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Meeting Development Objectives with Agricultural Research: Priority Setting in Zimbabwe
G.Mutangadura
1997
Aннотация:
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.
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