Evolving Predictions for Executive Pay Features in Board Networks

Board Structure and Executive Pay: Evidence from the UK

We examine the impact of board structure on executive pay for 1,880 UK public firms over 1983-2002, using panel data analysis. Firstly, the proportion of non-executive directors tends to decrease the rate of increase in executive pay whilst board size tends to increase it. Secondly, the proportion of non-executives strengthens the relation between the rate of increase in executive pay and chang...

Say on Pay Design , Executive Pay , and Board Dependence ∗ July 2011 , this version October 2011

Motivated by important international differences in the design of ”say on pay” (SoP), this paper studies how its enforceability and its timing affects compensation decisions of the board of directors (BoD) and the level of board dependence. The analysis suggests that SoP design can have significant economic consequences that should be considered by regulatory authorities. In the context of a th...

Board Independence, Executive Pay Structures, and Pay Disclosure: Evidence from Europe

Using a broad sample of the largest European companies, I examine whether the two governance mechanisms, namely (i) independent monitoring by a board of directors and (ii) grants and disclosures of incentive-based executive pay, are substitutes for one another. I find that companies with proportionately more executives on their boards of directors grant greater incentive-based pay to their exec...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Evolving Features in Neural Networks for System Identification

Given N data pairs {Xi, yi}, i = 1, 2, ..., N , where each Xi is an n-dimensional vector of independent variables (Xi =< xi1 , xi2 , . . . , xin >) and yi is a dependent variable, the function approximation problem (FAP) is finding a function that best explains the N pairs of Xi and yi. From the universal approximation theorem and inherent approximation capabilities proved by various researches...