This article uses panel data estimation techniques to examine technical efficiency of individual dairy farms in northern Germany. To the extent that agricultural production is characterised by heterogeneous production conditions, estimation techniques that do not account for unobserved...

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 field of production frontier estimation is divided between the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper explores an amalgam of DEA and SFA that melds a nonparametric frontier with a stochastic composite...

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...

In this study, we provide a guideline for dealing with endogenous inputs and environmental variables in Battese and Coelli's (1995) stochastic frontier model. Our Monte Carlo simulations show that our estimators perform well

This study provides a guideline for dealing with endogenous inputs and environmental variables in Battese and Coelli's (1995) stochastic frontier model, which has been used in a vast number of empirical studies. The presence of endogenous variables in Battese and Coelli's model leads to...

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...

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...

Results of assessments of total labor factor productivity TFP showed improvements where it recorded higher rate of 73.5% compared to previous periods. However, that was related with constant rate of returns as compared with variable rate of return. When technical efficiency was compared with...