Meeting Development Objectives with Agricultural Research: Priority Setting in Zimbabwe
College of Agriculture and Life Sciences
|Тематические разделы:||Экономика, Экономика отраслевых рынков, Экономика отраслевых рынков: Аграрная экономика, Экономика отраслевых рынков: Аграрная экономика: Агропродовольственная политика|
In times of tightening national budgets as a result of structural adjustment requirements, the need to make choices in Zimbabwe¹s publicly funded research is heightened. Adoption of quantitative priority setting methods help improve the objectivity of decision-making while fostering consistency of research priorities with the attainment of research system objectives This study develops and applies a quantitative methodology for agricultural research priority setting for Zimbabwe¹s Department of Research and Specialist Services (DR&SS) under multiple objectives.
Such a methodology must incorporate the structural characteristics of Zimbabwe¹s agricultural sector: the existence of different farmer types, five different agro-ecological regions and multiple objectives. A three part procedure was used in this study to prioritize agricultural research in Zimbabwe. The first part involved identifying the research objectives, defining the list of commodity and non-commodity programs to be prioritized, defining the agro-ecological zones and collecting technology related data and published information. Researchers, extension workers, and farmer representatives were interviewed using a questionnaire to obtain technology-related data. The second part involved economic analysis to measure the contributions of agricultural research to total economic benefits and their distribution by farmer type and agro-ecological region. Net present values (NPV) of economic surplus gains by research program were used to summarize the total economic efficiency gains projected over fifteen years. Once the benefits have been estimated, the third part of the procedure involved using mathematical programming (MP) to project the optimal allocation of research resources among the various commodities under alternative weights on objectives.
A ranking of the expected NPVs indicated that agricultural research priorities are different between smallholder farmers and large scale commercial farmers, with maize cotton, groundnuts, sunflower, goats, pulses and millets being of high priority for smallholder farmers, while maize, beef, cotton, coffee, wheat, dairy, stonefruit, soybeans and roses were top priority for large scale commercial farmers. Research discipline priorities for smallholder farmers include agronomy, plant breeding and chemistry and soils while for large-scale commercial farmers the priorities are plant breeding, agronomy, and plant protection. Optimal allocation of research resources given two objectives (efficiency and equity) were assessed in a series of runs with the mathematical programming model.
The tradeoff costs associated with putting an extra weight of different sizes on the equity objective, given the current total budget constraint were relatively modest implying that DR&SS can allocate resources to research on smallholder farming without great loss in efficiency.