Table VI.

Sensitivity analysis

Non-audit fees to total fees ratio Log of audit feeLog of non-audit fee
 Model 1: Chair Model 2: DirectorsModel 1: ChairModel 2: DirectorsModel 1: ChairModel 2: Directors
Dependent variableCoef.t-statCoef.t-statCoef.t-statCoef.t-statCoef.t-statCoef.t-stat
Panel A: robust regression using least absolute values (LAV) regression
Affiliated alumni chair0.1324.536***  −0.128−3.020***  0.2663.022***  
Unaffiliated alumni chair−0.007−0.335  −0.033−1.485  −0.053−0.762  
Affiliated alumni  0.0611.634  −0.142−3.819***  0.0800.836
Unaffiliated alumni  −0.015−0.698  −0.057−2.006**  −0.148−1.836*
Panel B: first differencing
 Non-audit fees to total fees ratio Log of audit feeLog of non-audit fee
 Model 1: Directors Model 1: Directors Model 1: Directors
 Coef.t-stat Coef.t-stat Coef.t-stat
Δ Alumni change0.0140.650 −0.053−1.681* −0.387−0.894

Notes:

All p-values are two-tailed. *, **, and *** denote p < 0.1, p < 0.05 and p < 0.01, respectively. The standard errors to calculate p-values are obtained after clustering observations from unique firms. Results are based on the same model as in Table III, but for brevity, the control variables are not tabulated. The standard errors used in the LAV regressions in Panel A are bootstrapped standard errors. Following Ettredge et al. (2014) we define change values in Panel B for the test variables and all continuous variables, whereas we keep dichotomous variables as in equation (1). All variables are as defined in Table I 

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