This chapter responds to the growing importance of business analytics on "big data" in managerial decision-making, by providing a comprehensive primer on analyzing compensation data. All aspects of compensation analytics are covered, starting with data acquisition, types of data, and formulation of a business question that can be informed by data analysis. A detailed, hands-on treatment of data cleaning is provided, equipping readers to prepare data for analysis by detecting and fixing data problems. Descriptive statistics are reviewed, and their utility in data cleaning explicated. Graphical methods are used in examples to detect and trim outliers. The basics of linear regression analysis are covered, with an emphasis on application and interpreting results in the context of the business question(s) posed. One section covers the question of whether or not the pay measure (as a dependent variable) should be transformed via a logarithm, and the implications of that choice for interpreting the results are explained. Precision of regression estimates is covered via an intuitive, non-technical treatment of standard errors. An appendix covers nonlinear relationships among variables.

This chapter covers a core problem that managers regularly face (i.e., negotiating with current or prospective employees over pay). The topic is usually omitted from compensation texts and is covered in separate courses in business programs. But negotiation over pay is such an integral part of strategic compensation and talent management that it cannot be omitted from a book that aims to train managers to think strategically about pay. For example, talent retention (Chapter 12) requires managers to respond correctly when employees receive outside offers from competitors, which immediately triggers bargaining and negotiation over pay. The chapter opens by stressing the importance of defining your objective. The most important ingredient to successful negotiation is information, so the questions of when and how to reveal and collect information are addressed in depth. Sections 14.4 and 14.5 examine threats and bluffs as negotiating tools, as well as how managers should think about and respond to counteroffers. As discussed in the final section, sometimes employers can gain the upper hand during bargaining by complicating the discussion, whereas other times simplification is better.

My chapter considers the operation of trust in contracts and fiduciary relationships. Much has been written about how trust might figure in each setting, but there is little academic literature comparing the profile and workings of trust against the backdrop of the two legal forms. The gist of my argument is that contracts tend to orient and channel trust in one set of ways, and fiduciary relationships in a different set of ways. Part 2 draws a distinction between interpersonal trust and what, informed by work in sociology, I call ‘confidence’ in the predictable functioning of social or technological systems. I then argue that confidence is likely to develop differently in contracts than in fiduciary relationships, and that this has implications for how trust is likely to develop in each legal setting. In Part 3 of the paper I argue that there are reasons to think that the content of trusting beliefs might be different in fiduciary settings than in contractual settings. These reasons look to key differences between the contract form and the form of fiduciary relationships. I then explore some types of case in which contract and fiduciary forms interact in ways that might affect the content of trusting beliefs.

The chapter's premise is that understanding how something works requires studying it when it’s broken. The book is about labor contracts, i.e., formal or informal agreements between employers and employees. Sometimes employers breach these contracts by failing to pay their workers. Some workers (e.g., undocumented immigrants) are particularly vulnerable to “wage theft”. The timing of the parties' exchange of work and pay, and how it relates to wage theft, is discussed. Regulatory remedies to the wage-theft problem are studied, and it is shown that such regulations can lower workers’ average pay level by reducing the risk premium that compensates workers for wage-theft risk. Other remedies are given that involve no government intervention. Employers’ passive cuts to workers' real (as opposed to nominal) pay, via the erosive role of inflation, are discussed. Wage theft is offered as an example of a compensating differential (because it is an undesirable job attribute) before that topic is introduced. Themes from the wage-theft discussion recur throughout the book (e.g., in Chapter 10, on executive compensation, there is discussion of firms reneging on CEOs’ expected bonus payments).

Why you care: What is the point of running an experiment if you cannot analyze it in a trustworthy way? Variance is the core of experiment analysis. Almost all the key statistical concepts we have introduced are related to variance, such as statistical significance, p-value, power, and confidence interval. It is imperative to not only correctly estimate variance, but also to understand how to achieve variance reduction to gain sensitivity of the statistical hypothesis tests.

In the previous chapter we were introduced to the concept of learning – both for humans and for machines. In either case, a primary way one learns is first knowing what is a correct outcome or label of a given data point or a behavior. As it happens, there are many situations when we have training examples with correct labels. In other words, we have data for which we know the correct outcome value. This set of data problems collectively fall under supervised learning.

Political (Dis)Trust and Fiduciary Government analyzes the relationship between two key ideas in modern political thought: political trust and fiduciary government. The chapter begins with fiduciary government. Miller distinguishes ‘thick’ from ‘thin’ variants on the idea of fiduciary government. Thick variants place substantial normative weight on the idea, claiming, for example, that it solves the problem of political authority and provides an independent normative basis for the recognition of specific legal rights. Thin variants make much more modest claims. Miller’s own thin account, deployed here, suggests that fiduciary government articulates conditions under which the conduct of government can be understood as truly representative. By comparison with this thin conception of fiduciary government, an understanding of political trust as a particularized (or focused) and objective (or manifest) form of trust shown (or withheld) by citizens in public officials does distinct work. Briefly: it illuminates understanding of the political conditions and activity on which fiduciary government depends. That said, Miller also notes that ideals of fiduciary government and of political trust, where instantiated, dovetail: demands of fiduciary government enable public officials to prove trustworthy in ways that promote political trust, while also creating space for constructive forms of political distrust.

Sherlock Holmes would have loved living in the twenty-first century. We are drenched in data, and so many of our problems (including a murder mystery) can be solved using large amounts of data existing at personal and societal levels.

These days it is fair to assume that most people are familiar with the term “data.” We see it everywhere. And if you have a cellphone, then chances are this is something you have encountered frequently. Assuming you are a “connected” person who has a smartphone, you probably have a data plan from your phone service provider.

Why you care: In most experiment analyses, we assume that the behavior of each unit in the experiment is unaffected by variant assignment to other units. This is a plausible assumption in most practical applications. However, there are also many cases where this assumption fails.

This chapter teaches readers to think about training both as a form of current compensation and as an investment in future pay (because training makes workers more productive, allowing them to earn more in the future). Training is a form of current pay because workers value training (precisely because it increases their future expected compensation) and, for that reason, they are willing to accept lower current compensation than they would receive in an alternative job that is otherwise the same but that does not offer training. This evokes compensating differentials (Chapter 3). The portability of training across firms is covered, as well as whether employees or employers should pay for training and whether the skills imparted by training are general (i.e., useful across many employers) or specific to the current employer. The internal rate of return (or breakeven interest rate) is covered in the context of whether it is profitable to train workers. Section 8.5, on practical applications, gives tips for how managers can obtain information on the key components of the training decision, i.e., employee productivity and expected tenure after training, costs, and the interest rate.

The chapter explains why the EU explicitly decided not to intervene in private fair trade governance on two separate occasions, in 1999 and in 2009. The chapter starts by comparing private fair trade governance schemes, including Fairtrade International, Rainforest Alliance, and UTZ Certified. It then discusses why EU policymakers in the 1990s focused on Fairtrade only and declined to intervene because of the specific North–South trade dynamics of this issue area; the lack of concrete productive opportunities in the EU; and institutional constraints of the international trade regime. The Fair Trade movement’s successful harmonization of complementary private governance schemes also contributed to the EU’s non-interventionist approach. The broadening of the policy domain beyond Fairtrade in the early 2000s did not lead to fragmentation concerns, since differences among the schemes were framed as commercial and economic-ideological in nature and not problematized as a fragmentation issue. Active lobbying by and on behalf of private governance schemes ensured this outcome, resulting in a market for private governance that remains free of public intervention.