Experimetrics
eBook - PDF

Experimetrics

Econometrics for Experimental Economics

  1. 496 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Experimetrics

Econometrics for Experimental Economics

About this book

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

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Yes, you can access Experimetrics by Peter Moffatt in PDF and/or ePUB format, as well as other popular books in Business & Organisational Behaviour. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Red Globe Press
Year
2020
Print ISBN
9780230250239
eBook ISBN
9781137456595
Edition
1
Topic
Business
Subtopic
Organisational Behaviour
Index
Business

Table of contents

  1. Cover
  2. Contents
  3. Acknowledgements
  4. 1 Introduction and Overview
  5. 2 Statistical Aspects of Experimental Design in Experimental Economics
  6. 3 Treatment Testing
  7. 4 Theory Testing, Regression, and Dependence
  8. 5 Modelling of Decision Times Using Regression Analysis
  9. 6 Dealing with Discreteness in Experimental Data
  10. 7 Ordinal Data in Experimetrics
  11. 8 Dealing with Heterogeneity: Finite Mixture Models
  12. 9 Simulating Experimental Data, and the Monte Carlo Method
  13. 10 Introduction to the Method of Maximum Simulated Likelihood (MSL)
  14. 11 Dealing with Zeros: Hurdle Models
  15. 12 Choice under Risk: Theoretical Issues
  16. 13 Choice under Risk: Econometric Modelling
  17. 14 Optimal Design in Binary Choice Experiments
  18. 15 Social Preference Models
  19. 16 Repeated Games and Quantal Response Models
  20. 17 Depth of Reasoning Models
  21. 18 Learning Models
  22. 19 Summary and Conclusion
  23. A List of Data Files and Other Files
  24. B List of STATA Commands
  25. C Choice Problems Used in Chapters 5 and 13
  26. References
  27. Index