while at the same time low-cost products have entered advanced economies from developing economies， profiting both Western enterprises and consumers. Therefore， it is widely accepted that FDI is a win-win choice of both home and host countries and “a major catalyst to development” （Organization for Economic Co-operation and Development， OECD， 2002）.
Considering the following two questions， the first being how nations attract FDI and the second being how MNEs decide where to invest， there exists a short answer for both questions： to minimize risks. Indeed， given their influences in affecting firms’ profitability， various risks， such as a sudden political upheaval， a huge fluctuation in exchange rate， or an unfavourable amendment of legal provisions， etc.， are primary concerns for investors. Those risks， in particular， are more striking and common in developing countries， as those countries typically have weak and fragile political， economic and legal frameworks. Thus， minimizing risks is a key to success for both nations seeking capitals and MNEs creating FDI. ▲▲Section 1 Literature Review
1.1 A Brief Review of the History and Phenomenon of FDI
Foreign direct investment is a major form of international capital flows. It involves a physical investment by a company from one country to another （Sullivan and Sheffrin， 2003）. Foreign direct investment distinguishes itself from international portfolio investment by the degree of control of a foreign affiliate （IMF， 1993）. According to the IMF’s definition， when an investment into a foreign company is worth more than 10% of the voting power of the company， the investment is defined as a foreign direct investment. In calculation， FDI is commonly divided into three parts： equity capital， reinvested earnings and intra-company loans. However， UNCTAD （2009） pointed out that countries do not always compile with those three categories when collecting and allocating data.
To understand the incentives behind the decisions of firms in undertaking investments abroad， Seyf （2001） identified the following motivations： to explore new markets； to acquire new technologies； to overcome tariff and other protective restrictions； to enhance efficiency of servicing a foreign market by localizing production； to reduce risk by diversifying market as well as product； to be able to combat the threat of rivals in the international marketplace and so on.
1.2 Theoretical Analysis of Risks Associated with FDI
As noted at the beginning of this paper， given MNEs’ ultimate goal of maximizing profits， various risks which directly affect profitability are the primary concerns of firms who seek offshore investments. Many scholars pointed out that investing aboard carries additional risks compared with investing domestically （Lessard， 1996； Musonera， 2008）. Those additional risks which were frequently mentioned in previous studies include political risk， economic risk， exchange rate risk， legal risk， sovereign risk， and so on.
Political Risk
One common concept given to political risk is known as “the actions of national governments which interfere with or prevent business transactions， or change the terms of agreements， or cause the confiscation of wholly or partially foreign owned business property” （Weston and Sorge， 1972）. In this context， political risk partially represents the concept of legal risk. Especially， in many developing countries， administrative authorities hold tremendous influences over the operation of the judicial systems， which means that some judicial actions against foreign firms may be reflections of political decisions. However， Robock （1971） criticized the opinion by pointing out that “political fluctuations which do not change the business environment significantly do not represent risk for international business”. Economic Risk
Economic risk of host countries ranks high in the list of risks associated with FDI， as Musonera （2008） claimed that “the level of economic activity of a country sets the stage for business operations.” Meldrum （2000） defined economic risk as a significant change in the economic structure or growth rate that produces a major change in the expected return of an investment. This definition makes it clear that FDI are subject to the economic factors of host countries， as it affects the profitability of MNEs.
Exchange Rate Risk
Exchange rate risk has become an increasingly highlighted risk since the collapse of the Bretton Woods system in the early 1970s which marked the end of fixed exchange rates regime among world’s major economies （Schmidt and Broll， 2008）. In general， exchange rate risk refers to “the effect that unanticipated exchange rate changes have on the value of the firm” （Giddy and Dufey， 1997）. More specifically， it is a risk stemming from changes in the exchange rates for different currencies and affecting investments and business operations of companies undertaking international business （BNET， 2007）.
Legal risk
A sound legal environment is considered to be crucial to investors， especially foreign investors， in operating their businesses. Perry-Kessaris （2003） pointed out that it is common to argue that the direction of FDI to some extent depends on the effectiveness of destination countries’ legal systems. Contrary to such a sound legal environment which possesses characteristics including transparency， certainty， accountability， and consistency， etc.， legal risk arises from uncertainty due to “legal actions or uncertainty in the applicability or interpretation of contracts， laws or regulations” （Riskglossary.com， 2004）.
1.3 Previous Empirical Studies on the Relationship between Risks and FDI
Ramcharran （1999） pointed out that there are two types of empirical studies – “survey method” and “statistical analysis” in analyzing the correlation between country risk and FDI. In using the survey method， researchers typically request a large number of executives from different multinational firms to rank or list risks which may affect their overseas investment decisions. By employing this method， Basi （1963）， Aharoni （1966）， and Agodo （1978） among others found that the risk mangers concern the most is political risk. Obviously， a common criticism regarding the survey method is solely dependent on respondents’ subjectivity （Kobrin， 1979； Brewer， 1981）. The statistical analysis requires the use of econometric techniques. Ordinary least square estimation is a fundamental technique applied by researchers when studying the relationship between country risk and FDI. Also， panel data is often employed and fixed or random effect can be applied depending on the current circumstances.
▲▲2 Empirical Studies
2.1 Methodology
This paper studies the relationship between risks and FDI focusing on the U.S. outward FDI flows in 43 developing countries during the period of 1984 to 2007. The choice of this period allows the empirical analysis of this paper to be based on a more recent time spam than most of previous studies. In analyzing the impact of various risks on FDI flows， panel dataset is employed in this paper. As Hsiao （2003） and Baltagi （2005） identified， applying panel data analysis has the following advantages. Firstly， panel data analysis controls individual heterogeneity in the way illustrated later. Secondly， effects that are not detectable in cross-sectional or time-series dataset will be captured by panel data analysis. Thirdly， more complicated behavioural models are able to be constructed and tested in panel data analysis. Finally， panel data analysis offers more variability， reduces collinearity among variables， and enhances degrees of freedom and efficiency.
The regression model applied in the estimation is stated as follow：
（1）
where ， and .
In the model， is the amount of U.S. outward FDI to country at time ， is a vector of variables including controls as well as key variables that are under primary interest. is the time invariant country specific characteristics and is the error term that varies both across time and countries.
By using panel dataset， this paper applies “fixed effect” in estimating the regression equation above. It is assumed the country specific effect is correlated with the explanatory variables. One of the major advantages of using fixed effect is that this econometric technique eliminates the country specific characteristics before estimation. If such characteristics exist， the regression results are likely to be biased. For example， a MNE’s decision to invest into a particular country may be based on that country’s specific location and culture. However， those country specific features may well correlate with variables that are included in the regression equation， making the estimation results biased because some of the effects of time invariant variables that are not included in the equation have been absorbed by variables that are included in the equation. The following steps illustrate how the within estimation solves this potential problem. Firstly， by taking the equation above and average across time we obtain （2）
where .
Secondly， by subtracting （2） from （1） we have
（3）
It can be seen from （3） that the country specific characteristic is eliminated. Therefore， （3） is the final equation to be estimated and the technique is referred as fixed， or within estimation. Furthermore， robust standard error is applied through the Fixed Effect estimations.
Based on the above model and the availability of data， the general form of the estimation equation can be written as below：
FDI = FDI （economic risk， political risk， control variables）
where economic risk is measured by inflation rates of host countries， political risk is measured by the indices of bureaucracy quality and democratic accountability of host countries， both issued in the International Country Risk Guide （ICRG）. Control variables include gross domestic product （GDP） per capita and exchange rates of host countries.
It is important and necessary to include variables which also affect flows of U.S. outward FDI along with various risk factors in the regression estimation. This is because if those variables are excluded， their effects on the flows of U.S. outward FDI will be captured by the error term. Given the potential correlation between those variables and various types of risks， the error term in the regression equation will be correlated with the key risk variables that are under primary interest. As a result， it leads to the violation of Gauss-Markov conditions which biases the estimation results.
The reason why exchange rates act as a control variable here rather than a measure of exchange rates risk results from the unavailability of daily， monthly or quarterly exchange rates between the U.S. and host countries， which restricts the calculation of volatilities of exchange rates used to measure exchange rates risk.
According to above analysis， an appropriate empirical model for analyzing the relationship between flows of the U.S. outward FDI and political and economic risks can be given in the following linear form.
where ， and .
In the equation， denotes flows of U.S. outward FDI into country i in year t ； denotes inflation rate of country i in year t ； denotes bureaucracy quality of country i in year t ； denotes democratic accountability of country i in year t ； denotes average official exchange rate in a year between the U.S. and country i in year t ； country i in year t ； country i in year t ； denotes GDP per capita of country i in year t . Besides， β0 is a constant； βs are estimated coefficients of each variable； εis an error term with a zero conditional mean. The justification of all independent variables is shown as follows：
1. Inflation rate. Acting as a proxy of economic risk， inflation rate is expected to have a negative correlation with flows of U.S. outward FDI. That is， other things being equal， when a country’s inflation rate increases， especially when it increases sharply， U.S. outward FDI to that country is expect to decrease， because a higher inflation rate indicates lower macroeconomic stability and higher risk， vice versa.
2. Bureaucracy quality. Bureaucracy quality is an indicator of political risk. According to the PRS Group （2009） who is responsible for the conducting of ICRG， bureaucracy quality measures “the institutional strength and quality of the bureaucracy”. It is rated between 0 and 4 with 0 indicating the lowest bureaucracy quality and the highest political risk because of drastic changes in policy or interruptions in government services （ICRG， 2009） and 4 indicating the highest bureaucracy quality and the lowest political risk. Thus， it is expected to have a negative correlation between bureaucracy quality and FDI. That is， other things being equal， when a country is assigned a low rating of bureaucracy quality， suggesting the country has high political risk， flows of U.S. outward FDI to that country is expected to be low， vice versa.
3. Democratic accountability. Democratic accountability is another proxy of political risk. It measures the responsiveness of a government to its citizens such that the irresponsiveness may cause the failure of the government （ICRG， 2009）. Countries are rated between 0 and 6 in terms of their democratic accountabilities. The higher a country is rated， the lower the political risk of that country possesses and vice versa. Hence， a negative correlation between democratic accountability and flows of U.S. outward FDI is expected.
4. GDP per capita. GDP per capita represents the size of a country’s economy. One of the main incentives for MNEs to invest abroad directly is to gain access to foreign market. As a result， countries with higher GDP per capita are likely to attract more FDI from the U.S.， ceteris paribus. To analyse the effects of different risks on U.S. FDI outflow， it is necessary to control for GDP per capita of the host countries， otherwise， estimated coefficients may be biased as different forms of risks of a country is likely to be correlated with its level of GDP per capita.
5. Exchange rate. Exchange rate is measured in terms of local currency units per U.S. dollar， so that an increase in exchange rate indicates a depreciation of a host country’s currency. As explained earlier， exchange rate is a control variable in the regression， which means that it acts as a general determinant of the flows of U.S. outward FDI. Thus， exchange rate is expected to positively correlate with the flows of U.S. outward FDI， ceteris paribus. The rationale behind this expected relationship is that when a country’s currency depreciates， foreign firms homed in another country with a relatively stronger currency would have their production costs reduced and profitability increased. 2.2 Data Sources
The flows of U.S. outward FDI are obtained from the website of the Bureau of Economic Analysis （BEA） of the U.S. Department of Commerce. The data have been adjusted into constant 2000 U.S. dollars in the unit of million.
Variables including inflation rate， GDP per capita and exchange rate come from the World Development Indicators （WDI） in the version of June， 2009. WDI is conducted by the World Bank and published on the Bank’s website. In the empirical studies， inflation rates of individual countries are given in decimal. Data of GDP per capita are in constant 2000 U.S. dollars. Exchange rates are real exchange rates derived from official ones. The reason of using official exchange rates is that although they may undervalue or overvalue domestic currencies， given MNEs have to transfer funds through legal channels in most cases， it is these rates concerning MNEs.
As noted previously， two risk measures of bureaucracy quality and democratic accountability are conducted by the International Country Risk Guide， a product of the PRS Group.
2.3 Data Description
Table 1 illustrates the statistics of variables contained in the regression which shows numbers of observations， means， standard deviations， minimums and maximums of both dependent variable and independent variables. While the dependent variable of the flows of U.S. outward FDI and three independent variables of GDP per capita， inflation rate， and exchange rate has substantial variation， the other two independent variables， namely bureaucracy quality and democratic accountability， only have very small variations because of their rating-based characteristic.
Table 2 presents the correlation matrix of independent variables included in the regression equation. The correlation coefficients among those independent variables are in the range of -0.0815 to 0.3337， indicating it is unlikely to have the problem of severe multicollinearity.
2.4 Empirical Results
Table 3 Regression estimates of each independent variables
Independent Variables Coefficients Robust Standard Errors P-values
GDPPC 3.015874 .6543028 0.000***
INFL -1.124499 .6546437 0.086*
EXRATE .0483234 .0288662 0.094*
BQ 859.2279 283.2691 0.002***
DA 399.4627 161.8561 0.014**
*** Statistical significance at 1% level； ** Statistical significance at 5% level； * Statistical significance at 10% level
Table 3 displays the parameter estimates of both risk factors and control variables by using fixed-effect. Satisfactorily， coefficients of all variables have the signs as theories suggest and are statistically significant 10% significant level with bureaucracy quality and GDP per capita being significant at 5% and 1% levels respectively. Looking separately， inflation rate， which acts as a measure of economic risk， indicates that higher economic risk of a country tends to reduce flows of FDI from the U.S. to that country， ceteris paribus. As two political risk indicators， the coefficients of bureaucracy quality and democratic accountability suggest that U.S. investors are very concerned by a foreign country’s political risk. In other words， when a country’s political risk level is lifted by a professional institution， such as the PGS group in this case， flows of U.S. outward FDI to that country tend to decrease substantially. This finding is consistent with the results of recent empirical studies that political risk and flows of U.S. outward FDI are positively correlated with each other. In terms of control variables， GDP per capita indicates that when a country’s market gets bigger， U.S. investors will make more investment to that country， in part to serve the purpose of exploring a new market or better serving a foreign market. The coefficient of exchange rate demonstrates that exchange rate does not affect flows of U.S. outward FDI strongly. One reason may be U.S. firms’ capacities to use hedging instruments against some unfavourable exchange rate movements.
▲▲3. Conclusion
3.1 Evaluation
Admittedly， although the results of empirical studies are rather reasonable and satisfactory， there exist several drawbacks in the paper. One major shortcoming， as mentioned in the section of introduction， is the severe data limitation which prevents the paper from studying more risks together and comprehensively. Exchange rate risk and legal risk were not included in the empirical studies， instead， they were analyzed theoretically in the section of literature review.
Moreover， as shown in table 2， the independent variables of bureaucracy quality and democratic accountability are measured at a limited scale and thus have very small variations as a result of their rating-based characteristic， therefore the variables are not as informative as otherwise they would be， causing the regression results less precise. However， if measurements of the two variables were rated at a larger scale， they would be more informative and the preciseness of the regression’s estimates can be improved.
3.2 End Remarks
It has been widely recognized that FDI benefits both enterprises who operating business abroad and countries who receive foreign capitals. However， a common issue that draws attentions from firms and countries is the various risks associated with FDI. Indeed， empirical results of this paper demonstrate that when risks of a country undermine the profitability of foreign firms， it also means that the attractiveness of the country to foreign firms falls. Furthermore， the results show that political risk has substantial influence on the direction of a foreign firm’s overseas investment， regardless how political risk is measured. Besides， although economic risk is measured by inflation rate only， the result still highlights the adverse impact of economic risk on the flows of U.S. outward FDI. There is no doubt that political risk and economic risk are not the only risks concerning a foreign investor. Subject to the severe limitation of data， this paper fails to empirically assess other risks associated with FDI. However， the paper does not arbitrarily lead to the conclusion that other risks have no effect on FDI. To the contrary， given the feature that political risk overlaps with legal risk to some extent， together with the fact that this overlapping is more striking in developing countries who are also the subject of this paper， it can be argued that the high coefficients of two political risk factors hint the possible existence of the effect of legal risk on FDI.
References：
[1]Busse， Matthias and Carsten Hefeker， 2005. “Political Risk， Institutions and Foreign Direct Investment”， HWWA Discussion Paper 315.
[2]Fitzpatrick， Mark， 1983. “The Definition and Assessment of Political Risk in International Business： A Review of the Literature”， Academy of Management Review， 1983， Vol. 8， No.2， pp. 249-254.
[3]Goldberg， Linda S.， 1993. “Exchange Rates and Investment in United States Industry”， The Review of Economics and Statistics， Vol. LXXV， No.4.
[4]Korbin， Stephen J.， 1981. “Political assessment by international firms – Models or Methodologies”， Journal of Policy Modeling， 1983， Vol. 3， Issue 2， pp. 251-270.
【作者简介】姓名：王博 出生年月：1988年4月16日 性别：男 民族：汉 籍贯：北京 学历：硕士 研究方向：金融
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