Experimetrics: Econometrics for Experimental Economics

Description

This advanced textbook is an essential guide to discovering new and more illuminating ways to analyse the econometric modelling of experimental 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. Contents Acknowledgements 1 Introduction and Overview 2 Statistical Aspects of Experimental Design in Experimental Economics 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 (MSL) 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