Inferring strategies from observed actions: a nonparametric, binary tree classification approach
✍ Scribed by Jim Engle-Warnick
- Book ID
- 104293349
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 283 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0165-1889
No coin nor oath required. For personal study only.
✦ Synopsis
This paper introduces a non-parametric binary classiÿcation tree approach to inferring unobserved strategies from the observed actions of economic agents. The strategies are in the form of possibly nested if-then statements. We apply our approach to experimental data from the repeated ultimatum game, which was conducted in four di erent countries by Roth et al. (Am. Econ. Rev. 81 (1991) 1068). We ÿnd that strategy inference is consistent with existing inference, provides new explanations for subject behavior, and provides new empirically based hypotheses regarding ultimatum game strategies. We conclude that strategy inference is potentially useful as a complementary method of statistical inference in applied research.