Peter Moffatt

Experimetrics

Econometrics for Experimental Economics

• Broschiertes Buch

Produktbeschreibung

An essential guide to techniques used to analyse experimental data in economics, written by one of the world's experts in the field. Designed to show advanced economics students and researchers how to tackle difficult econometric problems inherent in the methodology such as between-subject heterogeneity, and upper and lower censoring.

---

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

Produktdetails

• Verlag: Bloomsbury Academic / Macmillan Education
• 2015 edition
• Seitenzahl: 496
• Erscheinungstermin: 4. Dezember 2015
• Englisch
• Abmessung: 235mm x 155mm x 26mm
• Gewicht: 744g
• ISBN-13: 9780230250239
• ISBN-10: 0230250238
• Artikelnr.: 43335542

Autorenporträt

Peter Moffatt

Inhaltsangabe

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 Appendix A: List of Data Files and Other Files Appendix B: List
of STATA Commands Appendix C: Choice Problems used in Chapters 5 and 13
References.