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<p>China’s structural and economic expansion, coupled with its growing financing activities across the globe, has significant developmental implications for developing economies particularly in digital sectors, due to its political, social, economic, and environmental impacts. Understanding these financial cofinancing mechanisms for the digital economic expansion of the recipient economies are critical for policy formulation that ensures inclusive, resilient, and technologically driven growth. Thus, this research aims to examine the effect of China’s cofinancing projects (CCF) focusing on those projects which are cofinanced by the host economy (CF) and those which are not cofinanced (NCF), on the digital economy (Digieco) across 24 economies. The analysis utilizes annual data spanning from 2005 t0 2019, with a specific focus on the moderating role of artificial intelligence (AI) on the CCF-Digieco nexus. Firstly, our empirical analysis reveals that CCF exerts a positive impact (0.035%) on the Digieco, suggesting that an increase in CCF corresponds with an enhancement in the Digieco. This effect is comparatively stronger and statistically significant in the case of CF, where the impact remains positive and significant both without controls (0.073%) and with controls (0.025%), whereas the impact of NCF on the digital economy is positive and insignificant when controls are included (0.021%) but significant when controls are excluded (0.039%). Secondly, the individual and moderating effects of AI are both negative and significant in relation to CCF and CF, whereas they are positive and insignificant with NCF. Thirdly, the heterogeneity analysis based on different regions and social development shows that the effect of CCF on Digieco is stronger in economies participating in the Belt and Road Initiative (BRI) compared to those outside the BRI framework. Conversely, within high-income and African economies, the influence of CCF is negative and insignificant, whereas it is positive and significant in upper middle and North &amp; South America. Furthermore, the heterogeneity analysis based on country specific characteristics indicates that in economies characterized by high sustainability, low vulnerability to climate change, and high CO<sub>2</sub>-emitting, the impact of CCF on the digital economy is positively significant. These findings are further supported through Method of Moment of Quantile Regression (MMQR) analysis, offering valuable insights for policymakers aimed at advancing the digital economy. These findings are critical for strengthening sustainability measures, accounting for the regional technological inequalities, and promoting carbon-neutrality, thereby ensuring maximum socially desirable outcomes from CCFs.</p>

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Chinese cofinancing, sustainability challenges and digital economy: the moderating role of artificial intelligence

  • 期刊论文

  • 发表日期：

    2026年6月19日

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  • Khadim Hussain,
  • Zhong Jian,
  • Ding‑Hong Peng

摘要

China’s structural and economic expansion, coupled with its growing financing activities across the globe, has significant developmental implications for developing economies particularly in digital sectors, due to its political, social, economic, and environmental impacts. Understanding these financial cofinancing mechanisms for the digital economic expansion of the recipient economies are critical for policy formulation that ensures inclusive, resilient, and technologically driven growth. Thus, this research aims to examine the effect of China’s cofinancing projects (CCF) focusing on those projects which are cofinanced by the host economy (CF) and those which are not cofinanced (NCF), on the digital economy (Digieco) across 24 economies. The analysis utilizes annual data spanning from 2005 t0 2019, with a specific focus on the moderating role of artificial intelligence (AI) on the CCF-Digieco nexus. Firstly, our empirical analysis reveals that CCF exerts a positive impact (0.035%) on the Digieco, suggesting that an increase in CCF corresponds with an enhancement in the Digieco. This effect is comparatively stronger and statistically significant in the case of CF, where the impact remains positive and significant both without controls (0.073%) and with controls (0.025%), whereas the impact of NCF on the digital economy is positive and insignificant when controls are included (0.021%) but significant when controls are excluded (0.039%). Secondly, the individual and moderating effects of AI are both negative and significant in relation to CCF and CF, whereas they are positive and insignificant with NCF. Thirdly, the heterogeneity analysis based on different regions and social development shows that the effect of CCF on Digieco is stronger in economies participating in the Belt and Road Initiative (BRI) compared to those outside the BRI framework. Conversely, within high-income and African economies, the influence of CCF is negative and insignificant, whereas it is positive and significant in upper middle and North & South America. Furthermore, the heterogeneity analysis based on country specific characteristics indicates that in economies characterized by high sustainability, low vulnerability to climate change, and high CO2-emitting, the impact of CCF on the digital economy is positively significant. These findings are further supported through Method of Moment of Quantile Regression (MMQR) analysis, offering valuable insights for policymakers aimed at advancing the digital economy. These findings are critical for strengthening sustainability measures, accounting for the regional technological inequalities, and promoting carbon-neutrality, thereby ensuring maximum socially desirable outcomes from CCFs.