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This paper explores the impact of China’s growing prominence in global and regional foreign direct investment (FDI) fl ows on the Southeast Asian countries as investment locations. Providing internal social and economic cohesion is maintained, China is likely to exert a greater pull on regional FDI after WTO accession. To benefit from China’s success, the Southeast Asian countries will need to replace deteriorating individual locational advantages relative to China with a superior regional one. The ASEAN Free Trade Agreement or the Asian Investment Area or both are likely to be important policy solutions.

This paper aims to investigate the primary motivations for China’s outward foreign direct investment (ODI) decisions.

Using a panel data sample covering the period 2003–2012 and a comprehensive set of 176 host countries.

This study finds that market size, trade variables and natural resource variables are strongly related to the Chinese ODI stocks. This indicates that Chinese ODI decisions are driven by both market- and resource-seeking motives. The subperiod sample test results lend even stronger support to the market-seeking motive for ODI.

These results seem to emerge from the policy changes that were undertaken during the sample period. Consistent with subgroup tests, this study finds that the main purposes of China’s ODI in the top 100 countries are natural resource explorations and production line replacements.

The upsurge of Chinese and Indian outward foreign direct investment (FDI) raises an unanswered question about locational determinants of direct investment from the two countries. Using an unbalanced bilateral FDI database, we find that Chinese and Indian FDI are attracted to countries with large market size, low GDP growth, high volumes of imports from China or India, and low corporate tax rates. We also find important differences between China and India. While Chinese FDI is drawn to countries with open economic regimes, depreciated host currencies, better institutional environments, and English speaking status, none of these factors are important for Indian FDI. Chinese FDI is also deterred by geographic distance and OCED membership. However, neither of these has any impact on Indian FDI.

This paper aims to explore the spatio-temporal patterns of Chinese foreign direct investment (FDI) since the inception of the Belt and Road Initiative (BRI) in 2013 as an extended version of geographically weighted regression.

The panel data are used to examine spatial and temporal dynamics of the magnitude and the direction of China's outward FDI stock and its flow from 2011 to 2015 at a country level. Using the geographically and temporally weighted regression (GTWR), spatio-temporal distribution of FDI is explained through Logistic Performance Index, the size of gross domestic product (GDP), Shipping Linear Connectivity Index and Container Port Throughput.

A comparative analysis between participating and non-participating countries in the BRI shows that the size of GDP and Container Port Throughput of the participating countries have a positive effect on the increases of China's outward FDI Stock to Asia especially after 2013, while non-participating countries, such as North America, Western Europe and Western Africa, have no significant effect on it before and after the implementation of the BRI.

The findings, however, will not necessarily provide insight into the needs of China's outward FDI in certain countries to develop their economy. The findings provide the evidence to inform policy making to help identify the winners and losers of the investment, scale and direction of investment and the key drivers that shape the distributive investment patterns globally.

The study provides the empirical evidence to inform investment policy and strategic realignment by quantifying scale, direction and drivers that shape the spatio-temporal shifts of China's FDI.

The analysis also guides the Chinese government improve bilateral trade, build infrastructure and business partnerships with preferential countries participating in the BRI.

There is an urgent need to adopt a new perspective to unfold the spatial temporal complexity of FDI that incorporates space and time dependencies, and the drivers of the situated context to model their effects on FDI. The model is based on GTWR and an extended geographically weighted regression (GWR) allowing the simultaneous analysis of spatial and temporal decencies of exploratory variables.

In recent decades, with China's “Go Global” and “Belt and Road” strategies, Chinese multinational corporations (MNCs) have been provided with a new development direction. This chapter aims to identify the features of the entry of Chinese multinationals into Kazakhstan and analyze their characteristics in terms of investment attractiveness and location advantages. The basic method for evaluating the characteristics of the development of Chinese MNCs in Kazakhstan is a statistical analysis based on UNCTADstat. Based on the analysis, the authors conclude that although China has many MNCs, their rate of transnationality and competitiveness index are far behind those of European and American ones. The number of Chinese multinational companies investing in Kazakhstan (1,234 companies) ranks third in the number of foreign companies in the country. Chinese multinationals investing in Kazakhstan are mainly concentrated in Xinjiang because it borders Kazakhstan and has geographical and cultural advantages. China's direct investment in Kazakhstan covers a wide range of industries, including agriculture, animal husbandry, planting, construction, mining, transportation and communication, hotel and catering industry, trade and auto repair industry, etc. However, most registered enterprises are engaged in developing and utilizing energy fields in Kazakhstan.

The study aims to analyze the role of the Made in China 2025 (MIC2025) initiative in China's Outward Foreign Direct Investment (OFDI) and the factors affecting the success or failure of Chinese enterprises' OFDI from the perspectives of the heterogeneity of home country enterprises.

Based on data on China's OFDI obtained from the China Global Investment Tracker (CGIT), the study uses the difference-in-differences model to analyze 2,670 completed OFDI deals and 211 failed OFDI deals by Chinese enterprises, from 2009 to 2018.

The study found that the effect of MIC2025 on Chinese enterprises' OFDI varies according to the ownership structure of the home country's enterprises. For successful OFDI, MIC2025 significantly impacted central state-owned enterprises (CSOEs), while it did not significantly influence local SOEs and privately owned enterprises. For failed OFDI, the MIC2025 plan only increased the failure of CSOEs' OFDI for the technology-seeking motivation in high-income host countries. Further, the investment options of local SOEs differ from those of CSOEs. Considering their aim to drive the local economy and seek profits, they are more similar to those of privately owned enterprises.

This study used a new database (i.e. the CGIT) to analyze Chinese enterprises' OFDI. It discussed the role of MIC2025 for different enterprises from the perspectives of successful and failed OFDI. It thus provided a new basis for analyzing policy affecting the OFDI of Chinese enterprises.

Since China initiated its “go global” policy that promotes its overseas investment, China’s Outward Foreign Direct Investment (OFDI) has increased almost twenty times during the last 10 years, reaching $55.9 billion in 2008. The issue of internationalization of Chinese OFDI has attracted increasing attention of researchers from a business perspective. This article systematically reviews the previous studies on overseas investments by Chinese MNEs and discusses the characteristics of Chinese internationalization behavior at both firm level and country level. The internationalization of Chinese companies cannot be understood as a simple game of “catch up” with established MNEs, and more firm‐level empirical studies should be carried out on how these characteristics influence firms’ strategic decisions.

The purpose of this paper is to investigate the impacts of Chinese direct investment in Thailand on the Sino-Thai bilateral trade. The economic relationship between Thailand and China has been strengthened through both trade and Chinese direct investment in Thailand for past decades.

AR(p) model was used to examine the effects of Chinese direct investment on both Thailand exports and Thailand imports.

This paper shows that Chinese direct investment in Thailand has contributed to the decrease of intermediate goods of Thailand exports to China. On the other hand, Chinese direct investment has contributed to the increase of finished products of Thailand exports to China. In addition, Chinese direct investment in Thailand has contributed to increase of Thailand imports from China. This suggests that strengthening cooperation for economic growth in either of the two countries can generate mutual benefits through trade.

The studies focus only on the effects of foreign direct investment (FDI) on trade, while the effects of trade on FDI are neglected.

Policies should be devised to reduce reliance on exports of raw and semi-raw materials by turning on to final products with more value-added products and should improve the equality of infrastructure in the country to attract more FDI into the economy.

This paper provides evidence that Chinese direct investment in Thailand is an important determinant factor of the rapid growth of the bilateral trade. It also shows that the appreciation of Thai Baht against Chinese RMB is associated with a decrease in Thailand trade surplus in the bilateral trade.

For the developing countries involving in the Belt and Road Initiative (BRI) with China as the main source of foreign development investment (FDI) and development as the top priority, it appears to attract more and more attention on how to make the best use of China’s outward foreign development investment. However, the contradictory evidence in the previous studies of FDI spillover effect and the remarkable time-lag feature of spillovers motivate us to analyze the mechanism of FDI spillover effect. The paper aims to discuss this issue.

The mechanism of FDI spillovers and the unavoidable lag effect in this process are empirically analyzed. Based on the panel data from the Belt and Road developing countries (BRDCs) and China’s direct investments (CDIs) from 2003 to 2017, the authors establish a panel vector autoregressive model, employing impulse response function and variance decomposition analysis, together with Granger causality test.

Results suggest a dynamic interactive causality mechanism. First, CDI promotes the economic growth of BRDCs through technical efficiency, human capital and institutional transition with combined lags of five, nine and eight years. Second, improvements in the technical efficiency and institutional quality promote economic growth by facilitating the human capital with integrated delays of six and eight years. Third, China’s investment directly affects the economic growth of BRDCs, with a time lag of six years. The average time lag is about eight years.

Based on the analysis on the mechanism and time lag of FDI spillovers, the authors have shown that many previous articles using one-year lagged FDI to examine the spillover effect have systematic biases, which contributes to the research on the FDI spillover mechanism. It provides new views for host countries on how to make more effective use of FDI, especially for BRDCs using CDIs.

Known as the major capital providers in Belt and Road countries and the largest carbon emitter in the world, what role China's outward direct investment (ODI) plays in carbon neutralization has become a matter of concern. This study aims to measure the impact of China's ODI on the carbon emissions of Belt and Road countries.

Based on an econometric model and an inter-regional input–output model, a new model measuring the carbon emission effects of ODI is developed.

The empirical results show that (1) in general, China's ODI generates an emission-reduction effect in Belt and Road countries; (2) The relationship between the emission-reduction effect and income level of host countries shows an approximate inverted U-shaped trend; and (3) China's ODI generates stronger emission-reduction effects on capital-intensive industries.

This study quantitatively measures the scale of carbon emission-increase and reduction effect, which is relatively lacking in previous studies. This study explores the heterogeneity from the perspectives of regions, countries and industries. The authors have compiled an inter-regional input–output table for the Belt and Road countries for 2014 to provide a broad basis for the study of related issues.