Heterogeneity of Funds and Information Disclosure: Evidence

ABSTRACT

Institutional investors, especially public funds, play an important role in governing listed firms as they grow in Chinese stock markets. We classify each fund as “dedicated,” “transient,” or “mixed,” according to the concentration, turnover, and profit sensitivity of their stock holdings. We find that listed firms with more shares held by dedicated funds have a higher disclosure quality, while firms with more shares held by transient funds have a lower disclosure quality. These findings are consistent in different model settings. In addition, dedicated funds improve the disclosure quality of non-state-owned enterprises more than state-owned enterprises. Dedicated funds can benefit from the lower debt-financing cost and higher stock liquidity of firms with better disclosure quality.

KEY WORDS:

• emerging market
• information disclosure
• public funds

JEL Code:

• G23
• G34

Acknowledgments

The authors would like to express their gratitude to the two anonymous referees for their useful comments and suggestions which greatly helped them in revising the article. All errors remain their own. The first author, ZHU Yanjian, and the corresponding author, YANG Xiaolin, would like to acknowledge, respectively, the financial support from the National Natural Science Foundation of China (No. 71403238) and the Key Program of National Social Science Foundation of China (No. 16ATJ003) for this research.

Notes

^1. In China, funds are divided between those that are available to the public and those that are only available privately. Shares of public funds are sold to investors publicly upon approval of the CSRC. For public funds, there are no limit on the number of buyers. Shares in private funds are sold privately and only to high-net-worth individuals. Private funds do not need to obtain approval from the CSRC but do need to file with it, and are limit in the number of investors. Harvest Fund Management Co. Ltd is one of the best-known public fund management companies. It is managing more than 100 public funds.

^2. We thank the anonymous reviewer for making this suggestion.

^3. We conducted a small anonymous survey of fund managers in China and received 38 responses. Among the 14 funds who classified themselves as dedicated institutions, over 90% thought that they have information asymmetry with the controlling shareholder, about 78% can obtain private information from listed firms and the other institutions, about 85% have incentives to improve the information disclosure quality, about 15% have no incentives because improvement of disclosure quality is costly to institutions and brings little benefit, and about half thought that they are able to push listed firms to improve their disclosure quality. Only one fund manager classified his or her fund as a transient institution; 15 funds were classified as mixed institutions; and the rest could not be classified.

^4. Special treatment (ST) firms are those with negative net income in two recent and consecutive years. Firms marked *ST had negative net income in three recent and consecutive years.

^5. The table is available upon request.

^6. We use a different classification method for a robustness check. We aggregate the holdings of all dedicated funds for each firm. The aggregated holdings are zero if the firm was not held by any dedicated funds. We then divide all firms, including those with and without dedicated funds, into two equal groups according to their aggregated holdings. HD1 equals one for the half of firms with the largest dedicated fund holdings. HD1 equals zero for the remainder of firms. HD2 and HD3 are defined in a similar way. We find that all our empirical results remain the same. All the tables are available upon request.

^7. We also investigated the relationship between the change in disclosure quality and the analyst prediction accuracy and agency cost. We did not find a significant association. We do not report those results.

^8. The variables LEV and GROWTH have extreme outliers. We do robustness checks in two ways to avoid distortion in the two variables. First, we winsorize them at the 5% and 95% percentiles and repeat Tables 3 and 5; second, we delete the two variables from the regressions in Tables 3 and 5. Our main results remain the same. We add the results in Tables 3 and 5. We thank the anonymous reviewer for making this suggestion.

^9. The table regarding the correlation coefficients is available upon request.

¹⁰ As suggested by Ajinkya, Bhojraj, and Sengupta (2005) and Bushee and Noe (2000), we use the changes in the holdings of dedicated, transient, and mixed funds as independent variables for a robustness check. The main results remain significant at the 10% level.

^11. For brevity, we do not include the first-stage results here. The table is available upon request.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [71403238]; Key Program of National Social Science Foundation of China [16ATJ003].