This paper proposes a semiparametric smooth-coefficient (SPSC) stochastic production frontier model where regression coefficients are unknown smooth functions of environmental factors (ZZ). Technical inefficiency is specified in the form of a parametric scaling function which also depends on the ZZ variables. Thus, in our SPSC model the ZZ variables affect productivity directly via the technology parameters as well as through inefficiency. A residual-based bootstrap test of the relevance of the environmental factors in the SPSC model is suggested. An empirical application is also used to illustrate the technique
We compare three recently developed frontier estimators, namely the conditional DEA (Daraio and Sima...
This paper proposes a stochastic frontier model which includes time-invariant unobserved heterogenei...
Almost all previous approaches to estimating semiparametric frontier models, where the functional fo...
This paper proposes a semiparametric smooth-coefficient (SPSC) stochastic production frontier model ...
This paper proposes a semiparametric smooth-coefficient stochastic production frontier model where a...
Parametric production frontier function has been commonly employed in stochas-tic frontier model but...
Parametric production frontier functions are frequently used in stochastic frontier models, but the...
The stochastic frontier model was first proposed in the context of production function estimation to...
This paper considers the estimation of a spatial autoregressive stochastic frontier model, where the...
A number of studies have explored the semi- and nonparametric estimation of stochastic frontier mode...
This article considers the semiparametric stochastic frontier model with panel data that arises in t...
Parametric production frontier functions are frequently used in stochastic frontier models, but ther...
This paper considers the semiparametric stochastic frontier model with panel data which arises in th...
This study examines in an empirical comparison how different econometric specifications of stochasti...
This paper proposes a general formulation of a nonparametric frontier model introducingexternal envi...
We compare three recently developed frontier estimators, namely the conditional DEA (Daraio and Sima...
This paper proposes a stochastic frontier model which includes time-invariant unobserved heterogenei...
Almost all previous approaches to estimating semiparametric frontier models, where the functional fo...
This paper proposes a semiparametric smooth-coefficient (SPSC) stochastic production frontier model ...
This paper proposes a semiparametric smooth-coefficient stochastic production frontier model where a...
Parametric production frontier function has been commonly employed in stochas-tic frontier model but...
Parametric production frontier functions are frequently used in stochastic frontier models, but the...
The stochastic frontier model was first proposed in the context of production function estimation to...
This paper considers the estimation of a spatial autoregressive stochastic frontier model, where the...
A number of studies have explored the semi- and nonparametric estimation of stochastic frontier mode...
This article considers the semiparametric stochastic frontier model with panel data that arises in t...
Parametric production frontier functions are frequently used in stochastic frontier models, but ther...
This paper considers the semiparametric stochastic frontier model with panel data which arises in th...
This study examines in an empirical comparison how different econometric specifications of stochasti...
This paper proposes a general formulation of a nonparametric frontier model introducingexternal envi...
We compare three recently developed frontier estimators, namely the conditional DEA (Daraio and Sima...
This paper proposes a stochastic frontier model which includes time-invariant unobserved heterogenei...
Almost all previous approaches to estimating semiparametric frontier models, where the functional fo...