Some factors affecting upland rice production : the economic effect of management, Cale, Tanauan, Batangas, Philippines

Abstract

This study was carried out to contribute to the understanding of the factors affecting variations in the yield of Dagge, a native upland rice variety, in Cale, Tanauan, Batangas, Philippines. The main hypothesis of the study is that management is an important explanatory variable on yield. Viewing the farmer as a "goal-oriented system seeking to produce a desirable outcome" (Nielson farmer-manager model), he possesses a biography of past experiences, drives and motivations and capabilities which produce management behaviour and in turn generate an outcome. With this in mind, a management survey was done to collect information on the characteristics of Cale farmers related to their biography, technical knowledge, drives and motivations, and decision-making. Based on these characteristics, a pattern analysis technique was utilized to classify the farmers into homogeneous management groups. Three management groups were considered and were represented in the production function by dummy variables, in addition to the usual inputs to production like fertilizer, labour, etc. Using the Cobb-Douglas production function, regression models were formulated to determine the effects of management level on the general productivity level (intercept) only (Model 1), the factor elasticity only (Model 2) and both the general productivity level and factor elasticity as well (Model 3). Inclusion of the management dummy variables resulted in a substantial improvement in the fit of the production function. The unadjusted R for the model with only the conventional inputs is 0.35, while the unadjusted R² for Model 1 is 0.56, for Model 2A is 0.55, for Model 2B is 0.56, for Model 3A is 0.57 and for Model 3B is 0.59. The analysis of variance for all the models showed that the contribution of management to the variations in the yield of Dagge is significant at the one per cent level. This supported the regression results. Of the models considered, it was argued that the model which reflects the effect of management through the changes in the factor elasticity is the most appropriate one to determine and analyze the effects of management in the production function analysis (Model 2). The inputs considered with which management is importantly related to management were fertilizer and labour. It was advanced that the proper usage of fertilizer, the amount of fertilizer applied, the proper time of its application and the correct timing of farm operations are a reflection of the managerial capabilities of the farmer. Model 2A was designed to test whether the management effect is on fertilizer elasticity only, while Model 2B tests whether the management effect is on the elasticity of labour only. This model indicates that management ability of the farmer has an important effect on the efficiency of fertilizer use, while Model 23 also shows that labour is an important input on which management may have a direct effect. Models 2A and 2B were used to examine the farmer's resource allocation. The results showed that farmers in management group 3 are better managers of labour and fertilizer inputs than farmers in management group 2 and management group 1. It appears that management group 3 farmers utilized their resources more efficiently than other farmers. They also obtained a higher yield, with an average of 2366 kg/ha compared to management group 2 farmers (1861 kg/ha) and management group 1 farmers (1358 kg/ha). In general, it appears that management group 3 farmers possess characteristics which reflect good managerial ability as compared to the other farmers. The farmers in management group 3 are young and receptive to change, are more knowledgeable of proper fertilizer and chemical use than the other farmers and have a different perception of progress in farming and farming as a way of life from the rest. It appears from the levels of yield and input use and the regression results that farmers in management group 3 are better farmer-managers than farmers in management group 2 and management group 1 farmers. On the whole, the production function analysis indicated that a significant percentage of variations in the yield of Dagge can be explained in terms of differences in resource inputs and productivities. In addition, it has been demonstrated that management explained a great proportion of variations in the yield of Dagge. Perhaps a better understanding of the farmer and his behavioural characteristics would be a great aid in the formulation of agricultural policies. Hence, it will be a great help to future researchers and programs on agricultural productivity to consider differential management abilities in their studies. Show more