Stochastic frontier analysis of productive efficiency in China's Forestry Industry

2017 ◽  
Vol 28 ◽  
pp. 87-95 ◽  
Author(s):  
Jiandong Chen ◽  
Yinyin Wu ◽  
Malin Song ◽  
Zunhong Zhu
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Productive Efficiency ◽  
Frontier Analysis ◽  
Forestry Industry

Technical Efficiency Through Innovative Methods and Estimations in Financial Markets

2021 ◽  
pp. 55-70
Author(s):  
Aikaterini Kokkinou
Keyword(s):  
Financial Markets ◽  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Productive Efficiency ◽  
Data Envelopment ◽  
Frontier Analysis ◽  
Parametric Data ◽  
Efficiency Estimation ◽  
Non Parametric

This paper investigates technical efficiency estimation in financial markets, using both parametric and non-parametric techniques: parametric Stochastic Frontier Analysis (SFA) approach or non-parametric Data Envelopment Analysis (DEA). This chapter focuses on reviewing the stochastic frontier analysis literature regarding estimating inefficiency in financial markets level, as well as explaining producer heterogeneity along with the relationships with productive efficiency level. This chapter investigates technical efficiency estimation in financial markets, using both parametric and non-parametric techniques: parametric Stochastic Frontier Analysis (SFA) approach or non-parametric Data Envelopment Analysis (DEA). More specifically, this chapter focuses on reviewing the stochastic frontier analysis literature regarding estimating inefficiency, its industrial level, as well as explaining producer heterogeneity along with the relationships with productive efficiency level.

scholarly journals Productive efficiency analysis of quantitative economics journals through Stochastic Frontier Analysis using panel data

2020 ◽  
Vol 30 ◽  
pp. 297-311
Author(s):  
José Manuel Gavilan Ruiz ◽  
Francisco Javier Ortega Irizo
Keyword(s):  
Production Process ◽  
Stochastic Frontier Analysis ◽  
Scientific Journal ◽  
Stochastic Frontier ◽  
Productive Efficiency ◽  
Mathematical Methods ◽  
Frontier Analysis ◽  
Economics Journals ◽  
Using Data ◽  
Number Of Citations

The main goal of a scientific journal is to diffuse new knowledge. The number of citations received by a journal can be considered as a measure of this objective and, in turn, as a measure of productivity in relation to the production process in which the journals are involved. In order to assess this production process, in this paper econometric models using data panel are employed to obtain measures of efficiency for those journals belonging simultaneously to the areas of “economics” and “social science, mathematical methods” in the Web of Science database. This efficiency is measured in terms of the distance between the actual production of the journals and their estimated maximum achievable number of citations based on their available resources.

scholarly journals Productive efficiency of wine grape producers in the North of Portugal

2021 ◽  
Author(s):  
Micael Santos ◽  
Xosé Antón Rodríguez ◽  
Ana Marta-Costa
Keyword(s):  
Value Chain ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Productive Efficiency ◽  
Structural Factors ◽  
Frontier Analysis ◽  
Face To Face ◽  
The North ◽  
Major Player ◽  
Output Information

Portugal is a country traditionally dedicated to viticulture and characterized by the production of wines of high quality. However, although it continues to be a major player in the world, both in the extension of vineyards and in the production of wine, it is certain that in recent years Portugal have lost market share in these areas. In this context, it is interesting to analyze if this situation could be related to the level of productive efficiency of vineyards. Therefore, the aims of this study are to analyse the farms that are efficiently allocating resources to achieve maximum production and to identify characteristics that make the farm more efficient. In addition, we want to analyse the productive efficiency of the farms from a regional perspective. To achieve this purpose, we use a database collected by face-to-face surveys from a sample of 154 wine-growing farms with specific input-output information from 2017. These farms are locating in the three regions of the North of Portugal (Minho, Douro and Trás-os-Montes), which represents more than 40% of the Portuguese vineyard area. To analyse the productive efficiency of the farms, we use the Stochastic Frontier Analysis (SFA). The results show that the efficiency level in the wine-growing farms from the North of Portugal is arround 67%, but with significant differences at regional level. Many of these discrepancies may be due to structural factors, such as the type of grape produced in each region. In conclusion, the findings make evident that the most efficient farms are not the most profitable due to the structure of the existing value chain.

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