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This exciting textbook introduces the basic tenets and methodologies of empirical legal research. Explaining how to initiate and conduct empirical research projects, how to evaluate the methods used and how to analyze and engage with the results, Kees van den Bos provides a vibrant and reliable primer for students and practitioners looking to engage actively in legal research. Key features include:· A straightforward, non-technical and accessible style to engage new researchers in empirical legal research· A step-by-step guide to empirical research, leading students through establishing and building a research project, to interpreting and reporting on empirical data· An exploration of an array of methodologies to gather empirical data, including interviews, surveys and experiments, providing plenty of avenues for research· Exercises to allow students to put new skills into practice and suggested further reading to deepen students' understanding of new topics. Offering an enthusiastic introduction to a valuable subject, this is crucial reading for advanced law students hoping to pursue their own empirical legal research projects. Its insights into cutting-edge research methodologies will also be of benefit to students with a keen interest in the sociology of law, as well as socio-legal studies more widely.

An Introduction to Empirical Legal Research introduces empirical methodology in a legal context, explaining how empirical analysis can inform legal arguments; how lawyers can set about framing empirical questions, conducting empirical research, analysing data, and presenting or evaluating the results.

I briefly review the emergence of " design-based" research methods in labor economics in the 1980s and early 1990s. These methods were seen as a partial solution to the problems of credible inference identified by Ashenfelter (1974), Leamer (1978), Hendry (1980), and others. Designed-based studies typically use a simplified one-equation model of the outcome of interest—in contrast to model-based studies that specify a data generating process for all factors determining the outcome. I discuss some of the strengths and weaknesses of the design-based approach and the value of such research in the field. (JEL C20, J01, J24, J31, J38, J51, J53)

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research.