Search Results (5)

In 2013, China proposed the “Belt & Road Initiative” which aims to invest the “Belt & Road” countries so as to help them develop their infrastructure and economy. China consumes the largest part of fossil energy of the whole world, so it is China’s priority to consider its energy supplying security. Therefore, it becomes urgent for China to invest the “Belt & Road” countries’ energy facilities. There comes a question: how to evaluate the overseas energy investment risk? To answer this question, this paper proposes a deep learning method to assess such risk of the 50 “Belt & Road” countries. Specifically, this paper first proposes an indicator system in which 6 main factors are separated into 36 sub-factors. This paper makes use of hierarchical convolution neural networks (CNN) to encode the historical statistics. The hierarchical structure could help CNN handle the long historical statistics more effectively and efficiently. Afterward, this paper leverages the self-attention layer to calculate the weights of each sub-factor. It could be observed that the resource potential is the most important indicator, while “years of China’s diplomatic relations” is the most important sub-indicator. Finally, we use a conditional random field (CRF) layer and softmax layer to compute the assessment scores of each country. Based on the experimental results, this paper suggests Russia, United Arab Emirates (UAE), Malaysia, Saudi Arabia, Pakistan, Indonesia, and Kazakhstan to be China’s most reliable choices for energy investment. Full article

Building on the tradition, promises, and advances brought by the historical Silk Road, the Belt and Road Initiative (BRI), launched by the Chinese government in 2013, has a profound impact on international business and the established forms of international collaboration. Exploiting the advantages of liberalization of trade in goods, services, capital, and public procurement, BRI will benefit the Chinese economy. At the same time, it will prompt substantial changes in the field of international business, e.g., by means of fostering business to business (B2B) and peer to peer (P2P) collaboration. It will also influence patterns of Outward Foreign Direct Investment (OFDI). Geography plays a role in BRI; geopolitics is also in the cards. Given the profound implications BRI is likely to generate in the fields of businesses, economy, society, and politics, it is imperative to frame and streamline the discussion to identify the key mechanisms and causal relationships that it induces. This is precisely what this Special Issue sought to do. Full article

Intellectual property rights protection (IPRP) has caused great concern in China, especially since the introduction of the Belt and Road (B&R) initiative. The Chinese government has increased investments to the countries along the B&R, most of which are developing countries with high investment risks. Using the panel data of China’s outward foreign direct investment (OFDI) in 121 countries from 2003 to 2017, the sustainable relationships between the IPRP of host countries and China’s OFDI has been analyzed. The results of this paper show that, from the worldwide perspective, the stronger the IPRP of the host country, the greater attraction to China’s OFDI. While the IPRP of the countries along the B&R has a nonlinear U-shaped effect on China’s OFDI, which is related to the complex environments of the countries. When the IPRP of the B&R countries is within a certain range, China’s OFDI is biased toward a country with lower IPRP, and when the IPRP exceeds a certain range, China’s OFDI is biased toward a country with higher IPRP. Moreover, the market size, natural resources endowment and political environment of the host country are influential upon China’s OFDI as well. What deserves our attention is that China’s OFDI is more biased towards countries with poor political conditions, which can be related to the enterprise type and that most of the large multinational enterprises in China are state-controlled, resulting in investment decisions largely reflected by the national political goals rather than simple market targets. Full article

Existing studies on the Belt and Road Initiative (BRI) primarily explain its impact on foreign trade, foreign direct investment and economic development of the countries concerned, whereas its impact on the performance of outward foreign direct investment (OFDI) enterprises has rarely been examined. By considering the BRI as exogenous policy shock, this paper analyzes the mechanism and impact of the BRI on the research and development (R&D) investment of China’s OFDI enterprises investing in countries along the Belt and Road. With propensity score matching and a difference-in-difference approach, it tackles the endogeneity problem caused by self-selecting into the BRI enterprise group. The estimates indicate that BRI has not effectively promoted the R&D investment of OFDI enterprises, but plays an inhibitory role in the short term, and the marginal effect increases firstly and then decreases. Further mechanism analysis shows that the BRI leads to the addition of overseas revenue and the reduction of return on assets, which are the main reasons for the decrease of the R&D investment. In addition, the ownership heterogeneity analysis finds a higher negative effect on the state-owned enterprises, while a smaller effect on non-state-owned enterprises. Full article

This research is employed to examine the environmental issues embedded in Belt & Road Initiative (BRI), to be more specific: testify which of these hypotheses: Pollution Havens Hypothesis, Pollution Halo Hypothesis, Environmental Kuznets Curve is in accordance with the current development condition of BRI counties; whether there exists a bidirectional relationship among Ecological Footprint, Gross Domestic Production, Foreign Direct Investment (FDI) in Belt & Road Initiative countries. In this paper, Panel Vector Autoregression is utilized to analyze a dataset of 44-member countries in this initiative, ranges from 1990 to 2016, to empirically testify the environmental evaluation of this project. Results are analyzed on both long-run and short-run cases through Orthogonalized Impulse-Response Functions (IRF). This research displays a great heterogeneity among different target variables, FDI as a main variable of interest does not expose a bidirectional relationship with Ecological Footprint, only Ecological Footprint demonstrates robust influence on FDI. In addition, Pollution Havens Hypothesis is certified to be true for FDI and GDP among Belt & Road Initiative member countries. Full article