Low‐carbon economy transformation performance evaluation and spatial trends in China: a provincial aspect

Regional heterogeneity during low‐carbon economy development among provinces in China should be considered with more concerns by central government. Spatial coordination can bring more opportunities for underdeveloped provinces. Under this background, provincial low‐carbon economy transformation performance is evaluated during 2000–2016 and spatial characters are analyzed to supply detailed development information. Based on parametric input–output evaluation model and linear programming method, provincial low‐carbon economy transformation performance is evaluated. Spatial analysis methods such as Moran index, Moran scatter diagram, and Markov chain are implemented to analyze their spatial characters and dynamic trends. Main results are as follows: First, linear programing supplies reliable parameter results to evaluate the transformation performance. Mean value rises during 2000−2011 and there is a slight downward trend during 2013−2016. Economy transformation performance is still at lower medium level for most provinces nowadays and there is a long way to go further. Second, according to Markov chain results, more than 90% provinces exist as state self‐locking and less than 10% may exist as state jumping. Third, spatial correlation exists among provinces and ‘lower−lower’ type dominates with respect to low‐carbon economy transformation performance. They are mainly underdeveloped provinces in northwestern China. Absorbing greener production technology is the best choice for them. Yangtze River Delta provinces such as Shanghai, Jiangsu, and Zhejiang are of ‘higher–higher’ type. Regional cooperatives can exert lots of potentials and are beneficial to stimulate transformation performance. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.