Efficiency measurement using a latent class stochastic frontier model

2004 ◽  
Vol 29 (1) ◽  
pp. 169-183 ◽  
Author(s):  
Luis Orea ◽  
Subal C. Kumbhakar
Keyword(s):  
Latent Class ◽  
Stochastic Frontier ◽  
Efficiency Measurement ◽  
Stochastic Frontier Model

scholarly journals Eficiencia técnica de pesquerías con heterogeneidad inobservada

2019 ◽  
Vol 37 (3) ◽  
pp. 101
Author(s):  
David Castilla Espino ◽  
Juan José García del Hoyo
Keyword(s):  
Technical Efficiency ◽  
Latent Class ◽  
Stochastic Frontier Analysis ◽  
Unobserved Heterogeneity ◽  
Stochastic Frontier ◽  
Production Model ◽  
Stochastic Frontier Model ◽  
Production Frontier ◽  
Frontier Analysis ◽  
Production Activity

Fisheries production is subject to a significant variability caused no only by the stochastic nature of fisheries due to uncontrolled environmental and biological conditions, but also by factors related to production activity. It is necessary to take into consideration all these factors to avoid biases on production model estimates. This paper aims to go through this variability in Stochastic Frontier Analysis to account for observed and unobserved heterogeneity together with technical efficiency and randomness. This paper exemplifies the application of a Latent Class Stochastic Frontier model to the anchovy fishery of Southeastern Black Sea to account for production frontier heterogeneity. Results show a mean level of technical efficiency of 55%, which is higher than those produced by the standard stochastic frontier model. Moreover, results allow identifying two latent classes in the fleet. They also provide sound scientific advice for de management of the fishery.

scholarly journals Measurement of hospital efficiency, using a latent class stochastic frontier model

2011 ◽  
Vol 45 (1) ◽  
pp. 47-54 ◽  
Author(s):  
Carlos Pestana Barros ◽  
António Gomes de Menezes ◽  
José Cabral Vieira
Keyword(s):  
Latent Class ◽  
Stochastic Frontier ◽  
Hospital Efficiency ◽  
Stochastic Frontier Model

scholarly journals How efficient are German life sciences? Econometric evidence from a latent class stochastic output distance model

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247437
Author(s):  
Denitsa Angelova ◽  
Maya Göser ◽  
Stefan Wimmer ◽  
Johannes Sauer
Keyword(s):  
Technical Efficiency ◽  
Production Technology ◽  
Latent Class ◽  
Latent Class Model ◽  
Stochastic Frontier ◽  
Life Sciences ◽  
Latent Classes ◽  
Stochastic Frontier Model ◽  
Class Model ◽  
Decision Making Unit

This article investigates the technical efficiency in German higher education while accounting for possible heterogeneity in the production technology. We investigate whether a latent class model would identify the different sub-disciplines of life sciences in a sample of biology and agricultural units based on technological differences. We fit a latent class stochastic frontier model to estimate the parameters of an output distance function formulation of the production technology to investigate if a technological separation is meaningful along sub-disciplinary lines. We apply bootstrapping techniques for model validation. Our analysis relies on evaluating a unique dataset that matches information on higher educational institutions provided by the Federal Statistical Office of Germany with the bibliometric information extracted from the ISI Web of Science Database. The estimates indicate that neglecting to account for the possible existence of latent classes leads to a biased perception of efficiency. A classification into a research-focused and teaching-focused decision-making unit improves model fit compared to the pooled stochastic frontier model. Additionally, research-focused units have a higher median technical efficiency than teaching-focused units. As the research focus is more prevalent in the biology subsample an analysis not considering the potential existence of latent classes might misleadingly give the appearance of a higher mean efficiency of biology. In fact, we find no evidence of a difference in the mean technical efficiencies for German agricultural sciences and biology using the latent class model.

scholarly journals Some Recent Developments in Efficiency Measurement in Stochastic Frontier Models

2011 ◽  
Vol 2011 ◽  
pp. 1-25 ◽  
Author(s):  
Subal C. Kumbhakar ◽  
Efthymios G. Tsionas
Keyword(s):  
Latent Class ◽  
Stochastic Frontier ◽  
Local Maximum ◽  
Latent Class Models ◽  
Economic Behavior ◽  
Efficiency Measurement ◽  
Likelihood Method ◽  
Stochastic Frontier Models ◽  
Recent Developments ◽  
Local Maximum Likelihood

This paper addresses some of the recent developments in efficiency measurement using stochastic frontier (SF) models in some selected areas. The following three issues are discussed in details. First, estimation of SF models with input-oriented technical efficiency. Second, estimation of latent class models to address technological heterogeneity as well as heterogeneity in economic behavior. Finally, estimation of SF models using local maximum likelihood method. Estimation of some of these models in the past was considered to be too difficult. We focus on the advances that have been made in recent years to estimate some of these so-called difficult models. We complement these with some developments in other areas as well.

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