A combined input–output and sensitivity analysis of CO2 emissions in the high energy-consuming industries: A case study of China

This paper employed an input–output approach combined with a sensitivity analysis to explore the impact of technological changes on CO2 emissions in the high energy-consuming industries. In contrast to most papers in the literature, which focused on the changes between two input–output tables in two different periods, this study analyzed the sensitivity of variations in the quantity of emissions caused by small changes in technical coefficients. An indicator, namely TCE (technical coefficient elasticity), was established to identify the transactions between economic sectors which lead to a large impact on CO2 emissions in the high energy-consuming industries. Additionally, by analyzing factors affecting TCE, this paper divided TCE into structure-relevant TCE and technology-relevant TCE. Sectors have a higher structural TCE value because their products are much demanded by other sectors. Sectors have a higher technological TCE value because they have a large propensity to consume inputs which require many products of the high energy-consuming industries. Our results show that technical coefficients with a higher TCE value correspond to the direct requirements by the high energy-consuming industries themselves. However, the impacts of technological changes in the non-high energy-consuming industries on high energy-consuming industries cannot be overlooked, especially in Transportation industry, Construction industry and manufacturing industries. Several industries have a higher structural TCE value, thus, their influence on CO2 emissions in the high energy-consuming industries is related to a high level of demand of their respective products. However, several industries have a higher technological TCE value, thus, technology innovation will be more effective to decrease CO2 emissions. Therefore, different measures should be adopted for reducing CO2 emissions in the high energy-consuming industries according to different conditions.