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Estimation and Inference in the Presence of Neighborhood Unobservables

Neglecting neighborhood unobservables or shocks may hinder the identification of causal effects. However, if unobservables are smooth over space and units are paired based on proximity, a neighborhood data transformation can effectively eliminate …

Imposing monotonicity in stochastic frontier models: an iterative nonlinear least squares procedure

Despite its importance, the monotonicity condition is typically overlooked in stochastic frontier analysis. This article illustrates a straightforward and useful method for the estimation of semiparametric stochastic frontier models imposing such …