Measuring capacity utilization under the constraints of energy consumption and CO2 emissions using meta-frontier DEA: A case of China's non-ferrous metal industries

Currently, China's non-ferrous metal industry (NMI) still has the problem of overcapacity, measuring its capacity utilization (CU) and revealing its determinants is an important way to resolve the overcapacity problem of China's NMI. Using the panel data of China's 29 NMIs, this paper constructs a meta-frontier data envelopment analysis (DEA) to measure CU by taking into account the energy consumption and CO2 emissions constraints, and decompose the CU into four parts: technical efficiency, technology gap, scale efficiency, and equipment utili-zation. The main findings indicate that during the period of 2004-2017, the CU of China's NMI is generally low. Non-ferrous metal alloy manufacturing and rolling processing has the highest CU, while non-ferrous metals mining and dressing shows the lowest CU. From the dynamic perspective, mining and dressing experienced CU decrease, while other two sub-industries achieved CU increase. Technical inefficiency and technology gap enlargement are two main barriers of China's NMIs' CU. Besides, among 29 NMIs, there are only ten industries witnessed a CU improvement, while the remaining nineteen industries all experienced decrease of CU. CU and its determinants across China's 29 NMIs are quite different. Thus, the policies to improve CU should be made tailored to each industry's features.

Automated summary

China's non-ferrous metal industry is currently facing the challenge of overcapacity. This study uses panel data analysis to measure capacity utilization by considering energy consumption and CO2 emissions constraints. The findings show that overall, the capacity utilization in China's non-ferrous metal industry is low, with variations among different sub-industries. Technical inefficiency and technology gap are identified as the main barriers to improving capacity utilization. Tailored policies should be implemented based on the characteristics of each industry to enhance capacity utilization.