Manager sentiment and its effect on corporate innovation
Xun Xiong and
Long Zhao
Economic Modelling, 2025, vol. 143, issue C
Abstract:
Identifying the factors that predict managers’ commitment to innovation is crucial for understanding firm growth and competitiveness. However, the impact of the textual tone in financial reports on corporate innovation is relatively understudied. This study investigates whether manager sentiment, captured through the textual tone in the Management Discussion and Analysis (MD&A) section of annual financial statements, helps predict firm innovation. Using data from China’s listed firms during 2003–2017, we provide robust evidence that manager sentiment is positively associated with corporate innovation, particularly for firms with low growth, low liquidity, low profitability, high distress, and state-owned enterprises. Our analysis shows that this relationship operates through increased institutional ownership, reduced capital costs, and improved access to external financing. These findings highlight the value of MD&A textual tone as a tool for stakeholders to assess a firm’s future innovation potential and competitiveness.
Keywords: MD&A; Corporate innovation; Manager sentiment; Textual analysis (search for similar items in EconPapers)
JEL-codes: F24 G30 O32 O34 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0264999324003250
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:143:y:2025:i:c:s0264999324003250
DOI: 10.1016/j.econmod.2024.106968
Access Statistics for this article
Economic Modelling is currently edited by S. Hall and P. Pauly
More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().