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Three Essays on Executive Compensation - KOPS - Universität ...

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Which Pay for what Performance? Evidence from <strong>Executive</strong><br />

Compensati<strong>on</strong> in Germany and the United States<br />

why in U.S. firms stock performance is a significant determinant for cash b<strong>on</strong>uses<br />

throughout the sample period, whereas in German firms <strong>on</strong>ly accounting measures<br />

are c<strong>on</strong>sistently significant for cash b<strong>on</strong>uses. We may also interpret this finding in<br />

the spirit of Kaplan (1994) who argues that executive compensati<strong>on</strong> in the U.S. is<br />

more related to stock returns than in Japan because of the market-oriented U.S.<br />

ec<strong>on</strong>omy. In Japan, earnings determine executive compensati<strong>on</strong> because, similar to<br />

Germany, the Japanese ec<strong>on</strong>omy is rather bank-oriented than stock-market oriented.<br />

Cash B<strong>on</strong>uses and Firm Size<br />

It is known from previous studies that some firm characteristics have an impact <strong>on</strong><br />

the link between firm performance and executive compensati<strong>on</strong>. For example, firm<br />

size is an important c<strong>on</strong>trol variable because it is a robust finding that executives<br />

earn more in larger firms. In all our regressi<strong>on</strong>s we have included total assets as a<br />

c<strong>on</strong>trol variable for firm size, which turned out to be insignificant in most regressi<strong>on</strong>s<br />

because of the fixed effects. However, Cichello (2005) also finds that not <strong>on</strong>ly pay<br />

levels but also pay-performance sensitivities vary with firm size. To analyze whether<br />

firm size has an impact <strong>on</strong> pay-performance sensitivities in our two samples, we<br />

proceed as follows. First, we look for a linear relati<strong>on</strong> by including in our regressi<strong>on</strong><br />

an interacti<strong>on</strong> term between each performance measure and a rank measure of firm<br />

size. This rank measure is c<strong>on</strong>structed by ranking all firms with respect to total<br />

assets and dividing by the number of observati<strong>on</strong>s 49 . Sec<strong>on</strong>d, if the interacti<strong>on</strong><br />

term is not significant, we look for a potential n<strong>on</strong>-linear relati<strong>on</strong>. We create a<br />

dummy variable (’LARGE’) which is <strong>on</strong>e if the firm bel<strong>on</strong>gs to the upper half of the<br />

size distributi<strong>on</strong> and zero else. Again we interact this dummy variable with each<br />

performance measure.<br />

We expect different coefficient signs for these interacti<strong>on</strong> terms. The interacti<strong>on</strong><br />

term between firm size and EBIT should be negative, while the interacti<strong>on</strong> terms<br />

between firm size and stock return or sales growth, respectively, should be positive.<br />

To see why, c<strong>on</strong>sider <strong>on</strong>e small and <strong>on</strong>e large firm. Generating 10 milli<strong>on</strong> Euro in<br />

EBIT may be a good result for the small firm, but a very poor result for the large<br />

firm. This should be reflected in cash b<strong>on</strong>uses in the two firms. Hence in the cross<br />

secti<strong>on</strong> pay-performance sensitivity based <strong>on</strong> EBIT should be lower in larger firms.<br />

49 This rank measure has thus a value of <strong>on</strong>e (zero) for the largest (smallest) firm in the sample.<br />

84

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