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Peter G. Moffatt

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Peter G. Moffatt

This chapter describes and illustrates a number of techniques used in the econometric analysis of data from economic experiments. The principal theme is experiments on choice under risk. Most, but not all, examples used are within this theme. The techniques range from the simple (treatment testing), through the intermediate techniques such as probit estimation, finding predicted probabilities and marginal effects, and interval regression, to a fairly advanced set of techniques that are applicable when repeated decisions are available from each subject (i.e., in panel data settings). Within the context of each example, the pros and cons of various methods of data analysis are discussed. Some examples are accompanied by STATA code.

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Peter G. Moffatt

The theme of this chapter is the parametric estimation of depth-of-reasoning models. The most popular depth-of-reasoning models are variants of the Level-k model and the cognitive hierarchy model. After describing these models, previous attempts at econometric estimation of them are surveyed. Then a number of estimation issues are addressed. Firstly, identification problems that arise when applying the models to certain 2-player games are discussed. This leads into a discussion of the applications to situations in which the strategy space is continuous. The most popular application is the beauty contest game. In this context, a number of other econometric issues are addressed, including dealing with censoring at the extremes of the strategy space. A number of post-estimation tools and the key assumption underlying levels of reasoning models that agents actually form specific beliefs, and best-respond are illustrated. We will consider methods for testing this assumption in a simple auction experiment.