An analysis of optimal scale and factor intensity in Nepalese agriculture: an application of a ray–homothetic production function

1986 ◽  
Vol 18 (10) ◽  
pp. 1051-1063 ◽  
Author(s):  
R. Grabowski ◽  
K. Belbase
Keyword(s):  
Production Function ◽  
Factor Intensity ◽  
Optimal Scale

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

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.

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