日本在中国外商直接投资的区位因素研究【外文翻译】

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外商直接投资区位选择的影响因素研究

外商直接投资区位选择的影响因素研究

外商直接投资区位选择的影响因素研究外商直接投资区位选择的影响因素研究摘要:随着经济全球化程度的加深和中国改革开放的深化,外商直接投资进入中国的步伐显著加快。

中国已成为吸收利用外商直接投资的领先国家。

但是进入中国的外商直接投资在区域分布上以及各区域内的行业分布上存在着巨大的不平衡。

外商直接投资在中国内地表现出的地区差异性,既反映了资本寻求利益最大化的战略性考虑,又显现出外商对中国各区域环境特征和优势资源的选择性利用。

因此,研究外商直接投资在中国的区域分布及投资的区位选择行为,对了解中国各区域的经济特征与吸收利用外商直接投资的相关性以及如何改善劣势地区条件以便更好的吸收利用外商直接投资,促进区域协调发展具有重要的现实意义。

关键词:外商直接投资;趋势;区位;影响因素一、引言外商直接投资的区位决策是一个复杂的多阶段的过程。

在大多数情况下,外商首先选择要投资的国家,然后再具体确定国内建厂地区和厂址。

因此,外商直接投资区位研究实际上包括两个方面的内容:一是外商直接投资的国别选择;二是外商直接投资的国内区位选择。

二战以后,随着世界全球化进程的不断加快,外商直接投资开始在国际舞台上发挥着不可估量的作用,因此,外商直接投资问题日益成为国际学术界研究的热门话题。

近年来,学术界已有大量的理论和实证研究深入地探讨了外商直接投资的区位问题,但迄今为止,还并未形成统一的外商直接投资区位理论。

近期,在国际直接投资区位理论中占主流的仍是邓宁(Dunning)于20世纪70年代提出的国际生产折衷理论。

邓宁在吸收前人研究的基础上,将国际贸易理论,产业组织理论以及区位理论融合在一起,提出了“国际生产折衷理论”。

国际生产折衷理论认为,要进行国际投资必须具备三个基本要素,即所有权优势、内部化优势和区位优势。

区位优势具体表现为:东道国市场的地理分布状况、生产要素的成本及质量、运输成本、基础设施、政府干预范围与程度、各国的制度、国内外市场的差异程度,以及由于、文化、风俗偏好、商业惯例而形成的心理距离等。

FDI外商直接投资区位选择外文文献翻译2014年中文译文3100字

FDI外商直接投资区位选择外文文献翻译2014年中文译文3100字

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外商直接投资在中国东部地区的实证研究【外文翻译】

外商直接投资在中国东部地区的实证研究【外文翻译】

外文翻译原文An Empirical Study of Foreign Direct Investment Location in Eastern China Material Source: The Chinese Economy, vol. 41, no. 6, November–December 2008,pp. 75–98.Author: Xing Li, Keqiang Hou, and M.W. Luke ChanAbstract: This paper examines the determinants of foreign direct investment (FDI) for the Eastern Region of China as a whole by excluding the two lesser jurisdictions and concentrating on the Big Five jurisdictions from 1993 to 2005. Robust estimates and a better understanding of FDI in Eastern China are obtained by employing robust Ordinary Least Squares (OLS), the random effect model, and the fixed-effect model separately on each case. Without any outliers and serial correlation in residuals, the Big Five case gives us the most reliable estimates of determinants of FDI in Eastern China. Market size and labor quality are found to have a positive, significant, and quantitatively large effect on FDI in Eastern China, whereas education and infrastructure have a statistically non-significant positive direct effect on FDI. As for the level of local physical investment, we found a small crowding-out effect on FDI in the Big Five case.Foreign direct investment (FDI) in China has been subjected to many years of discussion and study. This is a direct result of the level and impact of such investments on China’s overall development. The economic growth in China since 1979 and the beginning of its open-door policy have been keenly observed and studied. The economic growth phenomenon witnessed in the past two decades is something never before seen in human history. Many factors have triggered and propelled such growth, including new technology from developed countries, the influx of modern management, and, of course, foreign direct investment.In analyzing the impact of FDI on the growth and development of the Chinese economy, China’s different economic regions will be divided to isolate and identify the regional differences where such investment added to the growth of the economy (Hsiao and Yan 2003; Zhang 2006). Economic reform in China has progressedrapidly, but although the open-door policy began in the early 1980s, FDI did not begin until the early 1990s. Because of this time lag there is a lack of time series observations, and virtually all empirical analyses of FDI use panel data. The present study is no exception.This study differs from previous studies in that the focus is placed on only one region, namely the eastern region, which in turn will be deconstructed into three hierarchical groups. Local physical investment is introduced as one of the determinants, since the effect of local investment on FDI is ambiguous. We hope to find the underlying determinants of FDI in the eastern region from the empirical results of this study.Wage rate rather than educational quality will be used as a proxy for labor quality. In many previous empirical studies of the Chinese economy, labor quality was measured by such criteria as educational level, experience, and diligence. In our view, the wage rate represents all these factors, since it equals the marginal product of labor according to classic microeconomic theory. We use separate controls for educational level and labor quality in order to study their respective effects on FDI. We found that employee educational level is just a small part of labor quality in determining FDI. Our results show that labor quality has a positive, significant and quantitatively large effect on FDI in eastern China even when we control for the regional educational level, whereas educational level only exhibits an insignificant and quantitatively small effect on FDI, albeit positive.Foreign direct investment by multinational enterprises is an important feature of the global economy. Most developing countries consider FDI inflows as one of the most important channels for economic development. Since Dunning’s (1979) seminal work on eclectic theory, scholars in the field of international business have sought to examine location factors as determinants of FDI. They view location-bound assets as complements to their own core competencies, since location-specific factors present themselves with varying degrees of attractiveness to foreign investors. Relevant to our study is location theory, which is often used to explain why multinational corporations choose to invest in a particular host country. It can also be used to explain why foreign investors choose to invest in a specific location within a host country. The determinants of FDI location have been extensively studied (Chen 1996; Cheng and Kwan 2000a, 2000b; Coughlin, Terza, and Arromdee 1991; Friedman, Gerlowski, and Silberman, 1992; Head, Reis, and Swenson 1995; Wheeler and Mody 1992). The main determinants of FDI locationsuggested by these studies can be classified as market-access factors, labor-cost factors, infrastructure, government policies, agglomeration effects, and market potential effects (Blonigen et al. 2004; Head and Mayer 2004).Figure 1 provides a schematic summary of the selected determinants of FDI based upon theoretical prediction and empirical results.FDI Distribution in ChinaChina can be divided into three geographic regions: eastern, central and western. The eastern region covers eleven provinces and autonomous municipalities: Liaoning, Beijing, Tianjin, Hebei,Shandong, Jiangsu, Zhejiang, Shanghai, Fujian, Guangdong, and Hainan. The central region covers nine provinces: Heilongjiang, Jilin, Inner Mongolia, Shanxi, Henan, Anhui, Hubei, Jiangxi, and Hunan. The western region encompasses ten provinces in the northwest and southwest.From 1993 to 2005, the eastern region had about 85 percent of the FDI in China, peaking in 2000 at almost 92 percent. The other eighteen provinces and autonomous municipalities of the central and western regions had less than 15 percent of the total FDI. The Tibet Autonomous Region had virtually no FDI, while the proportions of FDI in Qinghai and Ningxia were only 0.01 percent and 0.13 percent of the total. During the period from 1993 to 2005, Gansu, Xinjiang, Guizhou , Inner Mongolia, and Yunnan accounted for less than 0.2 percent of FDI in China. Figure 2 shows the FDI in the three different regions in percentage terms from 1993 to 2005.Obviously, the regional variation of FDI is very big even by visual inspection. It is difficult, although possible, to draw accurate references and inferences on empirical analysis for the three vastly different regions. However, if one examines the pattern of FDI in the eleven geographic areas of the eastern region, one can also see a vast difference in the investment pattern. Instead of showing the year-by-year FDI flow into the eleven provinces and autonomous municipalities, we present in Figure 3a, the cumulative FDI in the different geographic area from 1993 to 2005, inclusively.Statistical information from the Ministry of Commerce shows a clear difference in the actual FDI amounts in the eastern region. The maximum cumulative FDI, located in Guangdong province, amounted to US$151.65 billion from 1993 to 2005. This is almost twenty times as much as the US$7.79 billion investment in Hainan province, the lowest of the FDI indices among all eleven areas. It is evident that FDI gravitates mostly to three locations in the eastern region: Guangdong, Jiangsu, and Shanghai. Guangdong has the largest share of FDI in the eastern region, making up28.70 percent of the total in the region, and 24.37 percent in all of China. FDI in Jiangsu follows with US$89.84 billion, making up 17 percent in the region. Shanghai makes up 10.48 percent, with the actual FDI totaling to US$55.39 billion. In addition, the Big Five jurisdictions in the eastern region have an accumulative FDI of US$151.66 billion for Guangdong, US$89.85 billion for Jiangsu, US$55.39 billion for Shanghai, US$52.93 billion for Shandong, and US$47.85 billion for Fujian. These five areas account for 75.25 percent of all FDI in the eastern provinces and 63.90 percent of all FDI in China.It is interesting and important to note that the flow of FDI into the eastern region shows no sign of abatement. Figure 3b shows the pattern of FDI flow into the eleven provinces/autonomous municipalities of the eastern region.From 1998, after the Asian financial crisis of July 1997, to 2005, both the level and the trend of FDI in the eastern region in China were strong. Six of the areas in the eleven jurisdictions had experienced an upward trend: Shandong, Shanghai, Zhejiang, Jiangsu, Beijing, and Tianjin. In fact, Shandong showed the strongest annual rate of growth at 43.34 percent, followed closely by Zhejiang at 42.17 percent and Shanghai at 12.33 percent. For Jiangsu, Beijing, and Tianjin, the growth rates were estimated to be at 6.18 percent, 8.96 percent and 2.16 percent, respectively. The jurisdictions where there had been an obvious downward trend were Fujian, Hebei, and Hainan where the estimated rate of decrease was 7.29 percent, 9.12 percent, and 13.41 percent, respectively.It is evident that the eastern region of China is undoubtedly the most important region for FDI. This makes it essential to focus more attention on the deterministic behavior of FDI in this region. By doing so, we hope to isolate and identify factors and influences that are critical to FDI in eastern China and perhaps in China as a whole, and this will enable policy makers to formulate rules and guidelines to attract further investment.In general, several important observations can be drawn. First, the eastern region is the most important area in attracting FDI. Second, two of its eleven provinces/autonomous municipalities, Hebei and Hainan, stand out as different from the others. The levels of FDI in these two provinces are very low and have been trending downward throughout the period. Including these two areas in our overall analysis of the eastern region will undoubtedly produce biased and unreliable results. Third, the lion’s share of FDI goes to five provinces autonomous municipalities, which experienced the highest cumulative share of FDI from 1993 to 2005. The fivejurisdictions are Guangdong, Jiangsu, Shanghai, Shandong, and Fujian.Empirical Models and AnalysisData DescriptionFDI location factors can be generally categorized into the following four major groups: market size, educational level, openness of the economy, and state of the infrastructure. Five major FDI locations have been chosen for study. Apart from the above four variables, labor quality and local physical investment in the region have been added as other determinants.The influence of market size on FDI determination is captured by using the level of GDP of the region as a proxy. Educational level is measured by the number of undergraduate students as a percentage of the total population of the province or region. This number should provide a good indication of the level of education and quality of the labor force. The degree of openness in the economy and readiness to accept FDI undoubtedly has a positive effect on the level of FDI. The degree of openness is captured by using the export to GDP ratio as a proxy.Three different variables are employed to measure the infrastructure readiness of the province or region: highways, railways, and telecommunications. For highways, we calculate the total kilometers of highways per square kilometer of land. Similarly, we use the length of railway lines per square kilometer. The level of expenditure on telecommunications per person in the province or region is used as a proxy of activity and intensity of telecommunication.Domestic or local investment comprises all other investment coming from domestic sources, while foreign direct investment comprises investment in the region coming from foreign countries.Finally, the quality of labor in the province or region is also an important factor in determining FDI. To determine this, the average wage rate for industrial workers in three industrial sectors (mining and quarrying, manufacturing, and electricity, gas, and water production and supply) is calculated using sectorial employment numbers as weights.译文外商直接投资在中国东部地区的实证研究资料来源: The Chinese Economy, 2008(11-12)作者:M.W. Luke摘要:本文主要是通过考察从1993年到2005年期间外商直接投资集中在中国东部地区的决定因素。

日本对华直接投资的区位选择及其影响因素——基于城市尺度的面板解读

日本对华直接投资的区位选择及其影响因素——基于城市尺度的面板解读

日本对华直接投资的区位选择及其影响因素——基于城市尺度的面板数据分析摘要:改革开放以来,日本对华直接投资总体呈快速波动增长趋势,2007年已成为我国最大的FDI流入国。

日本对华直接投资,绝大部分都集中在我国东部沿海地区,投向中西部地区甚少。

本文主要从城市尺度考察了日本对华直接投资的区位选择特征,并采用面板数据方法分析了其主要影响因素,发现潜在市场规模、劳动力成本、基础设施水平和集聚效应等因素基本决定了日本对华直接投资的区位选择趋势,特别是其中的基础设施水平和集聚效应对日本对华直接投资的区位选择具有显著作用。

关键词:日本,直接投资,区位选择,集聚效应,面板数据自改革开放以来,特别是我国2000年加入世界贸易组织(WTO)之后,外商在华直接投资(FDI)开始快速增长,已成为吸收外商直接投资最多的发展中国家。

这些外商投资主要来自香港、台湾、澳门及其他华人华侨,来自日本的投资仅次于香港,居来华外商投资第二位。

根据日本贸易白皮书统计,截至2007年10月底,日本对华投资累计项目数达3.9万个,实际到位资金额为607.8亿美元,在战后日本的对外贸易中,我国大陆首次超过美国成为日本的第一大贸易伙伴国,相应地日本也成为我国最大的FDI流入国(财务省,贸易统计速报 2007)。

日本在华直接投资的发展及其区位选择,已对我国经济特别是区域经济的发展产生了重要影响。

本文拟主要从城市尺度考察日本在华直接投资的区位选择及其影响因素,从一个方面探讨日本在华直接投资的区位选择机制,为更好地利用在华日资、加快经济发展提供政策依据。

1 日本在华直接投资概况1.1规模增长日本对华直接投资始于1981年改革开放之初。

从1981年至1992年的大致10年时间为起步阶段,由于日本企业对外投资素来谨慎,所以在此起步阶段对华投资规模较小,少于同期的香港和美国,基本上属于观望性、“投石问路”的试探性投资。

自1992年后,我国加快改革开放步伐,不断改善制度等投资环境,所以吸引日本企业投资规模总体呈稳定增长态势,到1997年已达到432647万美元。

中国跨国公司对外直接投资区位选择研究

中国跨国公司对外直接投资区位选择研究

中国跨国公司对外直接投资区位选择研究中国跨国公司对外直接投资区位选择研究引言近年来,中国跨国公司对外直接投资(FDI)呈现出快速增长的趋势。

与此同时,中国在全球经济中的地位也不断提升。

选择适当的投资区位对于实现投资项目的成功运营和最大化回报至关重要。

本文将对中国跨国公司对外直接投资区位选择进行研究,并探讨影响其决策的因素。

一、投资区位选择的重要性投资区位选择是指跨国公司在决定对外直接投资时,选择的特定国家或地区进行投资的决策过程。

区位选择的合理性直接影响着投资项目的成败。

一个适当的投资区位可以提供经济和政策环境的便利条件,从而减少企业运营成本,提高市场渗透能力和竞争力。

二、影响区位选择的因素(一)经济因素1. 市场规模和增长潜力:跨国公司往往会优先选择市场规模较大且增长潜力较大的地区进行投资,以保证项目的可持续发展。

2. 劳动力成本和素质水平:劳动力成本是跨国公司投资区位选择的重要因素之一。

相对低廉的劳动力成本可以降低生产成本,增强企业竞争力。

此外,素质较高的劳动力也能提高企业的技术创新能力和产品质量。

(二)政策因素1. 政府政策支持:政府提供的税收减免、土地使用权和外汇管理等政策支持,对于跨国公司的投资决策具有重要影响。

2. 法律和法规环境:一个良好的法律和法规环境可以保护跨国公司的知识产权,降低经营风险。

(三)资源因素1. 资源可获性:某些行业对于资源的需求较大,因此跨国公司会考虑投资区位的资源可获性,以确保生产过程的顺利进行。

2. 交通和基础设施:良好的交通和基础设施条件可以提供便利条件,降低跨国公司的物流成本和时间成本。

三、中国跨国公司对外直接投资区位选择的实证研究(一)中国跨国公司对外直接投资的趋势中国跨国公司在过去几十年的发展中,呈现出跨越式的增长。

根据统计数据,2019年中国跨国公司的对外直接投资额达到1823亿美元,较上一年增长14.1%。

(二)中国跨国公司对外直接投资区位选择的特点1. 亚洲地区是中国跨国公司的首选投资区位。

外商直接投资在中国区域一级的决定因素分析【外文翻译】

外商直接投资在中国区域一级的决定因素分析【外文翻译】

原文Determinants of foreign direct investment at the regional level in ChinaAs the worlds most populated country, China has attracted a great deal of attention from a wide range companies seeking to leverage the low relative cost of employing a Chinese work force, or to gain access to the growing Chinese middle and upper classes. From the investor's point of view, picking the right location that provides a competitive advantage is critical to developing a sustainable business model. The location he or she would choose as the destination of FDI must ultimately be more profitable to invest in than in others (Coughlin et al., 1991). Choosing the right location often involves many different factors.Hymer (1960) found that American FDI was mainly concentrated in a few industries and monopolized by several companies. Multinational companies (MNC's) were the product of imperfect markets and monopoly advantages where the companies had the advantage with regards to choosing where to invest. A number of conclusions can be drawn from Hymer's analysis that helps frame up this study:•First, FDI tends to flow into differentiated markets where a MNC believes they will have an advantage competitively.•Second, companies that are able to make investments overseas all have certain advantages, such as economies of scale, differentiated products, special skills, and low-cost production. These companies will make investments in regions that do not have these advantages.•Third, there are many ways in which MNCs can invest overseas in such as exporting, and licensing, in addition to direct investment. MNCs without local partners always prefer to choose foreign direct investment.•Last but not the least Hymer found that about half of the overseas operating capital of American firms came from host countries; thus FDI tends to flow into the countries or regions that have developed financial systems and capital markets. The case for China as a host for FDI has increased substantially since Hymer first published his thoughts in 1960. China as a source of low cost labor, and with an attractive, rapidly growing domestic market represents growth for many companies.The fact that the coastal regions – especially those in close proximity to Hong Kong, and with historic ties to the West and Taiwan also have sophisticated financial systems and capital markets supports Hymers conclusions (Figure 1).Other factors may also contribute to the emergence of China as a leading host for FDI. In the 1970s and early 1980s, Buckley and Casson (1976) and Rugman (1981) put forward the concept of internalization. Internalization[2] means the process of establishing a market inside the company and substituting the internal market for an external market. The transfer price inside the company enables the internal market to operate as effectively as the external market. The theory holds the opinion that the imperfection of external markets compels the company to exchange certain products inside the company. When this happens across national boundaries, it acts as FDI of MNCs. Countries that bring about the imperfections in the external markets (such as high tariff of non-tariff barriers) are where FDI tends to flow. The trend toward collaboration through joint ventures, partnerships, and other forms of collaborative relationships may suggest that companies are attem pting to create “internal markets” with a select group of companies. The central and regional governments – through the degree of openness (i.e. foreign, private ownership of state owned enterprises) may be significantly responsible for the creation of the se “internal markets.”While low cost, access to the domestic markets, and the creation of internal markets that simplify the transfer of FDI are often compelling from a country point of view from a regional perspective, selecting the right location can be a significant challenge. Dunning (1977) assumed that to make a FDI, companies should have three advantages: an ownership advantage; a location advantage; and an internalization advantage. Influenced by industry location theory, Dunning determined the definition of location advantage as the advantage one location had over another based upon: •natural and human resources;•the price, quality and productivity of inputs;•international transportation and communication cost;•investment favor or discrimination;•man-made barriers to trade;•fundamental facilities;•cross-national values, language, culture, commercial practice and politics;•research and development;•the concentration of production and sales;•economic system and political strategy;•resource allocation system. (pp. 395-418)The location advantage (or edge) theory is relevant to this study as it holds the opinion that the reason why an international company makes direct investments in a particular region is that the company would like to attain certain location advantages which do not exist in other host countries. Various studies (Table I) have highlighted the factors that investors care about including: labor cost, market size and market potential, trade barriers and country risks. Those host countries with lower labor cost, lower transport cost, greater market potential, trade protectionism, smaller country risk, better infrastructure and better educated and skilled populations are typically the focus of FDI.According to traditional location theory, investment incentives can be mainly divided into two types: First, those targeted at cost savings, which pursue a production cost edge in host countries where FDI is mainly focused on producing locally and then exporting; and second, for those companies who aim to expand their market presence through increasing their pene tration in “local” markets. FDI mainly focuses on local production and local sale (as opposed to exporting), so this kind of FDI places a high emphasis on market size, market growth, and consumption ability.Empirical worksLocal markets are often considered by country or by region. There is a vast amount of existing literature focused on the geographical distribution of FDI (Table II). Numerous studies have been done that identify the determinants of FDI for regions, countries, regions within countries, as well as FDI flows between countries.While there is not necessarily a single set of factors that consistently determine FDI, infrastructure, skilled labor, labor cost/wage, agglomeration, and government support in terms of openness, and/or attempts at attracting FDI are often cited as having a significant relationship between FDI and the location choice. And while regions thatreceive substantial FDI may benefit, it is ultimately the linkages between education, government, and industry that perpetuate the development of new activities in the region, leading to innovation, and further investment (Porter and Stern, 2001).With the fast development of its economy, China has been of crucial importance to FDI, thus the study of investments in China has been growing (Table III). Wang and Swain (1995) examine the determinants of FDI in China, finding that FDI in the manufacturing sector is positively related to China's GDP, GDP growth, wages, and trade barriers, but negatively related to interest rate and exchange rate.Bhagwati and Srinivasan (1983) conducted a survey to rank provinces of China with the best investment environment. They identified a number of variables: market size; wage, education, extent of industrialization, infrastructure (transport facilities, communication facilities, living environment), and the level of scientific research. Chen (1996) divided China into East, Central and West regions, and found that wage has no relation with spatial distribution of FDI but, that market size has the most influence on the Central Area. Wei (1999) found that bribery and other dishonest behaviors of governors influenced the inflow of FDI. LuMinghong (2000) identified some additional determinants besides general economic factors such as an infrastructure factor with energy consumption as proxy; labor quality with the literacy percentage as proxy; and a system factor with honest government and degree of openness as proxy. Bhagwati and Srinivasan (1983), and Sun et al.(2002) found a correlation between investment in scientific research and FDI flows. Tong and Yueting (2000) considered the hometown connections of overseas Chinese investors as a determinant of FDI flow into China, noting that Taiwanese investors have often invested through Hong Kong to limit delays due to government and bureaucracy. Sun et al.(2002, p. 88)identified possible determinants of FDI flow within China including market demand and size, agglomeration, labor quality, labor cost, level of scientific research, degree of openness, country risk.Empirical frameworkThe location of FDI in China has striking spatial characteristics. The provinces in China are classified into three regions: Eastern, Central, and Western. FDI is unevenlydistributed across the three. Table IV shows that in 2002, the Eastern region received more than 86 percent of the total FDI amount while the Central and Western regions together received less than 14 percent. This is consistent with past trends for FDI in China and has been cited as one of the reasons that have led to the fast development of the coastal provinces and the widening gap in terms of economic development between the coastal and inland provinces. (Cheng and Zhang, 1998) Moreover, the FDI flow into Eastern China has continued to increase. From 2001, the amount of FDI in the eastern regions has increased by 1.19 percent while in the central regions, FDI has only risen by 0.2 percent. In the western regions, FDI actually decreased by 1.39 percent (Lu, 2003d). From these figures it is clear that the location of FDI in China is characterized by enormous spatial diversity.There are other two main characteristics of China's FDI pattern, which may have some certain links with the spatial pattern. Table IVshows that investment activity tends to concentrate on secondary industries like utilities, manufacturing, and property development, while the primary sector attracts only about one fourth of the total FDI. Table IV also shows that foreign capital flows mainly from Asian countries, with more than 60 percent of the total foreign capital comes from Hong Kong, Taiwan, Japan, Korean and other Southeast Asian countries. In terms of the total accumulative amount of foreign capital that the country or area actually used ($100 million), the top four sources of FDI were: Hong Kong (2,048.75 mn), the USA (398.89 mn), Japan (363.40 mn), and Taiwan Province (331.10 mn). (Lu, 2003d) These four sources of FDI contribute more than two thirds of total FDI; however, Hong Kong's share of FDI far exceeds those of other countries and regions (Figure 2). Part of this may be explained to the pass through investments made by investors from Taiwan and other countries to ease the flow of capital.At the regional level, the data shows that distribution of FDI across China's regions is very uneven. In 2002, the top four areas are Guangdong, Jiangsu, Shandong, and Shanghai, which accounted for 59.28 percent of the total FDI (Figure 3) (Lu, 2003a, b, c).The reasons for FDI by region are –as stated previously –varied. In the Eastern regions, it has been argued that proximity, history, culture, and language all play asignificant role in determining FDI. Others (Table III) have found a wide range of other significant determinants of FDI. From these past analyses of potential determinants of FDI in China, five were chosen to determine if there was any significant relationship between them and FDI across the regions within China (Table V). Table VI reveals the distributions of FDI according to these determinants (Table VII).•The first determinant is the market size (GDP). It directly affects the expected revenue of the investment. In fact, one major motivation for FDI is to look for new markets (Shapiro, 1998). The larger the market size of a particular region, the more FDI the region should attract given other things remain constant. Kravis and Lipesey (1982), Blomstrom and Lipsey (1991) and others have identified market size as having a positive impact on FDI. We use GDP per capita for demand and size effect.•The second determinant is agglomeration (ROAD) which refers to the concentration of economic activities that leads to positive externalities and the economies of scale. Coughlin et al.(1991), Wheeler and Mody (1992) and Braunerhjelm and Svensson (1996) amongst others found that the level of agglomeration was positively related to the FDI in a particular country. This study uses infrastructure quality to capture the agglomeration benefits. The highway and railway mileage per square kilometer is proxy for the quality of infrastructure.•The third determinant is labor quality (SCHN). This study used the total number of the primary, and secondary schools, as well as universities as a proxy for education and further for labor quality. Mody and Srinivasan (1998), LuMinghong (2000) and Akinlo (2004), all found that labor quality has a positive impact on FDI.•The fourth determinant is labor cost (WAGE), as measured by wage. Bhagwati and Srinivasan (1983), Coughlin et al. (1991),Wang and Swain (1995) all found a relationship between wage or labor cost, and FDI. However, labor cost may have a negative correlation. Multinational firms in China tend to hire quality workers who earn higher wages as a possible reflection of this higher labor quality. Hence, wages in those provinces that attract more FDI may be higher.•The fifth determinant is the degree of openness and progress of reform (SHARE). Sun et al.(2002) and Fujita and Hu (2001)found that a significant relationship between the degree of openness –as defined by the percentage of states owned enterprises (SOE's) and FDI. On the one hand, a more open economy means that foreign investors are more familiar with the host economy and may therefore be more willing to invest in the country. On the other hand, openness can have a negative impact on FDI as it may attract more competition, lessening any competitive advantage a firm may have hoped to realize. We use the share of state-owned enterprises in all enterprises of a region to measure its degree of openness and progress of reform.As noted previously, there are many other commonly used determinants that may have a correlation with FDI in China – determinants like the number of telephone sets, number of tourists, level of scientific research, degree of industrialization, agglomeration of FDI, promotion expenditures for attracting FDI, tax structure, and the special treatment offered to foreign investors that may have impacts, too. However, such data is more difficult to obtain on a regional or provincial level in China, which led to the focus on the five aforementioned determinants.The typical method of estimating the effect of potential determinants of FDI is to regress the chosen dependent variable, such as the amount of FDI in a location, on a set of independent variables which would possibly affect the profitability of investment. These variables typically reflect local market potential, and the cost of production and transport, as well as the general environment faced by the multinational company. On the basis of the existing statistical analyses of the location of FDI in China, we postulate that for the amount of FDI in region i: Equation 1 where GDP, ROAD, SCHN, WAGE, and SHARE represent the variables for market size and demand, agglomeration/infrastructure, labor quality, wage, degree of openness and progress of reform, respectively.Since, our dependent variable is the per capita amount of FDI, we use per capita GDP to capture the regional market potential or market size. In order to experiment with an appropriate choice of the infrastructure variable (ROAD), three alternative proxies were tested:1the total lengths of roads per unit of land mass;1the total lengths of high grade paved roads per unit of land mass; and1the total lengths of railway per unit of land mass.A region's labor cost (WAGE) is given by its average labor cost divided by its retail price index. Our education variable (SCHN) is the total number of primary, secondary schools, and universities for a given region. All real variables are measured in current prices. In our sample, a region is either a province, centrally administered municipality, or an autonomous region.As the determinants of FDI distribution were examined across regions regardless of time trends and with known data limitations, this assignment only requires ordinary least-squares (OLS) estimation. The data used in this study are obtained from China's Statistical Yearbook2003, the China Statistical Yearbook for Regional Economy2003, the China Foreign Economic Statistical Yearbook2003, and the White Books of China's Trade and Economics (2003). For this study, two elements of FDI were used: “Signed Agreement” and “Actually Utilized”. The later one is the actual amount of FDI invested in the region. Since, GDP and wage are denominated in RMB and the FDI in US dollars, we converted the FDI into RMB using the average yearly exchange rate in 2002. It is possible that a high correlation between the various proxies may come out and that the proxies may overlap with one another, which may lead to serious multicollinearity. In order to cope with multicollinearity, those highly correlated pairs were excluded. Specifically, all variables were transformed into the natural logarithm form and were then stacked up across the 30 regions.In summary, foreign direct investment at the regional level in China was expected to be affected by the region's market demand and market size (GDP), infrastructure (ROAD), labor quality (SCHN), labor cost (WAGE), and the degree of openness and progress of reform (SHARE).A general pooled regression model is used on these variables and is specified as: Equation 2 Where subscript i refers to individual provinces; αi is the intercept; ɛ is an error term; βi (i=1, 2, 3, 4, 5) are vectors of unknown coefficients to be estimated.Analysis of resultsThis section determines how location factors determine flows of FDI. reports the OLS estimation results of equation (1) on the regional level. The model is regression with a common intercept and the OLS estimates are significant except for ROAD and SCHN. The Adjusted R2 value of 0.793 further suggests that the model fits the data well.Summary of resultsThis study has found that three of the variables have a statistically significant relationship with FDI in the 30 different regions studied in China. The relationship between a regions market demand and market size (GDP) was a significant and positive factor in attracting FDI in 2002. The Coefficient estimate 2.843 indicates that foreign direct investment is very responsive to differences in per capita GDP across provinces. A 1 percent increase in GDP is estimated to lead to a 2.843 percent increase in FDI. This supports the hypothesis that the market demand and size as well as the general development level of a region have a positive impact on attracting FDI. This would seem to suggest that foreign firms may be motivated to invest in China under an assumption that to do so will allow them to gain access to China's growing middle class.The higher the quality of labor the more attractive a region was to FDI. The results suggest a positive relation between FDI and the quality of labor, as proxied by the number of primary, and secondary schools, and universities. A 1 percent increase in SCHN is estimated to lead to a 0.847 percent increase in FDI. The level of significance suggests that labor quality is important to FDI consideration. Although China is making major investments in education, the still relatively low quality of labor in China may discourage some Western FDI in capital-intensive projects where a skilled work force is a prerequisite for success.The final variable that exhibited a significant relationship with FDI was the degree of openness and level of reform in each region. A 1 percent increase in the share of state enterprise in industrial output is estimated to lead to a 1.147 percent drop in FDI. The more ownership governments have in business enterprises, the lower the FDI. The positive and significant coefficient of SHARE indicates that foreign investors respond positively to the economic reform – as determined by a reduction in the level of stateownership for enterprises in a particular region. The result also gives evidence that an open economic policy and further economic reforms are crucial in attracting FDI to China.The other two variables did not meet the test of statistical significance. As a proxy of the level of infrastructure, ROAD shows no significance in the regression. Since, this variable is used to capture the agglomeration effect, the result is not supportive of the agglomeration argument, i.e. that the level of similar and related businesses in a region may lead to an increase in FDI. There is some evidence, however, to suggest that the positive result gives mild evidence that there is a positive relationship between infrastructure and FDI.A major disadvantage of using the OLS regression is that it cannot resolve or reduce the magnitude of key econometric problems that often arise in empirical studies, namely, the unobserved variables that are correlated with explanatory variables. In the application here, equation does not allow for fixed effects in the cross-section so that intercepts need to be identical across different provinces. As such, unique but unobserved factors driving the FDI amount of individual provinces would not be captured in the respective intercepts in the equation.LimitationsOur study has several limitations that deserve further investigation. First, the importance of determining factors may change over time. Similarly, the location determinants of foreign direct investment may differ by industry. Furthermore, due to data limitation, we were not able to consider the effect of FDI policies, tax incentives, cumulative FDI, and foreign portfolio investment to FDI in China. Finally, we believe corruption and the effects of bureaucratic red tape are also important deterring factors of FDI.本科毕业论文外文翻译外文题目:Determinants of foreign direct investment at the regional level in China出处:Journal of Technology Management in China作者:Lv Na, W.S. Lightfoot译文:外商直接投资在中国区域一级的决定因素分析作为世界上人口最多的国家,中国的劳动力日益吸引了外国公司的广泛注意,外国公司进入中国广泛的寻求利用相对低的中国的雇用劳动力成本。

外商直接投资区位选择的影响因素研究

外商直接投资区位选择的影响因素研究

外商直接投资区位选择的影响因素研究朱先勇20101342077摘要:改革开放以来,特别是加入WTO以后,外商直接投资(FDI)以空前的速度在我国发展起来,但是其地区分布却高度不均衡。

东部沿海地区集中了超过85%的绝大部分外资,中西部地区的外商直接投资则很少。

同时地区经济也呈现出东部地区发达,中西地区相对落后的格局。

为探讨上述现象呈现原因,本文将结合一些国内外对外直接投资理论,介绍外商在我国直接投资的分布状况,并从主客观因素详细分析FDI区位选择的影响因素,最后在结论与启示中简单提出了一些中西部地区如何有效吸引外资,缩小区域经济差距,协调区域经济发展的建议,以期对我国各地区制定适宜的招商引资策略具有参考和借鉴意义。

关键词:FDI;我国;分布;区位选择;影响因素一、引言中国自对外开放以来,顺应国际产业转移的趋势,凭借廉价的劳动力和土地资源在各项优惠政策引导和各级政府部门努力下,吸引了世界各地的外商前来投资,现已成为国际直接投资最为集中的国家之一。

FDI的流入不仅为我国经济发展提供了资本来源,还带来了先进的技术、组织、管理技能以及其他无形资产。

实践证明,FDI的流入极大的带动了当地相关产业的竞争、革新、储蓄和资本的形成,同时有力的促进了对外贸易、经济增长和就业。

但是,由于国内各地区的经济发展水平差异较大,东部地区依靠相对完善的基础设施和优越的地理位置集中了全国绝大部分的外商投资企业,而中西部的一些地区连基本的区位条件都不具备,这就导致FDI在中国分布的两极分化现象。

如何看待FDI 这种区位分布的差异,其区位选择影响因素又是什么,弄清这些问题,对于各地政府,尤其是对于广大的中西部地区,无疑具有重要的理论和现实意义。

二、文献综述FDI的区位选择本质上仍是一个厂商选址问题(吴丰,2002),一是外国直接投资的国别选择;二是外国直接投资的国内区位选择。

本文的主要目的是为了说明后者,即外商在我国直接投资时的区位选择。

外商直接投资区位选择影响因素研究

外商直接投资区位选择影响因素研究

外商直接投资区位选择影响因素研究摘要:本文在对中国31个省市自治区按照社会发展水平进行聚类分析的基础上,对不同类别地区的FDI区位影响因素进行实证检验,结果显示巨大的市场规模及市场潜力、开放的市场经济和良好的基础设施都有利于吸引FDI,而低市场化程度和过多政府干预对FDI有显著的负面影响。

另外,集聚效应对FDI 的区位选择产生的影响也比较大。

比较出乎意料的是工资水平的提升反而会带动FDI的流入,因为高工资的地区有着优秀的人力资源,意味着较高的劳动生产率,实际工资水平反而较低,从而更加吸引外资企业目光。

关键词:外商直接投资;区位选择;影响因素;聚类分析The influential factors of foreign direct investment location choiceAbstract: Based on Chinese 31 provinces and autonomous regions shall be carried out in accordance with the level of social development, on the basis of cluster analysis, FDI location of different categories in the empirical test, the factors which influence the results showed that the huge market size and market potential, the opening of the market economy and good infrastructure to attract FDI, and low market degree and excessive government intervention has a significant negative effect on FDI. In addition, the impact of agglomeration effects of FDI location choice is also relatively large. More surprisingly wage level of ascension will drive the FDI inflows, because of the high wages region has good human resources, means higher labor productivity, and instead of real wages is low, thus more attractive to foreign capital enterprise.Keywords: Foreign direct investment; location choice; Influencing factors; Clustering analysis一、引言近年来,我国外商直接投资发展非常迅速。

日本对华投资区位选择影响因素

日本对华投资区位选择影响因素

2011年第8期山东社会科学No.8总第192期SHANDONG SOCIAL SCIENCES General No.192日本对华投资区位选择影响因素分析沈明伟(山东师范大学经济学院,山东济南250014)[摘要]日本对中国大陆投资的区位选择总体上呈现出从沿海向内陆扩展的态势,但其直接投资的重点还是集中在长江三角洲、珠江三角洲、环渤海经济开发区等重点区域。

采用因子分析法把选取影响日本对华投资的11个变量转变为两个公因子,再用日本对华投资金额与两个因子值以及几个重要变量作回归分析,以找出他们之间的关系;计算各省市公因子得分和投资吸引力;根据各省市得分结果分析吸引日商投资的主要影响因素。

[关键词]日本对华投资;区位选择;影响因素[中图分类号]F753[文献标识码]A[文章编号]1003-4145[2011]08-0043-04总体上看,日本对中国大陆投资的区位选择呈现出从沿海向内陆扩展的态势,但其直接投资的重点还是集中在长江三角洲、珠江三角洲、环渤海经济开发区等重点区域。

而且,三个经济区域由于投资环境的差异,从而表现在吸引日本投资的数量上也有所差异。

研究日本对华投资区位选择的影响因素,有利于中国大陆各省改善投资环境,发挥区位优势,合理引进外资。

一、变量选取与数据来源(一)主要被解释变量日本对华投资的金额。

本文采用《2008日本在华投资企业名录》中所统计的截至2007年底日本对中国大陆各省市日本企业、中日合资企业的累计投资总额。

主要被解释变量采用《2008日本在华投资企业名录》的统计数据,主要是基于以下原因:其一,该统计数据准确性较高,且较完整,样本量可达30个省、市、自治区(不含西藏);其二,历年来中国大陆各省市统计的日本对华实际投资总额数据不全;其三,商务部对日本在大陆投资的统计没有分省数据,仅有每年的投资总数。

(二)主要解释变量主要解释变量包括各省的GDP总量、第三产业从业人员、在校高等学校学生数量、电力消费量、资金配套能力、①外贸依存度、②实际外商投资金额、邮电业务总量、工业企业数、非国企比、社会消费品零售总额、交通密度、职工平均工资。

外商在华投资的区位影响因素分析

外商在华投资的区位影响因素分析

外商在华投资的区位影响因素分析外商在华投资的区位影响因素是指在选择投资区域时,外商考虑的一些重要因素。

这些因素包括地理位置、交通便利性、人力资源、市场规模、政策环境和基础设施等。

本文将分析这些因素对外商投资区位的影响,并提出相关建议。

首先,地理位置是外商选择投资区位的一个重要因素。

中国的地理位置非常优越,毗邻东南亚和西亚欧洲等重要市场,交通便利,极大地促进了外商的投资。

例如,沿海地区拥有丰富的港口资源,可以方便地进行海上贸易和物流,吸引了大量的外资。

此外,内陆地区也具有优势,比如西部地区的巨大市场潜力和资源优势,吸引了一些外商的投资。

其次,交通便利性也是外商选择投资区位的重要考虑因素。

中国具有完善的基础设施建设,包括高速公路、铁路和航空网络等。

这些交通设施的发展使得外商能够更加方便快捷地进行物流和分销,降低了物流成本,提高了投资的效益。

同时,交通便利性也有助于外商与合作伙伴和供应商的联络和沟通,提供了更好的投资环境。

人力资源是外商选择投资区位的关键因素之一、中国的劳动力数量庞大,具有相对廉价的劳动力成本和高素质的劳动力。

外商在中国投资可以得到充足的劳动力供应,并且能够根据自身需求进行培训和管理。

此外,中国的人力资源也具有较高的技术水平和创新能力,可以为外商提供更多的合作机会和创新优势。

市场规模是外商选择投资区位的重要考虑因素。

中国的市场规模庞大,消费潜力巨大,是全球最大的市场之一、外商选择在中国投资可以充分利用中国庞大的市场需求和潜力,提高产品销售和盈利能力。

此外,中国的市场还具有相对不饱和的地区性市场,为外商提供了更多的发展机会。

政策环境也是外商选择投资区位的重要因素之一、中国政府积极推动外商投资,提供一系列的优惠政策和扶持措施,包括税收优惠、土地租赁和劳动力使用等。

这些政策为外商投资创造了良好的政策环境,降低了投资风险和成本,增加了外商的投资动力。

最后,基础设施是外商选择投资区位的关键因素之一、中国具有全面发展的基础设施体系,包括电力、通信和供水等。

日韩企业在华投资区位选择研究

日韩企业在华投资区位选择研究

日韩企业在华投资区位选择研究摘要:受传统文化和地域因素的影响,中国吸收的跨国公司的投资主要来源于亚洲地区,其中日本与韩国更是其中比较重要的投资来源。

文章介绍了相关的区位优势理论并分析了在经济全球化大背景下,日韩企业在华跨国公司的区位选择动态和现状以及存在问题,并分析了未来应该调整的对华投资策略。

日韩企业在华的区位选择主要集中在沿海地区并且以制造业为主,但近年来日韩与中国的贸易由于三国的经济政治关系的变化而面临着一些威胁,文章在分析了日韩与中国的贸易所存在的问题之后提出了日韩两国在中国投资可以选择的战略决策。

关键词:日韩企业;在华投资;区位优势理论;对华投资策略调整企业投资的区位选择是一个复杂的动态决策过程,不仅要考虑生产成本方面的比较优势,如运输成本、劳动力成本、交易成本等,而且要考虑市场和产业等方面的因素,如市场规模、产业聚集程度等。

另外,一些制度因素,如关税、非关税壁垒税收优惠,以及文化差异等也会影响投资流向。

当我们研究的是外国企业在中国的区位选择时,我们可能看出中国不同经济区在成本、市场规模以及产业聚集程度的优劣势。

这对我们改进不同地理位置的经济水平并且制定相应政策法规来刺激一个地区的经济水平很有必要。

对跨国企业在华区位选择的研究可以更好的促进中国与国外的贸易往来并且缩小不同地区经济方面的差异。

这就是本篇文章选题的原因。

1相关区位优势理论基础与决定因素区位优势即区位的综合资源优势,即某一地区在发展经济方面客观存在的有利条件或优越地位。

其构成因素主要包括:自然资源、地理位置,以及社会、经济、科技、管理、政治、政策、文化、教育、旅游等方面,区位优势是一个综合性概念,单项优势往往难以形成区位优势。

一个地区的区位优势主要就是由自然资源、劳力、工业聚集、地理位置、交通等决定。

同时区位优势也是一个发展的概念,随着有关条件的变化而变化。

关于区位优势理论,邓宁的国际生产折衷理论是最具代表的理论之一。

区位优势往往是与跨国公司对外投资动因紧密相关。

外商在华直接投资区位选择影响因素研究

外商在华直接投资区位选择影响因素研究


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间产 品供 给 越 多 , 对外 资 的 吸 引力 就 越 大 。 由于 江

日本企业の対中国直接投资の课题ぃ関する一考察—现地経営の贩壳

日本企业の対中国直接投资の课题ぃ関する一考察—现地経営の贩壳
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7’ / 一 岛屯日本企柴 中国市埸獾 得意谶 今後 岛【 二高 圭否二 第 2位 奄占功 否 5【 = 一 ) 广 二 、 米国 对 中投资 方c 土大型化 L L 、 否。 艺c 去罐 吏 艺思 丰 ) 才 , L 否。 日本 企 柴 中 国 【 =本 格 的 【 二连 出 卺 鞠 始 L 弓 屯. j一一 ) 收益率 【 = 影 辔 奄 与 走 否要 因蚀 、 日 米企 柴( 7 ) 投 资 勤 横 相 逵

日本对华FDI区域分布的影响因素分析

日本对华FDI区域分布的影响因素分析

1 9 年 我国2 个 省 区外 资数 据分析 了投 资环境 对F 区位 的 5 9 9 DI 影 响 ,发现 GD 、第 三 产 业 比重 、 城镇 化 水平 、政 策优 惠 P 度 、经 济外 向度 与F I D 成正 相 关关 系 ,而 劳动 力成 本和 国有 工 业 产值 比重 与F I 负相 关 关 系 。 魏后 凯等 以秦 皇 岛市 D成 的外 商投 资企 业 为调 查 对 象进 行 的研 究表 明 ,影 响外 商在
深度调 研
/ 江统计 2 0 年3 / 浙 0 9 期
日本对华F 区域分布的 D I 影响因素分析
佘德容 ( 浙江工业大学经 贸管理学 院,浙江 杭州 3 2 1 0 3) 0
摘要 :日本是我 国重要的F 投 资国,但 日本的投资在 东、 中、西部 分布极 不均衡。本文借助 DI
山 西 、吉 林 、 黑 龙 江 、安 徽 、 江西 、河 南 、湖 北 、湖 南等 8 :西 部 地 区包 括 重 庆 、 四川 、贵 州 、云 南 、西 藏 、陕 省 西 、甘 肃 、 青海 、 宁夏 、 新疆 、广 西 、 内蒙 古 等 1 个省 、 2 市 、 自治 区 。 本 文 使 用 的数 据 来 源 于 《中 美元 , 占全 国吸收 日资总量 中的 比 .2
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地 区吸 收 日本F 的实际投 资额 极 不均 衡 ,详见表 1 DI 。
浙 江统计 j2 0 年3 0 9 期
表_ 19 - 0 6 1 9 7 2 0 年中国各地区日 本实际投资额 ( 亿美元 )
地 区 1 9 1 9 1 9 2 o 2 o 2 o 2 0 2 0 2 0 2 ( 9 7 9 8 99 O o o l o 2 o3 0 4 0 5 06 )

日本对华直接投资的行业布局及对策研究

日本对华直接投资的行业布局及对策研究

Industrial Distribution and Optimization of Japan's Direct Investment in China
作者: 王恕立;崔惠莉
作者机构: 武汉理工大学经济学院,湖北武汉430070
出版物刊名: 武汉理工大学学报:社会科学版
页码: 204-207页
主题词: 日本对华直接投资;行业布局;优化;对策
摘要:入世后,我国利用外资的战略思想更加凸显出对'结构、质量、效益'的偏好,战略目标
确定为以优化产业结构为重点,增强利用外资的总体经济效益.日本是我国引进外资的主要来源国之一,日本企业对华直接投资的行业比较多.文章分析了日资企业产业分布的现状、原因,并提出了优化日资企业产业分布的对策.。

外文翻译--外国直接投资在中国的分布

外文翻译--外国直接投资在中国的分布

The Distribution of Foreign Direct Investment in ChinaHarry G. Broadman and Xiaolun SunLabour cost. Foreign investors generally aim to take advantage of host countries’cheaper factor inputs (relative to their home countries), and the cost of labour is often considered important in this regard. In other words, foreign investors display sensitivity to inter-country variations in labour costs in making their location decisions. However, the sensitivity of FDI location decisions to intra-country labour cost differentials is unlikely to be as pronounced. Indeed, even though the decision to invest in China is no doubt heavily influenced by the country’s prevailing low wage rate, once the choice is made to locate an investment in China, finding the cheapest possible labour within China may not be an important consideration as wage differentials may not be significant. In fact, it is likely to be the case that observed wage rates(including bonuses and in- kind benefits) do not vary as much between regions within China as within other countries because of China’s legacy of central planning, which has tended to homogenize wage rates. Thus, while the provinces with higher labour costs can be expected to compete less favourably in their efforts to attract foreign investment, our expectation is that this variable is not likely to yield a strong negative relationship with provincial FDI accumulation. The measure of labour cost we use is the average annual provincial wage to staff and worker in 1992.Human capital. A host region’s labour supply influences foreign investors’ location decisions not only in terms of input costs, but also through the quality of the skills of the labour force——especially if the price mechanism is repressed, as is the case in China’s labour markets. All other things being equal, locales with highly skilled workers——most easily measured by education levels——would be expected to compete more favourably than others in their FDI attractiveness. In this study, adult illiteracy is taken to represent the extent of basic education of a province’s workers. The data are taken from China’s Fourth National Population Census in1990, where the population is classified as illiterate and semi-illiterate. These two classifications are divided by provincial population ‘up to age 6’and ‘over age 6’to obtain an illiteracy ratio.Infrastructure. There is no dispute that the extent of an area’s infrastructure development is important in an investor’s location choice. Infrastructure, of course, covers many dimensions, ranging from highways to railroads to telecommunication systems to even institutional development (e.g., extensiveness of business-related services such as accounting, legal services, etc.). Owing to the difficulty of capturing all these various dimensions in an easily calculable variable, for this study we settled on using as a measure of a province’s infrastructure development the total length of transportation routes within the province, calculated as the sum of the length of the (i)railways in operation, (ii) the navigable inland waterways and (iii) the constructed highways in 1992, normalize by provincial geographical size. In effect, this variable measures provincial transportation route density. It is expected to be positively related to the level of FDI stock.Geographical location. As in other countries, another factor that is likely to be an important determinant of the geographical distribution of FDI in China is whether a province has a coastal location and thus is in close proximity to major shipping ports. In China, coastal location may also be important because of the government’s FDI policy regime——namely that fiscal incentives for foreign investors, such as lower income tax rates and reduced tariffs for imports used in the production of exports, have been heavily slanted in favour of cities along the coast. Although, as the empirical literature shows (as noted above), such incentives only marginally affect FDI decisions in other countries, it would be helpful to assess their effects in the Chinese context. But this is impossible in our case given the unavailability of data on the other explanatory variables: SEZs (or other similar tax preference units) are not jurisdictions on which GNP, illiteracy, labour costs and infrastructure development are measured; hence our unit of analysis is the province. We thus use a dummy variable to reflect coastal location; for this variable the twelve coastal provinces take on the value 1, while others are 0. This variable is expected to be positively related to a province’s FDI accumulation.All the reported coefficient estimates in Model II bear the expected sign and are statistically significant at the 10 per cent or above confidence level (except the intercept). More than 80 per cent of the variation in provincial FDI stocks in China can be explained linearly by the variations in the four independent variables. For a cross-section analysis such as this one, an adjusted R-square of 82 per cent is considered high.The total GNP level is one of the most important factors in foreign investors’ location choice in China. The coefficient estimate for this variable results in the highest statistical significance among our explanatory variables. A one per cent increase in the market size of a host province brings about nearly one percentage point more FDI into the region. This outcome is consistent with previous cross-country studies on FDI destination.The results also confirm our expectation that FDI in China goes to where there is greater development of basic infrastructure; the extensiveness of transportation facilities is shown to have a significantly positive effect on the location of FDI. A one per cent increase in transportation route density is associated with a 0.46 per cent increase in provincial FDI accumulation.Adult literacy has a small, nonetheless significant, positive effect on the destination of FDI in china. As we noted above, when the cost of labour is relatively insignificant(as is the case in China where wage rates vary little from region to region), the quality of the labour force is expected to have a foreign investor’s FDI location decision. A one per cent decrease in the adult illiteracy ratio is shown to be associated with a 0.05 percentage point increase in FDI.As expected, a province’s geographical location makes a significant difference in its FDI accumulation potential. The coastal regions have shown a clear advantage over inland provinces in their ability to attract FDI. The dummy variable that puts the 29 provinces and autonomous regions into two broad categories is shown to be highly sensitive to the pattern of Chinese FDI distribution. Our results imply that coastal provinces have a 1.3 percentage point edge over their inland counterparts. It is the combined effects of being close to major shipping ports and being granted special investment incentives that set the coastal regions apart from others.We thus conclude that to a large extent the destination of FDI within China is determined by market size, the extent of infrastructure development, the basic education level among adults, vicinity to import and export markets as well as capital sources, and special investment policies.劳动力成本。

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外文翻译原文Locational Determinants of Japanese Foreign Direct Investment in ChinaMaterial Source: Asia Pacific Journal of Management, 19, 63–86, 2002 c 2002 Kl uwer Ac adem i c P ubl i s hers. M anuf a ct ured i n T he N et herl ands.Author:ANDREW DELIOS CHANGHUI ZHOU2. Background on FDI in ChinaForeign investment in China has a long history. In the early 1900s, British, French, German and Russian firms were the most active foreign investors in China. Collectively, firms from these countries accounted for nearly 90 percent of all foreign investment in China in 1902 (Wu, 1958). The importance of these nations as foreign investors in China declined in the next forty years as the nominal value of Japanese investment in China grew from a low position of US $53 million (3.5 percent of the total value of FDI in China in 1902) to US $6,829 million in 1944. The latter figure represented 75 percent of all foreign investment in China in 1944. It marked the peak value of investment in China during Japan’s occupation of China (Wu, 1958). Notable about foreign investment during this period is the relative absence of joint ventures, and its concentration in Shanghai and the northern provinces of China (Hayter and Han, 1997).Between 1949 and 1976, China followed its economic strategy of self-reliance. After the institution of the Act of Joint Venture Enterprises in 1979, which formally re-opened China’s doors to FDI, foreign inve stment began to resume. The Act mandated that foreign firms take a minimum equity share of 25 percent in foreign invested enterprises, but it did not prescribe a maximum. As well, in the original Act, foreign investment was limited to four Special Economic Zones (SEZs): Shantou, Shenzhen, Xiamen and Zhuhai. Th e fifth SEZ, Hainan, was added in 1988 (see Table 1).In these SEZs, a variety of FDI incentives were promoted. For example, a two-year tax holiday was granted to foreign subsidiaries on the first two-years of profitable operations; the third to fifth years of profitability were taxed at 50% of normal rates. Duties were eased on the import of equipment and the export of product;and other barriers, such as entry and exit formalities, were reduced (Jia, 1994). Among other factors, vast tracts of land were allocated for commercial uses and greenfield establishments, which especially attracted much of the Hong Kong investment in the early periods. Even with the establishment of SEZs; however,several barriers to investment still existed. Lockett (1987), for example, i dentified poor infrastructure, bureaucracy, low labor productivity and a weak legal framework as the main problems faced by managers of foreign subsidiaries in SEZs.The geographic scope of FDI promotion was broadened in 1984 and 1985. The size of the original SEZs was expanded to become open economic zones and another fourteen coastal cities, known as Open Coastal Cities (OCCs), were opened to FDI. In fact, many OCCs had a higher level of economic and infrastructure development than the SEZs in the early 1980s. Foreign investors in OCCs received tax concessions similar to, but not as munificent, as those in SEZs. For instance, foreign invested enterprises located in the OCCs generally paid national profit taxes at rates of 24 to 30 percent, while those in the SEZs often enjoyed rates as low as 15 percent. Similar differences existed in other areas such as exemptions and reductions of profit taxes, import duties, and land use fees (Cheng and Kwan, 2000).SEZs and OCCs were confined to a small set of cities along the coast. To attract FDI to more regions, the Chinese government introduced new and high-technology industrial development zones (NTZ). These zones had two levels. There was the national level which included 52 newly-established regions created in the 1991 to 1992 period. There was also local level development in which provincial governments imitated national level creations of these new development zones. The new and high technology industrial development zones mirrored the policies of economic and technology zones created in other countries.Another type of zone, created shortly after the opening coastal cities were instituted, has been labelled Economic and/or Technology Development Zones (ETDZs). The creation of ETDZs helped to partially compensate for the unbalanced development of China. If we consider the SEZs to be five points in the south, and OCCs are the fourteen cities connected through the north to the south as a line along China’s east coast, ETDZs are small areas within cities in different provinces that are distributed widely in China. ETDZs, in a sense,are not directly comparable to SEZs or OCCs as only a small area within a city enjoys a preferential policy in the case of an ETDZ, compared to the city-wide coverage of an SEZ or OCC.ETDZs differ fromSEZs as the administrators within an ETDZ have more freedom to issue preferential policies.The focus of ETDZs is also somewhat different from SEZs. ETDZs focus on enhancing the competitiveness of specific industries by emphasizing the development of productive capabilities and technology research, while prioritizing infrastructure development and the provision of energy and communications (Jia, 1994). SEZs, meanwhile, aimed to develop export-oriented businesses.3. Location choice and FDIEmpirically, a large volume of research has examined locational determinants of FDI. The vast majority of the previous statistical investigations focused on developed countries—mostly the US—as the host country environment (e.g. Bartik, 1985; Coughlin, Joseph and Arromdee, 1991; Friedman, Gerlowski and Silberman, 1992; Woodward, 1992; Hill and Munday, 1992). A recurrent theme is the emphasis of the following four sets of factors as the locational determinants of FDI: market-related factors, labor cost, transportation infrastructure, and government policy (see Dunning (1993) for an extensive review).The rationale for considering market-related factors is straightforward: a large market grants benefits such as scale economies and high revenue generation. The literature has provided supporting evidence that market size and market growth are important factors in the location decisions of FDI (Scaperlanda, 1967; Schmitz, 1970; Goldberg, 1972; Lunn, 1980; Hill and Munday, 1992; Yamawaki, Thiran and Barbarito, 1996).Cost is also a major concern for the site selection of FDI, which reflects mostly on the theory of international division of labour (Zhao and Zhu, 2000). In light of this, high wage rates and high unionisation rates were often found to act as deterrents to FDI flows (Friedman, Gerlowski and Silberman, 1992), but contrasting results exist (Zhao and Zhu, 2000).Transportation infrastructure relates to the nature of production, which requires the avail-ability of adequate roads, railways, ports, and other facilities for the purpose of opera tional efficiency. Studies have confirmed that FDI was attracted to regions that had better transportation infrastructure (Coughlin, Joseph and Arromdee, 1991; Loree and Guisinger, 1995).Finally, government policy has generally been viewed as a key variable that can alter the flows of FDI across regions. In this regard, early research has tended to emphasize the influence of trade tariffs on the location cho ice of FDI (Scaperlanda,1967; Schmitz, 1970; Goldberg, 1972). Lunn (1980), for example, found high trade barriers led to high levels of US FDI in European countries. Other studies focussed on other types of government policy such as corporate tax rates, lengths of tax holidays and other financial incentives (Bartik,1985; Luger and Shetty, 1985; Grubert and Mutti, 1991; Loree and Guisinger, 1995). With few exceptions (Scaperlanda, 1967; Contractor, 1991), extant research provides general support for the idea that policy promotions have a positive impact on FDI flows.Recent research has moved from a focus on cross-national location choice to a focus on a sub-national level examination of locational determinants (Coughlin, Joseph and Arromdee, 1991; Friedman, Gerlowski and Silberman, 1992; Hill and Munday, 1992; Woodward, 1992; Kotabe, 1993; Head, Ries and Swenson, 1995; Shaver and Flyer, 2000). Arguably, a sub-national level allows for a more fine-grained analysis of regional differences, and therefore may offer more accurate evidence for the sensitivity of FDI decisions to locational determinants. Similar to national level studies, studies of sub-national determinants of the location of FDI have confirmed the positive and significant effect of market-related factors while providing inconclusive findings about other factors. Hill and Munday (1992), for example, identified market access factors and financial incentives as important determinants of the distribution of FDI in the United Kingdom. A series of other studies, however, reported mixed results about the effects of policy determinants such as taxes and promotional activities on the location of FDI in the US (Coughlin, Joseph and Arromdee, 1991; Friedman, Gerlowski and Silberman, 1992; Woodward, 1992; Kotabe, 1993).The mixed findings of the policy effect may rest in several areas. First, a local government often implements a variety of investment promotions, such as tax concessions, subsidies, waiving environmental or employment safety standards, and relaxing some sort of performance requirements. Such data, however, are often not only lacking consistency and availability, but are also difficult to operationalize (Kotabe, 1993; Loree and Guisinger, 1995). This results in discrepancy in using policy measures and difficult ies in generating consistent empirical findings across studies. Second, investment attraction programs are usually an ongoing effort involving various promotional activities. As such, any static analysis, which is often based on different samples of cross-sectional data, might not capture the dynamic cause-effect relationship between promotional activities and resultant FDI in a hostregion (Kotabe, 1993). Third, measures of FDI vary from study to study. Loree and Guisinger (1995) used a flow measure, Coughli n, Joseph and Arromdee (1991) adopted counts of subsidiary establishments, and Kotabe (1993) studied investment cases. Different measures capture different variations of location choice and therefore may give rise to different results for policy variables.Aside from the characteristics of regions, research has also begun to explore how foreign investment histories in a region and firm heterogeneity influence location choice. The former is typically captured by the term agglomeration economies (Wheeler and Mody, 1992; Shaver and Flyer, 2000; Nachum, 2000). Agglomeration economies refer to positive externalities that result from locating in close proximity to geographical clusters of industry. Interestingly, Japanese FDI seems to be particularly sensitive to agglomeration (Kotabe, 1993; Smith and Florida, 1994; Head, Ries and Swenson, 1995).Research on firm heterogeneity has shown that firms place differential valuations on a region’s locational characteristics. Shaver and Flyer(2000) argued that although agglom eration exists, it tends to be most prevalent among firms with weaker advantages. In a similar research context, Chung and Alcacer (2001) observed that firms differentially valued locational advantages of a state, with firms that had relatively low R&D intensities more likely to chose states where more technical capabilities resided.译文日本在中国外商直接投资的区位因素研究(节选)资料来源:亚太管理期刊,19,63-86,2002 c 2002学术出版社,荷兰出版作者:ANDREW DELIOS CHANGHUI ZHOU2.中国外商直接投资的背景分析外商投资企业在中国有悠久的历史,在20世纪早期,英国,法国,德国和俄罗斯企业是在中国最活跃的外国投资商,总的来说,在1902年,中国的外商投资者中有90%来自于这些国家(Wu, 1958)。

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