Contents -- Acknowledgements -- 1. Introduction and Overview -- 2. Statistical Aspects of Experimental Design in Experimental Econometrics -- 3. Treatment Testing -- 4. Theory Testing, Regression and Dependence -- 5. Modelling of Decision Times using Regression Analysis -- 6. Dealing with Discreteness in Experimental Data -- 7. Ordinal Data in Experimetrics -- 8. Dealing with Heterogeneity: Finite Mixture Models -- 9. Simulating Experimental Data, and the Monte-Carlo Method -- 10. Introduction to the Method of Maximum Simulated Likelihood -- 11. Dealing with Zeros: Hurdle Models -- 12. Choice under Risk: Theoretical Issues -- 13. Choice under Risk: Econometric Modelling -- 14. Optimal Design in Binary Choice Experiments -- 15. Social Preference Models --16. Repeated Games and Quantal Response Models -- 17. Depth of Reasoning Models -- 18. Learning Models -- 19. Summary and Conclusion -- A: List of Data Files and Other Files -- B: List of STATA Commands -- C: Choice Problems used in Chapters 5 and 13 -- References. -- Index.

Experimetrics is an essential guide to discovering new and more illuminating ways to analyse experimental econometric data.

Peter Moffatt, one of the world's experts in the field, covers a range of techniques: from the familiar, such as treatment testing, to lesser known ones such as finite mixture models and the method of maximum simulated likelihood. The book takes a hands-on approach by explaining STATA commands in detail. In addition, difficult problems inherent in the methodology are addressed, such as the parametric estimation of social preference models, quantal response models, and learning models.

An indispensable book for researchers and advanced students in experimental and behavioural economics who want to come to grips with the field of Experimetrics.