Green merger and acquisition decision driven by environmental regulation and its impact on green innovation: evidence from Chinese heavily polluting listed enterprises.

Ziyuan Sun, Xiao Sun, Wei Wang, Mengxin Sun, Wenjiao Wang
Author Information
  1. Ziyuan Sun: School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116 China.
  2. Xiao Sun: School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116 China. ORCID
  3. Wei Wang: School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116 China.
  4. Mengxin Sun: School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116 China.
  5. Wenjiao Wang: School of Economics and Management, China University of Mining and Technology, Xuzhou, 221116 China.

Abstract

How heavily polluting enterprises achieve sustainable development has become an urgent issue to be solved. Based on the data of Chinese heavily polluting listed enterprises during the period of 2010-2020, this paper adopts the probit method to examine how heterogeneous environmental regulations affect green merger and acquisition (GMA) decision, and propensity score matching and difference-in-differences method to explore innovation performance of GMA. The findings are as follows: (1) Command-and-control environmental regulation (CMCER) can promote GMA, while there exists a U-shaped relationship between market-based environmental regulation (MBER) and GMA; (2) from a dynamic perspective, it turns out that GMA can promote green innovation (GI) in the first and second post-acquisition year, but this effect disappears in the third year; (3) compared with CMCER, MBER has a more pronounced positive effect on the relationship between GMA and GI; (4) heterogeneous analysis indicates that the above GMA performance is more persistent when the acquirer is state-owned, with high media attention, with high internal control or engages in vertical GMA. The findings further enrich the literature on GMA driver and performance and provide references for optimizing ER policies and promoting corporate sustainable development.

Keywords

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Word Cloud

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