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Research Detail

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S. Akhter
Ex-post graduate student
Department of Agricultural Economics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

M. H. A. Rashid
Professor
Department of Agricultural Economics, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

This study was conducted to assess the comparative efficiency of Aftab Bahumukhi Farm Limited (ABFL) supervised broiler farms and farmers’ own managed broiler farms. Data were collected from randomly selected 90 broiler farmers of which 45 were ABFL supervised farmers and 45 were own managed farmers. Cobb-Douglas stochastic production function and cost frontier function were applied to determine the technical, allocative and economic efficiency of broiler farming. Technical and economic inefficiency effect models were also estimated. The estimated mean technical efficiency of all farms was 94.06 percent. Whereas it was 94.49 percent for ABFL supervised farmers and 93.66 percent for the own managed broiler farm owners. The estimated mean allocative efficiency was 96.76 percent for all farmers, and 96.51 for ABFL supervised farmers and 96.45 percent for own managed broiler farm owners. The mean economic efficiency was estimated at about 91.60 percent for ABFL supervised farmers, 90.34 percent for own managed farmers and 91.00 percent for all farmers. This implies that the cost of broiler production per farm can be reduced by 9 percent keeping the output constant. The findings reveal that ABFL supervised farmers and own managed farmers were not significantly different in terms of efficiency.

  Economic efficiency, Broiler farming, Own management
  Bajitpur, Kuliarchar and Kishoreganj sadar upazilas, Kishoreganj district, Bangladesh
  00-02-2008
  00-04-2008
  Socio-economic and Policy
  Management

To generate valuable information on productivity performance of supervised broiler enterprise and independently managed broiler farms along with identification of factors affecting efficiency.

The present study was carried out at 3 upazilas of Kishoreganj district namely : Bajitpur, Kuliarchar and Kishoreganj sadar. Data were collected from the sample broiler farmers of these areas during the months of February to April 2008 through direct interviews. At first a list of 100 contract broiler farmers was prepared with the help of the officials of ABFL. Then a sample size of 45 broilers farms under ABFL supervision was randomly chosen and a sample size of 45 own managed broiler farms was purposively chosen from the study area. The final survey questionnaire included general information on ABFL supervised farms and farmer’s own managed farms, information on family size, education, occupation, and land ownership of sample farmers, cost of day old chicks (DOC), cost of feeds, cost of human labor, vaccine and medicine costs, cost of equipment, housing costs, income from broilers, terms and condition of contract etc. All the collected data were then edited and it was converted into standard international units. Data were analyzed using the Microsoft Excel, SPSS and Frontier 4.1 Package Program. In the present study, Cobb-Douglas stochastic production frontier function was used with inefficiency variables to determine the technical efficiency effects and effects of most important variables to the returns of broiler farms. And Cobb Douglas stochastic cost function was used to assess the economic efficiency. A Cobb-Douglas stochastic production function was specified with inefficiency variables as follows: lnYi = α0 + α1lnX1i + α2lnX2i + α3lnX3i + α4lnX4i + α5lnX5i + Farm type(dummy) + Vi − Ui . . . (1). and ui= δo + δ1Z1i + δ2Z2i + δ3Z3i . . . (2). where, ln represents the natural logarithm (i.e. to the base e) and i refers to the ith farm in the sample; Yi = Gross return from broiler production (Tk.), X1i = Cost of feed for the ith farm (Tk), X2i = Cost of DOC for the ith farm (Tk.), X3i = Labor cost for the ith farm (Tk), X4i = Medicine cost for the ith farm (Tk), X5i = Litter cost for the ith farm (Tk), Farm type (dummy) = 1 for ABFL supervised farms; 0 for farmer’s own managed farms. α1 − α5 are parameters to be estimated. Vi represents the random variations in output due to factors outside the control of the farm operator. The ui’s in equation (2) are non negative random variables, associated with the technical inefficiency of production of the farmers in the population. where, Z1i denotes the age of the ith farmer; Z2i denotes the education of the ith farmer; Z3i denotes the experiences of the ith farmer; δ0, δ1, δ2, and δ3 are unknown parameters to be estimated. The stochastic frontier cost function: lnCi = α0 + α1 ln Y + α2 ln P1 + α2 ln P2 + α3 lnP2 + α3 ln P2 + α4 ln P3 + Farm type (dummy) + Vi + Ui … (3) and ui = δ0 + δ1Z1i + δ2Z2i + δ3Z3i …  (4). where, ln represents the natural logarithm (ie, to the base e), C = Gross costs of broiler production, Y = Quantity of live broiler (kg), P1 = Price of feed (Tk/kg), P2 = Price of day old chicks (Tk.), P3 = Wage rate of labor (Tk.), Farm type (dummy) = 1 for ABFL supervised farms, 0 for farmer’s own managed farms α1 . .  α4 are parameters to be estimated. Again, allocative efficiency was determined from the following relationship EE = TE × AE, AE = EE / TE, where, EE denotes economic efficiency; TE denotes technical efficiency; and AE denotes allocative efficiency. The model for the inefficiency effects can only be estimated if the inefficiency effects are stochastic and have a particular distributional specification. Hence there is interest to test the null hypothesis that the efficiency effects are not present. H0: γ= δ0 = δ1 =δ2 =δ3 = 0. This null hypothesis of interest was tested using the generalized likelihood ratio test and t test.

  Progress. Agric. 19(2) : 195-204, 2008 ISSN 1017-8139
  http://www.banglajol.info/index.php/PA/article/view/16962/11913
Funding Source:
  

From the present study a positive influence of education on efficiency was found. Educated farmers were found to have positive impact on production and were technically and economically more efficient. Thus, it can be recommended from this study that education should be one of the top priorities of the government to develop the necessary human capitals for sustainable development. The government should take various training programs for the less educated farmers.

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