Zhigang Zuo
Government R&D subsidies and firm innovation performance: The moderating role of accounting information quality
Zuo, Zhigang; Lin, Zhibin
Abstract
The effects of government R&D subsidies can vary across recipient firms, depending on the various characteristics of a firm, potentially including the firm’s accounting information quality (AIQ). It has been well recognized that high AIQ helps to reduce information asymmetry between investors and firms and, consequently, improves investment efficiency. However, there is a lack of clear understanding about the specific role of corporate accounting information in the ex-post effectiveness of government R&D subsidies. This study thus examines the main effects of government R&D subsidies on both firms’ R&D inputs and innovation outputs, and the positive moderating role played by the quality of corporate accounting information. The data include 1,561 sample firms listed in the stock markets in China and 11,853 firm-year observations between 2007 and 2015. We find that the moderating effect of AIQ is economically sizable where an improved AIQ (discretionary accruals), by a standard deviation, increases the additionality effect by 16% for corporate R&D investment and 4% for the growth of firms’ R&D inputs. In addition, we find the subsidies have a stronger favorable effect on firms’ R&D outputs (the number of patents) for those firms with a higher AIQ.
Citation
Zuo, Z., & Lin, Z. (2022). Government R&D subsidies and firm innovation performance: The moderating role of accounting information quality. Journal of Innovation & Knowledge, 7(2), Article 100176. https://doi.org/10.1016/j.jik.2022.100176
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 2, 2022 |
Online Publication Date | Mar 11, 2022 |
Publication Date | 2022-06 |
Deposit Date | Mar 4, 2022 |
Publicly Available Date | Mar 18, 2022 |
Journal | Journal of Innovation & Knowledge |
Electronic ISSN | 2444-569X |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 7 |
Issue | 2 |
Article Number | 100176 |
DOI | https://doi.org/10.1016/j.jik.2022.100176 |
Public URL | https://durham-repository.worktribe.com/output/1212231 |
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Copyright Statement
© 2022 The Authors. Published by Elsevier España, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/)
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