Do certain firm characteristics matter?

After having illustrated the reducing effect of the listing rule changes on the VOV, we next test if this baseline effect is conditional on particular cross-sectional differences that existed between treated firms prior to the event. It is possible that dynamics within specific firms have an impact on the oversight function carried out by the independent directors. Therefore, we examine several firm characteristics that could potentially affect the independent directors’ effectiveness.

In particular, we analyze the moderating effect of further CEO and board dynamics, external governance, and the fundamental riskiness of the firm.

We start with CEO power for which we use two common measures: CEO-chair duality and CEO tenure. More powerful CEOs may be able to withstand pressure from the board to change their investment strategies. Next, we consider board size and the degree of co-option, which have been shown to affect board effectiveness (Yermack, 1996; Cheng, 2008; Coles et al., 2014).²² Additionally, we use the E index to check for a potential moderating effect of external governance (Cremers and Nair, 2005). Finally, the ratio of R&D expenditures to assets serves as the proxy for the level of fundamental firm risk (Kothari et al., 2002). High risk firms may be even harder for outsiders to evaluate and thus, independent directors might feel a greater urge to reduce the VOV.

To test for moderating effects of these firm characteristics empirically we re-estimate our initial

22Even though newly appointed directors are, by definition, co-opted as well, the high demand and the reduced pool of available candidates during the time of the introduction of the board independence requirement (Linck et al., 2009) most likely made it harder for CEOs to still find directors they could co-opt.

model, while splitting the treatment effect. More precisely, we take Equation (4.1) and replace the initial interaction with two triple interaction terms in which we add dummy variables that indicate whether a firm exhibits high or low values for the respective characteristic in the pre-treatment period. The modified model then looks as follows:

V OVi,t =α+β₁P ostt×T reatedi×Highi+β₂P ostt×T reatedi×Lowi

+γ Controlsi,t+λi+φt+i,t

(4.2)

where Highi (Lowi) is a dummy variable equal to one if the treated firm’s average value for the respective characteristic during the years 1998–2001 is above (below or equal to) the median average value among the treated firms and zero otherwise. The rest of the variables are the same as in Equation (4.1). Just as in our main analysis, the coefficients on both interaction terms represent the average change of the difference in VOV between the treated and the control firms from before to after the change in regulation. This effect, however, is now separated along the particular characteristics of interest. Table 4.6 presents the results. We only present the results for the full model, since they have a slightly higher adjustedR². The results for the reduced model are nearly identical. For brevity, the coefficient estimates for the control variables are omitted.

StructureandAmbiguity Table 4.6: Further firm characteristics that matter

(1) (2) (3) (4) (5) (6)

Scaled VOV Scaled VOV Scaled VOV Scaled VOV Scaled VOV Scaled VOV Post×Treated×CEO Duality High -1.6031**

(0.0270) Post×Treated×CEO Duality Low -1.5916**

(0.0159)

Post×Treated×CEO Tenure High -2.1224***

(0.0011) Post×Treated×CEO Tenure Low -0.9559 (0.1974)

Post×Treated×Board Size High -1.1890*

(0.0625)

Post×Treated×Board Size Low -2.0758***

(0.0058)

Post×Treated×Co-Option High -1.6902**

(0.0233)

Post×Treated×Co-Option Low -1.4231**

(0.0469)

Post×Treated×E Index High -1.8146**

(0.0253)

Post×Treated×E Index Low -1.5106**

(0.0134)

Post×Treated×R&D/Assets High -1.5641**

(0.0252)

Post×Treated×R&D/Assets Low -1.6201**

(0.0164)

CEO Controls Yes Yes Yes Yes Yes Yes

Firm Controls Yes Yes Yes Yes Yes Yes

Firm Fixed Effects Yes Yes Yes Yes Yes Yes

Year Fixed Effects Yes Yes Yes Yes Yes Yes

Sample Size 14,025 14,025 14,025 13,555 14,025 14,025

Adj. R-Squared 0.1461 0.1462 0.1462 0.1463 0.1461 0.1461

This table presents the coefficient estimates from regressions in which we separate the treatment effect along several pre-treatment cross-sectional differences that could potentially moderate the effect on theScaled VOV. Each regression is performed on the matched sample. Post is a dummy variable equal to one if the fiscal year is 2002 or later and zero otherwise. Treatedis a dummy variable equal to one if a firm does not comply with the board independence requirement in fiscal year 2001 and zero otherwise.

For each dimension,High (Low) is a dummy variable equal to one if a treated firm’s average value for the respective characteristic during the years 1998-2001 is above (equal or above) the median average value among the treated firms and zero otherwise. Definitions for the remaining variables can be found in Table C.1 in Appendix C. All models include firm and year fixed effects, as well as a constant term. Thep-values are based on standard errors clustered at the firm-level and are reported in parentheses, with *,

**, and *** indicating significance levels of 10%, 5%, and 1%, respectively.

The results show that, for nearly all the firm characteristics considered in this analysis, the baseline DID effect occurs in both groups of treated firms—high and low—and with very similar magnitudes. CEO tenure in Column (2) represents the only exception, as the effect is only significant for treated firms that have CEOs with above-median tenure. This could indicate that independent directors intervene more forcefully in these firms so that more powerful CEOs are controlled more strongly. For all other tests, however, the VOV reduction occurs in both groups of treated firms by similar amounts, as indicated by similar coefficient estimates and significance levels. Interestingly, the effect is somewhat stronger economically and statistically for firms with smaller boards, as shown in Column (6), supporting the view that smaller boards can monitor more effectively. With respect to the fundamental riskiness of the firm, we again see an almost equal VOV reduction in both groups. In an unreported analysis, we use the market-to-book ratio as an alternative risk proxy (Griffin and Lemmon, 2002) and find that the effect also occurs in both groups, yet appears to be statistically and economically somewhat stronger in the low-risk group.

Taken together, the overall results in this section strongly suggest that the effect does not depend on internal firm characteristics such as further CEO and board dynamics, external governance, or the fundamental riskiness of the firm.