Crowding-out or Calling-out? The influence of mandatory industry-related firm-specific information disclosure on analyst reports

• Chinese regulators introduced industry-related firm-specific Information Disclosure (IFID) guidelines in 2013. • Mandatory IFID may have unintended consequences for analysts. • Machine learning and textual mining for analyst reports provide a deeper understanding of their text content. • IFID plays a calling-out effect on analyst reports, leading to an increase in industry-related information in analyst reports. To improve the information environment, the Chinese stock exchanges issued mandatory industry-related firm-specific information disclosure ( IFID ) guidelines for various industries in batches from 2013 to 2021. Utilizing the staggered implementation of IFID guidelines, we apply a staggered difference-in-difference method to assess analysts’ reactions to mandatory IFID . Our analysis, which employs text analysis and machine learning techniques, reveals that mandatory IFID stimulates more industry-related firm-specific information in analyst reports, supporting the calling-out effect of IFID on analyst reports. Furthermore, we document that IFID significantly reduces the text similarity of industry-related information across different analyst reports for the same firm, suggesting that analysts engage in more personalized, in-depth industry-related analyses rather than simply replicating the firm’s disclosed information post- IFID . Additionally, IFID prompts analysts to conduct more on-site visits to gather private information and produce more comprehensive industry-related insights. We also explore various factors that may influence the effectiveness of IFID at the industry , firm, and analyst levels. The heterogeneity test results show that the calling-out effect of IFID on analyst reports is strengthened by lower industry competition, better firm transparency, and higher analyst specialization. Overall, our study demonstrates that mandatory IFID in China improves the information environment by directly compelling listed firms to disclose more industry-related operating information and indirectly encouraging analysts to produce more differentiated and insightful analyses.

Authors

Publication Details

Journal
Journal of Accounting and Public Policy
Published
2024-11-24
DOI
https://doi.org/10.1016/j.jaccpubpol.2024.107266
Citations
6
Primary Topic
Auditing, Earnings Management, Governance
Type
article
Field-Weighted Citation Impact
5.68

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Crowding-out or Calling-out? The influence of mandatory industry-related firm-specific information disclosure on analyst reports

Long Zhang, Yuhuan Wang, Hui Liu, Yaxin Song
6 citations
Journal of Accounting and Public Policy
Auditing, Earnings Management, Governance
5.68
article

Crowding-out or Calling-out? The influence of mandatory industry-related firm-specific information disclosure on analyst reports

Long Zhang, Yuhuan Wang, Hui Liu, Yaxin Song
article en
6 citations

Abstract

• Chinese regulators introduced industry-related firm-specific Information Disclosure (IFID) guidelines in 2013. • Mandatory IFID may have unintended consequences for analysts. • Machine learning and textual mining for analyst reports provide a deeper understanding of their text content. • IFID plays a calling-out effect on analyst reports, leading to an increase in industry-related information in analyst reports. To improve the information environment, the Chinese stock exchanges issued mandatory industry-related firm-specific information disclosure ( IFID ) guidelines for various industries in batches from 2013 to 2021. Utilizing the staggered implementation of IFID guidelines, we apply a staggered difference-in-difference method to assess analysts’ reactions to mandatory IFID . Our analysis, which employs text analysis and machine learning techniques, reveals that mandatory IFID stimulates more industry-related firm-specific information in analyst reports, supporting the calling-out effect of IFID on analyst reports. Furthermore, we document that IFID significantly reduces the text similarity of industry-related information across different analyst reports for the same firm, suggesting that analysts engage in more personalized, in-depth industry-related analyses rather than simply replicating the firm’s disclosed information post- IFID . Additionally, IFID prompts analysts to conduct more on-site visits to gather private information and produce more comprehensive industry-related insights. We also explore various factors that may influence the effectiveness of IFID at the industry , firm, and analyst levels. The heterogeneity test results show that the calling-out effect of IFID on analyst reports is strengthened by lower industry competition, better firm transparency, and higher analyst specialization. Overall, our study demonstrates that mandatory IFID in China improves the information environment by directly compelling listed firms to disclose more industry-related operating information and indirectly encouraging analysts to produce more differentiated and insightful analyses.

Journal of Accounting and Public PolicyVol. 49
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Auditing, Earnings Management, Governance
5.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.