Managerial Attributes and Executive Compensation by Graham, Li, and Qiu (2012) Pascal Kieren

Transcription

1 by Graham, Li, and Qiu (2012) Pascal Kieren April 7, 2017

2 Agenda I. Research questions and contribution II. Methodology III. Empirical findings IV. Conclusion 2

3 I. Research Question and contribution Goal: Study the direct influence of firm and manager fixed effects on executive compensation and investigate their relative importance How do they contribute to the literature? Authors disentangle the relative importance of firm and manager fixed effects in determining executive pay and find that manager fixed effects and firm time-varying effects are most important Show that previously documented effects on executive pay are likely to be overstated due to endogeneity concerns Relate manager fixed compensation effects to different management styles in corporate policies and find that more aggressive managers appear to be remunerated The authors introduce the AKM -Method to financial literature 3

4 II. Methodology I Ln y it = βx it + γw jt + θ i + φ j + μ t + ε it Two way fixed effects model to control for unobservable time-invariant variables (estimated by LSDV or within approach) Model estimated is: Ln y it = βx it + γw jt + V s + μ t + ε it Problem: Cannot disentangle the firm and manager fixed effects If a company has no managerial turnover, firm and manager fixed effects cannot be disentangled (perfect collinear) MDV-Method suggests to restrict the sample to movers and to estimate the equation using the LSDV approach 1. Spell Method 2. MDV Method Mover Dummy Variable Problem: Manager differences and sample size * Firm level variables include firm size, M/B-ratio, stock returns, accounting returns and return volatility while manager variables include managerial tenure and CEO 4

5 II. Methodology II Ln y it = βx it + γw jt + θ i + φ j + μ t + ε it 3. AKM Method (Abowd, Kramarz & Margolis, 1999) Separates firm and manager fixed effects as long as the nonmovers work in firms that have hired at least one mover by using group connection to construct a sample Estimation of AKM-Method with LSDV frequently infeasible because of the large number of dummy variables. Regular within transformation is also not possible because the correspondence between firms and managers is unpatterned AKM-method first sweeps out manager fixed effects using the withinperson transformation while keeping time and firm fixed effects and then uses the LSDV approach to estimate variable coefficients and firm and year fixed effects Group connection Start with an arbitrary individual and include all companies for which he or she worked Add all individuals who have ever worked in any of those companies and continue adding all firms for which these individuals worked 5

6 III. Empirical findings Significant improvement of adj. R² indicates that FEs play an important role Manager FE and observable time-variant firm characteristics are the most important factors in explaining the variation in executive pay However: Analyses do not imply that observable characteristics have little power, if variation in these characteristics is mainly crosssectional Explanatory power of fixed effects Table 1: Determinants of Executive Compensation OLS (no FE) Firm FE Manager FE Firm + Manager FE Adj. R 2 (AKM) Obs. 65,421 65,421 65,421 65,421 Adj. R 2 (Spell) Obs. 112, , , ,546 Relative importance of different factors Table 2: Relative importance of different components (AKM-Method) (1) Mean (2) SD (3) Fraction of R 2 Log (total compensation) Observable time-variant frim (25%) Observable time-variant manager (5%) Firm FE (5%) Manager FE (54%) Year Effects (11%) Residuals R 2 = cov(ln y it, መβX it + γw jt + θ i + φ j + μ t ) Var (Ln y it ) 6

7 III. Implications for executive compensation research Comparing findings Implications Determinants of executive compensation (AKM-Method) (1) Pooled OLS (2) Firm and Manager FE Log(assets) t *** 0.21 *** Market to book t *** 0.10 *** Stock return t 0.20 *** 0.17 *** Return on assets t 0.40 *** 0.29 *** Return on assets t *** 0.36 *** Stock return volatility t 0.91 *** 0.10 CEO indicator 0.92 *** 0.30 *** Log(tenure) t 0.03 *** 0.05 *** Female *** N.A. Source: Graham, Li & Qiu (2006) While the signs of the coefficients are similar, the magnitudes in the three-way fixed effect model are significantly smaller Empirical methods that do not account for fixed effects most likely suffer from endogeneity problems (previous studies document effects similar in magnitude to the pooled OLS results) CEO indicator in pooled OLS captures two potential influences on compensation: personal (e.g. ability) and job promotion (pay increase due to new position) 7

8 III. Management Styles Lastly, the authors investigate whether different management styles (as defined by Bertrand and Schoar, 2003) are accordingly remunerated, estimating the following models: FE(comp) i = α + β FE z i + ε i Table 4: Relation between managerial fixed compensation and fixed policy effects Manager fixed effects (AKM) Change in pay ($thousand) R&D 1.51 *** 180 Investment 0.41 *** 258 Leverage 0.17 ** 57 Cash holdings *** -66 Dividend paying indicator 0.26 *** 659 Dividend yield 1.66 *** 96 Results suggest that fixed effects present in compensation correspond to differences in management styles across managers (e.g. better-paid managers invest more in both R&D and capital investments, employ more debt, pay more dividends and hold less cash) 8

9 IV. Conclusion Authors determine the relative importance of various manager and firm characteristics (time variant and invariant) and provide evidence that previous studies on executive compensation likely suffer from endogeneity concerns The AKM-Method provides a strong framework on how to create an appropriate sample and how to estimate models with unpatterned fixed effects One shortcoming might be that the authors cannot address the potential synergies between firm and managers ( matching ) 9