Does Ceo Incentive Pay Improve Bank Performance? A Quantile Regression Analysis of U.S. Commercial Banks

Abstract

The U.S. subprime crisis in 2008 have raised concerns about bank performance and the incentive pay of CEOs. Whether the CEO's incentive compensation improves bank performance deserves further investigation. This research studies the improvement in bank performance by examining the CEO incentive pay of 68 U.S. commercial banks from 1993 to 2005 using quantile regression (QR) analysis. The empirical evidence indicates that the relationship between bank performance and incentive pay does vary based on bank performance levels. Our results confirm that CEO incentive compensation improves the performance of high-performing banks and, at the same time, the accrued risks need to be taken into consideration and controlled through the efficient monitoring of outside directors. For low-performing banks, we find that outside directors have a significantly positive effect on performance regardless of whether such performance is adjusted or not adjusted. We suggest that banks with various performance levels require different mechanisms to enhance their performance. A "stick" approach consisting of efficient monitoring by outside directors may ensure that low-performing banks improve their performance improvements, whereas a "carrot" approach (i.e. CEO incentive pay) is appropriate for

Mediating effect of ESG performance on executive incentive compensation-financial performance relationship: evidence from MENA banking sector

“…2.1 Effect of executive incentive compensation on banks' financial performance Chan et al (2014) studied the relationship between bank performance and executive incentive compensation in 68 US commercial banks from 1993 to 2005 and found that this relationship varies according to the bank's performance levels. The results confirm that executive incentive compensation improves bank performance.…”

Recent Developments in Quantitative Finance: An Overview

“…The papers cover a range of interesting topics by experts in the field, including fast methods for large-scale non-elliptical portfolio optimization (Paolella, 2014), the impact of acquisitions on new technology stocks: the Google-Motorola case (Gao, Wang and Hafner, 2014), the effects of firm characteristics and recognition policy on employee stock options prices after controlling for self-selection (Kuo and Yu, 2014), searching for landmines in equity markets (Chang, Chang and Hung, 2014), whether CEO incentive pay improves bank performance, using a quantile regression analysis of U.S. commercial banks (Chan, Lin, Liang and Chen, 2014), testing price pressure, information, feedback trading, and smoothing effects for energy exchange traded funds (Chang and Ke, 2014), actuarial implications of structural changes in El Niño-Southern Oscillation Index dynamics (Chen and Huang, 2014), credit spreads and bankruptcy information from options data (Tzeng, 2014), QMLE of a standard exponential ACD model: asymptotic distribution and residual correlation (Sin, 2014), and using two-part quantile regression to analyze how earnings shocks affect stock repurchases (Chi, Yu, Li and Lu, 2014). 3 The interesting, timely and novel contributions to this special issue should highlight and encourage innovative research in a variety of challenging areas in quantitative finance.…”