Assignment at the Frontier: Identifying the Frontier Structural Function and Bounding Mean Deviations
This paper analyzes a model in which an outcome equals a frontier function of inputs minus a nonnegative unobserved deviation. We allow the deviation’s distribution to depend on inputs, thereby not ruling out endogeneity. If zero lies in the support of the deviation given inputs—an assumption we term assignment at the frontier—then the frontier is identified by the supremum of the outcome at those inputs, obviating the need for instrumental variables. We then introduce random error, whose distribution may also depend on inputs. In addition to providing estimators for the frontier and mean deviation, we derive a robust lower bound for the mean deviation based only on variance and skewness. This bound remains valid even when data are sparse near the frontier. We apply our methods to estimate a firm-level frontier production function and inefficiency.
Date: 17 October 2025, 14:15
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar Room C
Speaker: Dan Ben-Moshe (University of the Negev)
Organising department: Department of Economics
Part of: Nuffield Econometrics Seminar
Booking required?: Not required
Audience: Members of the University only
Editor: Edward Valenzano