Experimetrics: Econometrics for Experimental Economics [Paperback]

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.

The companion website www.palgrave.com/moffatt contains:
- All data sets (in Stata format) used as examples in the book
- An executable Stata 'do-file' containing stata commands and programs used in examples

And
- An Excel file containing some Excel calculations presented in the text

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

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