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This chapter describes research methods for investigating social learning in the laboratory. In recent decades laboratory experiments have been conducted to explore the population-level aspects of social transmission; an example is the investigation of aspects of tradition, diffusion, and innovation. This chapter discusses traditional social learning experimental designs, studies of linear transmission chains and replacement transmission chains, and controlled diffusion studies. It also considers some recent neuroscientific analyses of social learning, which extend the study of social learning beyond the behavioral level. In particular, it examines innovation, the biological bases of social learning, neuroendocrinological studies, social learning of fear, and neural mechanisms of observational learning.

This chapter discusses the admissibility of eyewitness expert testimony under Daubert standards. It explores the scientific reliability of the laboratory experiments underlying eyewitness expert opinions, and their applicability to assessing real world witnesses. It examines common eyewitness expert opinions, and demonstrate that these opinions often are neither scientifically reliable nor generally accepted. The chapter then discusses the relevance of eyewitness expert testimony to jury assessment of real witnesses, and whether such testimony is beyond the ken of the jury. It discusses jurors' understanding of the fallibility of eyewitness identification in this post-DNA world. Relying upon a recent survey, the chapter demonstrates potential jurors' general understanding of the issues which may affect eyewitness testimony, and discusses how the trial process can refine that understanding. Finally, it discusses how eyewitness expert testimony may actually confuse, rather than assist, jurors.

This chapter discusses an “attribute” of the experimenter which, like those considered just before, is also defined in terms of the particular experiment being conducted. That attribute is the performance of the experimenter himself of the same task he sets his subjects. For some experiments, this experimenter attribute will be a more enduring characteristic, such as intelligence or authoritarianism. For other experiments, this attribute will be a less enduring one, such as an opinion on a timely public issue, though such less enduring attributes may often be related to more enduring ones. When there is a significant relationship between the experimenter's own performance of the particular task he requires of his subjects and the performance he obtains from his subjects, we may speak of an experimenter's “modeling” effect. The evidence for this effect comes from the literature of survey research, clinical psychology, and laboratory experiments.

Chapter 2 showed that when the exact question being asked is mirrored in a laboratory experiment and the population being studied is the same as in the field, the outcomes from the experiment can be just as clear and informative. This result suggests that when either the exact question being asked is not mirrored or the population being studied differs, the outcomes from the experiment probably do not parallel those observed in the field. This chapter uses this insight to draw four lessons for experimental design using the games, methods, and results from the previous chapters. Among these lessons are that Major League Soccer players would not be an appropriate pool of subjects to conduct the type of study implemented in Chapter 2, and that a zero-sum situation played among friends does not represent the way subjects interact in the field.

The global community faces several very pressing environmental challenges such as climate change, depletion of the high-sea fisheries, and unprecedented rates of biodiversity loss. Governments are in the process of designing environmental policies to address these problems unilaterally, but also collectively (in the form of international agreements). Meanwhile, private citizens and firms are observed to voluntarily take protective action. Whereas standard game theory would predict that formal government intervention can only provide an extra stimulus for protective action, there are many examples of external interventions decreasing agents' propensity to undertake socially desired activities. This chapter provides an overview of the literature on the circumstances under which formal interventions can crowd out voluntary contributions to the common good. Furthermore, it is discussed how the effectiveness of government intervention may be improved by preserving the agents' intrinsic motivation to contribute to the common good.

This chapter presents evidence showing that mandate disclosure consistently fails to accomplish its stated goals. It begins by asking what standard we should use to assess mandated disclosure and goes on to apply the standard that lawmakers and disclosurites set for it. The chapter then reviews empirical studies of disclosure's success as well as results from laboratory experiments that attempt to make disclosure work with research subjects. It also considers signs of deteriorating faith in disclosure among some sophisticated lawmakers and commentators. The chapter shows that some lawmakers have doubts about mandates so they reform them so often and so much, while regulators are expressly critical. Based on the evidence, it shows that mandated disclosure is a regulatory device thats ambitions outweigh its abilities.

This introduction to part iii addresses a persistent confusion in discussions of experimental practice that is predicated on there being something that is a "direct" experimental system, and while this is rarely explicit in discussions, its importance is revealed by the contrast class of "indirect" experiments. The introduction lays out the plan of the part to undermine the notion of direct experiment and to establish that all experiment is indirect. When that is done the conceptual distance between natural experiment, analogical experiment, thought experiment, simulation experiment, and standard laboratory experiments will be closed and they will all be seen to be of a single type, experiment.

Laboratory experiments, thought experiments, and literary fictions are felicitous falsehoods. They distance themselves from the facts they bear on to screen out irrelevant, potentially confounding factors. This enables them to exemplify, and provide epistemic access to features that would otherwise be obscured.

This chapter comments on two articles, by Kagel and by Harrison, Lau, and Rutstrom. These articles emphasize “control” as one of the most important aspects of experimental economics. By contrast, the chapter suggests that “control” is not always an unambiguously good thing. There are three reasons why control might be undesirable. First, many economic decisions take more time to reach than the typical time limits in a laboratory session. Second, despite careful laboratory protocols to prevent communication, people often do talk to others when making real-world decisions. Third, we do not know whether economic theory is correct in its primitive assumptions, such as modeling charities as public goods or (b) bidder values to be privately known in auctions. If it turns out that such features matter for economic decision-making, we will only know the truth by going outside the traditional laboratory setting.

This chapter comments on the papers of Levitt and List and of Camerer. It explains why for most laboratory studies it is only relevant whether the qualitative or directional results of the study are externally valid. It argues that laboratory studies are conducted to identify general principles of behavior and therefore promise to generalize. It then examines whether laboratory experiments live up to this promise. It discusses the extent to which qualitative results persist outside of the lab and how we should respond when they do not. The chapter concludes by arguing that the lab and field methodologies are highly complementary and that both provide important insights to the understanding of economics.

This chapter discusses the ways in which laboratory experiments and field experiments can be complementary in understanding the field setting of interest. It uses two examples: the winner’s curse in common-value auctions and gift exchange in experimental labor markets. It highlights three points. First, learning, which is endemic to most experimental studies, tends to be context specific and difficult to generalize from one environment to another. Second, although hopefully we can all agree on the “facts”of a particular economic experiment, there is typically wide room for disagreement on the interpretation of those facts as they apply to the broader issues at hand. Third, even in cases where the laboratory setting seems rather removed and abstract relative to the field setting one has in mind, the experimental results may be quite relevant to that field setting.

This chapter reviews some of the theoretical approaches to the study of altruism in an attempt to clarify some basic concepts, focusing on the models and statistical tools that have appeared in the levels of selection literature and attempting to make connections between different theoretical approaches in the process. It also describes laboratory and field experiments that have addressed the evolution of different forms of altruism, some directly and some indirectly. The chapter ends by discussing some philosophical issues in the debate over the levels of selection, and the general impact of theoretical and empirical results for this debate.

This chapter proposes a systematic approach to research where theory, lab results, common sense, field data, and econometrics are all integrated into one’s research toolkit. The approach is illustrated by considering work done on an artifactual field experiment in Denmark. The chapter is organized into four sections. The section entitled “Policy Lotteries” introduces the concept of policy lotteries, giving a few examples. The section entitled “Risk Aversion” discusses how to draw inferences about risk attitudes using the systematic approach that includes conditioning these inferences on smaller-scale lab experiments, on sample selection effects and elicitation methods, on econometric and statistical strategies such as sampling frame and structural estimation approaches, and on theoretical and common sense considerations about out-of-domain predictions. The section entitled “Discount Rates” discusses inferences about discount rates and demonstrate the power of joint estimation of risk and time preferences as motivated by theory. The section entitled “Lessons Learned” expands the joint inference discussion to longitudinal issues such as temporal stability.

Amphibians and reptiles are coming to be regarded in Europe as indicator groups for a general decline in species diversity. The decline of these groups has been well documented in Europe and on other continents as a result of numerous population surveys. A scientifically based analysis of causal relations is essential to effective conservation efforts since it leads to the prediction of appropriate countermeasures. The most important type of database for the documentation of the declines of amphibians and reptiles and their potential causes results from regular surveys of a specific geographic area. This chapter describes the available methods of causal analysis, as well as their limitations, by applying the methods in the analysis of a long-term surveying project for amphibian population declines. It also presents remarks on the optimization of surveying projects that will facilitate subsequent causal analyses. In addition, it discusses the advantages and disadvantages of three experimental approaches for evaluating causal relations in ecology: laboratory experiments, field experiments, and unplanned or natural experiments.

This chapter considers the current debate about the value of field experiments compared to the value of laboratory experiments. It suggests that what is needed in approaching experimental economics is a wide variety of approaches and that the best tool depends on the question being asked, but no one tool is right for all environments. The lab is better for theory testing and to identify treatment effects whereas the field captures more realistic behavior. In either case, one needs a theory to transport findings to new populations or environments.

This chapter addresses the Levitt and List criticism that lab experimental findings may not generalize to field settings. It has three main points. First, special concern about generalizability of lab results might result from an aversion to the stylized perspective on what economics experiments are meant to do, which most experimentalists hold (called the scientific view). Second, even in the scientific perspective it is certainly true that some economics experiments have features that make them less likely to generalize to some naturally occurring settings. Third, it reviews economics experiments which are specifically designed to generalize from the lab to the field. Generalization between lab and field is generally rather good.

This chapter establishes what is known about the impact of subjects typically used in experimental economics by reviewing prior studies that have used both the standard subject pool and an unusual pool of professionals. The papers are loosely organized in four thematic sections: other-regarding preferences, market experiments, information signals, and a miscellaneous group. The results overall suggest that, although there are situations where focusing on students is too narrow, in general the conclusions reached by using the standard experimental subject pool generalize to professionals. Nonetheless, studying professionals can prove insightful in ways that studying undergraduates is not.

This chapter begins by presenting a brief set-up of the question addressed by the book—what is the role of altruism in human life? —and looking at the importance of laboratory experiments in providing an answer. The book will present a theory of altruistic motivation, review evidence obtained from direct tests of the central tenet of the theory, the empathy-altruism hypothesis, and consider implications of the theory at both a conceptual and a practical level. Not only will the book make a case that altruism exists; it will also present evidence that altruism is an important force in human affairs. Altruism is not an easy topic; there are many conceptual subtleties, inferential complexities, and empirical challenges that cannot be usefully addressed by oversimplification. But neither can they be usefully addressed by obfuscation. Throughout, an effort will be made to be clear and direct, while not shying away from subtleties, complexities, and challenges.

Originated from the Athenian practice, ostracism or the temporary exclusion by consensus and the act of ignoring is analyzed by Kip William and Lisa Zadro. Laboratory manipulations and real-life observations are the main data-gathering procedures of the study. Apart from the emphasis that ostracism may occur across all ages, the experimental efforts particularly set the foundations of numerous frameworks for the field. Even if there has been small amount of psychological literature about the phenomenon, enough studies have illustrated its short- and long-term consequences. Conformity and increased motivation for better performance comprise the short-term effects, while for long-term results, internalization of low levels of self-esteem and control, as well as suicide attempts, are evident. New models are devised in the attempt to capture the complexities of ostracism, which were not noted by early researches. These frameworks come with various data-gathering methods such as structured interviews, narratives, and contingency plans.

This chapter outlines the state of research. First, basic biological cooperation mechanisms are examined for their relevance for success in the management of natural resources. In a second step, findings from economic behavioral experiments (public goods games) are summarized in order to identify cooperation-enhancing factors in social dilemmas. Finally, the common-pool resource dilemma will be characterized more precisely. After these broader discussions, social-ecological systems and potential success factors for sustainable management are characterized more precisely by a literature review.