繼起的 數理計劃法(Recursive Progamming)과 農業開發 分析

Recursive Programming and Analysis of Agricultural Development

This paper presents crucial features of recursive programming theory and its applications to agricultural development in general. Theoretical discussions, heavily drawn from Day (1963), Day and Kennedy (1970), Singh (1971), are given to a (mathematical programming system in a static sense, and b) recursive feedbacks which ccnnect current decision problems with decisions already executed in the previous periods. Putting a mathematical programming problem and recursive feedbacks together, “recursive programming” (RP) is defined as a sequential optimizing method involving behavioral feedbacks which take account of uncertainty, myopia, limited information and the like. It is further emphasized that a recursive decision system deals more with the temporal elements of decision making in a positive sense and less with what decisions ought to be made in terms of some optimum or normative decision rules. Applied to a developing agriculture among other things, recursive programming is capable of treating multi-activities of farm households and their changes over time, changes of technologies, capital use and capital formation, and ordering of multiple goals at a farm level. In order to consider in a decomposition framework vast heterogeneities of production and technological change in agricultural development, the model can be constructed by farm size, farm type, or some other physical characteristics. This will enable us to treat explicitely competitiveness of economic subaggregates for “coupling” resources. Also presented are some empirical results of recursive programming analysis of an agricultural development from the works by Ahn (1972), Ahn and Singh (1974). They show some operational capacities of the model to generate quantititatively past economic history and to forecast likely changes of agricultural development under alternative policies.