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The impacts of government R&D subsidies on green innovation: Evidence from Chinese energy-intensive firms

Bai, Yu, Song, Siyi, Jiao, Jianling, Yang, Ranran·2019·Journal of Cleaner Production

Abstract

Abstract Energy-intensive industries are a priority for achieving low-carbon economic growth in China, and a large number of government R&D subsidies have been injected into energy-intensive firms to support green innovation in recent years. Most of the existing literature has studied the impacts of R&D subsidies on the general innovation of high-tech firms or emerging enterprises. This paper explores the impacts of government R&D subsidies on the green innovation of energy-intensive firms. By employing propensity score matching with 527 samples of listed companies from 2010 to 2015, the empirical results show that government R&D subsidies increase the green innovation of energy-intensive firms, specifically their tendency and performance, by 107.3% and 54.1%, respectively. Heterogeneity analyses show that the impact is stronger in state-owned enterprises and in small and medium enterprises. Finally, some practical implications are put forward that may help to improve the efficiency of government R&D subsidies and promote the green innovation of energy-intensive firms.

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Metadata

Authors
Bai, Y., Song, S., Jiao, J., & Yang, R.
Venue
Journal of Cleaner Production
Publisher
Elsevier BV
Published
2019-10
Volume
233
Pages
819-829
ISSN
0959-6526 (ISSN-L)
OpenAlex
W2951901227
Cited by
634
References
0
FWCI
53.61
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The impacts of government R&D subsidies on green innovation: Evidence from Chinese energy-intensive firms. https://app.cochat.ai/papers/10.1016/j.jclepro.2019.06.107
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Bai, Y., Song, S., Jiao, J., & Yang, R. (2019). The impacts of government R&D subsidies on green innovation: Evidence from Chinese energy-intensive firms. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.06.107

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.