Assignment at the Frontier: Identifying the Frontier Structural Function and Bounding Mean Deviations

Dan Ben-Moshe and David Genesove

Papers from arXiv.org

Abstract: This paper analyzes a model in which an outcome equals a frontier function of inputs minus a nonnegative unobserved deviation. Inputs may be endogenous (statistically dependent on the deviation). 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 consider estimation of the frontier in the presence of random error that is mean-independent of inputs but may be heteroskedastic. Finally, we derive a lower bound on the mean deviation, using only variance and skewness, that is robust to a scarcity of data near the frontier. We apply our methods to estimate a firm-level frontier production function and mean inefficiency.

Date: 2025-04, Revised 2025-10
New Economics Papers: this item is included in nep-ecm and nep-eff
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2504.19832

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