This paper proposes a stochastic frontier panel data model which includes time-invariant unobserved heterogeneity along with the efficiency effects. Following Paul and Shankar (2018), the efficiency effects are specified by a standard normal cumulative distribution function of exogenous variables which ensures the efficiency scores to lie in a unit interval. This specification eschews one-sided error term present in almost all the existing inefficiency effects models. The model parameters can be estimated by non-linear least squares after removing the individual effects by the usual within transformation or using non-linear least squares dummy variables (NLLSDV) estimator. The efficiency scores are directly calculated once the model is esti...
The traditional Stochastic Frontier Model (SFM) suffers from a very restrictive assumption of indepe...
Firms and organizations, public or private, often operate on markets characterized by non-competitiv...
This article introduces a dynamic stochastic frontier analysis (SFA) framework with unobserved heter...
This paper proposes a stochastic frontier panel data model which includes time-invariant unobserved ...
This paper proposes a stochastic frontier model which includes time-invariant unobserved heterogenei...
This paper proposes a panel data based stochastic frontier model which accommodates time-invariant u...
Traditional panel stochastic frontier models do not distinguish between unobserved individual hetero...
The accuracy of technical efficiency measures is important given the interest in such measures in po...
Received analyses based on stochastic frontier modeling with panel data have relied primarily on res...
In previous studies, measures of technical inefficiency effects derived from stochastic production f...
In previous studies, measures of technical inefficiency effects derived from stochastic production f...
This paper presents a new stochastic frontier (SF) model for panel data. The new model moves the SF ...
Stochastic frontier models with autocorrelated inefficiency have been proposed in the past as a way ...
This thesis is concerned with the specification, estimation, application and testing of stochastic f...
This paper extends the fixed effect panel stochastic frontier models to allow group heterogeneity in...
The traditional Stochastic Frontier Model (SFM) suffers from a very restrictive assumption of indepe...
Firms and organizations, public or private, often operate on markets characterized by non-competitiv...
This article introduces a dynamic stochastic frontier analysis (SFA) framework with unobserved heter...
This paper proposes a stochastic frontier panel data model which includes time-invariant unobserved ...
This paper proposes a stochastic frontier model which includes time-invariant unobserved heterogenei...
This paper proposes a panel data based stochastic frontier model which accommodates time-invariant u...
Traditional panel stochastic frontier models do not distinguish between unobserved individual hetero...
The accuracy of technical efficiency measures is important given the interest in such measures in po...
Received analyses based on stochastic frontier modeling with panel data have relied primarily on res...
In previous studies, measures of technical inefficiency effects derived from stochastic production f...
In previous studies, measures of technical inefficiency effects derived from stochastic production f...
This paper presents a new stochastic frontier (SF) model for panel data. The new model moves the SF ...
Stochastic frontier models with autocorrelated inefficiency have been proposed in the past as a way ...
This thesis is concerned with the specification, estimation, application and testing of stochastic f...
This paper extends the fixed effect panel stochastic frontier models to allow group heterogeneity in...
The traditional Stochastic Frontier Model (SFM) suffers from a very restrictive assumption of indepe...
Firms and organizations, public or private, often operate on markets characterized by non-competitiv...
This article introduces a dynamic stochastic frontier analysis (SFA) framework with unobserved heter...