Increasingly, political scientists use the term 'experiment' or 'experimental' to describe their empirical research. One of the primary reasons for doing so is the advantage of experiments in establishing causal inferences. In this book, Rebecca B. Morton and Kenneth C. Williams discuss in detail how experiments and experimental reasoning with observational data can help researchers determine causality. They explore how control and random assignment mechanisms work, examining both the Rubin causal model and the formal theory approaches to causality. They also cover general topics in experimentation such as the history of experimentation in political science; internal and external validity of experimental research; types of experiments - field, laboratory, virtual, and survey - and how to choose, recruit, and motivate subjects in experiments. They investigate ethical issues in experimentation, the process of securing approval from institutional review boards for human subject research, and the use of deception in experimentation.

This volume provides a methodological toolbox for conducting policy research. Recognizing that policy research spans various academic disciplines, each of which takes a different view on causality, the volume introduces a methodologically pluralistic approach to policy studies. Each chapter clarifies the research question that each technique can answer, the research design and data treatment that each technique requires for its results to be sound, the validity domain of its results, and the actual deployment of the technique through a replicable example. Techniques covered include quasi-experimental designs, approaches to account for selection bias and observed imbalances, directed acyclic graphs and structural equation models, Qualitative Comparative Analysis, Bayesian case study and process tracing, and Agent-Based Modelling. By working through the volume, readers will understand how to learn from different techniques, apply them consciously, and triangulate them to make better sense of findings. This volume is intended for advanced academic courses, as well as scholars and practitioners in policy-related fields, such as political science, economics, sociology, and public administration. This is an open access book.

This textbook introduces the scientific study of politics, supplying students with the basic tools to be critical consumers and producers of scholarly research.

World political processes, such as wars and globalisation, are engendered by complex sets of causes and conditions. Although the idea of causation is fundamental to the field of International Relations, what the concept of cause means or entails has remained an unresolved and contested matter. In recent decades ferocious debates have surrounded the idea of causal analysis, some scholars even questioning the legitimacy of applying the notion of cause in the study of International Relations. This book suggests that underlying the debates on causation in the field of International Relations is a set of problematic assumptions (deterministic, mechanistic and empiricist) and that we should reclaim causal analysis from the dominant discourse of causation. Milja Kurki argues that reinterpreting the meaning, aims and methods of social scientific causal analysis opens up multi-causal and methodologically pluralist avenues for future International Relations scholarship.

Approximately one in six top economic research papers draws an explicitly causal conclusion. But what do economists mean when they conclude that A ‘causes’ B? Does ‘cause’ say that we can influence B by intervening on A, or is it only a label for the correlation of variables? Do quantitative analyses of observational data followed by such causal inferences constitute sufficient grounds for guiding economic policymaking? The Philosophy of Causality in Economics addresses these questions by analyzing the meaning of causal claims made by economists and the philosophical presuppositions underlying the research methods used. The book considers five key causal approaches: the regularity approach, probabilistic theories, counterfactual theories, mechanisms, and interventions and manipulability. Each chapter opens with a summary of literature on the relevant approach and discusses its reception among economists. The text details case studies, and goes on to examine papers which have adopted the approach in order to highlight the methods of causal inference used in contemporary economics. It analyzes the meaning of the causal claim put forward, and finally reconstructs the philosophical presuppositions accepted implicitly by economists. The strengths and limitations of each method of causal inference are also considered in the context of using the results as evidence for policymaking. This book is essential reading to those interested in literature on the philosophy of economics, as well as the philosophy of causality and economic methodology in general.

An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the basis of arguments—economic and otherwise—since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It’s rare that a book prompts readers to expand their outlook; this one did for me.”—Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied—for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.

There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.

Causality in a Social World introduces innovative new statistical research and strategies for investigating moderated intervention effects, mediated intervention effects, and spill-over effects using experimental or quasi-experimental data. The book uses potential outcomes to define causal effects, explains and evaluates identification assumptions using application examples, and compares innovative statistical strategies with conventional analysis methods. Whilst highlighting the crucial role of good research design and the evaluation of assumptions required for identifying causal effects in the context of each application, the author demonstrates that improved statistical procedures will greatly enhance the empirical study of causal relationship theory. Applications focus on interventions designed to improve outcomes for participants who are embedded in social settings, including families, classrooms, schools, neighbourhoods, and workplaces.

A seminal text in European studies, which addresses issues of research design and causal analysis. The chapters draw on different methodological traditions, notions of causality, and methods and use strong research design to address substantive problems in public policy, party politics, foreign policy and legislative studies.

Volume One of the Classics of Comparative Policy Analysis, "Theory and Methods in Comparative Policy Analysis Studies" includes chapters that apply or further theory and methodology in the comparative study of public policy, in general, and policy analysis, in particular. Throughout the volume the chapters engage in theory building by assessing the relevance of theoretical approaches drawn from the social sciences, as well as some which are distinctive to policy analysis. Other chapters focus on various comparative approaches based on developments and challenges in the methodology of policy analysis. Together, this collection provides a comprehensive scholastic foundation to comparative policy analysis and comparative policy studies. "Theory and Methods in Comparative Policy Analysis Studies" will be of great interest to scholars and learners of public policy and social sciences, as well as to practitioners considering what can be learned or facilitated through methodologically and theoretically sound approaches. The chapters were originally published as articles in the Journal of Comparative Policy Analysis which in the last two decades has pioneered the development of comparative public policy. The volume is part of a four-volume series, the Classics of Comparative Policy Analysis including Theories and Methods, Institutions and Governance, Regional Comparisons, and Policy Sectors. Each volume showcases a different new chapter comparing domains of study interrelated with comparative public policy: political science, public administration, governance and policy design, authored by the JCPA co-editors Giliberto Capano, Iris Geva-May, Michael Howlett, Leslie A. Pal and B. Guy Peters.