Agricultural input subsidy and farmers outcomes in Tanzania

Abstract

This paper examines the impact of the government input subsidy—the National Agriculture Input Voucher—on farmers’ production and welfare in Tanzania as well as the factors that influence agricultural production in the country. The analysis is based on the Living Standards Measurement Study-Integrated Surveys on Agriculture for 2008–13. The study uses panel fixed effects and difference-in-difference and propensity score matching methods to examine the two objectives. The results show that the input subsidy programme resulted in an initial increase in maize and rice production but not in the long run and only in a few regions. In addition, there was a decrease in total production in the southern region and the programme had little effect on farmers’ welfare. The results show that this programme only partly met the expected outcomes in Tanzania due to mistargeting, inaccurate identification of households, and poor implementation.

Digital Technology and Services for Sustainable Agriculture in Tanzania: A Literature Review

“…Since the 1960s, the government introduced 16 National Agriculture Input Voucher Systems (NAIVS) for farmers to access and use modern farm inputs (seeds and fertilizers) through contracted agro-dealers for improved production and income [70]. However, due to lack of government control, cheating and fraud, contracted agro-dealers sell the subsidized inputs at full market price, leading to deficient programs' impact on farmers [71].…”

Rice Commercialization in Mngeta Kilombero District, Tanzania: Policy Implications for Inclusive Poverty Reduction

“…A decline in the proportion of MPI poor households followed the same pattern (Figure 3b). Kinuthia (2020) similarly established that rice farmers in Tanzania had improved welfare throughout the interval from 2008 to 2012, which was attributed to the tradable nature of the crop. Comparison by gender showed that farmers in MHH experienced a significantly higher MPI decline (39.3%) as well as the decline in the proportion of MPI poor households (28.1%) compared to FHH, which calls for more efforts to enhance the inclusion of FHH to benefit from rice commercialization.…”

“…But the rate of using inorganic fertilizer (Kg/ha) decreased slightly. Reporting on the impact of the national agricultural subsidy in Tanzania covering eight years (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016), Kinuthia (2020) similarly reported 59% of respondents reduced the use of fertilizer and seed due to high cost and low availability. Meanwhile, there was a significant (p<0.05) increase in the percentage of households as well as the rate (Lt/ha) of using herbicides, reflecting farmers' substituting away from more expensive labour during land clearing and weeding.…”

“…The yield in villages with electricity was slightly higher than in villages without electricity during both waves. The yield trends of major food crops in Tanzania has been mixed; some researchers reporting improvement during the subsidy programme (Ray, 2019) while others reported the subsidy had little impact on yields due to poor targeting and management (Aloyce, et al 2014;Kato, 2007;Kinuthia 2020). The combined effect of decline in yield due to the decline in area under rice (Table 4) and reduction in inputs use (Table 6) led to a general decline in total volume of paddy harvested per household between the twoyear interval (Figure 1) for all farmer categories except medium scale farmers whose total harvest increased, benefiting from area expansion as reported earlier.…”

Employment policy in Mainland Tanzania: what's in it for women?

“…In the rural context, access to land is key to sustainable livelihoods and income increases, particularly for women with restrained access to quality waged work. In Tanzania, most households practise small-scale agriculture with low levels of productivity, highlighting the necessity for effective agricultural policies (see Kinuthia 2020). In this section, we will examine Tanzania's policies aimed at bolstering self-employment, enterprise growth, and agricultural productivity, with their effects on working-age women.…”