Abstract
By analyzing the Korean market characterized by chaebol firms, we provide evidence for the effectiveness of institutional blockholders’ monitoring of firms’ engagement in corporate social responsibility (CSR) activities. Lagged institutional blockholder ownership has a significantly positive effect on an investee firm’s current CSR index, suggesting that institutional blockholders actively engage with firms’ CSR activities to improve these firms’ long-term prosperity and performance, primarily because these blockholders cannot sell their large holdings without eroding the values of their investments. Domestic institutional blockholders have a greater effect on CSR than foreign institutional blockholders have, although the latter blockholders are becoming increasingly influential.
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Notes
We recognize that firms may simultaneously adopt socially responsible policies and attract more institutional blockholders. To assess this potential endogeneity issue, we conduct an additional test, the findings of which are discussed in the empirical analysis section.
Ensuring that institutional investors have sufficient disciplinary power is a necessary condition for examining their influence on CSR activities. Thus, we only consider blockholders with aggregate ownership of a minimum of 5% of a firm’s shares. Then, we examine how the K_CSR score reacts to incremental changes in blockholders’ shareholdings.
One-year lead-lag analysis is commonly used to mitigate simultaneity (e.g., Jo and Harjoto 2011, 2012). However, because the influence of institutional blockholders may take time to be reflected in CSR engagement, we re-estimate the main models based on 2- and 3-year lead-lag relationships. However, we still find significant, positive relationships between 2- and 3-year lagged institutional blockholdings and K_CSR. Thus, our main results are not necessarily affected by the simultaneity issue and complement the robustness test results shown in Table 9. However, we find that this relationship is weaker for the three-year lead-lag relationship. This difference could arise because more factors and information may affect CSR activities over three years than over two years. Moreover, corporate spending on CSR might not be determined by management three years ahead. Planning one or two years ahead seems more reasonable. The robustness test results are available upon request.
Note that D_IBO and F_IBO can replace IBO in Eq. (1).
To address the potential endogeneity problem stemming from chaebol-affiliated firms’ voluntary engagement in CSR activities to attract institutional blockholders, we conduct an endogeneity test. Specifically, we re-estimate Table 4 for chaebol-affiliated firms in the lowest CSR quartile. This approach helps to mitigate the potential endogeneity issue because we focus on chaebol-affiliated firms with a low level of CSR activities. Specifically, we identify these chaebol-affiliated firms using annual announcements by the Korea Fair Trade Commission. The results show that institutional blockholdings positively affect CSR activities even after we restrict the sample to chaebol-affiliated firms with low CSR engagement, suggesting that our results are robust to any endogeneity issue. The test results are available upon request.
To consider the possible loss of information due to the empirical setup using subsamples, we re-estimate the relevant tables using the interaction terms as complements. In particular, we utilize dummy variables for firm illiquidity and R&D expenses that take a value of one if a firm is in the top half of firms in terms of the Amihud (2002) illiquidity ratio and R&D expenses, respectively, in each year. Then, we construct interaction terms for these dummies and institutional blockholdings. The results show that the coefficients on both interaction terms are significant and positive, suggesting that institutional blockholders’ influence over CSR activities is more evident for firms with low liquidities and high R&D expenses. Thus, the findings of this analysis corroborate and complement those based on the subsample analyses reported in Table 7. The results are available upon request.
Institutional investors have heterogeneous resources and motivations for committing themselves to monitoring (Chen et al. 2007). Thus, a long-term (short-term) investment strategy is believed to indicate a high (low) likelihood of an investor being a monitoring institution. Based on Yan and Zhang (2009), we use institutional blockholdings with different investment horizons to estimate the relationships between short- and long-term institutional blockholdings and CSR activities. The results are consistent with the findings of related studies (e.g., Chung et al. 2015; Liu et al. 2018; Chung et al. forthcoming). Long-term institutional blockholders seem to be more interested in CSR activities because only long-term institutional blockholders exhibit a positive and significant relationship with CSR activities. This finding also implies that realizing the benefits of CSR activities takes time and, thus, that this time interval is more aligned with the investment horizons of long-term institutional blockholders, who seek larger gains over a longer period.
We choose the control variables by following Bushee and Noe (2000) and Bushee (2001). We include market-adjusted buy-and-hold returns (MRET), trading volumes (TVOL), betas from the market model (BETA), firm size (SIZE), financial leverage (LEV), income levels (EP), book-to-market ratios (BM), dividend payouts (DIVR), a market indicator dummy (MARKET_D), common shares outstanding (SHOUT), firm age (AGE), and R&D expenditures (RNDS) in the regression models, and we estimate them based on Petersen (2009). The control variables are described in detail in the Appendix.
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Appendix: List of control variables
Appendix: List of control variables
Variable | Definition |
---|---|
SIZE | The natural log of firm i’s sales in year t |
LEV | The ratio of firm i’s total debt to the market value of equity (current stock price multiplied by common shares outstanding) in year t |
ROA | The ratio of firm i’s earnings before interest and tax (EBIT) to total assets in year t |
Q | The ratio of firm i’s total market value (sum of market capitalization and long- and short-term liabilities) to total assets in year t |
RNDS | The ratio of firm i’s research and development expenses to sales in year t |
BM | The ratio of firm i’s total equity to the market value of equity in year t |
CASHF | The ratio of firm i’s operating cash flow to total assets in year t |
DIVR | The ratio of firm i’s cash dividend on common stocks outstanding to the market value of equity in year t |
TVOL | The ratio of firm i’s total trading volume to common stocks outstanding in year t |
BETA | The statistical estimation of the beta coefficient in the regression model given by \(R_{i,t} = \alpha + BETA \cdot R_{M,t} + \varepsilon_{i,t}.\)Ri,t is the daily stock return of firm i in year t, α is the active return relative to the benchmark KOSPI, RM,t is the daily return of the benchmark in year t, and ɛi,t is the unexplained return |
MRET | The difference between the return of an asset and that of the benchmark, defined as Ri,t − Rm,t, where Ri,t denotes the stock return for firm i in year t and Rm,t is the market (KOSPI) return for firm i in year t |
EP | The ratio of firm i’s EBIT to the market value of equity in year t |
SHOUT | The natural log of firm i’s common stocks outstanding in year t |
AGE | The number of years since the firm’s establishment, that is, the difference between year t and the firm establishment year |
HHI | The industry j specific Hirschman–Herfindahl index is calculated using the equation \(\sum\nolimits_{i = 1}^{N} {S_{ij}^{2} }.\) Firm i’s market share (%) in industry j, or sij, is the ratio of firm i’s sales to the sum of the sales of all N firms in industry j (using sales data for all possible KOSPI- & KOSDAQ-listed firms’). Each subscript j follows the industry classification provided by the KRX |
MARKET_D | A binary indicator which is used to identify the firm’s listing on the KOSPI 200. The value of one indicates the firm’s listing and zero otherwise |
SD | The standard deviation of daily stock returns for firm i in year t |
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Chung, C.Y., Cho, S.J., Ryu, D. et al. Institutional blockholders and corporate social responsibility. Asian Bus Manage 18, 143–186 (2019). https://doi.org/10.1057/s41291-018-00056-w
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DOI: https://doi.org/10.1057/s41291-018-00056-w
Keywords
- Asian market
- Corporate governance
- Corporate social responsibility
- Institutional blockholder
- Institutional monitoring