scholarly journals A production function analysis of commercial dairy farms in the Highlands of Eritrea using ridge regression

Agrekon ◽  
2006 ◽  
Vol 45 (2) ◽  
pp. 225-242 ◽  
Author(s):  
W K Ghebremariam ◽  
G F Ortmann ◽  
I V Nsahlai
1991 ◽  
Vol 21 (8) ◽  
pp. 1278-1287 ◽  
Author(s):  
David H. Newman

The analysis in this paper measures changes in forest productivity for 12 southern states using a modified, aggregate production function. The function combines cross section – time series, biological, and acreage data to estimate the shift in productivity, measured as either standing inventory plus removals or changes in inventory plus removals, over the past 4 decades. The annual shift in productivity is estimated to be approximately 0.5% for the standing volume measures used. However, productivity gains in the region have virtually stopped during the past decade. The largest contributions to productivity gains were from industrially owned lands and land managed as planted pine. Mixed pine–hardwood stands and public lands (except for plantations) showed lower productivity impacts. These results present an essential component for understanding the impact of technical change on aggregate forest productivity in the southern United States.


2017 ◽  
Vol 2 (1) ◽  
Author(s):  
. Sumartin

This study aims to  analyze the  economic, technical and price efficiency of  milkfish farmers participating fish culture training at Center of Education and Fisheries Training Banyuwangi, analyzing covering factors affecting production efficiency. Analysis of data used in the form of production function analysis Cobb Douglas stochastic frontier which is estimated by Ordinary Least Square Method (OLS). Estimation of Cobb-Douglas production function model using OLS method to know the efficiency of the average performance of fish culture business. Estimates with the maximum likelihood (MLE) method to determining the level of technical efficiency, using the 4.7 frontier computing program developed by Coelli (1996). To know the efficiency of the price can be calculated by the value of marginal product (VMP) of production factor. The results show that the level of economic efficiency of milkfish culture business in Gresik East Java, based on the results of estimation using MLE method, the result of six factors of production is in rational area, but not yet efficient because the obtained coefficient value of each area of pond (X1) 0.318, fertilizer (X2) 0.079, lime (X3) 0.009, seeds (X4) 0.005, probiotics (X6) 0.066 and labor (X7) 1.311. While one feed production factor (X5) is in an irrational area because it has a coefficient value of -0.017. While the variables that influence inefficiency are experiential variables (Z1), age of farmers (Z2) and formal education (Z3) each have elasticity of -0.0711458; -0,6270106 and -0,1504381. The value of Marginal Product (NPM) of pond production area (X1) is 0.00059 (<1), Fertilizer (X2) is greater than 1 ie 3,01413, lime production factor (X3) 3,35338, the other NPM factor production such as Seed (X4) and Labor (X7), with value less than 1 (0.00075 and 0.03865), NPM Feed (X5), is smaller than one ie -0.00364 (<1 ). NPM probiotic (X6) is 95,1491 (> 1). Overall allocation of the seven factors of production is the average value of price efficiency is also more than one that is equal to 101,553 and economic efficiency equal to 2,904. it can be concluded that fish breeding business has not been efficient. Keywords: efficiency, economy, technical, price, frontier, milkfish


2003 ◽  
Vol 48 (2) ◽  
pp. 205-216 ◽  
Author(s):  
Ljubomir Bastajic

The study was conducted with the objective of analyzing the economic effects provoked by the change in farm size, depending on the degree of production specialization (questionnaires encompassing 30 farms of different size were used) using comparative analysis, regression analysis, correlation analysis and production function analysis. Research comprised essential parameters of business conditions on the farms and results of their business. The farms analyzed were classified according to the size of used cultivable land and degree of production specialization. In both farm groups, with different degrees of production specialization, the indices of business results were found to rise with size increase and were noticed to be the most favorable in the case of over 10 ha-farms. Comparing farms of identical size but of different degree of specialization, the following may be concluded: more favorable business results were achieved on farms with higher degree of specialization.


1987 ◽  
Vol 16 (1) ◽  
pp. 10-16 ◽  
Author(s):  
Loren W. Tauer ◽  
Krishna P. Belbase

The technical efficiencies of New York dairy farms were estimated using a frontier production function. The average farm was 69 percent efficient. Individual farm efficiency was regressed on variables not considered inputs to explain why a farm was not on the frontier. Favorable location in the state and larger size (cows) as proxies for technology lead to greater efficiency. Participation in the Dairy Herd Improvement Cooperative and use of mail-in computerized records as proxies for management result in a reduction in efficiency. However, only 9 percent of variation in farm efficiency could be explained.


2016 ◽  
Vol 78 (5) ◽  
Author(s):  
Ismayani Ismayani

The objectives of this research is to find the factors impacted of turmeric farm and the efficiency of production factor allocation was efficient or not.  The  research location in Aceh Besar district. This research used survey method. The research was tested by Cobb Douglass production function analysis.  The result of research shows that area factor allocation 0,30 hectare not efficient.  Showing that area factor necessary to increased anyway the income of the farmer increasing.And the allocation of labor factor 17,43 man days per season be decreased cause not efficient and can be high the labor, over production and marginal production value lower.


2008 ◽  
Vol 14 (1) ◽  
Author(s):  
I B Adinya ◽  
O O Kuye ◽  
M U Awoke ◽  
S Ajayi ◽  
D I Agom ◽  
...  

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