The impact of environmental regulations on the location choice of newly built polluting firms: based on the perspective of new economic geography

Based on the unique micro-data of newly built polluting firms for the period of 2009–2018, this paper adopts the conditional logit model to empirically evaluate the impact of environmental regulations on the location choice of polluting firms. Moreover, we extend the theoretical model by considering...

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Veröffentlicht in:Environmental science and pollution research international 2022-08, Vol.29 (39), p.59802-59815
Hauptverfasser: Peng, Na, Zhang, Xiangjian
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Sprache:eng
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Zusammenfassung:Based on the unique micro-data of newly built polluting firms for the period of 2009–2018, this paper adopts the conditional logit model to empirically evaluate the impact of environmental regulations on the location choice of polluting firms. Moreover, we extend the theoretical model by considering that the environment regulations not only influence the pollution cost but also the level of technological innovation and labor cost. The empirical results show that polluting firms tend to flow into areas with stringent environmental regulations, which supports the Porter hypothesis, but the effect of environmental regulations have a divergent impact on heavily polluting firms. Heterogeneous analysis indicates that environmental regulations have shown a positive impact on the location choice of private and foreign-funded firms but no significant impact on that of state-owned firms; the impact of environmental regulation is consistent with pollution haven hypothesis for firms in the central region but is in line with Porter hypothesis for firms in other regions. Meanwhile, the probability of air polluting firms entering areas with stricter environmental regulations is higher than that of water-polluting ones. Finally, this paper further empirically tests the conduction mechanism, that is, environmental regulations can affect the location choice of polluting firms by affecting the regional technological innovation capabilities and labor cost.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-022-19956-8