Macro Determinants of Inward FDI to China:
A study from the differentials of country factor
perspective
The University of Groningen
The Faculty of Management and Organization
9747 AB Groningen, the Netherlands
October 31, 2007
Chen, Lie
Macro determinants of inward FDI to China:
A study from the differentials of country factor
perspective
University of Groningen
Acknowledgement: This paper is written as a Master degree thesis in the International Business and Management field at the University of Groningen, the Netherlands. After three months (During the period from 3rd of August to 31st of October) intensive work, I would really like to thank my supervisor Mr. I. Haxhi who showed great patience with my thesis and gave me many instructive comments. And I also appreciate the help from several of my friends who collected the data from China National Library, and assisted me with the statistical test.
Chen, Lie
Abstract
Given the tremendous growth of foreign direct investment (FDI) in China during last decade, this study explores the country factors differentials between China and its source countries to explain the inward FDI in China from 1985 to 2006. More specifically, we formulate five hypotheses linking the inward FDI to five economic and financial differentials (exchange rate, lending cost, market potential, market size and labor cost). Based on data from 15 home countries over a 23-year period, the statistical results show that the relative lower lending cost of home countries, the relative bigger host potential market and the its lower labor cost of host country contribute significantly to the China FDI inflow; however, the exchange rate and market size differentials do not show any significance for this respect.
Table of Content
1. Introduction………..….1
2. Literature Review………..………...5
3. Data and Method ……….….…..……….14
4. Results………..……….…18
5. Conclusion……..………..………...23
6. References………..….……….26
Introduction
During the past two decades, the foreign direct investment (FDI) has been significantly observed in a variety of directions, as well as the academic literatures to analyze and explain this issue from both the host country and the source country perspective. A major concern in this academic field today is to explore the phenomenon of the huge FDI inflow to China in accordance with its crucial position of FDI in the global. It is worth noting that since 1979, China launched the economic reforms and called for foreign capital participation in its economy, China has received a large part of international direct investment flows and has become the second largest FDI recipient in the world, after the United States; and the largest host country among developing countries. Actually, China’s position as a host of FDI is too far removed from any other developing country – and most developed countries – to be equaled. For twenty years (1979-1999), actual FDI inflows into China during this period amounted to US$306 billion, which is equivalent to 10 per cent of direct investment worldwide and about 30 per cent of the investment amount for all the developing countries put together( OECD working paper 2000/4). To day, China also kept its world's leading destination of FDI in recent years; especially in 2003, China attracted $53 billion compared to $40 billion of the U.S. economy to be the largest recipient of FDI all over the world (OECD observer). Meanwhile, China also maintained its development miracle of the GDP annual grow around 10%, and made a great progress in developing a policy framework to create good FDI environment burring the last decade (OECD 2003).
hence Chinese currency may possibly exert more flexible and stranger impact on the FID flows. Thus, it has become plausible that these ‘old’ results from the previous studies could still constantly explain the China FDI inflow in the today’s situation. For this reason, we believe that it is still necessary and critical to have a new and clear understanding of whether the country factor determinants still have the significant impact on the China FDI inflow in the recent situation.
In the present study, we explore the tremendous FDI inflow in China by examining a set of economic and finical factors across 15 source countries during the period from 1985 to 2006. More specifically, we formulate five hypotheses linking the Chinese inward FDI to five economic and financial differentials (exchange rate, lending cost, market potential, market size and labor cost).
In terms of method, observably, the increasing inflow of FDI to China is only made possible by the liberalizing regulation introduced since the early 1980s and by the constant investment environment improved by Chinese government; specifically, after examining the data availability, this study will use the data of range from 1985. As the extension of the previous studies, we formulated 5 hypotheses which are commonly used by the previous analyses. Afterwards, these hypotheses are utilized to examine the determents of the China FDI inflow by running the panel data statistical test. The model used in this paper is multivariate regression models; and the data are pooled time-series, cross-section observations of foreign direct investment in China and related factors from the various countries of origin.
understanding about the significant contributing factors of impacting the China FDI inflows among the new situation. By adding the latest data in this field, it also presents updating evidence with previous studies which were the perspective of macro factors differentials between China and its source counties.
Literature Review
The theoretical reasoning for this study primarily derives from the previous existing literatures in this field (Bajo-Rubio and Sosvilla-Rivero, 1994; Bhagwati, Dinopoulos and Wong, 1992; Schneider and Frey, 1985; Lall and Siddharthan, 1982 and Lunn, J. (1980); K.C. Fung etc 1999; Schneider and Frey 1985; Lunn, J. 1980; Tallman 1988; Culem 1988; Grosse and Trevino 1996; Stephane Dees 1998; Yigang Pan 2003; Hongxin Zhao 2003; Yuqing Xing 2004 and Satomi Kimino etc 2007). These literatures had chiefly examined and explained the motivations and reasons which are behind firm investment actions from a macro level.
the level of trade barriers, and the lagged foreign capital stock, but only related no-manufacturing labor cost. Moreover, Lunn, J. (1980) identified the determinants of U.S. direct foreign investment in the European Economic Community, and indicated that the size of the market, growth of the market, height of trade barriers, and lagged net plant and equipment expenditures are important determinants, but the data is too weak to permit strong policy statements from previous papers. K.C. Fung etc. 1999 examine the determinants of FDI from U.S. and Japan in China using the provincial data set from 1991 to 1997. The results of the regression analyses from this paper are further compared to those of the aggregated FDI as a benchmark case. This study found various similarities and differences in the importance and the magnitudes of the determinants of FDI among three FDI sources. It is shown that both level of GDP and the lagged GDP significantly affects inflow of FDI from all sources. The hypothesis that the good quality of infrastructure is conductive to attract FDI is strongly supported for all FDI sources, although the magnitude of the impact of the variable varies. The policy variables are also found to have significant positive effects on FDI. The labor quality exerts larger influence on Japanese FDI than on U.S. FDI, which may reflect the different structure for coordinating activities between U.S. and Japanese firms. The results for the wage variables are inconclusive. This study also shows the marginal support for the positive effect of cultural proximity between Japanese FDI and the provinces of Manchuria. However, the attractive factors of a given host county can not be examined along without perceiving and assessing the differences between this given host country and its source countries.
2003; Yigang Pan 2003; Yuqing Xing 2006) are range from the country factor differentials between host country and home country to examine the motivations and reasons of FDI flows. Tallman, (1988) developed a model with political and economic variables to explain that FDI inflows positively correlated with home country level of economic development and political. They also found significant results for other economic variables such as size of home country market, per capita income, relative cost of borrowing, and exchange rate and a cultural variable which are also positively correlated with FDI inflow. Moreover, Culem (1988) illustrated that market size and growth rate, as well as tariff barriers have already been shown to influence U.S. direct investments in the European Economic Community. He also tested the impact of unit labor costs and export flow determinants of FDI flows, and this paper also specified that in the investment decision process, foreign locations are in competition not only with each other, but also with the home country of the investors. In addition, Grosse and Trevino (1996) conducted a study to explore the factors that contribute to the explanation of FDI in the United States by country of origin of investment. Evidence from the past twelve years shows that the main significant positive influences are home country's exports to the United States and home country market size. Significant negative influences include the home country's imports from the United States, the cultural and geographic distances of the home country from the United States, and the exchange rate.
influencing inward FDI in other developed and transitional economies do not necessarily hold and cannot be generalized in the context of Japan. Thus, despite the conventional wisdom and previous empirical evidence regarding the effects of market size, exchange rates and labor costs on FDI, the empirical evidence in this paper suggests that all of these factors have a statistically insignificant effect on FDI flows into Japan. Nevertheless, with respect to other economic and country-specific influences on the inflow of FDI in Japan, relative exchange rate fluctuation, a higher borrowing cost in investing countries and the stability of the business climate in the investing country are all strong incentives for inducing FDI inflows to Japan. By contrast, the export performance of the source country was found to have a negative impact on the level of multinational activities in Japan.
determinant with Japanese direct investment in China.
Hypothesis development
labor cost. It can be assumed that the FDI inflow to China is impacted by the different business environments between China and source countries. And five hypotheses are specifically discussed below.
A few empirical studies (e.g. Cushman, 1985: Froot & Stein.1991, Grubert and Mutti 1991, Swenson 1994) illustrated that exchange rates affect FDI flows. These studies come up the conclusion that empirical evidence of depreciation of the host currency leads with a large FDI inflows. It is argued that firstly, in rough terms, the relative wealth of source country investors relative to host country investors is increased after the devaluation. Secondly, Devaluation in the currency in the host countries also reduces a relative local production cost. Moreover, Yuqing Xing (2005) argues China exchange rate policy played a critical role in its FDI boom. Devaluation of the Yuan (Chinese Currency) and the policy of pegging the Yuan to the Dollar both improved China’s competitiveness in attracting Foreign Direct Investment. By examining the hypothesis in the context of Japanese FDI for 9 Chinese manufacturing sectors from 1981 to 2002, the empirical results show that the real exchange rate between the RMB and Yen is one of the significant variables determining Japanese direct investment in China. The devaluation of the Yuan substantially enhanced inflows of direct investment from Japan, and the response of FDI to the change of the real exchange rate is elastic; however, one drawback in the literature is that these exchange rate effects have been tested only
exclusively with only one source country- Japan. Based on the theories above, it could be
expected that appreciating of source currency relative to the RMB (Chinese currency) will attract higher FDI inflow to China.
One investment resource for the firm is the capital from the financial institutions; the resource can be available in the source countries, or in the rest of the world. And it is true that the differences between the investment destination and the rest world can be an important consideration, when firms make its investment decision. Cushman (1985) illustrated this issue by his empirical study: When the cost of borrowing in the source country is lower relative to those in the host country, firms are more likely to invest abroad, because of the relative lower cost advantage over its opponents in the host country business environment. When the cost of borrowing becomes higher at home relative to the host country, firms are more likely to refrain from borrowing money at home for foreign investment (Grosse & Trevino, 1996). Therefore, it could be possibly assuming that the lower borrowing cost of source country relative to that of China will push more FDI inflow to China.
Hypothesis 2: The inward FDI to China has a negative relationship with the borrowing cost differential between source country and China
2002).
China has maintained a higher economy growth rate than most of other source country during last decade; and the market in China has the huge potential to be developed. Therefore it could expect that the higher economy growth of China relative of the source country will attract a higher FDI inflow to China.
Hypothesis 3: The inward FDI to China has a positive relationship with the market potential differentials between China and source country
A high percentage of gain will attract the firms to expand their operations internationally in a target country with its available potential resources. And a home country market with high growth rate is also a crucial indicator to motivate and attract the firms to utilize its beneficial capital ability and available intangible assets such as management experience technical knowledge and marketing expertise to explore its foreign market, especially Countries with many firms that are capable of expanding internationally are more likely to engage in FDI into a target nation. Empirical works tend to support this assumption (Loree and Guisinger, 1995; Grosse and Trevino, 1996). The larger the home market size, the more likely that there will be large firms there that are capable of expanding abroad and have the motives to put the continuous and huge investment in that market. The point is when a source country is more developed than host country, the developed source country could have the ability to operate in host country market, and simultaneously, the host country is big enough to abort the investment.
developed stage. Thus it could assume that China could attract the investment from developed source countries due to its less developed economic stage.
Hypothesis 4: The inward FDI to China has a positive relationship with the market size differentials between source country and China
The labor cost differentials between home and host countries is another important factor to impact the FDI flows. It is demonstrated by Barrell and Pain (1999a) that higher labor costs in target countries have a noticeable negative impact on FDI inflow; Some previous researches firmly spported that the labor cost differentials between source and host countries can be considered a important element to impact the FDI flows, and lower wages in foreign countries are a Major reason for establishing operations abroad (Woodward and Rolfe, 1993). Certainly, some empirical studies already support that relative cost of labor differential is a significant driver of inward; For instance Grub et al. (1990) illustrates that the low labor cost are the most important determinants of investments of U.S firms.
Because of the relative less development phase, the labor costs of China has presented much lower than the other developed sources countries. Although the annual wages dramatically increased during the last 10 year, it is still a big difference between developed industrialized countries and China. Therefore, it can be assume that the relative lower labor costs of China can be possible assumed to attract FDI inflow.
Data and Method
Data Collection and Sources
Germany, Italy, Japan, Netherlands, Singapore, Spain, Sweden, United Kingdom and United Stated, after examined availability of data for the inward FDI and other variables between 1985 and 2006. Then the dependent and independent variables will carefully specify in the following section
Dependent variable
FDI is the annual FDI inflow into China from each of 15 countries between 1985 and
2006, which is from the<China Commence Statistics Yearbook1985-2006>, and only the realized FDI is utilized in our study.
Independent variable
Exchange Rate (EX): annual average exchange rate is collected; this variable is
indicated by annual average exchange rate of Chinese currency minus that of source country currency. The data can be found at International Financial Statistics from 1985 to 2006.
Lending Rate (LR): lending rate variable is represented by the lending rate of source
country minus that of China. This part of data is from the source of International
Financial Statistics and OECD statistics from 1985-1996
Market Potential (MP): market potential is signified by GDP annual growth of
source country minus that of China. This part of the data can be found at website of World Bank database and the OECD database from 1985-2006.
Market Size (MS): market size is presented by GDP pre capital of source country
Labor Cost (LC): labor cost is revealed by the hourly minimum wage of source
countries1 minus that of China. The data is from International labor office (laborsta) database, and the OECD database.
Export of source country (EP): export of source country serviced as control variable,
and which is presented by the annual export from each source country into China from 1985-2006. The data is available at the IMF trade statistics before <China Statistic Yearbook>. The export of source country is employed as the control variable, due to the unfamiliarity of a newly opened market like China, trading with China often helps foreign firms gain necessary market knowledge prior to committing substantial investments (Hongxin Zhao, 2003). As the increase the export, the foreign firms can be possible to gain experience and knowledge to invest in China.
Method
Cross country pooled panel data of 15 source countries between 1985 and 2006 are conducted for the regression analysis. From the methodology point of view, there are some reasons to use panel data for this study, (1). More accurate inference of model parameters, and contain more degrees of freedom and less multi-collinearity than cross-sectional data. (2) Greater capacity for capturing the complexity of human behavior than a single cross-section or time series data. (3). the panel data study also can control the impact of omitted variables (Hsiao, 2003). Furthermore, Panel estimation also is capable of controlling for individual country heterogeneity, thereby enabling to minimize serious misspecification problems and improve with a panel specification. Moreover, ambiguity
1
may derive from the use of straightforward pooled data with a relatively short time frame and a limited number of countries. This pooling approach omits any unobserved country-specific effects, and can potentially lead to inappropriate parameter estimates. However, a fixed effects or common effects model effectively allows the intercept to vary over the sample of countries, which is an appropriate approach to examining the determinants of FDI inflow to host country, because the effects of omitted variables can be absorbed into the intercept term of the regression model. This ultimately allows both diversity and the specificity of various investors’ behaviors to be controlled for in the model (Kimino et. al 2007).
Based on the hypotheses, the model is presented as follows:
ln FDIi,t = bi + b2 ln EX i,t + b3 ln LRi,t + b4ln MP i,t-k+ b5 ln MSi,t + b6 ln LCi,t + ei,t
Where:
Results
The aim of this analysis is to examine whether the level of China FDI inflow can be attributed to the economic and financial factors differentials between China and its source countries in the given business investment environment. Before conducting the regression test, a correlation was run among the independent variables to determine the presence of multi-collinearity.
………. Insert table 1 here ……….
Table 1 represents some variables are truly marginally significantly correlated; and then in order to evaluate the severity of multicolinearity, the diagnostic statistic of variance inflation factor (VIF) was estimated by plotting the residuals from the ordinary least square estimation against independent variables. The VIF shows us how much the variance of the coefficient estimate is being inflated by multicollinearity.
………. Insert table 2 here ……….
with respect to the effects that are in the sample. ………. Insert table 3 here ……….
The test was running as pooled, time series regression. By using 15 countries from 1985 to 2006, we had a maximum of 330 observations of one dependent variable and six independent variables. However, some missing value (mainly from the early stage of the FDI inflow from source countries) resulted in 323 usable observations. Table 3 indicated results of the Model, except variables of exchange rate (EX) and market size (MS) that had no significant impacts on FDI, the statistical results of the remaining variables were consistent with hypotheses outlined in the early section. the results show that the contributing factors influencing FDI flows to China were lending rate(LR), and labor cost(LC) (at >.05), and market potential (MP) had even the most significantly influenced on the China inward FDI (at >.001) among these variables.
2007). And this stability of the Chinese currency kept a low flexible level with the currency of other countries. Moreover, before 2005, Chinese currency was very stable with US dollar, because, Chinese currency was pegged with U.S. dollar during this period. Another explanation could be, after 1998, four countries (Italy, France, Germany and Netherlands) join into the Euro zone, and then Chinese currency kept a very stable exchange rate with Euro. In addition, it is also possible that countries are highly eager to explore the newly opened transitional market; firms have to raise all necessary funds from their home countries for overseas investment
The lending rate variable is negatively significant, and supported by the statistic test at the level of 0.005. This result is highly consistent with the hypothesis, and also confirmed that the results from previous studies (Hongxin Zhao, 2003 and Yigang Pan, 2003) is still valid and robust in today’s environment .and shows that the higher cost of borrowing in source countries relative to the cost of borrowing in China discouraged outflow of FDI from 15 source countries. This result is also consistent with the previous findings (Cushman 1985; Grosse and Trevino, 1996) which focused on foreign direct investment inflow of the United Stated. Countries offering capital with low interest rates certainly have cost advantages for their firms over countries that offer high interest capital. Consequently, low capital costs could be stimulating investors to borrow money at home and precede FDI in China.
more mature and competitive, but still has the big potential gains for the foreign firms of accessing this market. Since the mid 1980s, China has maintained a higher relative growth rate than that of other source countries. Therefore, firms in source countries could possibly still take advantage of the fast growth, and to grow simultaneously with the Chinese market. Hence, the quick growth of Chinese economy still greatly contributes for the huge inward FDI.
Market size variable is not significantly supported by the statistic test. This result is not in line with the previous studies from Hongxin, Zhao (2003) and Yigang Pan, (2003). This factor is not contributed to the inflow of FDI from source countries to China. This is not along with previous findings which are concerning with other target countries, these findings mentioned that compared with a developing; a more developed country which contains a large number of competitive firms may have extra capital for outbound investment opportunities (Grosse and Trevino, 1996 and Stephand Dees 1998). It could be possible explained China maintains a fast growth speed for year, as long as the accumulation of the management experience, tangible asset and technologies etc, the wealth of source countries presents a weak impact on the investment decision making process. Market potential could not be a determinant for the FDI inflow as China developed at a new stage.
Conclusion
As the continuous huge foreign direct investment flowed into China in recent years, Careful reevaluation is necessary to ensure this crucial issue again in recent situation. It is true that host-country environments have impacts on the FDI, whereas source-country conditions relative to host-country conditions also affect the flow of FDI. Nevertheless, to date, the literatures under this issue are lagged behind the current situation; reasonably, analysis must be possessed to cohere with the current situation. In order to provide new comprehensive empirical evidence, our paper extended the previous analysis of country factors as determinants of FDI in China, and accomplished the objective: to empirically investigate and examine whether the country factor differentials which were already proved as the determinants of FDI inflow of China still have the significant influence in the current situation.
countries. However, our paper does not ensure other two factors namely exchange rate and market size. Exchange rate is not significant with FID inflow to China, and it is contradictory with some the previous literatures, it maybe because the fixed exchange rate of Chinese financial system once in place, can be maintained at rates that are inconsistent with economic fundamentals. And the size of economies implied how great availability of capital resources and intangible assets is not as the determinants of the FDI in the current situation.
This paper reevaluates the determinants of rapid and huge China FDI inflows from the differentials of country factors perspective by conducting the latest data, and it found some determinants are consistent with the previous researches, but others do not exert significant impact to the huge inward FDI of China in the current situation. These results illustrate the determinants for the huge and rapid China FDI inflow in the recent circumstances. And this study composed 15 developed source countries over a time range of 23 years, results appears broadly generable among the developed FDI source countries of China.
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Appendix
Table 1 correlation of independent variables
FDI EX LR MP MS LC EP FDI 1.000000 Exchange Rate 0.048644 1.000000 Lending Rate -0.155434 * -0.161304 * 1.000000 Market Potential 0.200230 0.053160 -0.084047 1.000000 Market Size 0.012875 0.284721* -0.356604* -0.076346 1.000000 Labor Cost 0.064423 -0.094382 0.065662 -0.082553 0.391343 1.000000 Export 0.002045 0.007385 -0.230665* -0.052659 0.418778 * -0.205319* 1.000000 *P<.10
Table 2 R-squared and VIF between independent variable
Independent Variable EX LR MP MS LC EP
R-squared 0.199965 0.194908 0.028811 0.583151 0.422695 0.384696
Table 3 regression result for China FDI inflow (common model)
Dependent Variable: Inward FDI Method: Pooled Least Squares Date: 09/23/07 Time: 19:54 Sample: 1985-2006
Included observations: 22
Total panel (unbalanced) observations 323
Variable Coefficient Std. Error t-Statistic Prob.
C 44999.45 14717.71 3.057504 0.0024 Exchange Rate 1256.871 1095.879 1.146907 0.2523 Lending Rate -3840.078 1291.334 -2.973729 0.0032 ** Market Potential 3717.092 1083.532 3.430533 0.0007*** Market Size -1.398965 0.760436 -1.839689 0.0668 Labor Cost 2572.433 1058.017 2.431371 0.0156** Export 0.003620 0.003586 1.009485 0.3135
R-squared 0.077915 Mean dependent var 15215.03 Adjusted R-squared 0.060407 S.D. dependent var 70473.55
S.E. of regression 68311.85 Sum squared resid 1.47E+12
Log likelihood -3473.846 F-statistic 4.450263
Durbin-Watson stat 0.650779 Prob (F-statistic) 0.000243 **p<0.05 and ***p<0.001
