M. A. Haque
Assosiate Professore
Economics division, Bangladesh Agricultural University and University of Tsukuba, Graduate School of Life and Environmental Sciences, Japan
T. Ahamed
Associate Professor
Tsukuba University, Japan
M. Akteruzzaman
Professor
Department of Agricultural Economics, Bangladesh Agricultural University, Mymensingh
A. Hashem
Professor
Department of Animal Science, Bangladesh Agricultural University, Mymensingh
S. Haque
Department of Animal Science, Bangladesh Agricultural University, Mymensingh
S. Akter
Department of Animal Science, Bangladesh Agricultural University, Mymensingh
M. M. Islam
Department of Animal Science, Bangladesh Agricultural University, Mymensingh
M. S. Alamgir
Department of Animal Science, Bangladesh Agricultural University, Mymensingh
M. M. Islam
Department of Animal Science, Bangladesh Agricultural University, Mymensingh
Bangladesh, Poultry Feed Mills, Livestock, Raw Materials, Profit
Dhaka, Gazipur, Narsingdi, Kishoreganj and Mymensingh districts, Bangladesh
Food Safety and Security
The study was mainly based on field surveys in addition of some secondary information. Purposive sampling technique was used in selected 30 feed mills. It was categorized by high, medium and low-quality feed mill on the basis of feed conversion ratio (FCR). One more important part of research work is sample selection. In a complete enumeration, the essential information is collected from different stakeholders’. The field work conducted with feed miller, dealer, different sizes of poultry farm owners and farmers. 30 feed mills were selected on the basis of quality (FCR) from Dhaka, Gazipur, Narsingdi, Kishoreganj and Mymensingh districts. FCR categorized on the basis of collected from firms level data from feed performance. Table 1 shows that a multi-stage stratified sampling was adopted in this study. The selected 30 feed mills categorized on the basis of feed conversion ratio (FCR) that is high-quality feed mills (FCR; below 1.5 to 1.6), medium quality feed mills (FCR: 1.6 up to 1.7) and low-quality feed mills (FCR: 1.7 up). The selected commercial farms were categorized by flock size small scale: < 1000 birds, medium scale: 1001-2000 birds and large scale: above 2000 birds. In conformity with the objectives of the study, a structured questionnaire developed for collecting relevant primary data from the poultry feed miller and farmers. The present study covered approximately from March –December 2013 to July-December 2014 study period and data analyzed with a combination of tabular and statistical techniques. For analyzing the data, descriptive statistics such as sum, average, ratio, percentages, etc. was derived and calculated to present the results. In this study, profit was calculated by deducting total costs from total returns. The following equation was used to assess the profitability of poultry feed production. The profitability of feed production was derived in terms of gross return, gross margin, net return and benefit cost ratio (undiscounted) of different enterprises. Gross margin Gross margin calculated by the difference between gross return and total variable costs. That is, GM= GR- TVC Where, GM= Gross margin; GR= Gross return and TVC = Total variable cost. Net return Net return analysis considered fixed costs i.e., cost of land rent, interest on operating capital, etc. Net return calculated by deducting all costs (variable and fixed) from the gross return. Specifications of the model: To explore the effects of variable inputs, both linear and Cobb-Douglas production function were estimated initially. The result of the Cobb-Douglas production appeared to be superior on theoretical and econometric grounds. So the CobbDouglas production was chosen under ordinary least squares (OLS) methods. The coefficients understand this specification for production elasticity and if all the related to the production are taken into account as the independent variables, the sum of the output increasing constant or decreasing returns to scale. Alene, 2002 and Anene, et al., 2010) used Cobb Douglas production function to measure resource use efficiency. In this model, the factor inputs donated from X1 to X6 representing; the implicit form of the model is as follows equation 1. Y = f (X1, X2, X3, X4, X5, X6, Vi-Ui) ……………………….. (1) Where, Y = Value of output; X1= Cost of ingredients; X2= Cost of additives X3= Cost of machineries X4= Cost of human labour 10 X5= Operational cost X6 = Cost of electricity Vi= Symmetric disturbance term accounting for random shocks and other statistical noise. Ui = Non-negative random errors depicting inefficiency in production Among other fitted functional forms, the double log form was chosen based on goodness of fit depending on the highest value of adjusted R² and t-value. The form is presented below (equation 2): lnY = lnβ + β1lnX1 + β2InX2 + β3lnX3 + β4lnX4 + β5lnX5 + β6lnX6 + βnlnXn + Vi-Ui …(2) Where, ln = Natural logarithm β= constant Y, X1, X2 … X6, and Vi-Ui is as defined in equation (1).
International Association of Agricultural Economists, July-28 to August 2, 2018, VANCOUVER
Journal