The Other Side of the Tradeoff: The Impact of Risk on Executive Compensation

The principal-agent model of executive compensation is of central importance to the modern theory of the firm and corporate governance, yet the existing empirical evidence supporting it is quite weak. The key predication of the model is that the executive's pay-performance sensitivity is decreasing in the variance of the firm's performance. We demonstrate strong empirical confirmation of this prediction using a comprehensive sample of executives at large corporations. In general, the pay-performance sensitivity for executives at firms with the least volatile stock prices is an order of magnitude greater than the pay-performance sensitivity for executives at firms with the most volatile stock prices. This result holds for both chief executive officers and for other highly compensated executives. We further show that estimates of the pay-performance sensitivity that do not explicitly account for the effect of the variance of firm performance are biased toward zero. We also test for relative performance evaluation of executives against the performance of other firms. We find little support for the relative performance evaluation model. Our findings suggest that executive compensation contracts incorporate the benefits of risk-sharing but do not incorporate the potential informational advantages of relative performance evaluation.

Executive Compensation, Strategic Competition, and Relative Performance Evaluation: Theory and Evidence

We argue that strategic interactions between firms in an oligopoly can explain the puzzling lack of high-powered incentives in executive compensation contracts written by shareholders whose objective is to maximize the value of their shares. We derive the optimal compensation contracts for managers and demonstrate that the use of high-powered incentives will be limited by the need to soften product market competition. In particular, when managers can be compensated based on their own and their rivals' performance, we show that there will be an inverse relationship between the magnitude of high-powered incentives and the degree of competition in the industry. More competitive industries are characterized by weaker pay-performance incentives. Empirically, we find strong evidence of this inverse relationship in the compensation of executives in the United States. Our econometric results are not consistent with alternative theories of the effect of competition on executive compensation. We conclude that strategic considerations can preclude the use of high-powered incentives, in contrast to the predictions of the standard principal-agent model.

Empire-Builders and Shirkers: Investment, Firm Performance, and Managerial Incentives

Do firms systematically over- or underinvest as a result of agency problems? We develop a contracting model between shareholders and managers in which managers have private benefits or private costs of investment. Managers overinvest when they have private benefits and underinvest when they have private costs. Optimal incentive contracts mitigate the over- or underinvestment problem. We derive comparative static predictions for the equilibrium relationships between incentives from compensation, investment, and firm performance for both cases. The relationship between firm performance and managerial incentives, in isolation, is insufficient to identify whether managers have private benefits or private costs of investment. In order to identify whether managers have private benefits or costs, we estimate the joint relationships between incentives and firm performance and between incentives and investment. Our empirical results show that both firm performance and investment are increasing in managerial incentives. These results are consistent with managers having private costs of investment. We find no support for overinvestment based on private benefits.

Performance Incentives Within Firms: The Effect of Managerial Responsibility

Empirical research on executive compensation has focused almost exclusively on the incentives provided to chief executive officers. However, firms are run by teams of managers, and a theory of the firm should also explain the distribution of incentives and responsibilities for other members of the top management team. An extension of the standard principal-agent model to allow for multiple signals of effort predicts that executives who have other, more precise signals of their effort than firm performance will have compensation that is less sensitive to the overall performance of the firm. We test this prediction in a comprehensive panel dataset of executives at large corporations by comparing executives with explicit divisional responsibilities to those with broad oversight authority over the firm and to CEOs. Controlling for executive fixed effects and the level of compensation, we find that CEOs have pay-performance incentives that are $5.85 per thousand dollar increase in shareholder wealth higher than the pay-performance incentives of executives with divisional responsibility. Executives with oversight authority have pay-performance incentives that are$1.26 per thousand higher than those of executives with divisional responsibility. The aggregate pay-performance sensitivity of the top management team is quite substantial, at $30.24 per thousand dollar increase in shareholder wealth for the median firm in our sample. Our work sheds light on the alignment of responsibility and incentives within firms and suggests that the principal-agent model provides an appropriate characterization of the internal organization of the firm.

A proficiency-based technical skills curriculum for laparoscopic surgery

Imperial Users onl

Access to Computer Technologies at Home Improves Wages in the Marketplace

This study suggests that having access to a computer and the Internet at home leads to better wages. We normally have the idea that people with higher wages have computers and Internet access at home. But with declining prices of home PCs and the increasing importance of Internet, this no longer seems to be the case. The new owners of PC today are considerably poorer and less educated than in the past. People with access to a PC and Internet at home appear to earn 8.6% more than their counterpart. This result seems to suggest that University policies requiring students seeking professional degrees like MBA to own a laptop or Home PC has merit and this policy could be extended to cover undergraduate students also. Universities could also provide dial-in-server access to their recent graduates for a specified period of time to boost their placement statistics

Convolutional Neural Networks for Raw Speech Recognition

State-of-the-art automatic speech recognition (ASR) systems map the speech signal into its corresponding text. Traditional ASR systems are based on Gaussian mixture model. The emergence of deep learning drastically improved the recognition rate of ASR systems. Such systems are replacing traditional ASR systems. These systems can also be trained in end-to-end manner. End-to-end ASR systems are gaining much popularity due to simplified model-building process and abilities to directly map speech into the text without any predefined alignments. Three major types of end-to-end architectures for ASR are attention-based methods, connectionist temporal classification, and convolutional neural network (CNN)-based direct raw speech model. In this chapter, CNN-based acoustic model for raw speech signal is discussed. It establishes the relation between raw speech signal and phones in a data-driven manner. Relevant features and classifier both are jointly learned from the raw speech. Raw speech is processed by first convolutional layer to learn the feature representation. The output of first convolutional layer, that is, intermediate representation, is more discriminative and further processed by rest convolutional layers. This system uses only few parameters and performs better than traditional cepstral feature-based systems. The performance of the system is evaluated for TIMIT and claimed similar performance as MFCC

Integration of Virtual Learning of Induction Machines for Undergraduates

In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied

Modern Pedagogy Techniques for DC Motor Speed Control

Based on a survey conducted for second and third year students of the electrical engineering department at Maharishi Markandeshwar University, India, it was found that around 92% of students felt that it would be better to introduce a virtual environment for laboratory experiments. Hence, a need was felt to perform modern pedagogy techniques for students which consist of a virtual environment using MATLAB/Simulink. In this paper, a virtual environment for the speed control of a DC motor is performed using MATLAB/Simulink. The various speed control methods for the DC motor include the field resistance control method and armature voltage control method. The performance analysis of the DC motor is hence analyzed