The Effect of Mandatory CSR Disclosure on Information Asymmetry: Evidence from a Quasi-Natural Experiment in China

2013 ◽  
Author(s):  
Mingyi Hung ◽  
Jing Shi ◽  
Yongxiang Wang
Keyword(s):  
Information Asymmetry ◽  
Natural Experiment ◽  
Csr Disclosure

Corporate social responsibility disclosure and information asymmetry: does boardroom attributes matter?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amal Hamrouni ◽  
Mondher Bouattour ◽  
Nadia Ben Farhat Toumi ◽  
Rim Boussaada
Keyword(s):  
Information Asymmetry ◽  
Gender Diversity ◽  
Moderating Effect ◽  
Board Independence ◽  
Environmental Disclosure ◽  
Content Type ◽  
Csr Disclosure ◽  
Corporate Social ◽  
The Relationship ◽  
Social Disclosure

PurposeThe current study aims to investigate the relation between corporate social responsibility (CSR) and information asymmetry, as well as the moderating effect of board characteristics (gender diversity, size and independence) on this relationship.Design/methodology/approachThis paper uses a panel data regression analysis with the system generalized method of moments (SGMM) estimator of nonfinancial French firms included in the SBF 120 index. The environmental and social disclosure scores are collected from the Bloomberg database, while financial data are collected from the FactSet database.FindingsThe empirical results demonstrate that environmental disclosure has a positive impact on the level of information asymmetry, while social disclosure has no effect on the information environment. Gender diversity and board independence negatively impact the opacity index, while board size has a positive effect. The presence of women in board composition has a substitution effect on the relationship between environmental disclosure and information asymmetry. There is no moderating effect of board size on the association between CSR disclosure and information asymmetry. However, the proportion of independent female directors and board independence operates as substitutes to social disclosure on reducing information asymmetry.Research limitations/implicationsAlthough the models include the most common control variables used in the literature, they omit some variables. Second, the results should be interpreted with caution and should not be generalized to the entire stock market since the sample is based on large French companies.Practical implicationsThe results of this study may be of interest to managers, investors and French market authorities since France is characterized by highly developed laws and reforms in the area of CSR. In addition, the paper leads to a better understanding of how women on the board, in particular, independent female directors, affect the relationship between CSR disclosure and information asymmetry. This could be of interest to French authorities, which has encouraged the appointment of women through the adoption of the Copé–Zimmermann law.Originality/valueFirst, to the best of the authors' knowledge, this is the first study to explore the moderating effect of board characteristics on the relationship between CSR and information asymmetry. Second, unlike previous studies using individual proxies to measure information asymmetry, the authors favor the opacity index of Anderson et al. (2009). They calculate this index by including a fifth individual measure, namely, share price volatility. The opacity index better describes the information environment of companies than individual measures since it reflects the perceptions of investors and analysts together.

Do Algorithmic Traders Improve Liquidity When Information Asymmetry is High?

2020 ◽  
pp. 2050015
Author(s):  
Archana Jain ◽  
Chinmay Jain ◽  
Revansiddha Basavaraj Khanapure
Keyword(s):  
Financial Markets ◽  
Information Asymmetry ◽  
Natural Experiment ◽  
Equity Markets ◽  
Algorithmic Trading ◽  
Unanswered Question ◽  
Earnings Announcement ◽  
Liquidity Provision ◽  
High Information

Hendershott et al. (2011, Does Algorithmic Trading Improve Liquidity? Journal of Finance 66, 1–33) show that algorithmic traders improve liquidity in equity markets. An equally important and unanswered question is whether they improve liquidity when information asymmetry is high. We use days surrounding earnings announcement as a period of high information asymmetry. First, we follow Hendershott et al. (2011, Does Algorithmic Trading Improve Liquidity? Journal of Finance 66, 1–33) to use introduction of NYSE autoquote as a natural experiment. We find that increased algorithmic trading (AT) as a result of NYSE autoquote does not improve liquidity around earnings announcements. Next, we use trade-to-order volume % and cancel rate as a proxy for algorithmic trading and find that abnormal spreads surrounding the days of earnings announcement are significantly higher for stocks with higher AT. Our findings indicate that algorithmic traders reduces their role of liquidity provision in markets when information asymmetry is high. These findings shed further light on the role of liquidity provision by algorithmic traders in the financial markets.

Information asymmetry and credit rating: A quasi-natural experiment from China

2019 ◽  
Vol 106 ◽  
pp. 132-152 ◽  
Author(s):  
Xiaolu Hu ◽  
Haozhi Huang ◽  
Zheyao Pan ◽  
Jing Shi
Keyword(s):  
Information Asymmetry ◽  
Natural Experiment ◽  
Credit Rating
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