• Energy Research

Abstract Of seven pilot emissions trading schemes (ETS) being run in China, the ETS in Hubei province is the only provincial pilot in the central and western regions of the country with a high GDP growth rate and heavy industrial structure. As such, it is quite representative of China as a whole and its ETS will therefore be reasonably characteristic of a future nationwide market. This paper describes the policy design of the Hubei ETS, including aspects of coverage, cap, allowance allocation, transactions, compliance and penalties. Then, after making a comparison with the other Chinese pilots and emissions trading schemes in the European Union (EU) and California, the paper offers a summary of several distinct features of the Hubei ETS. First, the small numbers of entities that are covered by the scheme produce a considerable proportion of the emissions. This makes Hubei the world׳s third largest carbon market. Second, the Hubei ETS applies several mechanisms to deal with the province’s rapid growth rate. Third, the scheme׳s policy design emphasizes liquidity. In addition to these unique features, the Hubei ETS also shares some common features with all the pilots in China.

Abstract The price elasticities of energy demand are intrinsically sectorally heterogeneous and time-varying, which is crucial for policy assessment, yet little studied. Therefore, in this study, we apply a semiparametric model that allows the coefficients to vary with continuous and categorical attributes to explore the sector-specific and year-specific price elasticities. We take China as an example, covering 32 industrial sectors from 1999 to 2015. Two main results have been found: (a) yearly average elasticities increased during the sample period and experienced faster growth since the 11th Five-Year-Plan period; and (b) the price elasticities showed significant sectoral heterogeneity in their magnitude, range, and trend. Nonmetal products (e.g., cement), metals, and chemicals have the largest elasticities. The mining and equipment manufacturing sectors are close to the sample average value. The light industry sector has the largest heterogeneity. The weighted mean of our results is consistent with those in the existing literature but provides more sector-specific information.