Strategic or substantive green innovation: How do non-green firms respond to green credit policy?

Yi HU; Shuchang JIN; Juan NI; Kai PENG; Lei ZHANG

doi:10.1016/j.econmod.2023.106451

Strategic or substantive green innovation: How do non-green firms respond to green credit policy?

Yi HU, Shuchang JIN, Juan NI, Kai PENG, Lei ZHANG

Research output: Journal Publications › Journal Article (refereed) › peer-review

28 Citations (Scopus)

Abstract

How does a green credit policy shape non-green firms' green innovation behavior? Previous literature shows that the green credit policy stimulates the quantity of green innovation but is less focused on its quality. Using the enforcement of the Green Credit Guidelines (GCG) in China as a natural experiment, we investigate the influence of the green credit policy on different types of green innovation (i.e., high and low quality). Consistent with the greenwashing hypothesis, we find that non-green firms strategically increase low-quality green innovations but not high-quality ones after the enforcement of the GCG. Additionally, we show that non-green firms are more likely to increase their patenting activities rather than innovation inputs to boost green patents after the enforcement of the GCG. Our study reveals the unintended consequences of the green credit policy and sheds light on non-green firms' strategic green innovation behavior.

Original language	English
Article number	106451
Journal	Economic Modelling
Volume	126
Early online date	21 Jul 2023
DOIs	https://doi.org/10.1016/j.econmod.2023.106451
Publication status	Published - Sept 2023
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2023

Funding

This study also proposes two competing hypotheses. First, the implementation of the GCG restricts the flow of funds to non-green firms, which increases the cost of debt and decreases the scale and maturity of debt for non-green firms (Xu and Li, 2020). However, innovation activities require substantial financial support, particularly long-term funding (Fang et al., 2017). Therefore, we expect the enforcement of the GCG to increase non-green firms' financial constraints, thus hindering their green innovations (the financial constraints hypothesis). Second, the government intends to raise environmental awareness and inspire non-green firms to make green transformations by implementing GCG. Thus, as intended, we expect that after the enforcement of the GCG, non-green firms will increase green innovations, especially high-quality ones (the inspiring hypothesis).

Keywords

Green credit policy
Green innovation
Greenwashing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.econmod.2023.106451

https://linkinghub.elsevier.com/retrieve/pii/S0264999323002638

Cite this

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title = "Strategic or substantive green innovation: How do non-green firms respond to green credit policy?",

abstract = "How does a green credit policy shape non-green firms' green innovation behavior? Previous literature shows that the green credit policy stimulates the quantity of green innovation but is less focused on its quality. Using the enforcement of the Green Credit Guidelines (GCG) in China as a natural experiment, we investigate the influence of the green credit policy on different types of green innovation (i.e., high and low quality). Consistent with the greenwashing hypothesis, we find that non-green firms strategically increase low-quality green innovations but not high-quality ones after the enforcement of the GCG. Additionally, we show that non-green firms are more likely to increase their patenting activities rather than innovation inputs to boost green patents after the enforcement of the GCG. Our study reveals the unintended consequences of the green credit policy and sheds light on non-green firms' strategic green innovation behavior.",

keywords = "Green credit policy, Green innovation, Greenwashing",

author = "Yi HU and Shuchang JIN and Juan NI and Kai PENG and Lei ZHANG",

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year = "2023",

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doi = "10.1016/j.econmod.2023.106451",

language = "English",

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journal = "Economic Modelling",