Abstract
Technology spillovers have the substantial effect on the industrial structure in emerging economies especially from OFDI (Outward Foreign Direct Investment). This research aims to examines the issue on how environmental regulation and biased policies can more effectively promote the OFDI reverse technology spillover effect, specifically the technology spillovers. By classifying the key industries mentioned in the ‘12th Five-Year Plan’ and ‘13th Five-Year Plan’, this research uses panel data from 2010 to 2019 obtained from provincial OFDI in China and utilizes difference in difference (DID) model and threshold regression approach to validate the analysis. The results show that the key industrial policy is favorable to the local OFDI reverse technology spillover. From the outlook of economic significance, the industrial policy increases the regional OFDI reverse technology spillover by 0.133%. Findings of our study further reveals that the environmental regulation and biased policy effectively promote the regional OFDI reverse technology spillover with certain stability. This study findings will be beneficial for policy makers to stimulate the reverse technology spillover impact of local OFDI more effectively from three aspects such as regional marketization level, innovation ability and financial structure.
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This research is funded by Humanities and Social Sciences Planning Project of Ministry of Education Grant No. 18XJAGJW001 and National Social Sciences Project Grant No. 20BJY090.
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All authors made significant contributions to the study conception and design. Data collection and methodology were performed by D.B. and L.C.L. S.F. did formal analysis and software. S.F. and D.B wrote the original draft. Review and editing were performed by D.B. and V.D.
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Shah Fahad, Dongbei Bai and Lingcai Liu contributed equally to this paper.
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Fahad, S., Bai, D., Liu, L. et al. Comprehending the environmental regulation, biased policies and OFDI reverse technology spillover effects: a contingent and dynamic perspective. Environ Sci Pollut Res 29, 33167–33179 (2022). https://doi.org/10.1007/s11356-021-17450-1
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DOI: https://doi.org/10.1007/s11356-021-17450-1