The rapid increase in outward foreign direct investment (OFDI) from emerging economies in the Global South, particularly from countries like China, has significantly impacted the established theoretical framework largely based on Global North experiences. Existing OFDI theories, predominantly developed from a perspective of developed nations, often fail to fully explain the investment behaviors of developing countries. The dominant position of Global North countries in international investment has been challenged by the rise of emerging economies. The global economic slowdown in 2020, coupled with the impact of COVID-19, further emphasized these shifts, as Global South countries demonstrated more aggressive outbound investment strategies compared to their Global North counterparts. Location choice, a crucial and largely irreversible decision for multinational enterprises (MNEs), remains a complex issue requiring comprehensive understanding of factors influencing such choices. The current literature lacks a holistic view of location determinants, especially concerning the specific contexts of developing economies. The study aims to fill this gap by comparing the OFDI location determinants of China (representing the Global South) and the United States (representing the Global North). It hypothesizes that there are significant differences in the underlying theoretical systems driving OFDI between these two groups, driven by factors beyond pure economic interests in the case of China.

The existing body of OFDI theory predominantly stems from Western scholars and focuses on corporate behavior in developed countries. Early theories like Hymer's imperfect markets approach and Vernon's product life cycle theory explain OFDI partially, but Dunning's eclectic (OLI) paradigm, while comprehensive, has limitations in explaining OFDI from emerging economies. The OLI framework's focus on ownership advantages, such as advanced technology and strong brands, doesn't adequately capture the motivations of MNEs from developing countries that may lack these advantages. Furthermore, traditional cost-benefit analyses based on developed-country contexts often fail to capture the unique circumstances and challenges faced by emerging economies in their outward investment strategies. The Investment Development Path (IDP) theory, while offering a dynamic approach, also shows limitations in empirical studies, especially regarding the Global South. Resource-based view and institutional theory offer some explanations for OFDI from emerging economies, highlighting the role of scarce resources and institutional support in driving investment decisions. However, previous studies often focus on the impact of specific factors without a broader view of the overall theoretical system. Existing empirical studies, although sometimes including emerging economies, primarily focus on market-seeking behaviors and resource acquisition, neglecting other crucial factors. The present study addresses these shortcomings by offering a comparative analysis of both economic and non-economic drivers of OFDI from the Global North and South.

This study employs a panel data regression method using data from 172 countries over the period 2005–2019, focusing on China and the US as case studies. The dependent variables are the stock of OFDI from China (COFDI) and the US (UOFDI) to each host country. Independent variables include indicators reflecting the investment climate of the target countries, encompassing economic factors (market size, GDP, imports, exports, openness), energy resources (oil and gas reserves, fuel and ore exports), logistics infrastructure (port, road, air, and rail infrastructure quality and capacity), and political risk (rule of law, control of corruption, government effectiveness, regulatory quality, voice and accountability, political stability). To account for the multidimensionality of these factors, principal component analysis (PCA) was used to reduce the 27 initial variables into six composite indicators representing the economy, energy, logistics infrastructure, and politics. Prior to model estimation, panel unit root tests (Breitung t-statistic, LLC, IPS, PP-Fisher, and ADF-Fisher) were conducted to ensure the stationarity of the data, and panel cointegration tests (Kao test) were used to identify long-run equilibrium relationships. A vector error correction model (VECM) was employed to analyze both short-term and long-term impacts of the investment climate on OFDI from China and the US. Impulse response analysis and variance decomposition were used to further analyze the dynamic effects of shocks in investment climate variables on OFDI.

The empirical analysis revealed significant differences in the OFDI theoretical systems between China and the United States. For China, the VECM results showed a strong positive long-term relationship between OFDI and energy resources and exports, indicating a resource-seeking motive. Conversely, logistics infrastructure quality and capacity exhibited a negative relationship with China's OFDI. This suggests that China invests in countries with potential for energy development even if the logistics infrastructure is not well-developed, possibly reflecting a strategy to develop infrastructure as part of the investment process. Political risk also showed a significant negative impact in the short term, indicating a preference for politically stable environments. In contrast, for the United States, the economy emerged as the most significant determinant of OFDI. Energy resources displayed a negative impact on US OFDI, possibly due to the sample composition. In the US model, logistics factors and political risk did not exhibit significant impacts. The Granger causality tests supported these findings. The impulse response analysis further highlighted the differing dynamic responses of China and US OFDI to shocks in the investment climate variables. China's OFDI showed a significant lag in reacting to shocks, with economic and energy variables exhibiting negative long-term impacts, while logistics factors showed positive impacts. The US OFDI response was quicker and primarily driven by economic variables. Variance decomposition analysis showed that the volatility of OFDI in both countries was primarily self-determined, yet with considerable variance explained by other investment variables, notably indicating a complex system. In China, the economy and energy factors significantly impact logistics, while in the US, economic factors drive both logistics and politics.

The findings underscore the limitations of existing OFDI theories developed primarily from Global North experiences in explaining the investment behavior of Global South countries. The study demonstrates that China's OFDI is guided by a long-term strategic vision that prioritizes energy security and infrastructure development, unlike the more market-driven approach of the US. This reflects broader geopolitical and developmental goals that extend beyond purely economic considerations. The results highlight the importance of considering the unique context and goals of developing countries when studying their OFDI patterns. The significant differences between the two theoretical systems suggest that a one-size-fits-all approach to understanding OFDI is insufficient. Policy implications are substantial, especially for Global South countries, who can learn from both the US's market-oriented and China's infrastructure-focused models. Policymakers in Global South countries should tailor their strategies to attract OFDI from different sources by focusing on their respective strengths and preferences.

This study contributes to the OFDI literature by highlighting significant differences in the theoretical systems driving OFDI from Global North and South countries, using China and the US as case studies. The results demonstrate that energy, logistics infrastructure, and political factors play a crucial role in China's OFDI, whereas economic factors are paramount for the US. This calls for a nuanced approach to understanding and attracting OFDI, recognizing the varying motivations and strategic goals of investors. Future research could explore the spillover effects of OFDI and incorporate spatial correlation analysis to improve the robustness of the findings. Further studies in different countries and regions are necessary to validate these findings and refine the theoretical understanding of OFDI.

This study's limitations include its focus on China and the United States as representative examples of Global South and North economies, respectively. The findings may not be directly generalizable to other countries due to variations in policies and investment environments. The study also excluded a detailed examination of spillover effects of OFDI and the influence of external shocks like COVID-19. Future research should address these aspects to provide a more comprehensive understanding of OFDI location determinants.