MINIMAX REGRET TREATMENT CHOICE WITH INCOMPLETE DATA AND MANY TREATMENTS

• Published in: Econometric theory Vol. 23; no. 1; pp. 190 - 199
• Main Author: Stoye, Jörg
• Format: Journal Article
• Language: English
• Published: New York, USA Cambridge University Press 01.02.2007
• Subjects: Ambiguity; Econometric models; Econometrics; Economic models; Equilibrium; Expected utility; Expected values; Games; Mathematical methods; Maximin; Minimax; Missing data; Nash equilibrium; NOTES AND PROBLEMS; Operations research; Probability; Regret; Saliency; Studies
• ISSN: 0266-4666; 1469-4360
• DOI: 10.1017/S0266466607070089

This note adds to the recent research project on treatment choice under ambiguity. I generalize the Manski (Journal of Econometrics, in press) analysis of minimax regret treatment choice by considering a more general setting and, more importantly, by solving for the treatment rule given finitely many (as opposed to two) treatments. The most interesting finding is that with three or more undominated treatments, the minimax regret treatment rule may assign the same treatment to all subjects; thus, the most salient feature of the two-treatment case does not generalize.I thank Chuck Manski, the co-editor, and especially an anonymous referee for helpful comments. Financial support through the Robert Eisner Memorial Fellowship, Department of Economics, Northwestern University, in addition to a Dissertation Year Fellowship, The Graduate School, Northwestern University, is gratefully acknowledged.