This chapter defines and describes trauma, adversity and trauma-informed practice. We explore how trauma impacts children and young people and how this may influence their engagement with education. A summary about how a student may present when experiencing trauma is provided. As teachers often hear about and address trauma and adversity faced by children, the concepts of compassion fatigue and vicarious trauma are also briefly explored. The chapter ends with examples of ways in which teachers can create trauma-informed classrooms and support and promote trauma-informed policies and practices in schools.

There is a parable about an entrepreneur who invents an amazing machine. Wheat, soybeans, lumber, and oil are fed into one end of the contraption. As if by magic, smartphones, coffee, and tea, and all manner of clothing and apparel come out the other end. The inventor is praised as a genius – until further investigation reveals that the wheat and the other inputs were being secretly shipped to other countries in exchange for the electronics and apparel that later emerged. When this news is made public, the inventor is denounced as an unpatriotic fraud who is destroying jobs.

In January 2017, just three days after taking office, President Donald Trump withdrew the United States from the Trans-Pacific Partnership, or TPP. This trade agreement involving about a dozen Pacific Rim countries would have reduced trade barriers and established rules governing trade in the region. “We’re going to stop the ridiculous trade deals that have taken … companies out of our country,” he stated. Trump had consistently argued that trade agreements such as the North American Free Trade Agreement (NAFTA) with Canada and Mexico were “a bad deal” for US workers and unfair to American business, allowing other countries “to take advantage of us.”

The automobile industry has long captured America’s imagination. Not only are cars an iconic part of national culture, but they are also essential for moving around – unless you happen to live in New York City.

The auto industry is dominated by a handful of large firms. Toyota, Volkswagen, Daimler, General Motors (GM), Ford, Honda, Fiat Chrysler, Nissan, and BMW are the global sales leaders. Each firm produces a wide array of vehicles: small and large sedans, minivans, SUVs, and pickups. And then there are specialty producers such as Tesla and Lamborghini.

After decades of roaring growth, the “East Asian Miracle” – as touted in a 1993 book published by the World Bank – seemed to be in full swing. Yet a mere four years later, the region was engulfed in chaos. What became known as the Asian Financial Crisis unfolded in July 1997. As foreign exchange reserves were depleted, the Bank of Thailand was forced to let the Thai baht float freely. The currency immediately depreciated by 21%. By January 1998, the baht was 54% weaker against the dollar than it had been six months earlier. The turmoil was not restricted to Thailand; Singapore, Malaysia, Indonesia, and the Philippines also experienced stresses on their balance of payments as capital flows reversed course, with net flowing out rather than in. In November 1997, the Bank of Korea floated its currency after years of keeping its currency, the won, tightly managed against the dollar. By January 1998, the won had fallen in value by 39%. Figure 18.1 tells the story graphically.

In June of 2016, voters in the United Kingdom narrowly approved a referendum on leaving the European Union (EU), a common market wherein labor, capital, and goods and services are free to move between countries without impediment. The vote in favor of Britain’s exit – or “Brexit” – set in motion a process by which the country would leave the EU within two years.

In this chapter, compared to Chapter 8 we assume that data or expert knowledge can tell us not only something about the possible values of the problem’s parameters but also about their relative likelihood, that is, the probability distribution.

We now consider problems in which the situation is not as simple as “first we make the decisions, then we observe the uncertainty and compute the costs”

When you switch on your smartphone, you are probably not aware of all the minerals that have been dug up around the world to make the electronics work. An iPhone screen has been polished with lanthanum and cerium, a magnet inside is made with neodymium and praseodymium, the circuitry in semiconductors uses arsenic metals, rechargeable batteries depend on cadmium, and light bulbs and heating elements rely on tungsten. It turns out that these so-called “rare earth” minerals are essential for modern life and are used in products ranging from smartphones to MRI machines to advanced defense technology to hair dryers.

You may not know it, but the tomato has always been the subject of controversy. Botanists debate whether the tomato is a vegetable or a fruit (it is actually a fruit). Linguists debate whether it is pronounced as to-may-toe or to-mah-toe (who cares!). Meanwhile, agricultural economists debate where the best place to produce this nutritious and delicious crop might be.

The introductory chapter sets the stage for the rest of the book. It begins by tracing the historical development of behavioral economics, then giving a working definition of the subject, followed by a discussion of the scope of behavioral economics. In particular, the various kinds of data that form the basis of inferences in behavioral economics are discussed. These include observational data, experimental lab data, field data, survey data, and neuroeconomic data. It is argued that no particular source of data holds hierarchical sway over any of the other sources of data. All sources of data have their pros and cons, and we need all of them to build a more rounded understanding of human behavior. We lay great emphasis on the scientific method and describe best practice in the natural sciences, following the Popperian tradition. It is vital that students get themselves well versed in these ideas to put them in the right frame of mind for taking a course in behavioral economics.

Chapter 2 relaxes two features of EU: linear probability weighting and utility defined over final wealth levels. Our main focus is on prospect theory (PT). The salient features of PT are reference dependence (utilities are derived from changes in wealth relative to a reference point), loss aversion (losses bite more than equivalent gains), and inverse S-shaped probability weighting functions that replace the “linearity of probabilities” in EU. Under PT, attitudes to risk are determined “jointly” by the shapes of the utility function and the probability weighting function, giving rise to a four-fold pattern of risk attitudes. We also give an exposition of rank dependent utility. We consider several applications of prospect theory. These include, exchange disparities; optimal contracts; tax evasion puzzles; backward bending labor supply curves; attitudes towards low probability events, and loss aversion among professional golf players. Close primate relatives also exhibit loss aversion; thus, loss aversion precedes the evolutionary separation of humans from close primate relatives. We also apply PT to the Ellsberg paradox.

Extensive empirical evidence demonstrates that humans possess other-regarding preferences, that is, they care about the well-being of others, in addition to their own. Humans are predisposed to cooperate with each other, but they are conditional cooperators; they respond to kindness with kindness and unkindness with unkindness. The intentionality of actions by others is important in judging the unkindness of their actions. This chapter explores the evidence on human sociality, using several experimental games such as: the ultimatum and dictator games, the trust and the gift exchange games, and the public goods game with and without punishments. The external validity of lab experiments is also considered. Other topics include the evolutionary origins of preferences and the behavioral differences between WEIRD and non-WEIRD societies. We consider the role of human morality and the aversion to lying and breaking promises. Even when lies cannot be discovered, a significant fraction of people chooses to remain honest, while others tell partial lies and only a few lie maximally. We also outline social identity theory, whereby humans treat ingroup members more favorably relative to outgroup members.