Profit Sharing with Executives
3.5 Empirical Analysis
3.5.1 Determinants of the Top Management’s Cash-Flow Share Based on Total Cash Compensation
We first estimate equation (3.4) to test Hypotheses 1a to 3 (Hypothesis 4 will be tested separately in section 5.4). Column one of Table 3.3 shows the results for
27As Ramalho et al. (2009) discuss, the QMLE approach can be applied to cases with a finite number of boundary observations. In our specification, there are some observations at the lower bound of 0, because some firms do not pay cash bonuses (but only cash salaries) in some years.
However, in no case are there observations on the upper bound of 1. Note that this makes a Tobit approach inappropriate. Technically, only the two-limit Tobit model ensures that the predicted values are restricted to the unit interval, but the two-limit Tobit model can only be applied when there are observations in both limits (Ramalho et al., 2009); as is the case, for example, in estimating household portfolio shares of asset classes with households choosing to allocate none, some or all of their investments in a particular asset class (see the analysis in Poterba and Samwick (2003)). Conceptually, a Tobit model is appropriate for censored data, but fractional data is defined on the unit interval and not the consequence of any type of censoring (Ramalho et al., 2009).
28Papke and Wooldridge (1996) show that their estimation approach with a logit transformation and heteroskedastic-robust standard errors delivers robust estimates within the unit interval and with satisfactory efficiency properties. Their method was later implemented into statistical software such as STATA and is described in detail by Baum (2008).
the cash ratio, CRit29. We find support for Hypothesis 1a. Capital intensity is negatively related to the cash ratio. Also the market-to-book ratio as a measure of investment opportunities is (weakly) significant and negatively related to the cash ratio. On the other hand, R&D intensity (R&D expenditures relative to total assets) and sales growth turn out to be insignificant. We conclude that firms with large capital investments allocate a lower fraction of cash to the top management, but these investments are not necessarily related to R&D. Also firms with superior investment opportunities retain cash and invest, rather than allocate a large fraction of cash to the top management.
We also find support for the two hypotheses on corporate financing and dividend policy. As predicted by Hypothesis 1b, the top management’s cash ratio is negatively related to interest payments (relative to total assets), but the firm’s overall level of indebtedness (measured by the leverage ratio) is not significantly related to the cash ratio. As predicted by Hypothesis 1c, the cash ratio is negatively related to dividend payments (relative to total assets). Also the dividend payout ratio is significant and positively related to the top management’s cash ratio. This suggests an equal payout policy with respect to managers and shareholders: In firms where shareholders receive a higher share of cash flows, the managerial share in cash flows is also higher (and a lower share is dedicated to investments).
Long-term incentive compensation is highly significant and negatively related to the top management’s cash ratio. This is strong support for Hypothesis 2 and suggests that cash compensation and non-cash compensation are used as substitutes.
We also find support for Hypothesis 3. Firm size is significant and has the expected negative sign. Larger firms pay a lower fraction of cash flow as compensation to the top management. Firm performance measured by stock return is (weakly) significant and positive. Thus the fraction of generated cash flow spent on top management compensation increases with stock market performance, which may be driven by convex bonus compensation. On the other hand, the coefficient of profitability is significantly negative. More profitable firms allocate a lower fraction of cash to the top management.
The time structure described by the year dummies suggests that the
cross-29Note that there is no high pairwise correlation between any two explanatory variables. The two highest correlations are 0.42 between the leverage ratio and the market-to-book ratio, and 0.37 between the leverage ratio and interest to total assets. All other correlations are below 0.3.
sectional average of the top management’s cash-flow share was not significantly different during the years 2005-2008, but in 2009 it was significantly lower. We also find that the industry dummies mainly confirm the differences between industries observed in Table 3.1 (not reported).
The coefficient estimates of the QMLE regression model cannot be interpreted as marginal effects because of non-linearities. Instead, we calculate the marginal effect of a statistically significant variable xk by holding all covariates xl, l 6= k, at their mean values. We then build two measures to assess the economic impact of xk. First, we multiply the marginal effect by a one-standard deviation change in xk. This measure indicates the effect of a one-standard deviation change in xk on CRit. Second, we also divide this measure by one standard deviation of CRit. This measure indicates how much of a one-standard deviation variation in CRit is explained by a one-standard deviation change inxk. Column one of Table 3.4 shows the first measure. For example, in firms with a capital intensity of one standard deviation above the average, the top management’s cash-flow share is 0.4 percentage points below the sample average of 3.2 percent (from Table 3.1). On average, the largest impact (in absolute terms) on the cash ratio stems from a one-standard deviation in firm size and long-term incentives. The second measure is listed in column two of Table 3.4. For example, one standard deviation in capital intensity explains about 7.7 percent of a one-standard deviation in CRit. This measure is 65.7 and 9.0 percent, respectively, for firm size and long-term incentives.
Finally, we repeat our analysis to test whether cash flow participation of CEOs and non-CEO executives is driven by the same set of explanatory factors. We estimate equation (3.4) separately for the CEO’s cash-flow share (the cash ratio based on cash payments to the CEO), and for the combined share of the four non-CEO executives of the top management in each firm. Columns one and three of Table 3.5 show the results30. Most of the coefficient estimates for CEOs and the top-four management team excluding the CEO are very similar to the estimates for the top-five management team in Table 3.3. The only notable difference is that the market-to-book ratio is not significant, whereas it was weakly significant in Table 3.3. We conclude that our previous findings are robust to excluding CEOs from the analysis and also hold for CEOs alone.
30The number of observations in the regressions based on CEOs alone is slightly lower because there are a few cases where we cannot identify the CEO.