The approaches discussed in previous chapters – checklists, frameworks, case studies, and comparative history – can generate theory. However, they do so in a mostly inductive way, by generalizing from observations. Scholars working inductively stay close to what they observe whether they are defining concepts, developing theories, laying out a framework, generating hypotheses, or performing tests. The alternative is to work deductively, starting from fundamental axioms and using logic or mathematics to derive hypotheses (which can then be subjected to tests). Deduction and induction sound like opposites in principle, but in practice any attempt at theorizing must do some of both. Observation is impossible without a preexisting set of concepts, a rudimentary theory that tells one what to observe; and deductive theories are always inspired to some extent by real-world cases. Nevertheless, scholars differ in the importance they attribute to the deductive and inductive stages of the theory-building process. Those who emphasize the deductive stages can be said to work with formal models and theories.

Some formal theorists are critical of the more inductive approaches. In fact, some – probably a minority – claim that only deductive theories qualify as theory at all; they demote other general propositions to the lesser status of atheoretical empirical generalizations (Green and Shapiro 1994, quoting Riker, Bueno de Mesquita, and Achen and Snidal). This stance inflates the value of deduction and devalues the inductive processes required for building any good theory. However, formal models have two characteristics that make them different from, if not better than, other sorts of theory. First, formal models have clear and explicit assumptions. They have to; without premises, it would be impossible to derive implications. Stating assumptions explicitly makes it possible for other scholars to see the relationship between one study and another as a sort of tree diagram. The assumptions they share locate their origins on the same trunk or branch; the different assumptions they make push them out onto different branches and twigs. Explicit assumptions therefore provide a way to achieve theoretical integration. Lacking this guidance, the more inductive approaches are harder to integrate. They end up with conclusions that are confined to provisionally bounded temporal-spatial domains that rarely coincide perfectly with the domains of other studies. Second, formal models also have a heuristic: a hypothesis-generating procedure that is logically rigorous, or truth preserving.

This chapter begins the survey of empirical testing of theories of the creation and survival of democratic regimes. Chapter 9 surveys the impact of institutions, socioeconomic development and performance, and other factors, all of which emphasize forces external to individuals. In noncultural approaches, individuals are in a sense interchangeable: their political behavior is determined by their social class, their occupation, their role in an institutional context, and so forth. In cultural approaches, people are not interchangeable: they are different inside and therefore respond differently to the same external forces. Those who study political culture believe that we cannot discover useful theories without getting inside the heads of political actors.

Political culture is not a distinct methodological approach like case studies and comparative history, formal modeling, or quantitative testing. In fact, culture is studied using a variety of methods ranging from the qualitative extreme found in anthropological research to highly technical quantitative analysis using survey data and experiments. It has its own chapter here because the debate about approaches to the study of culture illustrates well the trade-offs that are the central theme of this book and because it is a large, complex, and fascinating literature in its own right.

Chapters 3–6 developed criteria for a good theory and surveyed many of the strategies used to develop theories of democratization. Chapters 8 and 9 survey the results of theory testing. This chapter introduces these tests by laying out criteria for rigor in testing. How to test rigorously occupies most of the chapter because it is the most complex issue. Many discussions of rigorous testing are confined to statistical testing. My perspective gives equal weight to qualitative methods, which support rigorous testing of a different kind. I argue that there are two fundamentally different kinds of testing that serve different but complementary purposes. The first is extensive testing, which helps establish that a causal relationship is generally true, on average, in a large sample. The second is intensive testing, which reveals which of several competing explanations best explains a specific outcome in a single case. Ultimately, a good theory should make predictions that survive both extensive and intensive testing.

Before developing these arguments, there are three preliminary questions that must be answered: Why is testing necessary? When is a theory ready to be tested? And what about the theory should be tested? The prevalence of untested propositions in comparative politics (such as most of those discussed in Chapters 4–6) suggests that a justification of testing is needed. Testing is necessary because many propositions that seem obviously, incontrovertibly true turn out to be false when exposed to evidence. Why do they seem to be true? There are several reasons. First, some propositions are intuitively appealing; that is, they are consistent with other ideas that we do not question. The problems with intuition are that (1) it does not require any systematic comparison of the consistency of the new ideas with the old ones, and (2) the old ideas that have gone unquestioned may themselves be false. A good example is the common assumption of Washington policy makers and pundits that democracy and free-market capitalism are mutually reinforcing. The catchphrase “open markets, open societies” is widely accepted, but mostly because it conforms to the prevailing liberal individualist ideology, which conveniently overlooks promarket dictatorships and statist or protectionist democracies.

Scholars who set out to study a political phenomenon talk past one another if they define the phenomenon differently. Suppose two scholars want to understand “democracy,” but one understands “democracy” to refer to the liberal political democracies of advanced capitalist economies, whereas the other considers only the “people's democracies” of communist regimes to be truly democratic. They will end up studying completely different countries and will probably come to opposite conclusions. If they try to reconcile their findings, they will discover that they are not really studying the same phenomenon at all. In practice, the difference in definitions is rarely so stark, but clear and consistent conceptualization is essential for preventing misunderstandings.

Unfortunately, one of the most difficult challenges in studying democratization has been reaching agreement on what “democracy” is. In fact, W. B. Gallie once argued that democracy is one of the best examples of an “essentially contested” concept: a concept that is the focus of endless disputes that, “although not resolvable by argument of any kind, are nevertheless sustained by perfectly respectable arguments and evidence” (Gallie 1956). Democracy is a contested concept because nearly everyone values the label, but there are different reasonable and legitimate, yet incompatible, criteria for judging whether the label is deserved.

Surveying democratization research in tandem with a critique of research methods has given us a more balanced and solid perspective on what we know and how confident we can be about it. Each type of research – conceptualization and measurement, checklists and frameworks, case studies, comparative history, formal models and theories, political culture, and quantitative analysis – is useful for developing certain kinds of knowledge but unhelpful for developing others. Chapters 2, 4, 5, 6, 8, and 9 concluded with a broad summary of findings and a critique of the methods used to produce them. This chapter pulls together what we have learned so far from all approaches and highlights the limitations of this understanding to focus attention on areas that should be high priorities for future research.

One priority is for each approach to do a better job of playing to its strengths: for comparative histories to generate more complex explanations, for formal modeling to produce more tightly integrated theories, and for quantitative methods to test general propositions more rigorously. Another priority, however, is for each approach to compensate for its weaknesses. Comparative historians could reach for greater generalization and a more systematic grounding in deductive propositions; formal models could become more realistic and make predictions that are more suitable for rigorous testing; and quantitative analysis could test more complex models and incorporate stronger theoretical guidance. The more these separate approaches compensate for their weaknesses, the closer we will get to a unified comparative method.