Abstract
We present an algorithm to approximate the solutions to variational problems where set of admissible functions consists of convex functions. The main motivation behind the numerical method is to compute solutions to Adverse Selection problems within a Principal-Agent framework. Problems such as product lines design, optimal taxation, structured derivatives design, etc. can be studied through the scope of these models. We develop a method to estimate their optimal pricing schedules.
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We thank Guillaume Carlier and Yves Lucet for their thoughtful comments and suggestions. We would also like to acknowledge two anonymous referees and the editor, whose thorough reading and suggestions led to an improved version of our original manuscript.
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Ekeland, I., Moreno-Bromberg, S. An algorithm for computing solutions of variational problems with global convexity constraints. Numer. Math. 115, 45–69 (2010). https://doi.org/10.1007/s00211-009-0270-2
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DOI: https://doi.org/10.1007/s00211-009-0270-2