Distance functions and the analysis of inefficiency

Efficiency is a crucial factor in productivity growth and the optimal allocation of resources in the economy; therefore, measuring inefficiency is particularly important. This paper provides a comprehensive review of the latest developments in distance functions and the measurement of inefficiency within the stochastic frontier framework. Recent advances in several related areas are reviewed and evaluated, including various approaches to measuring inefficiency using distance functions, advancements in modeling inefficiency within the stochastic frontier framework, and the most common estimation techniques. A practical guide is provided on when these methods can be applied and how to implement them. The radial, hyperbolic, and directional measures of inefficiency are discussed and assessed. The development of modeling inefficiency concerning its temporal behavior, classification, and determinants is also examined. To ensure the use of appropriate estimation techniques, recent advancements in the most common estimation techniques are reviewed. This paper also addresses the importance of maintaining the theoretical regularity applied by neoclassical microeconomic theory when it is violated, as well as the econometric regularity when variables are non-stationary. Without regularity, inefficiency results can be extremely misleading. The paper discusses significant challenges related to estimation issues that must be managed in future applications. These challenges include the inaccurate choice of functional form, ignoring the possibility of heterogeneity and heteroskedasticity, and suffering from the endogeneity problem. The paper also examines various approaches to addressing these issues, as well as potentially productive areas for future research.