Since the 21st century, more and more countries have realized the importance of environmental protection and made great efforts to promote the development of green industry. As the largest emerging economy, China is engaged in green development actively. For example, the carbon dioxide emission per unit of GDP in 2020 decreases by about 48.4% compared with 2005, which has exceeded the commitment target of reducing by 40–45% by 2020.Abundant empirical evidence shows that a wide range of environmental policies implemented in China contributed to the reduction of pollution emissions mentioned above(Liu et al., 2021; Song et al., 2021; Du and Li, 2020;Sun et al., 2019). However, existing literature provides few evidence on what factors at the firm level determine the pollution output in China(Gao and Han, 2021; Zhang et al., 2021; Zhang et al., 2019). This paper extends the research from a unique pespectiveof industrial robots.
Existing research has shed some light on the relationship between industrial robots and energy intensity. According to Mazzanti and Zoboli(2009), energy intensity depends on the interaction between labour productivity(gross output per employee) and technical energy efficiency(energy use per employee). First, there is mounting literature arguing that the application of industrial robots can increase labour productivity (Graetz and Michaels, 2018; Acemoglu and Restrepo, 2018). Second, how does the application of industrial robots affect energy consumption? On the one hand, industrial robots itself require energy to program and drive(Pastras et al., 2019). For example, Meike and Ribickis(2011) found that firms with industrial robots use more electric than those without industrial robots. On the other hand, the use of industrial robots can motivate technology improvement(Liu et al., 2020). Meanwhile, technological progress changes the input mix of materials and fuels and thus results in a greater efficiency in the use of energy and materials(Dinda, 2018). Using data of industrial robots from 38 countries and 17 manufacturing sectors, Wang et al. (2021) demonstrate that industrial robots can increase total factor productivity (TFP) and thus improve energy intensity. Similarly, using data of industrial robots installed in 16 Chinese industrial subsectors, Liu et al. (2021) find that there is a negative relationship between energy intensity and the number of industrial robots and technological progress is a partial mediator which accounts for 78.3% of the total effect.
According to ISO 8373:2012, an industrial robot refers to “automatically controlled, reprogrammable, multipurpose manipulator, programmable in three or more axes, which can be either fixed in place or mobile for use in industrial automation applications.”, from which we can draw that industrial robots belong to the category of artificial intelligence(AI) and allow firms to improve production efficiency by automation production(Graetz and Michaels, 2018). Industrial robots have palyed an important role in modern manufacturing industry, especialy for Chinawhich has been the largest user of industrial robots in the world since 2016(Cheng et al., 2019). Chinese government has begun to pay attention to the combination of artificial intelligence (AI) and green development. In 2021, The State Council promulgated ‘Carbon peak action plan by 2030’, in which the intellectualization of industrial production is regarded as an important driving force for the greening of industrial field. Despite the high attention at the policy level, academic study has not given a clear conclusion about AI application to promote pollution abatement. Thus, our study has important practical significance.
However, the impact of industrial robots on pollution intensity lacks micro and direct evidence. We attempt to fill the gap by investigating the relationship between SO2 emission intensity and industrial robots based on the China’s manufacturing firms. Using matching data from China’s Industrial Enterprise Database(CIED), China’s Environmental Statistics Database (CESD) and China’s Customs Database(CCD), our study finds that industrial robots can significantly lower SO2 emission intensity that a 1% increase in the number of industrial robots adopted by firms causes a 0.276% decrease of SO2 emission intensity in our baseline regression. Heterogeneity test in conditional distribution shows that industrial robots have greater effects on reducing SO2 emission intensity at low quantiles. Industry heterogeneity test shows that the reduction of SO2 emission intensity in labor-intensive and technology-intensive industries benefits more from industrial robots.
This paper makes several contributions to the literature. On the one hand, it contributes to the literature on firm environmental performance. Prior research has identified the importance of environmental regulation and policy in clean-up of manufacturing(Shapiro and Walker, 2018; Gibson, 2019; Najjar and Cherniwchan, 2020). Our findings complement these studies from a unique and microcosmic perspective by showing that the application of industrial robots can realize the clean-up of manufacturing. On the other hand, this study enhances our understanding of the application of industrial robots. Although several studies have investigated the relationship between labor market and industrial robots. (Cheng et al., 2019; Fan et al., 2021; Acemoglu and Restrepo, 2020),we provide novel evidence from the largest emerging economy that the application of industrial robots can promote environmental protection, which provides useful reference for the implementation of carbon neutralization and carbon peak scheme in China.