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Agricultural production models based on technical coefficients derived from production and profit functions
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|Title:||Agricultural production models based on technical coefficients derived from production and profit functions|
|Authors:||Mian, Mohammad Aslam|
|Keywords:||Agriculture -- Economic aspects -- Mathematical models|
Agriculture -- Economic aspects -- Pakistan -- Lyallpur (District)
|Abstract:||From a methodological point of view, agricultural production models have been constructed using the classical approach of production functions. But the problems posed by the management factor and the simultaneous determination of variable inputs and outputs by the farm firm generally lead to biased estimates. The profit function was developed as an alternative to the production function. Since the arguments of this function are normalized input prices and fixed inputs, which are exogenously determined, the simultaneous equations bias is avoided. However, the non-availability of secondary data and the difficulty of collecting primary data, especially on prices and on the wage rates of agricultural labor in a developing economy, limit the applicability of profit functions. This study compared with results of both approaches applied to the agriculture of Pakistan. The enterprise combinations, obtained from linear programming models based on technical coefficients derived from production and profit functions, were also compared. The data, pertaining to the cropping year of 1974-75, were collected through a survey of 71 farms selected from a cluster of four villages in the Lyallpur district of Pakistan. The Ordinary Least Squares was the major analytical tool used to estimate the coefficients of the production and profit functions. A Cobb-Douglas form of the production function was postulated. Overall, the results indicated that whereas production functions produced many negative output elasticities, profit functions yielded coefficients consistent with production theory. The output elasticities of manual labor derived from the profit functions of sugarcane, cotton and wheat were significantly smaller than their counterparts derived from production equations. Similarly, output elasticities with respect to irrigation water also decreased. The production functions for some crops had negative coefficients for land while the profit functions produced significant and positive response coefficients for the same input. The drop in the cited coefficients and the improvement in those for land may be due to the reduction or elimination of the simultaneous equations bias in the estimates. The superiority of the profit function approach to that of the production functions may not be concluded as the production function model is capable of doing equally well if the production relationship is specified and tested in terms of simultaneous equations rather than a single equation. Ratio estimates and the reciprocals of statistically significant marginal physical products derived from production and profit functions were used as technical coefficients in the linear programming model. The model based on ratio estimates yielded results consistent with actual observations on farm enterprise mix. Thus, the hypothesis of rationality and responsiveness of farmers to changes in production determining forces is not rejected. The models based on technical coefficients derived from production and profit functions yielded different results; the differences lie in extent of production but not in its direction. This demonstration of the use of technical coefficients in L.P. production models showed that, theoretically as well as empirically, it is possible to construct models based on coefficients obtained from the two approaches of production and profit functions and that these coefficients were not very different from ratio estimates. However, there is a need to test these approaches on a more adequate data set such as time series of a cross-section.|
Thesis (Ph. D.)--University of Hawaii at Manoa, 1976.
Bibliography: leaves -188.
ix, 188 leaves
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|Appears in Collections:||Ph.D. - Agricultural Economics|
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