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Keywords = four components stochastic frontier model

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19 pages, 579 KB  
Article
Enhancing Efficiency: Halton Draws in the Generalized True Random Effects Model
by David H. Bernstein
Econometrics 2024, 12(4), 32; https://doi.org/10.3390/econometrics12040032 - 6 Nov 2024
Cited by 1 | Viewed by 2211
Abstract
This paper measures the impact of the number of Halton draws in excess of n on technical efficiency in the generalized true random effects (four-component) stochastic frontier model estimated by simulated maximum likelihood. A substantial set of Monte Carlo simulations demonstrates [...] Read more.
This paper measures the impact of the number of Halton draws in excess of n on technical efficiency in the generalized true random effects (four-component) stochastic frontier model estimated by simulated maximum likelihood. A substantial set of Monte Carlo simulations demonstrates that increasing the number of Halton draws to n3/4 (n2/3) decreases the mean squared error of the total technical efficiency estimates by 6.1 (4.9) percent. Furthermore, increasing the number of Halton draws either improves or has no detrimental impact on correlation, mean squared error, relative bias, and upward bias for persistent, transient, and total technical efficiency. An energy sector application is included, to demonstrate how these issues can arise in practice, and how increasing Halton draws can improve parameter and efficiency estimates in empirical work. Full article
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21 pages, 1176 KB  
Article
Productivity and Efficiency in European Milk Production: Can We Observe the Effects of Abolishing Milk Quotas?
by Lukáš Čechura, Zdeňka Žáková Kroupová and Irena Benešová
Agriculture 2021, 11(9), 835; https://doi.org/10.3390/agriculture11090835 - 31 Aug 2021
Cited by 18 | Viewed by 5866
Abstract
The study aims to explore the sources of competitiveness of dairy producers before and after the abolition of milk quotas in selected EU member states. The investigation is based on the stochastic frontier modelling of an input distance function in the specification of [...] Read more.
The study aims to explore the sources of competitiveness of dairy producers before and after the abolition of milk quotas in selected EU member states. The investigation is based on the stochastic frontier modelling of an input distance function in the specification of the four-error-component model. The model is estimated with a multistep procedure employing the generalized method of moments estimator, addressing the potential endogeneity of netputs, and panel data gained from the FADN database. The results revealed that total factor productivity experienced an increasing trend in the majority of the analysed countries. Since the main driver of productivity growth was found to be the scale effect, our findings support the hypothesis that abolishing milk quotas has a positive effect. Full article
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19 pages, 7664 KB  
Article
Technical Efficiency in the European Dairy Industry: Can We Observe Systematic Failures in the Efficiency of Input Use?
by Lukáš Čechura and Zdeňka Žáková Kroupová
Sustainability 2021, 13(4), 1830; https://doi.org/10.3390/su13041830 - 8 Feb 2021
Cited by 21 | Viewed by 3900
Abstract
The paper provides findings on the technical efficiency of the European dairy processing industry, which is one of the most important subsectors of the food processing industry in the European Union (EU). The ability to efficiently use inputs in the production of outputs [...] Read more.
The paper provides findings on the technical efficiency of the European dairy processing industry, which is one of the most important subsectors of the food processing industry in the European Union (EU). The ability to efficiently use inputs in the production of outputs is a prerequisite for the sustainability and competitiveness of the agri-food sector as well as for food security. Thus, the aim of this paper is to provide a robust estimate of technical efficiency by employing new advances in productivity and efficiency analysis, and to investigate the efficiency of input use in 10 selected European countries. The analysis is based on two-stage stochastic frontier modelling incorporating country-specific input distance function (IDF) estimates and a meta-frontier input distance function estimate, both in specification of the four-component model, which currently represents the most advanced approach to technical efficiency analysis. To provide a robust estimate of these models, the paper employs methods that control for the potential endogeneity of netputs in the multi-step estimation procedure. The results, based on the Amadeus dataset, reveal that companies manufacturing dairy products greatly exploited their production possibilities in 2006–2018. The dairy processing industry in the analysed countries cannot generally be characterized by a considerable waste of resources. The potential cost reduction is estimated at 4–8%, evaluated on the country samples mean. The overall technical inefficiency (OTE) is mainly a result of short-term shocks and unsystematic failures. However, the meta-frontier estimates also reveal a certain degree of systematic failure, e.g., permanent managerial failures and structural problems in European dairy processing industry. Full article
(This article belongs to the Special Issue Dairy Sector: Opportunities and Sustainability Challenges)
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17 pages, 433 KB  
Article
An Analysis of Energy Use Efficiency in China by Applying Stochastic Frontier Panel Data Models
by Xiaoyan Zheng and Almas Heshmati
Energies 2020, 13(8), 1892; https://doi.org/10.3390/en13081892 - 13 Apr 2020
Cited by 10 | Viewed by 3516
Abstract
This paper investigates energy use efficiency at the province level in China using the stochastic frontier panel data model approach. The stochastic frontier model is a parametric model which allows for the modeling of the relationship between energy use and its determinants using [...] Read more.
This paper investigates energy use efficiency at the province level in China using the stochastic frontier panel data model approach. The stochastic frontier model is a parametric model which allows for the modeling of the relationship between energy use and its determinants using different control variables. The main control variables in this paper are energy policy and environmental and regulatory variables. This paper uses province level data from all provinces in China for the period 2010–2017. Three different models are estimated accounting for the panel nature of the data; province-specific heterogeneity and province-specific energy inefficiency effects are separated. The models differ because of their underlying assumptions, but they also complement each other. The paper also explains the degree of inefficiency in energy use by its possible determinants, including those related to the public energy policy and environmental regulations. This research supplements existing research from the perspective of energy policy and regional heterogeneity. The paper identifies potential areas for improving energy efficiency in the western and northeastern regions of China. Its findings provide new empirical evidence for estimating and evaluating China’s energy efficiency and a transition to cleaner energy sources and production. Full article
(This article belongs to the Collection Energy Economics and Policy in Developed Countries)
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