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...

Paper applies stochastic frontier production (SFP) function to measure efficiency of textile firms in India. In SFP models with panel data (balanced or unbalanced) unobservable firm efficiency levels are related to explanatory variables. The SFP were first proposed by Aigner, Lovell and Schmidt...

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model...

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...

The purpose of this paper is two-fold. First, it compares the performance of various panel data models in estimating technical efficiency in production. Second, it applies various stochastic frontier panel data models to estimate the technical efficiency of Iran's cotton production and to...

Objective: This study proposes a novel empirical analysis of the total factor productivity (TFP) growth for Polish microenterprises, focusing on the effect of the global lockdown in 2020. We employed firm-level data covering enterprises with below ten employees to evaluate micro-firms'...

The system GMM estimator developed by Blundell and Bond (1998) for dynamic panel data models has been widely used in empirical work; however, it does not perform well with weak instruments. This paper proposes a variation on the system GMM estimator, based on a simple transformation of the...

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...

We consider fixed-effect estimation of a production function where inputs and outputs vary over time, space, and cross-sectional unit. Variability in the spatial dimension allows for time-varying individual effects, without parametric assumptions on the effects. Asymptotics along the spatial...

Typically, the error term in stochastic frontier models is assumed to be positively skewed; however, efficiency scores are biased if this assumption is violated. This paper considers the case in which also negative skewness is allowed in the model. In contrast to other approaches, this skewness is...