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Economics laboratories have become the primary locations of experimental economics research by the 1990s. They were a result of a decade long development from ad hoc opportune places to dedicated, purpose designed spaces. The distinctive feature of the economics laboratory and its key instrument became networked computers running custom-built software. However, the history of the economics laboratory is not just a history of evolving technology. I argue in this article that it is mainly a history of learning how to build an experimental economics community. Only a functioning community was able to change a physical place to a laboratory space. The distinction between place and space originates in the work of Michael de Certeau and I use it to analyze the evolution of economics laboratories. To this end, I analyze the case of Austin Hoggatt’s Management Science Laboratory at Berkeley in the 1960s as it illustrates the indispensability of creating a community centered on the laboratory. In contrast, the laboratories in Arizona and at Caltech since the 1980s, and in Amsterdam since the 1990s have become successful spaces, because, unlike Hoggatt, they focused equally on community building as on infrastructure and technology. This gave rise to social infrastructure and division of labor in the laboratory space.

Experimental economics has been treated with skepticism by some Austrian economists. We argue that experimental methods are consistent with strong versions of praxeology, and are therefore not methodologically problematic for Austrians. We further argue that experimental research methods have illustrated many uniquely Austrian themes and provide a fruitful method for future Austrian-inspired research.

What is behavioral economics? This chapter explores a mismatch between what is included in the field of behavioral economics and some of the most visible Austrian critiques of behavioral economics. While paternalism, nudging, and a focus on irrationalities and biases are a big part of modern behavioral economics, the portrayal of the field of behavioral economics as being focused predominately upon those areas leaves a swath of low-hanging fruit that would be beneficial for Austrian scholars to consume and use in their own work.

George Loewenstein, a prominent behavioral economist, recalls thatIn 1994, when Thaler, Camerer, Rabin, Prelec and I spent the year at the Center for Advanced Study in the Behavioral Sciences, we had a meeting to make a kind of final decision about what to call what we were doing. Remarkably, at that time, the name behavioral economics was not yet well established. I actually advocated “psychological economics,” and Thaler was strong on behavioral economics. I'm kind of glad that he prevailed; I think it's a better, catchier, label, although it creates confusion due to association with Behaviorism. (G. Loewenstein, personal email to author, June 16, 2008)

How should economists incorporate culture into their economic analysis? What empirical approaches to identifying, measuring, and analyzing the relationship between culture and economic action are most appropriate for economists? In particular, what can experimental economists learn from the methods of economic anthropologists, sociologists, and historians who study culture? We argue that while both quantitative and qualitative approaches can reveal interesting relationships between culture and economic actions/outcomes, especially in experimental research designs, qualitative methods help economists better understand people’s economic choices and the economic outcomes that emerge from those choices. This is because qualitative studies conceptualize culture as a pattern of meaning, take the relevant cultural data to be people’s thoughts and feelings, treat the market as a cultural phenomenon, and allow for novel explanations.

This chapter conducts a systematic comparison of behavioral economics’s challenges to the standard accounts of economic behaviors within three dimensions: under risk, over time, and regarding other people. A new perspective on two underlying methodological issues, i.e., inter-disciplinarity and the positive/normative distinction, is proposed by following the entanglement thesis of Hilary Putnam, Vivian Walsh, and Amartya Sen. This thesis holds that facts, values, and conventions have inter-dependent meanings in science which can be understood by scrutinizing formal and ordinary language uses. The goal is to provide a broad and self-contained picture of how behavioral economics is changing the mainstream of economics.

John and Storr (this volume) make the case that quantitative methods help establish whether culture matters, but do not tell us how culture matters. To better understand how culture matters, social scientists must use qualitative methods like interviews, in-depth case studies, and archival research. Currently, experimental economists engage qualitative methods through the coding of “chat” transcripts and informal talks with subjects while payments are arranged. Experimental economists do this because they know that it is a good idea to talk to the people they seek to understand and learn from their thought process. The goal of this chapter is to build on the insights from John and Storr about the importance of qualitative work and to provide experimental economists with some concrete ideas about qualitative methods that can improve their research.

Laboratory studies of social interaction have revealed a wide range of phenomena that are difficult to explain using standard economic models. For example, people will often sacrifice their own earnings in order to be generous, cooperative, punitive, and retributive in interactions with anonymous strangers. “Behavioral” models that redefine agents’ preferences attempt to provide an account of these phenomena as reflecting a “taste for fairness” or altruism, aversion to inequality, concern about others’ beliefs, and so on. Such models either fail to account for the rich sensitivity of actions to context or in allowing for rich context-dependence, these models ultimately substitute description for explanation. Hayek’s work provides a foundation for thinking about how to explain these phenomena, by conceiving of people as both purpose-seeking (as in economic models) and rule-following. Decisions are shaped both by material interests and by a normative framework that is evoked by context and helps people decide what one ought to do in a particular situation. The implication of this approach is that rather than trying to understand heterogeneity across individuals in terms of preferences, experimenters should instead try to understand heterogeneity across contexts in terms of the rules and norms that operate in the background and guide or constrain people’s purpose-seeking tendencies. What economics needs, then, is a theory of how and why these rules and norms vary with context as they do.