A growing body of research uses computational models to study political decision making and behavior such as voter turnout, vote choice, party competition, social networks, and cooperation in social dilemmas. Advances in the computational modeling of political decision making are closely related to the idea of bounded rationality. In effect, models of full rationality can usually be analyzed by hand, but models of bounded rationality are complex and require computer-assisted analysis. Most computational models used in the literature are agent based, that is, they specify how decisions are made by autonomous, interacting computational objects called “agents.” However, an important distinction can be made between two classes of models based on the approaches they take: behavioral and information processing. Behavioral models specify relatively simple behavioral rules to relax the standard rationality assumption and investigate the system-level consequences of these rules in conjunction with deductive, game-theoretic analysis. In contrast, information-processing models specify the underlying information processes of decision making—the way political actors receive, store, retrieve, and use information to make judgment and choice—within the structural constraints on human cognition, and examine whether and how these processes produce the observed behavior in question at the individual or aggregate level. Compared to behavioral models, information-processing computational models are relatively rare, new to political scientists, and underexplored. However, focusing on the underlying mental processes of decision making that must occur within the structural constraints on human cognition, they have the potential to provide a more general, psychologically realistic account for political decision making and behavior.
Article
Computational Models of Political Decision Making
Sung-youn Kim
Article
Fast and Frugal Heuristics
Konstantinos V. Katsikopoulos
Polymath, and also political scientist, Herbert Simon dared to point out that the amounts of time, information, computation, and other resources required for maximizing utility far exceed what is possible when real people have to make real decisions in the real world. In psychology, there are two main approaches to studying actual human judgment and decision making—the heuristics-and-bias and the fast-and-frugal-heuristics research programs. A distinctive characteristic of the fast-and-frugal-heuristics program is that it specifies formal models of heuristics and attempts to determine when people use them and what performance they achieve. These models rely on a few pieces of information that are processed in computationally simple ways. The information and computation are within human reach, which means that people rely on information they have relatively easy access to and employ simple operations such as summing or comparing numbers. Research in the laboratory and in the wild has found that most people use fast and frugal heuristics most of the time if a decision must be made quickly, information is expensive financially or cognitively to gather, or a single/few attributes of the problem strongly point towards an option. The ways in which people switch between heuristics is studied in the framework of the adaptive toolbox. Work employing computer simulations and mathematical analyses has uncovered conditions under which fast and frugal heuristics achieve higher performance than benchmarks from statistics and machine learning, and vice versa. These conditions constitute the theory of ecological rationality. This theory suggests that fast and frugal heuristics perform better than complex optimization models if the available information is of low quality or scarce, or if there exist dominant options or attributes. The bias-variance decomposition of statistical prediction error, which is explained in layperson’s terms, underpins these claims. Research on fast and frugal heuristics suggests a governance approach not based on nudging, but on boosting citizen competence.
Article
Genetics and Heritability Research on Political Decision Making
Levente Littvay
In 2005, political scientists claimed that parent-child similarities, in addition to parenting, socialization, or shared social factors by the family, are also driven by genetic similarity. This claim upended a century of orthodoxy in political science. Many social scientists are uncomfortable with this concept, and this discomfort often stems from a multitude of misunderstandings. Claims about the genetics and heritability of political phenomena predate 2005 and wave of studies over the decade that followed swept through political science and then died down as quickly as they came. The behavior genetic research agenda faces several challenges within political science, including (a) resistance to these ideas within all of the social sciences, (b) difficulties faced by scholars in the production of meaningful theoretical and empirical contributions, and (c) developments in the field of genetics and their (negative) impact on the related scholarship within the study of politics.
Article
The International Crisis Behavior Project
Kyle Beardsley, Patrick James, Jonathan Wilkenfeld, and Michael Brecher
Over the course of more than four decades the International Crisis Behavior (ICB) Project, a major and ongoing data-gathering enterprise in the social sciences, has compiled data that continues to be accessed heavily in scholarship on conflict processes. ICB holdings consist of full-length qualitative case studies, along with an expanding range of quantitative data sets. Founded in 1975, the ICB Project is among the most visible and influential within the discipline of International Relations (IR). A wide range of studies based either primarily or in part on the ICB’s concepts and data have accumulated and cover subjects that include the causes, processes, and consequences of crises. The breadth of ICB’s contribution has expanded over time to go beyond a purely state-centric approach to include crisis-related activities of transnational actors across a range of categories. ICB also offers depth through, for example, potential resolution of contemporary debates about mediation in crises on the basis of nuanced findings about long- versus short-term impact with regard to conflict resolution.
Article
Expected Utility and Political Decision Making
Jona Linde
Expected utility theory is widely used to formally model decisions in situations where outcomes are uncertain. As uncertainty is arguably commonplace in political decisions, being able to take that uncertainty into account is of great importance when building useful models and interpreting empirical results. Expected utility theory has provided possible explanations for a host of phenomena, from the failure of the median voter theorem to the making of vague campaign promises and the delegation of policymaking.
A good expected utility model may provide alternative explanations for empirical phenomena and can structure reasoning about the effect of political actors’ goals, circumstances, and beliefs on their behavior. For example, expected utility theory shows that whether the median voter theorem can be expected to hold or not depends on candidates’ goals (office, policy, or vote seeking), and the nature of their uncertainty about voters. In this way expected utility theory can help empirical researchers derive hypotheses and guide them towards the data required to exclude alternative explanations.
Expected utility has been especially successful in spatial voting models, but the range of topics to which it can be applied is far broader. Applications to pivotal voting or politicians’ redistribution decisions show this wider value. However, there is also a range of promising topics that have received ample attention from empirical researchers, but that have so far been largely ignored by theorists applying expected utility theory.
Although expected utility theory has its limitations, more modern theories that build on the expected utility framework, such as prospect theory, can help overcome these limitations. Notably these extensions rely on the same modeling techniques as expected utility theory and can similarly elucidate the mechanisms that may explain empirical phenomena. This structured way of thinking about behavior under uncertainty is the main benefit provided by both expected utility theory and its extensions.
Article
Agent-Based Modeling in Political Decision Making
Lin Qiu and Riyang Phang
Political systems involve citizens, voters, politicians, parties, legislatures, and governments. These political actors interact with each other and dynamically alter their strategies according to the results of their interactions. A major challenge in political science is to understand the dynamic interactions between political actors and extrapolate from the process of individual political decision making to collective outcomes. Agent-based modeling (ABM) offers a means to comprehend and theorize the nonlinear, recursive, and interactive political process. It views political systems as complex, self-organizing, self-reproducing, and adaptive systems consisting of large numbers of heterogeneous agents that follow a set of rules governing their interactions. It allows the specification of agent properties and rules governing agent interactions in a simulation to observe how micro-level processes generate macro-level phenomena. It forces researchers to make assumptions surrounding a theory explicit, facilitates the discovery of extensions and boundary conditions of the modeled theory through what-if computational experiments, and helps researchers understand dynamic processes in the real-world. ABM models have been built to address critical questions in political decision making, including why voter turnouts remain high, how party coalitions form, how voters’ knowledge and emotion affect election outcomes, and how political attitudes change through a campaign. These models illustrate the use of ABM in explicating assumptions and rules of theoretical frameworks, simulating repeated execution of these rules, and revealing emergent patterns and their boundary conditions. While ABM has limitations in external validity and robustness, it provides political scientists a bottom-up approach to study a complex system by clearly defining the behavior of various actors and generate theoretical insights on political phenomena.
Article
Media-Effects Experiments in Political Decision Making
Bryan Gervais
Recognizing its causal power, contemporary scholars of media effects commonly leverage experimental methodology. For most of the 20th century, however, political scientists and communication scholars relied on observational data, particularly after the development of scientific survey methodology around the mid-point of the century. As the millennium approached, Iyengar and Kinder’s seminal News That Matters experiments ushered in an era of renewed interest in experimental methods. Political communication scholars have been particularly reliant on experiments, due to their advantages over observational studies in identifying media effects. Although what is meant by “media effects” has not always been clear or undisputed, scholars generally agree that the news media influences mass opinion and behavior through its agenda-setting, framing, and priming powers. Scholars have adopted techniques and practices for gauging the particular effects these powers have, including measuring the mediating role of affect (or emotion).
Although experiments provide researchers with causal leverage, political communication scholars must consider challenges endemic to media-effects studies, including problems related to selective exposure. Various efforts to determine if selective exposure occurs and if it has consequences have come to different conclusions. The origin of conflicting conclusions can be traced back to the different methodological choices scholars have made. Achieving experimental realism has been a particularly difficult challenge for selective exposure experiments. Nonetheless, there are steps media-effects scholars can take to bolster causal arguments in an era of high media choice. While the advent of social media has brought new challenges for media-effects experimentalists, there are new opportunities in the form of objective measures of media exposure and effects.
Article
How Motivation Influences Political Decision Making
Brian J. Gaines and Benjamin R. Kantack
Although motivation undergirds virtually all aspects of political decision making, its influence is often unacknowledged, or taken for granted, in behavioral political science. Motivations are inevitably important in generic models of decision theory. In real-world politics, two crucially important venues for motivational effects are the decision of whether or not to vote, and how (or, whether) partisanship and other policy views color information-collection, so that people choose and then justify, rather than studying options before choosing. For researchers, motivations of survey respondents and experimental subjects are deeply important, but only just beginning to garner the attention they deserve.
Article
Using Online Experiments to Study Political Decision Making
Yotam Shmargad and Samara Klar
The field of political science is experiencing a new proliferation of experimental work, thanks to a growth in online experiments. Administering traditional experimental methods over the Internet allows for larger and more accessible samples, quick response times, and new methods for treating subjects and measuring outcomes. As we show in this chapter, a rapidly growing proportion of published experiments in political science take advantage of an array of sophisticated online tools. Indeed, during a relatively short period of time, political scientists have already made huge gains in the sophistication of what can be done with just a simple online survey experiment, particularly in realms of inquiry that have traditionally been logistically difficult to study. One such area is the important topic of social interaction. Whereas experimentalists once relied on resource- and labor-intensive face-to-face designs for manipulating social settings, creative online efforts and accessible platforms are making it increasingly easy for political scientists to study the influence of social settings and social interactions on political decision-making. In this chapter, we review the onset of online tools for carrying out experiments and we turn our focus toward cost-effective and user-friendly strategies that online experiments offer to scholars who wish to not only understand political decision-making in isolated settings but also in the company of others. We review existing work and provide guidance on how scholars with even limited resources and technical skills can exploit online settings to better understand how social factors change the way individuals think about politicians, politics, and policies.
Article
Social Network Influence on Political Behavior in Religious Contexts
Christina Ladam, Ian Shapiro, and Anand Sokhey
As the most common form of voluntary association in America, houses of worship remain an unquestionably critical component of American civil society. Major approaches to studying religion and politics in the United States are described, and the authors present an argument for focusing more attention on the organizational experience provided by religious contexts: studying how individuals’ social networks intersect with their associational involvements (i.e., studying religion from a “interpersonal” perspective) may actually shed new light on intrapersonal, psychological constructs like identity and religiosity.
Evidence is presented from two nationally representative data sets that suggests considerable variance in the degree to which individuals’ core social networks overlap with their houses of worship. This variance exists within and between individuals identifying with major religious traditions, and such networks are not characterized solely by agreement (as theories of self-selection might suggest).
