In this book, I have set out to explain why rising inequality has become a more or less permanent feature of life in most of the rich, industrialized democracies of Europe in the last thirty years. This has occurred despite public opinion in European societies that is staunchly opposed to inequality and supportive of state efforts to create more equitable societies (Osberg and Smeeding 2006; Kenworthy and McCall 2008; Kohut 2013; Sorapop and Norton 2014), and despite a growing consensus among experts that current levels of inequality are undesirable and even dangerous. My approach has been to study the politics and policy-making surrounding health inequalities, which most public health experts believe are closely linked to socioeconomic inequalities, but which policy-makers have tended to try to solve using different kinds of tools from those designed to impact directly the distribution of income and wealth.

In 2002, speaking at a school in east London, Prime Minister Tony Blair promised to “redistribute power, wealth, and opportunity.” This uncharacteristic – and perhaps unguarded, given the venue – remark was “one of the first times the prime minister has used the word ‘redistribute’ unprompted,” according to the Guardian reporter who covered the speech (The Guardian 2002). The surprised reporter went on to declare that redistribution was “previously a taboo expression in New Labour.”

Intellectual histories of health inequalities and of social epidemiology generally trace the modern “discovery” of health inequalities to the middle of the nineteenth century, when states began collecting sufficiently detailed data on mortality to allow for comparisons of death rates across small geographic areas or groups of individuals with particular occupations (see, e.g., Berkman and Kawachi 2000; Adler and Stewart 2010). In the 1820s and 1830s, Louis-René Villermé studied the link between poverty and mortality at various geographic scales from the street to the département1 in France, and in the 1840s he documented differences in life expectancy among workers in different industries, linking them to differences in lifestyles and working conditions (Julia and Valleron 2011). Rudolph Virchow, a pathologist and representative of the German Progress Party (Deutche Fortschrittspartei) in the Prussian parliament, was working around the same time on the spread of typhus; his 1848 research convinced him that “medicine is a social science and politics is nothing more than medicine on a large scale” (Mackenbach 2009). In 1845, Friedrich Engels, comparing working-class residents of Manchester, England, to their better-off neighbors, identified mechanisms linking socioeconomic status (SES) and health (Engels 1987). These authors and others laid the groundwork for the disciplines of social medicine and social epidemiology, whose central task is understanding how social conditions affect health in the population at large.

This chapter has two objectives. First, I define and describe the spatial and temporal variation in international capital and authoritarian politics. The former comprises the book’s key independent variable, while the latter is the book’s main dependent variable. Second, I illustrate the existence of an association between international capital and political survival in autocracies in the raw data. Such an examination is useful as it illustrates the book’s central empirical prediction without having to “finesse” the data to establish a statistical relationship between international capital and authoritarian politics. These associations provide motivation for further theoretical and empirical inquiry. To be clear, I do not claim a causal relationship between international capital and authoritarian politics in this chapter. Causal evaluations are the focus of Chapters 4 to 6.