中国对外直接投资对大湄公河次区域的影响

Nisit Panthamit, C. Chaiboonsri, Chira Bureecam
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摘要

摘要本研究旨在探讨中国对外投资(OFDI)对柬埔寨、老挝、缅甸、越南和泰国(CLMVT)的影响。本文背后的动机是研究作为中国“邻国模式”的这五个东道国在决定宏观经济因素方面的关键作用。利用2007-2019年中国对大湄公河次区域(GMS)五个邻国的面板数据。本文采用了经典统计和贝叶斯统计两种不同的面板规格的相关性模型,实证结果表明中国对外直接投资是CLMVT中对宏观经济因素产生正向影响的主要因素。当前,大湄公河次区域正以中国“走出去”战略的“邻接模式”挑战一般FDI理论,以对外直接投资作为发展中小国CLMVT成功的先驱者。许多研究表明,“一带一路”战略的实施将有助于中国增加对沿线国家的投资,这将进一步推动2013年以来“持续”战略的实施。本文利用2007-2019年中国对大湄公河次区域(GMS)五个邻国的面板数据,采用经典统计和贝叶斯统计的相关性两种不同的面板规格模型来衡量中国对外直接投资的潜力。本研究实现了贝叶斯定理的核心概念。该定理允许我们使用概率的先验信念与可以找到的证据相结合(更新CLMVT国家的每个经济状况),然后该方法将对后验概率分布进行新的预测。再一次从仿真算法中得到后验概率分布。它将根据我们对未来的信念,从可能发生的每一种情况的范围计算出来。贝叶斯相关检验仍然证实,中国对CLMVT国家人均GDP的FDI流入量对这五国经济宏观经济的拉动作用最为重要。
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Impact of China’s OFDI to the Greater Mekong Subregion (GMS)
Abstract The study aims to investigate the impact of China's outward foreign investment (OFDI) in Cambodia, Laos, Myanmar, Vietnam, and Thailand (CLMVT). The motivation behind this paper is to examine a pivotal role in determining the macroeconomic factors in these five hosting countries as the “neighboring model” of China. Using panel data for China's outward to her five neighboring countries in the Greater Mekong Subregion (GMS) for the period 2007–2019. This paper uses two different panel specifications models named correlation from classical statistics and Bayesian statistics where empirical results of this research qualify that China's OFDI is the main factor to have a positive influence on the macroeconomic factors in CLMVT. Highlights The GMS region is currently challenging the general FDI theory from the “neighboring model” of China’s going global” strategy using OFDI as a pioneer for success for the small developing country namely, CLMVT. Many studies showed that the implementation of the “Belt and Road” strategy will help China increase investment in countries along the route, which will further promote the implementation of the “on going” strategy since 2013. We use panel data for China's outward to her five neighboring countries in the Greater Mekong Subregion (GMS) for the period 2007–2019, measures the potential of China’s outward foreign direct investment by using two different panel specifications models named correlation from classical statistics and Bayesian statistics. This research implements the core concept of Bayes’ theorem. This theorem allows us to use a priori beliefs of probability to combine with evidence that it can be found (update every economic situation in CLMVT countries) then this method will have a new prediction of the posterior probability distribution. The posterior probability distribution will be received from the simulation algorithm once again. It would be calculated from the scope of every scenario that can be happening based on our belief in the future. The Bayesian correlation testing still confirms that the FDI inflow from China per GDP of CLMVT countries has the most play important role to drive the macroeconomic of these five countries’ economy.
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