Peter G. Moffatt is Professor of Econometrics at the University of East Anglia, UK.

'This is an invaluable text produced by an expert in the field. It provides guidance and reference for the increasingly large number of experimental economists who want to do some serious econometric analysis of their experimental data. It is breath-taking in its coverage and its precision, yet at the same time it is eminently readable. One can only admire the author for the clarity of the exposition of material which is inherently complicated. Not only does it explain the concepts cleanly and precisely, it also provides numerous examples of applications. It will become compulsory reading for all experimental economists.' John Hey, University of York, UK 'Every experimentalist should read this book, to understand when she generates challenging data, and to find out how to parry the challenge if it cannot be preempted by design.' Christoph Engel, Max Planck Institute, Germany "A long-awaited, systematic treatise of the econometric modelling of experimental data brilliantly accomplished. A work of art!" Anna Conte, University of Westminster, UK 'Rarely do we find a book on econometrics as absorbingly readable as this one. Each chapter begins with a clear explanation of the relevant economic model, introduces data from illustrative experiments from the literature, then walks the reader through the choice of econometric techniques best suited to analysing the data. He begins with the simplest methods, raising the sophistication as more and more features of the dataset are taken into consideration. Crucially, he includes annotated printouts of his many STATA programs so the reader may modify them for their own experiments. In short, I believe Experimetrics should become an indispensable part of every experimentalist's toolkit.' David Butler, Murdoch University, Australia 'Experimetrics is a very well-written book, providing an outstanding in-depth analysis of the econometric methodology into economics experiments. It is structured in a balanced way covering the most topical issues in the experimental literature. Superb writing style and coverage!' Michalis Drouvelis, University of Birmingham, UK 'Experimetrics provides an excellent overview of the issues concerning the econometric analysis of experimental data. Numerous STATA codes enrich the book and make the methods very accessible.' Charles Bellemare, Universite Laval, Canada

• 1. Introduction and Overview2. Statistical Aspects of Experimental Design in Experimental Econometrics3. Treatment Testing4. Theory Testing, Regression and Dependence5. Modelling of Decision Times using Regression Analysis6. Dealing with Discreteness in Experimental Data7. Ordinal Data in Experimetrics8. Dealing with Heterogeneity: Finite Mixture Models9. Simulating Experimental Data, and the Monte-Carlo Method10. Introduction to the Method of Maximum Simulated Likelihood11. Dealing with Zeros: Hurdle Models12. Choice under Risk: Theoretical Issues13. Choice under Risk: Econometric Modelling14. Optimal Design in Binary Choice Experiments15. Social Preference Models16. Repeated Games and Quantal Response Models17. Depth of Reasoning Models18. Learning Models19. Summary and ConclusionAppendix A: List of Data Files and Other FilesAppendix B: List of STATA CommandsAppendix C: Choice Problems used in Chapters 5 and 13References.

Peter G. Moffatt is Professor of Econometrics at the University of East Anglia, UK.

'This is an invaluable text produced by an expert in the field. It provides guidance and reference for the increasingly large number of experimental economists who want to do some serious econometric analysis of their experimental data. It is breath-taking in its coverage and its precision, yet at the same time it is eminently readable. One can only admire the author for the clarity of the exposition of material which is inherently complicated. Not only does it explain the concepts cleanly and precisely, it also provides numerous examples of applications. It will become compulsory reading for all experimental economists.' John Hey, University of York, UK 'Every experimentalist should read this book, to understand when she generates challenging data, and to find out how to parry the challenge if it cannot be preempted by design.' Christoph Engel, Max Planck Institute, Germany "A long-awaited, systematic treatise of the econometric modelling of experimental data brilliantly accomplished. A work of art!" Anna Conte, University of Westminster, UK 'Rarely do we find a book on econometrics as absorbingly readable as this one. Each chapter begins with a clear explanation of the relevant economic model, introduces data from illustrative experiments from the literature, then walks the reader through the choice of econometric techniques best suited to analysing the data. He begins with the simplest methods, raising the sophistication as more and more features of the dataset are taken into consideration. Crucially, he includes annotated printouts of his many STATA programs so the reader may modify them for their own experiments. In short, I believe Experimetrics should become an indispensable part of every experimentalist's toolkit.' David Butler, Murdoch University, Australia 'Experimetrics is a very well-written book, providing an outstanding in-depth analysis of the econometric methodology into economics experiments. It is structured in a balanced way covering the most topical issues in the experimental literature. Superb writing style and coverage!' Michalis Drouvelis, University of Birmingham, UK 'Experimetrics provides an excellent overview of the issues concerning the econometric analysis of experimental data. Numerous STATA codes enrich the book and make the methods very accessible.' Charles Bellemare, Universite Laval, Canada

• 1. Introduction and Overview2. Statistical Aspects of Experimental Design in Experimental Econometrics3. Treatment Testing4. Theory Testing, Regression and Dependence5. Modelling of Decision Times using Regression Analysis6. Dealing with Discreteness in Experimental Data7. Ordinal Data in Experimetrics8. Dealing with Heterogeneity: Finite Mixture Models9. Simulating Experimental Data, and the Monte-Carlo Method10. Introduction to the Method of Maximum Simulated Likelihood11. Dealing with Zeros: Hurdle Models12. Choice under Risk: Theoretical Issues13. Choice under Risk: Econometric Modelling14. Optimal Design in Binary Choice Experiments15. Social Preference Models16. Repeated Games and Quantal Response Models17. Depth of Reasoning Models18. Learning Models19. Summary and ConclusionAppendix A: List of Data Files and Other FilesAppendix B: List of STATA CommandsAppendix C: Choice Problems used in Chapters 5 and 13References.