The impact of country-specific factors on FDI inflow to China

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The impact of country-specific factors on FDI

inflow to China

New evidence under current economic circumstance

International Business and Management

Faculty of Economics and Business

The University of Groningen

Xin Niu

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Abstract

This paper is aiming to test whether five country-specific determinants (market size, market potential, labor cost, borrowing cost and exchange rate) which are derived from previous research are still able to explain FDI inflow to China when a more recent dataset is introduced. The statistical results show that China’s large market, relative cheap labor cost, relative higher borrowing cost together with depreciated currency strongly contribute to the large volume of FDI inflow to China. However, host country market size and China’s market potential do not exhibit significance for this respect. Additionally, the other purpose of this paper is to examine whether the magnitude of the impact of above-mentioned factors on FDI inflow is influenced by substantial changes in Chinese economy in the last ten years. The statistical results suggest that China’s market size and labor cost exert less influence on FDI inflow in recent years. Moreover, the pattern of FDI in China is transforming from export-oriented FDI to market-oriented FDI recently.

Key words:

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1. Introduction

The past few decades have witnessed a tremendous growth of foreign direct investment (FDI)1 which has exceeded both world output and world trade (Imad, 2002). Especially, the emergence of China as an attractive recipient of FDI in the world can not be ignored. The growth of FDI in China has been dramatic since 1978 and nowadays FDI represents the most important source of foreign capital in China. However, the investment environment in China had not been favorable to foreign investors because China formally opened its door to foreign direct investment in 1979. Since the inception of China’s reform and opening-up policy in 1979 which allows foreign firms to operate in China, China has experienced a boom of inward FDI by MNEs.

In general, FDI in China has gone through various phases as shown in Figure 1. In the first period, from 1979-1985, the growth rate of FDI in China was quite modest with limited amount of inflow due to the poor infrastructure, difficulties in accessing the Chinese market and the non-convertibility of the Chinese currency (Cletus & Eran, 1999). In 1983, the realized FDI inflow to China was still below 1 billion US$. In the late 1980s FDI flows climbed steadily and after 1990 achieved unprecedented growth given the fact that the inward of FDI increased stably from 1956 millions US$ in 1985 to 4366 millions US$ in 1991 with an annual growth rate of 21% in value terms.

The reason for this steady growth and relatively large inflows lies in the Chinese government’s FDI incentive policy that had the purpose of improving the climate for foreign investment in China which included the establishment of the special economic zones2 with the preferential treatment to joint ventures, the subsequently extension of preferential treatment in 14 coastal cities3 and Hainan Island, the establishment of a limited foreign currency market and the acceptance of wholly-owned foreign enterprise in China (Lenoine, 2000). Since 1992 the inflow of FDI has accelerated dramatically,

1

Foreign direct investment (FDI) is defined as a category of international investment that reflects the objective of a resident in one economy (the direct investor) obtaining a lasting interest which implies the existence of a long-term relationship between the direct investor and the direct investing enterprise, and a significant degree of influence by the investor on the management of the enterprise. This definition is quoted from the fifth edition of the IMF’s Balance of Payments Manual (BPM5)

2

The four original special economic zones are Xiamen in Fujian Province and Shenzhen, Zhuhai and Shantou in Guangdong Province.

3

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2 reaching about US$ 27.5 billions in 1993 and US$ 41.7 billions in 1996, and this increasing tendency reached its peak at approximately US$ 45.5 billions in 1998. In this period, China became the largest host country for FDI among the developing countries and the second largest host country in the world (UNCTAD, 1995). Although the upward trend has been interrupted in 1999 and 2000, the inward FDI in China started to increase again in 2001 to US$ 46.9 billions. Since that year, China has become the only country with continual growth rate of FDI inflow and in 2008 this amount went up to US$ 108 billions.

China’s unparalleled success in attracting FDI has drawn much attention from both academic scholars as well as business operators. One of the prime topics among these researches is to investigate the determinants of FDI in China from the perspective of country characteristics or put it in another way, to identify what are the most significant country-specific factors that influence foreign investors’ decision to invest in a country. Consequently, various empirical researches have been conducted to explain the substantial inward FDI to China at the macroeconomic level and the factors are ranging from the economic, financial, political and culture perspectives.

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3 to reexamine these determinants with the latest dataset because the economic condition has experienced remarkable changes during the last 10 years. The changes of investment environment might exert effects on investment decisions for different reasons. Firstly, in 2001, China entered WTO under the condition that it lowered its tariffs for imports, gave the permission to foreign firms to sell directly in the Chinese domestic markets and that the telecommunication and finance sectors were opened to more foreign competition. As pointed out by Chow (2001), under these conditions China will open up its market for more international trade and investment, then introduce foreign competition and speed up economic reform and finally stimulate the growth of GDP. Actually China’s GDP annual growth rate had been steadily decreasing since 1994 and it only started to continuously increase from 2001, from 8 percent to 13 percent in 2007 (Figure 2). Meanwhile, after several years FDI downturn due to the Asia financial crisis, foreign investment began to increase in 2001 and has kept a high growth rate ever since. Thus, it is reasonable to speculate that during this period FDI is more likely to be triggered by Chinese market potential which is indicated by the high GDP annual growth rate. Secondly, in 2005 China took an important step forwarding its move toward a market economy, announcing it would abandon its fixed exchange rate which pegged the value of the RMB against the value of U.S. dollar and consequently allowing the RMB to eventually float freely at the whim of global traders.4 Such a revolution of Chinese exchange rate system drove RMB to start appreciating and at the same time foreign investment stagnated in the following year after 2005. Therefore the assumption might be that the FDI stagnation is probably related to the new exchange rate system. Thirdly, the low labor cost is widely recognized as a favorable factor when foreign investors conduct investment in China. However, the annual wage for the manufacturing sector in China has risen from 275 U.S. dollars in 1986 to 680 U.S. dollars in 1996, and subsequently went up to 2001 U.S. dollars in 2006.5 Thus, it is reasonable to doubt that whether labor cost still acts as an essential factor in attracting the FDI inflow in recent years compared with previous years.

China’s economy has experienced enormous changes recently and thus it is rational to raise the question as to whether determinants of FDI which are derived from

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http://www.frbsf.org/publications/economics/letter/2005/el2005-23.html

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4 previous researches are still applicable when introducing a more recent dataset. Therefore, I formulate my first research question as: whether the country-specific determinants

which are derived from previous research still significantly influence the FDI inflow to China when a new dataset is introduced.

In addition, if these determinants are still valid under the current economic situation, it is also interesting to investigate whether these recent changes have exerted impact on the relationship between the determinants and FDI inflow and consequently the magnitude of the impact of the determinants on FDI inflow may increase (or decrease) under the new situation. Due to the dramatic changes in the last 10 years, I will choose year 2000 as the cutting point for the comparison between the new and old situation and thus the two time periods are 1985-2000 and 2000-2008. Thus the second research question is formulated as: comparing with the first period (1985-2000), whether the

magnitude of the impact of country-specific determinants on FDI inflow changes in the second period (2000-2008).

In this paper, a set of country-level factors which represent both home country and host country characteristics will be examined based on the panel data from top-15 FDI source countries during the period from 1985 to 2008. Specifically, I will employ 5 independent variables which have been commonly used and also have achieved significant results in the previous studies and test them by utilizing panel data and fixed effect model.

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2. Literature Review

There are a number of researches based on both primary data and secondary data have been conducted concerning the determinants of FDI inflow from home country to host country. Therefore, the theoretical reasoning for this paper is rooted in the existing literature concerning the determinants of FDI inflow at the national level and it will be analyzed by integrating both host country and home country factors.

2.1 Host country perspective

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7 effect on FDI. By extending Wei’s study with more recent data set and with different methodologies, Dees (1998) suggests that his empirical results are consistent with previous works which means that traditional determinants of FDI like market size, cost advantage and openness to the rest of the world is relevant to China as well. He finds that the level of GDP is positively related to inward investment with 1 percentage increase in Chinese market size being associated with a 1.8 percentage point increase in FDI inflow which is higher than the elasticity found by Wei. He also finds a negative relationship between FDI inflow and Chinese real wage as well as the real exchange rate.

Besides the empirical researches which are generally based on the secondary data, several authors also conducted studies focused on primary data. Grub et al. (1990) have used interviews and questionnaires to investigate the motivations of US MNEs who invest in China. They find that the potential market and cheap labor are the most important determinants which positively influence US investments. Exchange rate problems are the most serious consideration that US investors have to take since real exchange rate negatively influences FDI inflow. Moreover, the investment incentives offered by the Chinese government show moderately significant effect on investment decisions among U.S. firms. Wei and Shaukat (2005) also conducted a primary research by using questionnaires. They receive responses from 22 firms originating from different countries and industries and the observations describe what they see as the important considerations for them to undertake FDI in China. Results show that China’s large market size and growth rate received significant marks which indicate that market size and growth of China are the crucial factors that have impact on firm’s investment decisions. Similar evidence is also found towards labor costs and government incentives with significant indications that lower labor costs and the Chinese government’s inventive policies are attributable factors to attract foreign investors. Results for exchange rates, political stability, export platform and weak industrial infrastructure are inconclusive.

2.2 Home country perspective

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8 they only focused on the United States. The findings of these researches suggest that the level of economic development which is measured by GDP per capita, R&D intensity, exchange rates and capital costs of home countries affect FDI inflow to the United States (Froot & Stein, 1991; Grosse & Trevino, 1996; Klein & Rosengren, 1994; Tallman, 1988). Tallman (1988) develops a model to explain the relationship between FDI flows and home country characteristics. He finds significant results for economic variables such as size of home country market, per capita income, relative cost of borrowing and exchange rate. Also the results suggest that cultural variable is positively correlated with FDI flows. With the purpose of extending the existing literatures, Grosse and Trevino (1996) develop a comprehensive macroeconomic explanatory model of FDI in U.S. This model includes the following independent variables: size of home country, cost of borrowing, exchange rate between the home country and the U.S., bilateral trade, interest rate, political risk, cultural and geographic distance. The statistical results show that the most significantly contributing factors are home country market size, exchange rate and bilateral trade. The distance measures are also signed correctly and significantly. However, the relative cost of borrowing is insignificant in all specification which differs from Tallman’s finding.

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9 export ratio of the source country is found to be negatively related to the level of multinational activities in Japan.

With regard to the transitional economies such as China, Zhao (2003) conducts a systematic analysis and focuses on the effects of three sets of country-factor differentials between source countries and China on the FDI inflow. The statistical results demonstrate that while the market-condition variables such as market size and growth potential and the high values of home country currency is positively related to the FDI inflow to China, the relatively high borrowing costs of capital and political and operational risk in China inhibited the flow of FDI. Moreover, Pan (2003) believes that factors related to both the source country and the host country can better explain the inflow of FDI in China. The factors addressed in his study include economic, political and cultural considerations. However, unlike the evidence which is found in Zhao’s study, Pan does not find significant evidence to support the hypothesized relationship between exchange rate and FDI inflow. In addition, the contradicting sign of the size of source country indicates that the smaller the size of source country, the more FDI it tends to make. Furthermore, variables such as cost of borrowing and reliance on external trade are in line with previous studies in terms of the sign.

2.3 Hypothesis Development

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10 and host country attributes. In this manner, the five independent variables are market size, market potential, labor cost, borrowing cost and exchange rate which have been indicated in previous studies to have significant effect on FDI inflows in China.

2.3.1 Market Size

The market-size hypothesis believes that inward FDI is a function of the size of the host market and the importance of home country market size. This has been confirmed in numerous empirical studies (Ajami & Barniv, 1984; Tallman, 1988; Grosse & Trevino, 1996). They argue that the size of the home country market positively influences the amount of FDI inflow in the host country since larger domestic economies are expected to have a larger number of firms with available capital resources that are positioned to expand internationally. Meanwhile, size of host country market represents the host country’s economic conditions and the demand for its output and therefore it reflects the attractiveness of one market as the potential location for foreign capital. Additionally, host country with larger market size is likely to attract market-oriented FDI which is undertaken for the purpose of new market exploitation because it will provide more and better opportunities for foreign firms to exploit their ownership advantages. Even for the export-oriented FDI, host country market size is still essential since larger economy is able to provide bigger economies of scale. (OECD working paper, 2000).

The empirical results support the hypothesis that market size has a significant and positive impact on FDI inflows to host country. Many Chinese empirical researches (Liu et al, 1997; Wei & Liu, 2001; Zhang, 2000) have confirmed these results as well that the Chinese market size has a significant impact on inward FDI. Liu et al (1997) conclude that market size is the fourth most important economic factor for the pledged FDI in China. In the context of this study, the hypothesis will be formulated basing on both home country and Chinese market size because both of them will influence FDI flows.

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2.3.2 Market Potential

Market potential is another vital indicator for the foreign investor, especially for market-seeking investors and it was measured by the annual growth rate of GDP or GNP in previous studies. The rapid growth rate of the local economies indicates growing domestic market and business opportunities for foreign investors and thus they will gain benefits by riding the economic wave (Zhao, 2003). Additionally, a rapidly expanding domestic market in the host country would guarantee profitable investment because high market potential tends to have greater capability to absorb additional productive capacity (Brouthers, 2002). China has a population of 1.2 billion which indicates a huge potential for consumption. China’s GDP has grown between 8-9% annually since 1980 and it was regarded as the last enormous market that has not yet been developed in the whole world.

H2: The FDI inflow to China is positively related to its high market potential.

2.3.3 Labor Cost

The nature of MNCs is to seek profit maximization by minimizing their costs of production. Therefore, a firm may undertake foreign investment due to the cost advantage in the host country. Labor cost is an important part of total costs and plays a crucial role in decisions to invest abroad. Other things being equal, a high wage rate deters inward FDI, especially for the firms that engage in a labor-intensive industry; the lower the labor cost in the host country, the more attractive for the foreign investment. Barrell and Pain (1996) demonstrate that higher labor cost in host countries have a dramatic negative impact on FDI made by U.S. investors. Swain and Wang (1995) find that there is a positive relationship between the relatively cheap labor cost in China and inward FDI. Liu et al (1997) confirm this conclusion by showing that the low labor wage is one of the most important economic factors for FDI.

H3a: The FDI inflow to China is positively related to Chinese cheap labor costs.

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12 cost and FDI was used to produce labor intensive goods so as to re-export them to their traditional markets. An OECD working paper shows that the major proportion of FDI is invested in the manufacturing field and amongst the manufacturing sector half of FDI is directed towards the labor intensive industries. This indicates that to a large extent the motivation of foreign companies investing in China is to take advantage of lower labor costs. However, the low-labor-cost advantage may not be sustainable in recent years because of the competition that China faces from its neighboring countries such as Vietnam, Laos and India which are also endowed with cheap labor factors and the increase of the annual wage in the Chinese manufacturing sector which increased from 275 US dollars in 1986 to 680 US dollars in 1996 and was further raised to 2001 US dollars in 2006. Although China loses its relative advantage in labor cost, there is still a substantial proportion of FDI flowing to China in recent years. As Pan (2003) indicates, in recent years the underlying motivation of foreign firms investing in China is to take advantage of the Chinese domestic market which is characterized as a high market potential with GDP annual growth rate ranging from 8 to 13 percent. Thus, it is plausible to argue that original low-labor-cost advantage in China may no longer play as an important role in attracting FDI as it did in the early period and that Chinese high market potential is becoming more and more attractive for foreign investors.

H3b: Labor cost has less impact on FDI inflow to China in recent years than it had in the early stage.

H3c: High market potential has had more impact on FDI inflow to China in recent years than in the early stage.

2.3.4 Borrowing Cost

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13 increase such costs and as a result posit firms at a cost disadvantage in raising capital. In other words, the higher the borrowing cost in China relative to that in the home country, the greater the ability of foreign investors to compete in China and therefore the greater their direct investment. Thus, the differences in borrowing cost between China and home country should be taken into account when making foreign investment. However, this relationship has not been confirmed by the financial experts because in reality multinational firms are not restricted to raising money from a home country but are also able to raise money from the international capital market.

H4: The FDI inflow to China is negatively related to the borrowing cost differential between home country and China.

2.3.5 Exchange Rate

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14 depreciation of the dollar substantially promoted FDI into the U.S. Studies (Goldberg & Klein, Bayoumi & Lipworth, 1998) concerning the Southeast Asian economies, demonstrate that bilateral real exchange rates are one of the FDI determinants for these economies.

However, the role of the Chinese exchange rate in determining FDI is largely ignored in the literature. Only a few studies have been done on this topic. Based on analysis of Japanese FDI in China’s manufacturing, Xing (2005) argues that the Chinese exchange rate plays a vital role in its huge FDI inflows. The devaluation of RMB (Chinese currency) to the Dollar improves Chinese market competitiveness and thus significantly enhanced Japanese foreign direst investment in China. Liu et al (1997) and Wei (2001) also gain a positive coefficient on the exchange rate variable in the regression analysis designed to investigate the determinants of FDI inflow in China. However Pan (2003) does not find significant result on this variable.

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3. Methodology

3.1 Data

As discussed earlier, the literature shows that the most identified factors attracting FDI in China include market size, market potential, borrowing cost, labor cost and exchange rate. Therefore the data concerning FDI inflow by country of origin, market size, market potential, borrowing cost, labor cost and exchange rate used in this study will be taken from the China Statistical Yearbook, International Monetary Fund statistics and World Bank statistics. With regard to the sample, the top 15 source countries who have invested in China in the past decades and who have accounted for major proportion of Chinese inward FDI will be selected.

Among these 15 countries, even though Hong Kong and Taiwan have accounted for a substantial part of foreign investment in mainland China, both regions will be excluded from the sample due to the “round-tripping” issue. In this case round tripping refers to a phenomenon that Chinese firms transfer domestic money to Hong Kong and Taiwan and then reinvest it in the Chinese mainland as FDI inflows in order to benefit from the preferential policies such as low tax rates, favorable land use rights and convenient administrative supports providing to FDI by Chinese central and local governments. It is estimated that round-tripping may account for 20 percent of all Chinese FDI (World Bank 1997, p.21). According to a recent report from World Bank (2002), the scale of this round tripping could be as high as a quarter of the total FDI inflows into China. This fact is based primarily on China’s capital flight as reflected by the errors and omissions item of the Balance of Payment account. In this manner, if such round-tripping FDI is taken into consideration, it will overstate the scale of foreign direct investment in China and therefore it will generate bias in this study. Considering this issue, the top 15 source countries are United States, Canada, Japan, South Korea, Singapore, United Kingdom, Germany, Italy, France, the Netherlands, Australia, Sweden, Switzerland, Denmark and Malaysia.

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16 Consequently, the panel data in the analysis are constructed using 15 source countries’ investment between 1985 and 2008, which in theory should yield 360 observations. However the lending rate is not available for Sweden, Denmark and Malaysia in some years, therefore 341 observations are yielded in total. Moreover, Chinese economy has experienced huge changes in the last 10 years and one of the purposes of this study is to examine whether these recent changes have exerted impact on the relationship between the determinants and FDI inflow in China, therefore I choose 2000 as the cutting point for the comparison between the new and old situation. Thus, the two periods are 1985-2000 and 2000-2008 respectively.

3.2 Model and measurement of variables

In this study, FDI is regarded as an endogenous variable of the general framework being determined by various independent variables. The discussion of hypotheses in literature review implies the following economic relationship:

FDI

_it₌

_α

_{+ β}₁

MS

_it_{+ β}₂

MP

_it_{+ β}₃

BC

_it_{+ β}₄

LC

_it_{+ β}₅

ER

_it₊

_ε

Instead of assuming a simple linear relationship between the FDI inflow and independent variables, the log-linear form will be adopted in this study because there are several advantages of adopting a log-linear form. Firstly, there are extreme values arising from surges of FDI inflows in some years in China. The use of logarithms may counteract this problem statistically. Secondly, it can transform a likely non-linear relationship between inward FDI in China and the explanatory variables into a linear one. Finally, the logarithmic form will reduce the heteroskedasticity (Liu, 1997). Therefore, the model is formulated as follows:

ln

FDI

_it_=c+

_α

_{+ β}₁

_ln

MS

_it_{+ β}₂

_ln

MP

_it_{+ β}₃

_ln

BC

_it_{+ β}₄

_ln

LC

_it_{+ β}₅

_ln

ER

_it₊

_ε

where i= 1,2, … N countries; t=1,2, … T years;

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Dependent Variable

FDI is the annual FDI inflows into China in terms of U.S. dollars from each of 15 source countries range from 1985 to 2008. The realized FDI will be used in this study and the data are obtained from China Statistical Yearbook 1985-2008.

Independent Variable

Market Size (MS): here the market size indicates the size of both home country and host country market and it is measured by GDP per capita. The GDP per capita refers to the gross domestic product per person and it can be found in the World Bank Statistic database for respective years.

Market Potential (MP): is the Chinese market potential which is represented by GDP annual growth rate. The growth rates are the annual average based on constant price series and are collected from the World Bank database as well.

Borrowing Cost (BC): is the borrowing cost differential between home country and China. The borrowing cost is proxy by the lending rates which is defined by International Financial Statistics as the bank rate that usually meets the short-term financing needs of the private sector. The data is available at International Financial Statistics and World Bank Statistics.

Labor Cost (LC): is represented by the yearly average wage of staff and workers in China and the data is drawn from China Statistical Yearbook for respective years.

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3.3 Method

The empirical work in this study is based on a panel data which covers 15 source countries during the period from 1985 till 2008. In this case, panel data is the appropriate way to conduct a systematic and efficient analysis of the determinants of FDI inflow into China given the several major benefits from using panel data. These include the following: (1) Better controlling for individual heterogeneity than time-series and cross-section data since time series and cross-cross-section studies not controlling for this heterogeneity run the risk of obtaining biased results, (2) Panel data give more informative data and thus can produce more reliable parameter estimates, contain more degrees of freedom and less collinearity among variables, (3) Panel data are better able to identify and measure effects that are simply not detectable in pure cross-section or pure time-series data.

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19 changes in the variables over time to estimate the effects of the independent variables on the dependent variable. That is to say it allows the examination of the differences within countries and how these differences affect FDI inflow in China. Finally, the Hausman test results suggest that fixed effects model should be adopted due to a significant P-value of 0.0000 which is smaller than 0.05. Therefore, the fixed effects model is utilized as an analytical tool in this study.

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4. Results

4.1 Model testing

In this section, the dataset will be tested to see whether it fits with the regression model. Firstly, multicollinearity among the predictors should be checked. Multicollinearity occurs when independent variables move together in systematic ways. When there is a perfect linear relationship among the predictors, the data are not able to contain enough “information” regarding the individual effects of independent variables to allow us to estimate all the parameters of the statistical model precisely. As the degree of multicollinearity increases, the regression model estimates of the coefficients become unstable and the standard errors for the coefficients can get widely inflated. One simple way to detect collinear relationship is to use correlations coefficients between pairs of explanatory variables. “A commonly used rule of thumb is that a correlation coefficient between two explanatory variables greater than 0.8 in absolute value indicates a strong linear association and a potentially harmful collinear relationship” (Hill et al. 2001). To determine the presence of multicollinearity, a Pearson correlation is run first with all independent variables. As revealed in Table 1, host country GDP and labor cost are indeed correlated but marginally significant. To evaluate the severity of multicollinearity, the diagnostic statistic of variance inflation factor (VIF) is applied. The value of 1/VIF tells us that what proportion of an X variable’s variance is independent of all the other X variables’ variance. As a rule of thumb, a variable whose VIF value is greater than 10 may indicate potential problems. The results form Table 2 demonstrates that no VIF value exceeds 10 which is the threshold point, implying that there is no serious problems of multicollinearity (Hill et al. 2001).

Table 1 Correlation Matrix

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Table 2 VIF value of independent variables

Variable VIF 1/VIF

logmshost 1.30 0.768785 logmshome 1.38 0.722417 logmphost 1.03 0.966678 loglchost 1.26 0.791246 logbcdiff 1.21 0.823963 loger 1.13 0.883698 Mean VIF 1.22

Secondly, when using panel data, the existence of heteroskedasticity is often encountered. In this case, when the variances for all observations are not the same, it is said that heteroskedasticity exists. In order to detect heteroskedasticity, the Breusch-Pagan test will be used. The null hypothesis of the Breusch-Breusch-Pagan test is the variance of the residuals is homogenous which means there is no heteroskedasticity (Hill et al. 2001). The statistic result reveals a significant P-value, implying that the null hypothesis should be rejected and conclude heteroskedasticity in the model. The problem with this is that this may result in the wrong estimates of the standard errors for the coefficients and therefore their t-values. The way to deal with this problem is to use heteroskedasticity-robust standard errors so as to adjust the model to account for heterodkedasticity. To do this we can use the option “robust” to control for heteroskedasticity.

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Table 3 Levin-Lin-Chu unit-root test

H0: Panels contain unit roots Number of panels=15 H1: Panels are stationary Number of periods=24 Statistic P-value

Unadjusted t -6.9127

Adjusted t -5.7289 0.000

4.2 Results

4.2.1 Results for the entire sample period

Table 4 illustrates parameters estimates obtained from panel data for the entire sample period (1985-2008). The adjust R-sq value is 0.55, indicating that 55% of the variation in FDI inflow to China is explained by the variation in independent variables. Although the value of adjust R-sq obtained in early studies is higher than that in this study, overall the model in this study is quite satisfactory, indicating a relatively strong explanatory power of the model.

Table 4 Regression results

Dependent Variable: logFDI Method: Least Squares Number of observations: 341

Variables Coefficient Std. Error t-Statistic Prob.

C -3.113454 2.017618 -1.54 0.123 logmshost 2.263711 0.4275176 5.66 0.000 logmshome 0.1803334 0.2603947 0.69 0.489 logmphost 0.1378763 0.1700409 0.81 0.417 loglchost 3.376136 0.3584591 9.42 0.000 logbcdiff -0.050586 0.0249728 -2.03 0.043 loger -0.1508601 0.0504742 -2.99 0.003

R-squared 0.5579 Mean dependent variable 9.769418

Adjusted R-squared

0.5500 S.D. dependent variable 2.27158

Log Likelihood -621.278 F-statistic 140.61 Durbin-Watson

stat

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23 The panel estimates are generally consistent with expectations that with the exception of the variable of home country market size and Chinese market potential, the statistical results of the remaining variables are in line with hypotheses outlined in the previous section. The estimated coefficients of Chinese market size, labor cost, differential of borrowing cost and exchange rate are correctly signed and statistically significant at the 5% level, implying a strong economic relationship between explanatory variables and inward FDI in China. As the equation is in log form, the coefficient can be interpreted as elasticity (Dees, 1998).

Market size: The coefficient of Chinese GDP is positive and statistically significant at the 5% level, confirming hypothesis 1a that the China’s market size has a positive effect on the amount of FDI flows. Its elasticity is about 2.26 indicating that a 1% increase in size of the Chinese market is associated with a 2.26 percentage increase in FDI inflow to China. The sign regarding home country market size is correct as well indicating that home countries with large market size are more likely to invest in China. However, the coefficient is not statistically significant, therefore hypothesis 1b is rejected.

Market potential: The sign of market potential is positive as expected which suggests that FDI inflow to China is positively related to the fast growing market. Nevertheless the coefficient is not statistically significant implying that this factor does not strongly influence the FDI inflow to China and thus hypothesis 2 should be rejected. This finding is conflict with the prior evidence observed by Zhao (2003) that the high level of FDI occurred when Chinese market exhibited a higher growth rate than home countries.

Labor cost: With regard to labor cost variable, the coefficient is strongly significant at the 5% level. Furthermore, the magnitude of the effect of the variable is the largest among all the variables. The result is consistent with the consensus opinion and previous findings (Dees, 1998; Wang & Swain, 1995) and thus hypothesis 3a is confirmed.

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24 China (Zhao, 2003; Pan, 2003) as well as in the United Stated (Grosse & Trevino, 1996). Hence hypothesis 4 is accepted.

Exchange rate: The effect of real exchange rate on the FDI inflow is negative as expected and statistically significant. A 1% depreciation of Chinese currency is associated with a .15 percentage increase in the FDI inflow. This result is consistent with findings obtained by Xing (2006) that the real exchange rate between the Yuan and Yen is one of the significant variables determining Japanese direct investment in China. Therefore hypothesis 5 should be accepted.

4.2.2 Comparison of two time periods

When comparing the two time periods (Table 5), the result of the likelihood ration test reject null hypothesis and hence suggests that all coefficients in the model vary significantly between the first period (1985-2000) and the second period (2000-2008).

Table 5 Comparison of two periods

Year<2000 Year>=2000

Independent Variables

Coefficient P-value Coefficient P-value

logmshost 1.742924 0.016 1.371954 0.013 logmshome 0.5717981 0.140 0.3486629 0.174 logmphost 0.4527863 0.011 0.4995169 0.076 loglchost 1.092563 0.003 1.0542824 0.015 logbcdiff -0.0322335 0.272 -0.0443472 0.141 loger -0.1973593 0.049 -0.160238 0.174

Likelihood-ratio test LR chi2(7)= 375.55 Prob> chi2= 0.0000

The sign of both home country market size and differential of borrowing cost are correct but the coefficients are statistically insignificant. Therefore the comparison on both variables is impossible.

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25 the first period to the second period, indicating that the Chinese market size have less influence on FDI inflow in recent years (2000-2008).

With regard to GDP annual growth rate, the sign is positive as expected. However, the coefficient on this variable is significant in the first period but it turns to be insignificant in the second period. This fact rejects hypothesis 3c that high market potential has more impact on FDI inflow to China in recent years than in the early stage. The evidence suggests that the GDP annual growth rate did not exert influence on FDI inflow to China in recent years.

The coefficient of labor cost is positive and is statistically significant in both time periods implying that relative cheap labor cost is still the most attractive factor for foreign investors not only in the early time but also nowadays. The coefficient of this variable reduces from 1.09 to 1.05, revealing that the influence of labor cost on FDI inflow in China decreases in recent years. Based on this result, hypothesis 3b should be accepted.

The coefficient upon exchange rate is negative and exhibits statistically significance in the first period. In the second period, the coefficient on this variable is negative as well but not statistically significant. Thus, it is not possible to compare the effect of exchange rate on FDI inflow between the two time periods.

4.3 Discussion of results

4.3.1 Discussion for the entire time period

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26 financing ability, therefore home country market exhibits a weak impact on the decision making process and may not constrain FDI outflow for MNEs. The insignificant result on market potential suggests that China’s GDP annual growth rate does not contribute significantly to the explanation of FDI in China. It is probably because foreign investors believe that the statistic on GDP annual growth rate reported by Chinese government may hide or even exaggerate the real economic condition in China and consequently they may not consider GDP annual growth rate as an appropriate measurement for market potential. The evidence of strongly positive impact of labor cost variable on FDI receipts reveals that MNEs generally aim to take advantage of cheaper factor input in China, particularly cheaper labor. The finding regarding borrowing cost implies that home countries offering capital with relative low lending rates have cost advantages and consequently are more likely to borrow money at home and then conduct investment in China. The result concerning exchange rate indicates that the depreciation of the Chinese currency against the home country currency attracts FDI inflow to China. The reason is that the depreciation of Chinese currency reduces the cost of investing in China and therefore it is becoming more profitable to make an investment in China.

4.3.2 Discussion for the comparison of two time periods

The estimate results concerning the comparison of two time period demonstrate that except variables of home country market size and borrowing cost which are not significant in both periods, results concerning the magnitude of the remaining variables do show some changes from the first period to the second period. In addition, the result of the likelihood ration test implies that these changes are significant.

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27 possible reason lies in the reliability of this statistic as released by the Chinese Communist Party (CCP) in recent years. Some financial experts noted that if the Chinese economy were to really continue to grow at a two-digit growth rate, then it would have to contribute to the world economy and increase domestic demand. However this has not happened given such fact as the high rate of unemployment. Many economists give the criticism that China continues to systematically falsify economic growth rate and to deceive the international community and foreign investors. They believe the purpose of doing this is to trick international investors into directing funding in China. In this case, foreign investors may not take the announced GDP annual growth rate seriously into their consideration when they invest in China. The evidence concerning labor cost implies that cheaper labor exerts less impact on FDI inflow to China in recent years. The decreasing impact of labor cost on FDI inflow may result from the substantial increases in the Chinese annual wage of manufacturing sectors in the last two decades. As the labor cost in China increases, the labor cost gap between China and foreign investors decreases, resulting in less FDI inflow. It is also noticeable that the magnitude of the effect of this variable is the second largest among all variables in the second period, suggesting that labor cost still considerably has impact on FDI inflow to China in spite of the growing annual wage. The evidence reveals the fact that the pattern of FDI in China is in the process of transition, transforming from export oriented FDI to market oriented FDI. It is supported by recent news6 that more and more MNEs have planed to set up their R&D center in China. It is also proved by empirical study (Wen & Lin, 2005) suggesting that more and more foreign investors are transforming their R&D activities into China, aiming at market penetration in the Chinese market. Although the insignificant result on exchange rate in the second period making comparison impossible, the negative sign on this variable in the second period still reveals some facts. As demonstrate in Figure 3 that the Chinese Yuan has been following the devaluation path from 1985 till 1994 and afterwards pegged the RMB to the U.S. dollar at an exchange rate of 8.28. However, the fixed currency system together with the high value of Chinese currency has been criticized by China’s trading partner, the United States. Therefore, in 2005 the Chinese Central Bank announced to change its currency regime from the fixed exchange rate

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5. Conclusion

The huge volume of FDI inflow to China in the last two decades and the management implication of this flow for foreign investors have attracted attention among scholars in international business research as well as MNEs. The primary purpose of this paper is to find out whether country-specific determinants which are derived from previous research are still able to explain foreign direct investment in China when a more recent dataset is introduced and additionally to compare the magnitude of the impact of these factors on FDI inflow between two time periods. In this paper, panel data for the top 15 source countries over the period of 1985-2008 and the fixed effects model are applied.

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30 Results regarding the comparison of two different time periods suggest that dramatic changes in Chinese economy in the last ten years do influence the relationship between country-specific determinants and FDI inflow to China and consequently the magnitude of the impact of those determinants on FDI changes under the current economic circumstance. The findings demonstrate some salient features of FDI in China currently. Firstly, China’s market size exerts less influence on FDI inflow in the second period than in the first period. Secondly, GDP annual growth rate significantly influences FDI inflow to China in the first period but not in the second period. The reason for this result might be that foreign investors hold a susceptive view on the current growth rate as reported by Chinese government. Therefore, they will not take GDP annual growth rate seriously into their consideration when they make investment decision. Thirdly, labor cost strongly contributes to the FDI inflow to China in both periods. However the impact of labor cost on FDI inflow decreases from the first period to the second period because of the substantially increase in labor wage in China in recent years. In addition, the magnitude of the effect of labor cost in the second period reveals that FDI in China is transforming from export-oriented investment to market- oriented investment which is more likely to focuses on market penetration. Last but not the least, exchange rate significantly exerts effect on FDI inflow to China in the first period but not in the second period. However the negative sign of exchange rate in the second period reveals that appreciation of Chinese currency raises the cost of operating in China and therefore deters foreign investment in China.

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31 China’s market for export-oriented foreign investment. The decrease in export-oriented FDI will in turn weaken export growth, which acts as one of growth engines of the Chinese economy. Thus, Chinese government needs to keep its exchange rate at a benchmark level to avoid the slowdown of FDI due to the sharp appreciation of the Chinese currency.

Limitation

In general, findings in this paper are consistent with previous researches but also reveal some new characteristic of FDI inflow to China. However, there are still many limitations in this study which needs to be further improved.

This paper pays more attention to the characteristics of country level factors than to the industrial effect and firms’ specific characteristics which are beyond the scope of this analysis. However, in reality firms’ expansion strategy is a combination of all possible factors. As implied by Grosse and Trevino (1996) that the inclusion of industry and firm level factors is more likely to improve the explanatory power of the FDI flow model.

In addition, political risk and geographic and cultural distance which also act as the measurement of the macro investment condition are not taken into consideration. This also could be the subject for further improvement.

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Web sites

China Bureau of Statistics:

http://www.stats.gov.cn/english/statisticaldata/yearlydata/ China Minister of Commerce:

http://gzly.mofcom.gov.cn/website/comment/foreign/english_bbs.jsp Federal Reserve Bank of San Francisco

http://www.frbsf.org/publications/economics/letter/2005/el2005-23.html International Monetary Fund:

http://www.imfstatistics.org/imf/ LABORSTRA:

http://laborsta.ilo.org/STP/guest

State Administration for Industry & Commerce:

http://wzj.saic.gov.cn/pub/ShowContent.asp?CH=GZDT&ID=334&myRandom=.9779 The World Bank

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7. Appendix

Figure 1 Foreign Direct Investment in China (1979-2008)

Foreign Direct Investment in China from 1979-2008

0 20000 40000 60000 80000 100000 120000 19 79 19 81 19 83 19 85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 Year

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Figure 2 China’s GDP annual growth rate (1985-2008)

China's GDP annual growth rate

0 2 4 6 8 10 12 14 16 198 5 198 6 198 7 198 8 198 9 199 0 199 1 199 2 199 3 199 4 199 5 199 6 199 7 199 8 199 9 200 0 200 1 200 2 200 3 200 4 200 5 200 6 200 7 200 8 Series 1

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Figure 3 China’s exchange rate (1985-2008)

Exchange Rate(RMB/U.S.dollar) 0 1 2 3 4 5 6 7 8 9 198 5 198 7 198 9 199 1 199 3 199 5 199 7 199 9 200 1 200 3 200 5 200 7 year E x c h a n g e r a te Series1 f

The impact of country-specific factors on FDI inflow to China