The Process Production Function

1981 ◽  
pp. 3-8 ◽  
Author(s):  
Ronald W. Shephard
Keyword(s):  
Production Function

Significance of Experience, Farm Size, Quantity of Propagules and Location f or Seaweed Farmers in the Divided Island of Sebatik

2018 ◽  
Vol 9 (9) ◽  
pp. 825-832
Author(s):  
James M. Alin ◽  
◽  
Datu Razali Datu Eranza ◽  
Arsiah Bahron ◽  
◽  
...  
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Production Function ◽  
Weather Conditions ◽  
Education Level ◽  
Farm Size ◽  
Total Production ◽  
Explanatory Factors ◽  
Douglas Production Function

Seaweed-Kappaphycus-Euchema Cottonii and Denticulum species was first cultivated at Sabah side of Sebatik in 2009. By November 2014, sixty one Sabahan seaweed farmers cultivated 122 ha or 3,050 long lines. Thirty Sabahan seaweed farmers in Kampung Pendekar (3.2 m.t dried) and 31 in Burst Point (12.5 m.t dried) produced 16 metric tonnes of dried seaweed contributed 31% to Tawau’s total production (51 m.t). The remaining 69% were from farmers in Cowie Bay that separates Sebatik from municipality of Tawau. Indonesian in Desa Setabu, Sebatik started in 2008. However, the number of Indonesian seaweed farmers, their cultivated areas and production (as well as quality) in Sebatik increased many times higher and faster than the Sabah side of Sebatik. In 2009 more than 1,401 households in Kabupaten Nunukan (including Sebatik) cultivated over 700 ha and have produced 55,098.95 and 116, 73 m.t dried seaweed in 2010 and 2011 respectively. There is a divergence in productions from farming the sea off the same island under similar weather conditions. Which of the eight explanatory factors were affecting production of seaweeds in Sebatik? Using Cobb Douglas production function, Multiple Regression analysis was conducted on 100 samples (50 Sabahan and 50 Indonesian). Results; Variable significant at α = 0.05% are Experience in farming whereas Farm size; Quantity of propagules and Location — Dummy are the variables significant at α 0.01%. Not significant are variables Fuel; Age; Number of family members involved in farming and Education level.

Efficient Cobb-Douglas Production Function

2019 ◽  
Vol 1 (1) ◽  
pp. 16-23
Author(s):  
Farhad Savabi ◽  
Keyword(s):  
Production Function ◽  
Douglas Production Function

Biohydrogen Production Function of Operating pH and Seed Pre-Treatment

2017 ◽  
Vol 49 (004) ◽  
pp. 699--704
Author(s):  
Z. SIDDIQUI ◽  
S. A. MEMON ◽  
K. M. BROH
Keyword(s):  
Production Function ◽  
Biohydrogen Production ◽  
Pre Treatment

Choice Of Technique And The Volume Of Saving (A Re-Examination Of The Cobb-Douglas Model)

1968 ◽  
Vol 8 (4) ◽  
pp. 606-617
Author(s):  
Mohammad Anisur Rahman
Keyword(s):  
Economic Development ◽  
Production Function ◽  
Development Policy ◽  
Social Goals ◽  
The Other ◽  
Economic Development Policy ◽  
Labour Intensity ◽  
The One ◽  
Choice Of Technique ◽  
The Relationship

The purpose of this paper is to re-examine the relationship between the degree of aggregate labour-intensity and the aggregate volume of saving in an economy where a Cobb-6ouglas production function in its traditional form can be assumed to give a good approximation to reality. The relationship in ques¬tion has an obviously important bearing on economic development policy in the area of choice of labour intensity. To the extent that and in the range where an increase in labour intensity would adversely affect the volume of savings, a con¬flict arises between two important social objectives, i.e., higher rate of capital formation on the one hand and greater employment and distributive equity on the other. If relative resource endowments in the economy are such that such a "competitive" range of labour-intensity falls within the nation's attainable range of choice, development planners will have to arrive at a compromise between these two social goals.

PENERAPAN PENDUGAAN EFISIENSI ALOKATIF PADA USAHATANI BUNCIS (Phaseolus vulgaris, L)

2020 ◽  
Vol 21 (1) ◽  
pp. 81-90
Author(s):  
Marthen Robinson Pellokila
Keyword(s):  
Production Function ◽  
Allocative Efficiency ◽  
Maximum Output ◽  
Phaseolus Vulgaris L ◽  
Land Area ◽  
Price Efficiency ◽  
Efficiency Estimation ◽  
Area Use ◽  
A Company ◽  
Douglas Production Function

ABTRACT Efficiency is one of the important indicators to assess the performance of a company or farm. Efficiency guarantees the use of certain inputs to achieve maximum output levels (technical efficiency) and also efficiency ensures the use of certain inputs that maximize profits (price efficiency or allocative efficiency). This article discusses the application of the estimation of price efficiency / allocative efficiency of the use of production inputs in bean farming using the linearized Cobb-Douglas Production function. The results of the analysis shows that the application of price efficiency estimation for production inputs using the Cobb-Douglas production function is satisfactory as long as the classical assumptions required by the multiple regression are fulfilled. Of the five production inputs included in the model, only one production input provides a significant value to production, namely the production input for the land area use. Thus, only the production input for land area use is estimated at the value of its price efficiency. Based on the results of the analysis, it is found that the use of production inputs for land area use has not yet reached its price efficiency.

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