Applications of linear regression models in exploring the relationship between media attention, economic policy uncertainty and corporate green innovation

Author:

Xu Yang1,Zhu Conghao2,Yang Runze3,Ran Qiying45,Yang Xiaodong1

Affiliation:

1. School of Economics and Management, Xinjiang University, Urumqi, China

2. International Business School, Tianjin Foreign Studies University, Tianjin, China

3. School of Finance, Shanghai University of Finance and Economics, Shanghai, China

4. Shanghai Business School, Shanghai, China

5. Center for Innovation Management, Xinjiang University, Urumqi, China

Abstract

<abstract> <p>The media plays a dual role of "supervision" and "collusion" in governance mechanisms. This study investigates the impact of media attention and economic policy uncertainty on green innovation by analyzing A-share industrial listed enterprises data between 2011 and 2020. The results show that media attention can effectively promote green innovation and that this impact is significantly heterogeneous. Media attention significantly affects green innovation in non-state-owned enterprises and manufacturing companies positively, but it is insignificant for state-owned enterprises and mining and energy supply industries. Moreover, the results indicate that external economic policy uncertainty can lead enterprises to take early measures to hedge risks, thereby positively regulating the promotion effect of media attention on green innovation during economic fluctuations. Finally, media attention can promote green innovation by increasing environmental regulation intensity, reducing corporate financing constraints, and enhancing corporate social responsibility. Therefore, paying full attention to the media as an institutional subject outside of laws and regulations, gradually forming a pressure-driven mechanism for corporate green innovation, and reducing information opacity, is a pivotal way to promote enterprises' green innovation.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

General Mathematics

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