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 …
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 …