This chapter instills an appreciation for the powerful effects (both positive and negative) of performance pay on employee behavior. It opens with a performance-pay success story, namely a field experiment by Shearer (2004) in which the piece-rate compensation of Canadian tree planters was changed. It then develops some examples of the darker side of performance pay, including the Wells Fargo employees who opened false accounts to meet a quota. Section 9.2 provides visual representations of performance pay in which the pay graph has a positive slope (i.e., it increases when the worker’s performance measure increases), sometimes linearly as with piece-rate pay and sometimes nonlinearly as with bonuses. The chapter emphasizes the incentive and sorting effects associated with performance pay as well as its prevalence. Workers’ attitudes towards risk (of earnings fluctuations) and how risk affects performance pay is covered, along with performance measurement, various drawbacks of performance pay, and how to design performance-pay contracts. Readers will finish the chapter with an understanding of the advantages and disadvantages of performance pay and when it can be effectively used.

This chapter on executive compensation and stock options is effectively a continuation of Chapter 9 on performance pay. It provides an overview of executive compensation and an intuitive, non-technical treatment of stock options that focuses on the worker incentives that options create. There is a lot of discussion of risk (of income loss) that builds on Chapter 9, and the “pay for luck” discussion that ends the chapter concerns the possibility of firms’ reneging on CEOs’ bonus payments, which echoes the wage-theft themes from Chapter 2. Section 10.2 covers the executive bonuses known as “80/120” plans, representing them pictorially as nonlinear functions of a performance measure (that are upward-sloping in some parts, as in the performance-pay graphs of Chapter 9). The section on stock options is detailed and explains all of the key terminology and the most important concepts in this area. The distinction between the intrinsic value and the market value of an option is made carefully, with an intuitive, non-technical discussion of the Black–Scholes–Merton options valuation formula, and the role of risk is explained in detail.

An unavoidable cause of electrical noise is the random thermal motion of electrons in conducting media such as wires or resistors. Active circuits comprising MOS transistors suffer from similar random motion of electrons leading to noise. As long as communication systems are constructed from such devices, the noise will be with us. Amplifying arbitrarily weak signals to make them detectable is unrealistic, as the presence of noise sets a lower limit to minimum detectable signal.1 This ultimately limits the range where the transmitter and receiver can communicate, yet maintaining a minimum signal-to-noise ratio at the detector output.

We apply the results of the previous chapter to the classical Sturm-Liouville eigenvalue problem, showing that the eigenfunctions form a complete orthonormal basis for L^2. We analyse properties of the solutions of such problems using the Wronskian determinant and define the Green's function that enables us to write an arbitrary solution of the inhomogeneous problem in terms of two particular solutions of the homogeneous problem.