Scott de Marchi and Scott E. Page
This article provides a discussion on agent-based modeling. Two examples that show the ability of computational methods to extend game-theoretic results are presented. It then discusses modeling agents, modeling agent interactions, and system behaviour. In addition, it describes how agent-based models differ from and complement mathematical models and concludes with some suggestions for how one might best leverage the strengths of agent-based models to advance political science. Most mathematical analyses of game-theoretic models do not look into the stability and attainability of their equilibria and would be made richer by complementing them with agent-based models that explored those properties. The ability of computational models to test the robustness of formal results would be reason alone to add them to tool kits. As a methodology, agent-based modeling should be considered as in its infancy, its enormous potential limited only by the scientific and creative talents of its practitioners.
From an anthropological perspective, political leadership is a system of social relationships involving authority, charisma and other forms of personal or institutional power, whose rules are specific to, and embedded within, particular cultural contexts. More specifically, it is the art of controlling followers through the strategic mobilization of morality, rituals, and symbols. This article critically reviews anthropology’s contribution to the study of political leadership from the 1960s to the present. The article is in four parts. The first considers what political leadership is and why it matters. The second assesses pioneering works on leadership from 1960–1980 and the implications of the shift from small-scale, third-world communities towards more complex societies. The third considers studies since 1980, including seminal work on the relationship between political leadership, ritual and power, drawing on examples from Madagascar, Europe and the USA. The author also shows how post-1980, anthropological studies of leadership were subsumed within broader debates over ideology, hegemony, resistance, nation and state-formation, post-colonialism, and performance. Finally, the author considers some promising recent work that indicates new analytical directions. Anthropology’s key contribution lies in its attention to local social/cultural contexts, its understandings of how power is practised, and its concern with understanding the meanings of political leadership rather than simply its forms.
David Kinsella and Alexander H. Montgomery
Network analyses of global and regional arms flows (including small arms and light weapons, major conventional weapons, and weapons of mass destruction) and related international insecurity and criminality have so far been limited. Yet the literature contains hypotheses that could be explored or tested using network analysis. This chapter discusses supply and demand effects, structural tradeoffs between security and efficiency, pressures to become more or less centralized, and the effects of geography and other network layers. It concludes by reviewing existing data sets and analyses and gauges the potential for network analysis to inform the study of arms transfer networks. Given the general import of these networks for both security studies and policy, there should be a renaissance in the study of arms supply and proliferation networks.
Andrew D. Martin
This article surveys modern Bayesian methods of estimating statistical models. It first provides an introduction to the Bayesian approach for statistical inference, contrasting it with more conventional approaches. It then explains the Monte Carlo principle and reviews commonly used Markov Chain Monte Carlo (MCMC) methods. This is followed by a practical justification for the use of Bayesian methods in the social sciences, and a number of examples from the literature where Bayesian methods have proven useful are shown. The article finally provides a review of modern software for Bayesian inference, and a discussion of the future of Bayesian methods in political science. One area ripe for research is the use of prior information in statistical analyses. Mixture models and those with discrete parameters (such as change point models in the time-series context) are completely underutilized in political science.
Bruce W. Hardy
What role do presidential candidate character traits play in vote decisions? To some, the answer is obvious as campaigns, journalists, pundits, and voters frequently differentiate presidential candidates in terms of their personal qualities—traits are deemed important. On the other hand, past research suggests that, while candidate character traits are short term forces, they hold relatively limited in influence on vote preference. However, theoretical and methodological limitations may have hindered past research ability to detect the true influence of character traits in voter decisions. This author reviews past literature, offers a clear conceptualization of candidate character traits, presents ways in which trait may influence vote choice, and suggests areas for future research.
This article presents some guidance by cataloging nine different techniques for case selection: typical, diverse, extreme, deviant, influential, crucial, pathway, most similar, and most different. It also indicates that if the researcher is starting from a quantitative database, then methods for finding influential outliers can be used. In particular, the article clarifies the general principles that might guide the process of case selection in case-study research. Cases are more or less representative of some broader phenomenon and, on that score, may be considered better or worse subjects for intensive analysis. The article then draws attention to two ambiguities in case-selection strategies in case-study research. The first concerns the admixture of several case-selection strategies. The second concerns the changing status of a case as a study proceeds. Some case studies follow only one strategy of case selection.
This article presents a reconstructed definition of the case study approach to research. This definition emphasizes comparative politics, which has been closely linked to this method since its creation. The article uses this definition as a basis to explore a series of contrasts between cross-case study and case study research. This article attempts to provide better understanding of this persisting methodological debate as a matter of tradeoffs, which may also contribute to destroying the boundaries that have separated these rival genres within the subfield of comparative politics.
Case‐Oriented Configura‐Tional Research: Qualitative Comparative Analysis (Qca), Fuzzy Sets, and Related Techniques
This article investigates the tradition of case-oriented configurational research, focusing specifically on qualitative comparative analysis (QCA) as a tool for causal inference. It first presents two analytic procedures commonly used by comparative researchers. A short description of the state-of-the-art of QCA applications is offered, in terms of discipline, types of cases, models, combinations with other methods, and software development. It then reviews different uses of QCA, as well as generic ‘best practices’. Some key recent evolutions are illustrated: on the one hand the development, beyond dichotomous ‘crisp set’ QCA (csQCA), of multi-value QCA (mvQCA), fuzzy sets, and fuzzy-set QCA (fsQCA), and on the other hand technical advances and refinements in the use of the techniques. Finally, the article gives some concluding reflections as to expected developments, upcoming innovations, remaining challenges, expansion of fields of application, and cross-fertilization with other approaches.
Jon C. Rogowski and Betsy Sinclair
Though scholars have developed an increasingly rich set of research findings regarding the structure of political networks, identifying causal associations between these networks and political outcomes of interest presents a variety of challenges. Addressing these challenges is especially important given the prominence of networks in theories of individual and collective behavior. This chapter uses the framework of the Neyman-Rubin causal model (potential outcomes framework) to discuss challenges to identification researchers face when studying how networks affect political outcomes. It then describes a set of strategies researchers can employ to address these challenges, including suggestions for best practices in the context of both observational and experimental research designs.
Ines Levin and Betsy Sinclair
This article discusses methods that combine survey weighting and propensity score matching to estimate population average treatment effects. Beginning with an overview of causal inference techniques that incorporate data from complex surveys and the usefulness of survey weights, it then considers approaches for incorporating survey weights into three matching algorithms, along with their respective methodologies: nearest-neighbor matching, subclassification matching, and propensity score weighting. It also presents the results of a Monte Carlo simulation study that illustrates the benefits of incorporating survey weights into propensity score matching procedures, as well as the problems that arise when survey weights are ignored. Finally, it explores the differences between population-based inferences and sample-based inferences using real-world data from the 2012 panel of The American Panel Survey (TAPS). The article highlights the impact of social media usage on political participation, when such impact is not actually apparent in the target population.