Joint-Regression Analysis and Incorporation of Environmental Variables in Stochastic Frontier Production Function: An Application to Experimental Data of Winter Rye

2013 ◽  
pp. 325-336
Author(s):  
Dulce Gamito Pereira ◽  
Ana Sampaio
Keyword(s):  
Experimental Data ◽  
Regression Analysis ◽  
Production Function ◽  
Environmental Variables ◽  
Stochastic Frontier ◽  
Winter Rye ◽  
Stochastic Frontier Production Function ◽  
Joint Regression Analysis ◽  
Frontier Production Function

scholarly journals ESTIMASI FUNGSI PRODUKSI DAN EFISIENSI ALOKASI SUMBERDAYA PETANI KEDELAI DI LOMBOK BARAT

2006 ◽  
Vol 3 (1) ◽  
pp. 145-148 ◽  
Author(s):  
Nurhayatin Nufus
Keyword(s):  
Technical Efficiency ◽  
Production Function ◽  
Stochastic Frontier ◽  
Allocative Efficiency ◽  
Farm Management ◽  
Management Level ◽  
Stochastic Frontier Production Function ◽  
Stochastic Production ◽  
Frontier Production Function ◽  
Land Size

This research  aims  to analyses  factors  influence  on production  and  resources  allocation  of soybeans  by farmer  at  West Lombok.  Production  function  was estimated  from survey data and technical  efficiency  was used to indicate  farm management  level  through maximum  likelihood,  which  was transformed  into frontier stochastic  production  function.  The land  size,  fertilizer  (urea and  TSP), labor  and pesticide  influence  the production  of soybean  at site.  The technical efficciency  level of Soybean fann was 95,6 percent   The  usage of TSP and pesticide reached allocative efficiency while urea and seeds were al/ocative efficiency yet Key words:  technical  effICiency, allocative  effICiency, and stochastic  frontier  production  function.

scholarly journals Determinants and Differences of Grain Production Efficiency Between Main and Non-Main Producing Area in China

2019 ◽  
Vol 11 (19) ◽  
pp. 5225
Author(s):  
Furong Chen ◽  
Yifu Zhao
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Production Function ◽  
Production Efficiency ◽  
Stochastic Frontier ◽  
Grain Production ◽  
Marginal Productivity ◽  
Rural Labor ◽  
Stochastic Frontier Production Function ◽  
Frontier Production Function

This paper investigated the determinants, especially labor transformation, and differences of technical efficiency between main and non-main grain-producing area in China based on a panel data from 30 provinces in the period of 2001–2017. Stochastic frontier production function was used to estimate the level of technical efficiency and the marginal productivity of different inputs. The estimated results showed that land is the most important factor to improve China’s grain output, followed by fertilizers, labor, and machinery inputs. There was a significant 4.6 percent gap of production efficiency between main and non-main producing provinces. Influence of rural labor transformation was confirmed to be positive to improve technical efficiency.

scholarly journals ANALISA TINGKAT EFISIENSI SEKTORAL DAN RESPON KEBIJAKAN EKONOMI SEKTORAL DI DAERAH

2012 ◽  
Vol 14 (3) ◽  
pp. 317-338 ◽  
Author(s):  
M. Abdul Majid Ikram ◽  
Andry Prasmuko ◽  
Donni Fajar Anugerah ◽  
Ina Nurmalia Kurniati
Keyword(s):  
Technical Efficiency ◽  
Production Function ◽  
Stochastic Frontier ◽  
Regional Level ◽  
Primary Input ◽  
Stochastic Frontier Production Function ◽  
Production Function Approach ◽  
Input Efficiency ◽  
Frontier Production Function ◽  
Sectoral Performance

This paper analyzes the contributon of primary input; capital anda labor, on sectoral performance in Indonesia. The analysis cover sall sectors both in national and regional level, and also the dynamic of input efficiency across period. Using stochastic frontier production function approach, this paper found the aggregate share of capital is 0.20 and 0.34 for labor; conforming the dominance of labor. The highest three technical efficiency is Mining sector (88.65%), Manufacture (70.47%) and Financial (65.93%), while the lowest one is Electric, Gas and Water (25.38%).Keywords: efficiency, stochastic frontier, productivity, Indonesia.JEL Classification: D24, J24, O18

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