Determinants of rice production in Tanzania

Rice being among the three most important crops in Tanzania, it is both a vital and a commercial food crop for the majority of population. Additionally, the rice industry significantly contributes to food security, foreign exchange and employment. Due to the importance of rice towards national growth being very large, this makes it meaningful to study the determinants of rice production in Tanzania so as to know what factors will be able to positively affect rice production so as to meet the rice demand. In spite of government efforts towards pricing policies, rice production in Tanzania has not been able keep up with consumption making Tanzania the net importer of rice. This study analyses the pricing and non-pricing factors that affect rice output and examines the relationship between rice production in Tanzania and various household, farm and geographical characteristics. It used secondary cross-sectional data from the fourth wave of National Panel Survey (NPS) of 2014. Ordinal Least Square regression was used to estimate stochastic frontier production model to determine the effects of both pricing and non-pricing factors towards rice output. The descriptive analysis results indicate there was significant positive association between household size and amount of rice output and between gender and rice output, i.e. more output was noted among male headed households. The results further show that there was significant association between household land size and rice output. The regression results revealed that irrigation; average soil quality and land size costs of pesticides and herbs, hired labour, shadow wage and household size were statistically significant affecting rice production. Therefore, for the government to affect rice production positively, policies made should focus more on non-pricing factors such as subsidizing fertilizers, provisions of credits to farmers, adaptation of irrigation since these non-pricing factors have proven to affect more rice output compared to pricing factors.