The increasing digital transformation and the global need for sustainable energy solutions have sparked considerable interest in the examination of digital technologies' impact on the adoption of clean renewable energy. However, limited research focuses on energy consumption in rural households, especially in developing countries such as China.
This study leverages the quasi-natural experiment provided by the Broadband China Policy (BCP) and utilizes data from the China Labor-force Dynamics Survey (CLDS) spanning 2012 to 2016. Our investigation aims to understand the effect of the digital transition on the adoption of clean renewable energy within rural families. We employ staggered Difference-in-Difference (DID) and Doubly Robust Staggered DID estimators to assess this impact, allowing us to explore regional heterogeneity.
Our findings reveal that implementing the BCP significantly influences clean renewable energy adoption, although this effect varies across different regions. Specifically, in the middle region, the BCP results in a notable 5.8% increase in clean renewable energy adoption compared to non-pilot cities. However, in the east and west regions, the BCP is associated with a decrease of 12.6% and 13.5%, respectively, in clean renewable energy adoption. Dynamic effect analysis further indicates that the east region had already experienced high clean renewable energy adoption prior to the BCP's implementation, while the BCP positively influences clean renewable energy intentions in the west region.
Our analysis identifies three significant channels through which the BCP affects clean renewable energy adoption: population size, economic size, and income level. Larger populations and greater economic size enhance the BCP's impact on clean renewable energy adoption. These findings provide empirical evidence for developing countries that seek to harness digital development for technological advancement, industrial upgrading, and carbon emission reduction.