Decomposing capacity utilization under carbon dioxide emissions reduction constraints in data envelopment analysis: An application to Chinese regions
Xiaoling Zhang and
Energy Policy, 2020, vol. 139, issue C
Economic cycles in the form of capacity utilization might greatly affect productivity. In order to explore how does carbon dioxide emissions reduction influence capacity utilization, this paper proposes a novel method to decompose the total capacity utilization (TCU) rate under carbon dioxide emissions reduction constraints using data envelopment analysis. The TCU rate is decomposed into an equipment utilization rate (EU), low-carbon technology efficiency (CTE), and policy oriented capacity utilization rate (PCU), and four policy orientations are then simulated to investigate the performance of TCU and its components. Three main conclusions are drawn: (1) the TCU rate was basically maintained between 60% and 70%, indicating a serious overcapacity in China. (2) most regions with a higher TCU rate are the well-developed southeast coastal regions, those with lower TCU rates being mainly the central and western regions; (3) the mandatory emission reduction mode is one of the main causes of overcapacity, where the southeastern coastal areas in particular suffer the most severe capacity loss. In comparison, a win-win development mode is the most cost-effective for China, with a relatively small capacity loss. These conclusions could assist policy designers in improving capacity utilization through effective low-carbon policies.
Keywords: Capacity utilization; Low-carbon policy; Data envelopment analysis(DEA); Directional distance function(DDF) (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:enepol:v:139:y:2020:i:c:s0301421520300574
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