MSC-Thesis in agricultural Economics
Mbeya district has been receiving fertilizer subsidy fertilizers since the reintroduction of
the program by the government of Tanzania in 2003/04 crop season. The specific
objectives of this study were; (a) to review the current design and conduct of fertilizer
subsidy programme in the study area; (b) to examine the change in demand of fertilizer
among smallholder farmers as a result of fertilizer subsidy programme and (c) to determine
the effect of subsidy fertilizers in maize production by smallholder farmers. Data were
collected using structured questionnaire with closed and open ended questions from a
household head. The information was gathered from a sample size of 120 respondents,
whereby 20 respondents were randomly sampled from each village out of six villages. A
substantial part of the analysis was based on descriptive statistics. The Fertilizer demand
model (FMD) was used in examining the effect of fertilizer subsidies on demand of
fertilizer while the conditional outcome model (COM) was used in determining the effect
of subsidy fertilizers on maize output produced by the smallholder farmers. Data
processing and analysis were done using Statistical Package for Social Science (SPSS)
version (13.0) computer software in conformity with the specific objectives of the study.
The research findings have revealed that there is poor performance of the subsidy fertilizer
programme in the study area to meet the demand of fertilizer by the smallholder farmers.
The shortage of subsidy fertilizers and late delivery has resulted into using lower rates of
fertilizer. To improve the performance of the subsidy fertilizer program it is recommended
that; (i) farmers should be protected against low and volatile output prices by investing in
irrigation, drought-tolerant crops and storage systems; (ii) the input delivery system to
smallholder sector should be improved and enough funds should be allocated to the
programme and (iii) A fertilizer factory be built in southern highland zone to solve the
problem.