Cash liquidity in the adoption of new cropping systems in central Lampung Indonesia

Abstract

Linear programming approach was utilized to determine the feasibility of new cropping systems which give the highest income to farmers subject to capital, labour and land constraints. The results of the optimal solutions in this study have shown that at the present levels of beginning capital, labor and land, improved experimental cropping patterns introduced by Central Research Institute for Agriculture (CRIA) dominate the patterns to be adopted. The results show that an increase in beginning capital causes a decrease in cultivated area of old or farmers' patterns. Increasing the level of interest rate affects the patterns to be adopted by shifting cultivated area of the improved experimental patterns to the farmers' patterns. The improved experimental patterns have not been adopted in the presence of beginning capital shortage as well as credit shortage. Under the present conditions of available resources without capital generation in the model, credit is an important constraint in the production process and that added credit adds to net income. The hypotheses that the present level of credit used is not at optimum level is thus accepted. Parameterizing of available credit indicates further acceptance of the hypotheses that increasing cash flow through short-term credit will increase farm income and land use. This study also suggests that the credit received must be allocated within two seasons in order to maximize farm income. This allocation is important if capital generation is not involved in the farm business. In other words, credit for the second season is a necessary factor in maximizing farm income or in adopting improved experimental patterns. The farmers have more income and wider area to be cultivated Loan if the maturity is extended to 12 months rather than 6 months, present loan maturity. The findings allow us to hypothesize that extending loan maturity will increase farm income due to a shortage of capital in the second season. However, the above findings come out with the assumption that no risk aversion involved in the farmers' decision in adoption new improved experimental cropping patterns. Those findings as an optimal solution of linear programming approach are based on the assumption that constant return to scale is a characteristic of function. its production The linearity assumption in the objective function also makes the model inapplicable for activities that are inversely related e.g. the increase in output results in the lowering of the market price, farm size and others. Therefore, in order to achieve the objective