“…Enterprises may pay the costs of management due to the pressure of strict environmental regulation, which inhibits their R&D investment, and thus, their ability to innovate in green technologies [ 27 ]. The introduction of environmental regulation increases enterprises’ environmental expenditures and weakens their competitiveness, thereby inhibiting their technological innovation [ 28 , 29 ]. Some scholars have also argued that environmental regimes have a disincentive effect on resource-based industries’ green technology innovation [ 30 ].…”
The carbon emissions trading policy has profound impacts on the production and operation of enterprises. The aim of this study is to examine the effects of the carbon emissions trading policy on enterprises’ green technology innovations by using PSM−DID models. The results showed that: (1) the carbon emissions trading policy has a facilitating effect on green technology innovation of China’s enterprises in pilot cities; (2) there is significant spatial heterogeneity in this effect and it is extremely beneficial to enterprises’ green technology innovations in eastern China; and (3) the trading policy is proved to have significant positive effects on green technology innovations of non-state and non-high-tech enterprises, while it has no effects on that of state-owned and high-tech enterprises. The above findings were corroborated by the placebo test and other methods.
“…Enterprises may pay the costs of management due to the pressure of strict environmental regulation, which inhibits their R&D investment, and thus, their ability to innovate in green technologies [ 27 ]. The introduction of environmental regulation increases enterprises’ environmental expenditures and weakens their competitiveness, thereby inhibiting their technological innovation [ 28 , 29 ]. Some scholars have also argued that environmental regimes have a disincentive effect on resource-based industries’ green technology innovation [ 30 ].…”
The carbon emissions trading policy has profound impacts on the production and operation of enterprises. The aim of this study is to examine the effects of the carbon emissions trading policy on enterprises’ green technology innovations by using PSM−DID models. The results showed that: (1) the carbon emissions trading policy has a facilitating effect on green technology innovation of China’s enterprises in pilot cities; (2) there is significant spatial heterogeneity in this effect and it is extremely beneficial to enterprises’ green technology innovations in eastern China; and (3) the trading policy is proved to have significant positive effects on green technology innovations of non-state and non-high-tech enterprises, while it has no effects on that of state-owned and high-tech enterprises. The above findings were corroborated by the placebo test and other methods.
“…Moreover, different environmental regulations have various effects on the green development of different areas in China [14]. Other factors influencing the effectiveness of environmental regulations include regulatory stringency [15], measurement of environmental regulation [16], time-lag [17], and fiscal decentralization [10].…”
Environmental decentralization (ED), as an institutional factor, impacts the effectiveness of environmental regulation to achieve green productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper assessed GTFP, whose value is higher than 1. A two-step generalized method of moments (GMM) was employed to test the effects of environmental regulations (environmental protection investment (ENV) and pollutant discharge fees (PDF)) on GTFP with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV, while it is significantly promoted by PDF. Under the influences of environmental decentralization from the central to the local authorities (TED), ENV has insignificantly negative effects on GTFP; contrarily, PDF have positive effects on GTFP. As for moderating effects of environmental decentralization at different administrative levels within a province, the degree of provincial environmental decentralization (PTED) should be decreased, while the degrees of prefectural ED (UTED) and county-level ED (CTED) should be increased. Generally, rationally allocating environmental management power among various administrative levels in a province increases the effectiveness of PDF to achieve green productivity while decreases the negative effects of ENV.
“…Moreover, different environmental regulations have various effects on the green development of different areas in China [14]. Other factors influencing the effectiveness of environmental regulations include regulatory stringency [15], measurement of environmental regulation [16], time-lag [17], fiscal decentralization [10], and so on.…”
Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.