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...

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...

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...

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...

Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimating a) the conditional mean of inefficiency...

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...

This paper develops a non-linear stochastic frontier (SF) model. The main advantage of this model over standard SF models is that the model does not need an assumption for the distributional form of the inefficiency component. Another advantage of the developed model is that it can be used to...

Stochastic frontier models all need an assumption on the distributional form of the efficiency component. Generally this efficiency component is assumed to be half normally, truncated normally, or exponentially distributed. This paper shows that the exponential distribution is, just like 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...