Jason Seawright

Case Selection Techniques in Case Study Research: A Menu of Qualitative and Quantitative Options

How can scholars select cases from a large universe for in-depth case study analysis? Random sampling is not typically a viable approach when the total number of cases to be selected is small. Hence attention to purposive modes of sampling is needed. Yet, while the existing qualitative literature on case selection offers a wide range of suggestions for case selection, most techniques discussed require in-depth familiarity of each case. Seven case selection procedures are considered, each of which facilitates a different strategy for within-case analysis. The case selection procedures considered focus on typical, diverse, extreme, deviant, influential, most similar, and most different cases. For each case selection procedure, quantitative approaches are discussed that meet the goals of the approach, while still requiring information that can reasonably be gathered for a large number of cases.

Democracy and the Policy Preferences of Wealthy Americans

It is important to know what wealthy Americans seek from politics and how (if at all) their policy preferences differ from those of other citizens.There can be little doubt that the wealthy exert more political influence than the less affluent do. If they tend to get their way in some areas of public policy, and if they have policy preferences that differ significantly from those of most Americans, the results could be troubling for democratic policy making. Recent evidence indicates that “affluent” Americans in the top fifth of theincomedistributionaresociallymoreliberalbuteconomicallymoreconservativethanothers.Butuntilnowtherehasbeenlittle systematicevidenceaboutthetrulywealthy,suchasthetop1percent.Wereporttheresultsofapilotstudyofthepoliticalviewsand activities of the top 1 percent or so of US wealth-holders. We find that they are extremely active politically and that they are much moreconservativethantheAmericanpublicasawholewithrespecttoimportantpoliciesconcerningtaxation,economicregulation, and especially social welfare programs. Variation within this wealthy group suggests that the top one-tenth of 1 percent of wealthholders (people with

Qualitative Comparative Analysis vis-A-vis Regression*

40 million or more in net worth) may tend to hold still more conservative views that are even more distinct from those of the general public. We suggest that these distinctive policy preferences may help account for why certain public policiesintheUnitedStatesappeartodeviatefromwhatthemajorityofUScitizenswantsthegovernmenttodo.Ifthisisso,itraises serious issues for democratic theory.

Putting Typologies to Work: Concept Formation, Measurement, and Analytic Rigor

Discussions of Charles C. Ragin’s Qualitative Comparative Analysis (QCA) have not adequately considered the assumptions about causation on which this method depends. Yet in evaluating any method, it is important to ask the question: How many untestable, or hard-to-test, assumptions must be met for us to believe the findings it produces? Advocates of QCA claim that one of its major strengths is that it requires fewer restrictive assumptions than techniques such as regression analysis. Hence, close assessment of the assumptions that are entailed is particularly salient to evaluating QCA. This article addresses these issues by considering three of the most important kinds of assumptions discussed in the context of regression analysis: assumptions about the correct form of the relationship, missing variables, and inferring causation from association. For each assumption, the role of corresponding assumptions in QCA will be explored and illustrated through an analysis of leftparty electoral fortunes in Latin America. Regarding the correct form of causal relationships, QCA in effect builds highly demanding assumptions into measurement procedures. Concerning missing variables, whereas earlier versions of QCA require a strong assumption of no causally relevant missing variables, more recent procedures allow some kinds of missing variables, but build in mutually contradictory statistical assumptions about those variables. Resolving these contradictions essentially converts QCA into an application of regression analysis. Regarding the process of inferring causation from association, QCA makes causal inference on the basis of patterns of association purely by assumption. That is, association is assumed to have a one-to-one relationship with causation. For all three groups of assumptions, QCA is found to require assumptions that, are at least as restrictive as those employed in regression analysis.

Party-system collapse: the roots of crisis in Peru and Venezuela

Typologies are well-established analytic tools in the social sciences. They can be “put to work” in forming concepts, refining measurement, exploring dimensionality, and organizing explanatory claims. Yet some critics, basing their arguments on what they believe are relevant norms of quantitative measurement, consider typologies old-fashioned and unsophisticated. This critique is methodologically unsound, and research based on typologies can and should proceed according to high standards of rigor and careful measurement. These standards are summarized in guidelines for careful work with typologies, and an illustrative inventory of typologies, as well as a brief glossary, are included online.

Do Electoral Laws Affect Women’s Representation?

Most party systems are relatively stable over time. Yet in the 1980s and 1990s, established party systems in Peru and Venezuela broke down, leading to the elections of outsider Alberto Fujimori and anti-party populist Hugo Chavez. Focusing on these two cases, this book explores the causes of systemic collapse.

Rival Strategies of Validation Tools for Evaluating Measures of Democracy

Numerous studies have found that proportional electoral rules significantly increase women’s representation in national parliaments relative to majoritarian and mixed rules. These studies, however, suffer from serious methodological problems including the endogeneity of electoral laws, poor measures of cultural variables, and neglect of time trends. This article attempts to produce more accurate estimates of the effect of electoral rules on women’s representation by using within-country comparisons of electoral rule changes and bicameral systems as well as matching methods. The main finding is that the effect of electoral laws is not as strong as in previous studies and varies across cases. The policy implication is that changes in electoral laws may not provide a quick and consistent fix to the problem of low women’s representation.

The Case for Selecting Cases That Are Deviant or Extreme on the Independent Variable

The challenge of finding appropriate tools for measurement validation is an abiding concern in political science. This article considers four traditions of validation, using examples from cross-national research on democracy: the levels-of-measurement approach, structural-equation modeling with latent variables, the pragmatic tradition, and the case-based method. Methodologists have sharply disputed the merits of alternative traditions. We encourage scholars—and certainly analysts of democracy—to pay more attention to these disputes and to consider strengths and weaknesses in the validation tools they adopt. An online appendix summarizes the evaluation of six democracy data sets from the perspective of alternative approaches to validation. The overall goal is to open a new discussion of alternative validation strategies.

Nonparametric Combination (NPC): A Framework for Testing Elaborate Theories

Qualitative and multimethod scholars face a wide and often confusing array of alternatives for case selection using the results of a prior regression analysis. Methodologists have recommended alternatives including selection of typical cases, deviant cases, extreme cases on the independent variable, extreme cases on the dependent variable, influential cases, most similar cases, most different cases, pathway cases, and randomly sampled cases, among others. Yet this literature leaves it substantially unclear which of these approaches is best for any particular goal. Via statistical modeling and simulation, I argue that the rarely considered approach of selecting cases with extreme values on the main independent variable, as well as the more commonly discussed deviant case design, are the best alternatives for a broad range of discovery-related goals. By contrast, the widely discussed and advocated typical case, extreme-on-Y, and most similar cases approaches to case selection are much less valuable than scholars in the qualitative and multimethods research traditions have recognized to date.

Better Multimethod Design:The Promise of Integrative Multimethod Research

Social scientists are commonly advised to deduce and test all observable implications of their theories. We describe a principled framework for testing such “elaborate” theories: nonparametric combination. Nonparametric combination (NPC) assesses the joint probability of observing the theoretically predicted pattern of results under the sharp null of no effects. NPC accounts for the dependence among the component tests without relying on modeling assumptions or asymptotic approximations. Multiple-testing corrections are also easily implemented with NPC. As we demonstrate with four applications, NPC leverages theoretical knowledge into greater statistical power, which is particularly valuable for studies with strong research designs but small sample sizes. We implement these methods in a new R package, NPC.