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.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.