China's rapid economic growth has resulted in substantial carbon emissions, exceeding one-third of global emissions. The country faces immense pressure to reduce its carbon footprint, aiming to peak emissions by 2030. This challenge mirrors the struggles of many developing nations grappling with increasing carbon emissions, often exacerbated by the relocation of high-carbon industries. While environmental regulations are crucial, they can negatively impact economic growth. Therefore, exploring policies that simultaneously promote economic development and environmental protection is imperative. The digital economy (DE) is increasingly recognized as a potential tool for curbing environmental degradation. Policies supporting digital infrastructure construction (DIC) may provide a path towards sustainable development through digital transformation. However, the energy-intensive nature of ICT infrastructure and digital technologies has raised concerns about their impact on COE. This study focuses on the Broadband China Pilot (BBCP) policy, a Chinese initiative to promote DIC, to examine its effects on carbon emissions. The research question is whether the BBCP policy effectively reduces urban COE. A positive finding would demonstrate a "win-win" scenario, combining economic development with environmental improvement, providing valuable insights for other developing countries seeking similar outcomes.

Existing research highlights the significant contribution of population growth and energy consumption to increasing COE. Studies on the relationship between DE and COE have yielded mixed results, with some indicating an inverted U-shaped relationship – initially increasing COE before eventually decreasing it. Others have identified carbon rebound effects. The impact of DE on carbon emissions has been analyzed across various sectors, including industrial chains and exports, with multi-country studies showing varying effects on carbon intensity and per capita emissions. While substantial research exists on traditional infrastructure's impact on COE, the impact of DIC remains understudied. Some studies suggest that DIC itself might contribute to COE, questioning its role in long-term carbon neutrality. The existing literature often overlooks the potential spillover effects of DIC on other industries and its contribution to improving low-carbon ecological efficiency, which this study addresses. Previous research has established that DIC can enhance industrial ecology, regional innovation, and digital transformation in businesses, improve public health, but there is a scarcity of studies on its role in developing low-carbon cities.

This study employs a Difference-in-Differences (DID) model to evaluate the impact of the BBCP policy on urban COE in China from 2009 to 2019. Data were collected from various sources, including the "China City Statistical Yearbook," "China Urban Construction Statistical Yearbook," the China National Development and Reform Commission, and the China National Intellectual Property Office. COE was measured using annual consumption of coal, gas, methane, LPG, power, and heat energy, applying conversion factors from the 2006 IPCC Guidelines. The BBCP policy was represented by a dummy variable (BCPP), equaling 1 for pilot cities in and after the policy implementation year. Control variables included GDP, population, foreign direct investment, fiscal expenditure, and infrastructure level. The baseline DID model is specified as: COE_it = α + βBCPP_it + γControls_it + Year_t + City_i + ε_it. Robustness tests included a parallel trend test using an event study approach, a placebo test with 500 random policy-event shocks, propensity score matching DID to address selection bias, and local projection DID to handle potential confounding effects from multi-stage policy implementation. Heterogeneity analyses explored variations in the policy's effects based on green fund proportions, resource dependence, and fiscal expenditure. Mechanism analyses investigated the mediating roles of industrial structure upgrading and green technological progress using interaction terms in the regression models.

The baseline DID regression results showed that the BBCP policy significantly reduced carbon emissions by 9.4%, supporting the hypothesis that the policy has a negative effect on urban COE. Robustness tests consistently confirmed this negative impact. The parallel trend test demonstrated that the pre-treatment trends in COE were similar for both treatment and control groups, validating the DID assumption. The placebo test indicated that the observed COE reduction was unlikely due to random events. Propensity score matching DID and local projection DID analyses further strengthened the findings. Heterogeneity analysis revealed that the BBCP policy's impact on COE reduction was stronger in non-resource-based cities, cities with higher proportions of green funds, and cities with lower fiscal expenditure. Further analyses showed that the BBCP policy significantly improved low-carbon ecological efficiency and reduced COE intensity. Mechanism analysis confirmed that the policy's impact on COE was mediated through industrial structure upgrading (a shift towards the tertiary sector) and green technological progress. The interaction terms between BCPP and indicators for industrial structure and green technology innovation were both significantly negative.

The findings provide strong evidence that digital transformation policies, like the BBCP, can effectively mitigate urban carbon emissions. The results highlight the potential of DIC as a strategy for low-carbon city development, aligning with prior research on DE and low-carbon development. The study's findings on COE intensity reduction and improved low-carbon ecological efficiency are also consistent with existing literature. The significant negative interaction effects between the BBCP policy and both industrial structure and green technology innovation support the proposed mechanisms through which the policy achieves its carbon reduction effects. The study's findings on the heterogeneity of effects based on resource dependence, green finance, and fiscal expenditure provide valuable insights for policymakers seeking to optimize the implementation of DIC policies. The resource curse appears to hinder the effectiveness of the policy in resource-rich cities.

This study demonstrates a significant negative impact of the BBCP policy on urban carbon emissions in China. The findings highlight the potential of digital transformation policies as a tool for achieving both economic development and environmental sustainability. Future research could explore the impact of DIC on industrial and household COE separately, investigate the role of DIC in the integration of the DE and the real economy, and examine the long-term effects of the BBCP policy beyond the study period. Policy recommendations include providing tax incentives for DIC, leveraging green finance, and fostering green technological innovation through government support for the ICT sector.

The study's limitations include the lack of data on industrial and household COE, preventing a sector-specific analysis of the BBCP policy's impact. The study does not fully consider the impact of DIC on the integration of the DE and the real economy, which may affect the COE over the long term. These limitations suggest avenues for future research. The reliance on city-level data might mask variations within cities and potential confounding factors not captured by the control variables.