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Even before China's commitment to carbon neutrality and peak in September 2020, many programs had been implemented to save energy. One such program was the "Action Plan for Energy Conservation and Low-Carbon for Ten Thousand Enterprises" (hereafter Top-10,000 Enterprises Energy-Saving Program, or Top-10,000 Program, or Program) launched in 2011, which targets high energy users. The official assessment of this program, which began during China's 12th Five Year Plan period (2011–2015), claimed that it had achieved its goals. However, there has been no precise measurement of how much it has contributed to China's total energy conservation achievements and how enterprises responded to it. Employing the regression discontinuity design approach and Chinese taxation survey data, this study represents a pioneering attempt to assess the energy savings resulting from this program. Our study estimates that this program accounted for an average of 5.8% of nationwide energy savings. The primary methods employed by enterprises to save energy were enhancing energy efficiency and dynamically adjusting production scale. The results of our study suggest that regulatory environmental policies should not be hindered by short-term scale effects. Instead, further innovations are required to minimize the cost of energy savings. • The energy saving effect of China's Top-10,000 program is quantified • Utilization of a vast firm-level dataset employing regression discontinuity design • A pioneering assessment of the energy savings achieved through the Top-10,000 Program • Firms reduce production scale in the short-term responding to energy-saving policies • Firms expand production scale in the long-run reacting to energy-saving policies [ABSTRACT FROM AUTHOR]

This study measures the liquidity and volatility of the operation of the carbon trading and energy markets using liquidity ratio indicators and log return indicators. It adopts China's carbon trading and energy markets as the research objects, and evaluates the mean spillover effects and volatility spillover effects between the two using the vector autoregression (VAR) model and the BEKK-MGARCH model. The findings indicate that: (1) The liquidity of China's carbon trading market is better than that of the energy market. The average liquidity ratio of the Hubei and Shenzhen carbon trading markets is much lower than that of the coal market, 43016.131. It may be attributed to the fact that China's carbon trading market is currently small and easy to regulate. (2) The volatility of both the Chinese carbon trading market and energy market is small, and the absolute values of the mean log return rate are close to 0. It could be because China's carbon trading market is mainly distributed through free quota allocation, while the energy market has been mature and stable for many years. (3) There is a spillover effect between the carbon trading and energy markets in some parts of China, but the direction and degree of spillover effect vary, which may be due to differences in the economic development level, energy consumption structure, and environmental policies of each pilot carbon trading region. (4) The spillover effect between the two markets is stronger, perhaps due to China's current model of using coal as the main fuel. [Display omitted] • Use the VAR and BEKK-MGARCH models to evaluate the spillover effect. • The liquidity of China's carbon trading market is better than the energy market. • The volatility of both the Chinese carbon trading and energy markets is small. • Spillover effects exist between China's carbon trading and energy markets. [ABSTRACT FROM AUTHOR]