There is more empirical evidence to support the belief that vega increases the risk-taking behavior of CEOs. In contrast to agency theory, executive power theory posits that CEO pay deviated from firm performance due to the socially derived power of CEOs (Bebchuk et al., 2002). For example, Chourou et al. 2008) find that the referent power of CEOs has a negative effect on the total weight of stock options.
Therefore, we attempt to reconcile different theoretical perspectives when examining CEO pay incentives—firms' political conditions and CEOs' risk-increasing incentive provisions. There is a gap in the literature examining the impact of CEOs' incentive vega on managerial risk-taking behavior in Australia. As we hypothesized, the results show that vega is the risk-enhancing incentive that influences CEOs' adoption of an aggressive debt financing policy.
To overcome the risk-reducing effect of the delta, more convex (high wage-stock return volatility sensitivity) options were introduced into CEOs' contracts (Guay, 1999). There are few studies that indirectly examine CEO incentive firms' financial policy relationships in Australia. The proportion of assets that are growth opportunities affects the structure of CEOs' stock-based pay and the directors' pay firms' political conditions (Guay, 1999).
Firm size is related not only to stock option plans, but also to CEO compensation levels (Gaver and Gaver, 1993 and Smith and Watts, 1992).
Data and econometric modelling
These studies show that executives and directors make executive compensation decisions independent of shareholder influence, and the board is compromised by CEO influence over director appointment. We selected the initial sample companies from the ASX and the Standard and Poor's (S&P) Dow Jones 200 index, which consists of the 200 largest public companies that capture 80% of the total market capitalization6. However, a key assumption of OLS is that the corporate governance and control variables should be strictly exogenous to the regression errors (Broussard et al., 2004). Wintoki et al. 2012) summarize two sources of endogeneity that can invalidate the strict exogeneity assumption of the OLS estimator: unobservable heterogeneity and simultaneity.
However, corporate finance researchers often ignore another source of endogeneity—dynamic endogeneity, a situation where current observations of an explanatory variable such as CEO incentives are not independent of historical values of the dependent variable (firm policy) ( Wintoki et al., 2012). We attempt to address the dynamic endogeneity problem because sources of endogeneity may arise in the relationship of CEOs' policies and incentives. Although firm politics can be influenced by CEO compensation (Coles et al., 2006), it is also true that CEO incentives are influenced by firm politics.
Blundell and Bond (1998) point out that the lagged levels of the dependent and explanatory variables are inappropriate instruments for first-variety variables, if the lagged variables. dependent and explanatory variables are constant over time. Another advantage of the GMM estimator is that the time-invariant regressors, which are eliminated by We use a dynamic panel data model with the natural logarithm of the dependent variable - firms' book leverage - to test the effect of vega on the firms' risky financing policy.
We use equation (2) to estimate the determinants of vega, the risk-increasing incentives of the CEOs' option portfolio. We focus on the CEOs' option portfolio vega in our study because Hall and Liebman (1998) argue that an increase in option rewards is responsible for the increase in the sensitivity of CEOs' wealth to the companies' stock returns. Delta per option is the change in the dollar value of the CEO's option for a 1% change in the stock price at the end of period t.
Vega per option is the change in the dollar value of the CEO's option for a 1% change in stock return volatility or stock risk at the end of period t. Finally, we control for the volatility of stock returns in equation (2), since the volatility of the underlying stock is the most important variable in the B-S model that affects the vega of CEOs' option portfolio. In addition to the control variables for CEO risk aversion used in equations (1) and (2), we also control for leverage in equation (2) as a measure of firms' incentives to hedge.
S = price of the underlying stock on June 30 of each year; X = exercise price of the option; = annual standard deviation of the logarithmic daily return; r = ln (1+ risk-free interest rate 21 . rate); following Guay (1999), we use the yield on Reserve Bank of Australia (RBA) zero-coupon bonds (obtained from the RBA) with the same option maturity to estimate risk-free rates; T = time until option maturity.
Results
A major explanation for the significant increase in delta from 2005 shown in Figure 1 is the enactment of the Audit Reform and Corporate Disclosure Act 2004, which is based on the Company Law Economic Reform Program 9 (CLERP 9). One of the PC's recommendations is the 'two-strike' rule, which states that if more than 25% of shareholders vote against a company's In July 2011, the Australian Government made the 'two-strike' rule a new amendment to the Companies Act.
The most recent increase in the companies' book leverage after 2011 is the result of two consecutive cuts in the cash rate in 201112. After eliminating possible endogeneity problems, the result in column 4 (with the system GMM estimator), table 3, see that the coefficient of vega (12.763) is substantial and significant at the 10% level. However, the option moneyness coefficient becomes insignificant when the more robust GMM methods are used, indicating that the observed effect of CEO option moneyness on firm book leverage is driven by simultaneity and dynamic endogeneity biases.
This positive annual effect is likely due to the fact that the real interbank rate reached its minimum level in Australia in 2006 before the global financial crisis. We used two specification tests to check whether the lagged values of the dependent and explanatory variables are exogenous to the current dependent variable (Arellanlo and Bond, 1991). The results of the AR(2) test statistic in both GMM techniques indicate that there are no second-order autocorrelations in the differential errors (p-value=0.159 and 0.356, respectively).
These results fail to reject the null hypothesis and imply that subsets of both GMM instruments are valid and both models are not redundant. The results in Table 4 provide strong evidence that dynamic endogeneity exists and for the need to apply GMM methods. The results in Table 4 show that indicators of managerial risk aversion have significant negative effects on risk-taking incentives (vega), independent of.
For example, the estimated option moneyness ratio (ln(P/E)) has a significant negative effect of vega at the 1% level in all specifications. The estimated coefficient of ln(P/E) is -0.002 in column 4, which means that the effect of a standard deviation change in option moneyness is to decrease vega/TC by about 0.002. This finding strongly supports the argument of Coles et al. (2006) that the higher the cash component in total compensation, the more likely CEOs are entrenched and will avoid seeking risky projects.
We also note that years and 2010 have significant positive effects on vega when GSM methods are used. To check the robustness of the models, the AR(2) test statistic shows that there is no second-order autocorrelation in the differenced errors (p-value 0.3640 and 0.4100, respectively), which means that the instruments are valid.
Summary and conclusions
The coefficients for CEO age, tenure, and board insider ratio are not statistically significant, indicating that there is no evidence that firms with CEOs who are older, more experienced in the directorship, and with more insiders on the board are more likely. to adopt higher vega compensation plans. The main objective of our study is to examine the impact of CEOS' risk incentives vega on firms' risky financing policy in a dynamic setting. Consistent with Chava and Purnanandam (2010), Dong et al. 2006), we find that vega has a significant positive effect on management adoption of debt financing policy after addressing the possible endogeneity problems and controlling for a wide range of CEO risk aversion proxies in our estimation models.
Furthermore, our result suggests that the costs of director risk aversion, such as the cash value of CEO options and CEO cash compensation, can be substantial. Vega is lower for CEOs with more in-the-money options and more cash compensation. This suggests that cash options and cash compensation may reduce CEOs' preference for risky corporate policies in capital structure decisions.
To some extent, our results show that the series of executive pay reforms in Australia influenced boards of directors to set CEOs' contractual incentives to alleviate the agency problem. First, soft law makers such as the ASX Corporate Governance Council should include more restrictive disclosure requirements for executive remuneration related to option money and pay closer to the risk of executive capital in the guidelines. best practices. However, there is no reason to reduce the current level of stock options, because the CEOs' option portfolio vega leads to an increase in the firm's aggressive financing policy.
Bond, 1991, Some specification tests for panel data: Monte Carlo evidence and an application to employment equations. Bond, 1991, Some specification tests for panel data: Monte Carlo evidence and an application to employment equations. Guay, W., 1999, The sensitivity of CEO wealth to equity risk: an analysis of its magnitude and determinants.
Hutchinson, M., 2003, An analysis of the relationship between firm risk, executive stock options and accounting performance: some Australian evidence.
