Forecast of the time lag effect of carbon emissions based on a temporal input-output approach

Abstract

This paper investigates the time lag effect of carbon emissions using a novel temporal input-output approach (TIO). The sectoral average production time of various sectors is evaluated based on the turnover rate data of 3394 listed companies in China’s A-share market. Then, a polynomial function is developed to fit the indirect carbon emissions and time lag at each consumption stage in the industrial chains. Finally, an empirical study is carried out to forecast the time lag effect of carbon emissions with final demand fluctuations based on the latest 2017 input-output table for China. The results show that indirect carbon emissions caused by sectoral economic activities decline stage by stage in the industrial chains, and the decline rate and time lag intensity vary significantly among sectors. The logistics industry has the highest spread efficiency for indirect carbon emissions in the industrial chains, and the construction industry is the first industry affected by the indirect carbon emissions caused by the manufacturing industry. The power/thermal industry’s impact on China’s carbon emissions is the fastest, but its duration is the shortest, while the impact of the manufacturing and mining industries are more stable and durable. However, considering the fluctuations in final demand, the manufacturing industry has replaced the power/thermal industry as the most important industry affecting the time lag effect of China’s carbon emissions. This study provides important theoretical and practical value for indirect carbon emissions forecasting.