When benchmarking production units by non-parametric methods like data envelopment analysis (DEA), an assumption has to be made about the returns to scale of the underlying technology. Moreover, it is often also relevant to compare the frontiers across samples of producers. Until now, no exact...

This paper is concerned with significance testing of the effects of exogenous determinants upon the one-sided deviation term of a semiparametric stochastic frontier model. Two nonparametric significance tests for all or a subset of the determinants of inefficiency are proposed. The proposed...

The regression residual is commonly used as a productivity indicator. However, the observed input demands are endogenous if rational managers adjust their input use for inefficiency. A large stream of studies considers possible solutions to the endogeneity problem that require as little external...

From an empirical perspective, this paper critically examines the concepts of returns to scale (RTS) and economies of scale (EOS), and argues that the concept of EOS is more relevant and broader enough to exhibit proper scale economies behavior of firms. Two approaches, i.e., production function...

By integrating Battese and Coelli's (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a...

In this paper, we consider the stochastic ray production function that has been revived recently by Henningsen et al. (2017). We use a profit-maximizing framework to resolve endogeneity problems that are likely to arise, as in all distance functions, and we derive the system of equations after...

Output and input market distortions manifest as wedges in the firm's first order conditions. The production approach to markup estimation recovers the markup wedge using the output elasticity for a variable and undistorted input. We show that using the revenue elasticity for any variable input,...

Estimation of the one sided error component in stochastic frontier models may erroneously attribute firm characteristics to inefficiency if heterogeneity is unaccounted for. However, it is not clear in general in which component of the error distribution the covariates should be included. In the...

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a...