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The Impact of National New Generation Artificial Intelligence Innovation and Development Pilot Zones on Corporate Green Innovation: Causal Inference Based on Double/Debiased Machine Learning

Author(s)

Boming Zhao*

Affiliation(s)

School of Economics, Southwest Minzu University, Chengdu, Sichuan, China *Corresponding Author

Abstract

In contrast to the growing presence of artificial intelligence, it enables not merely the industrialization of organizations, but also opens up plenty of opportunities within the corporate green innovation sphere. Employing a double/debiased machine learning approach, this study treats the establishment of the National New Generation Artificial Intelligence Innovation and Development Pilot Zones (NAIPZ) as a quasi-natural experiment. By utilizing a comprehensive sample of A-share firms listed in Shanghai and Shenzhen between 2013 and 2023, it rigorously examines how the rise of AI shapes corporate green innovation alongside its specific driving pathways. It conducts both the robustness tests and endogeneity tests. The results of the research are the following: Firstly, the formation of the NAIPZ can be used to improve the green innovation rate of a company and boost the quantity of green patents; Secondly, the mechanism tests indicate that such pilot zones increase the amount of corporate green innovation by relaxing the corporate financing constraints and increasing the corporate R&D investment; Third, heterogeneity tests indicate that these pilot zones are more effective in their impact on state-owned companies and highly-polluting companies. The research conclusions present the micro-level data on the artificial intelligence revolution, and also give the empirical data on the pilot zone optimization and corporate green transformation.

Keywords

Artificial Intelligence; Double/Debiased Machine Learning; Corporate Green Innovation

References

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