An Economic Comparison between Alternative Rice Farming Systems in Tanzania Using a Monte Carlo Simulation Approach

Ibrahim L. Kadigi, Khamaldin D. Mutabazi, Damas Philip, James W. Richardson, Jean-Claude Bizimana, Winfred Mbungu, Henry F. Mahoo and Stefan Sieber
Additional contact information
Ibrahim L. Kadigi: School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro P.O. Box 3007, Tanzania
Khamaldin D. Mutabazi: School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro P.O. Box 3007, Tanzania
Damas Philip: School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, Morogoro P.O. Box 3007, Tanzania
James W. Richardson: Department of Agricultural Economics, Texas A&M University, 600 John Kimbrough Blvd/AGLS Blg, College Station, TX 77843-2124, USA
Jean-Claude Bizimana: Department of Agricultural Economics, Texas A&M University, 600 John Kimbrough Blvd/AGLS Blg, College Station, TX 77843-2124, USA
Winfred Mbungu: Department of Engineering Sciences and Technology, Sokoine University of Agriculture, Morogoro P.O. Box 3003, Tanzania
Henry F. Mahoo: Department of Engineering Sciences and Technology, Sokoine University of Agriculture, Morogoro P.O. Box 3003, Tanzania
Stefan Sieber: Leibniz-Centre for Agriculturald Landscape Research, Eberswalder Straße 84, 15374 Müncheberg, Germany

Sustainability, 2020, vol. 12, issue 16, 1-22

Abstract: Tanzania is the second-largest producer of rice ( Oryza sativa ) in Eastern, Central, and Southern Africa after Madagascar. Unfortunately, the sector has been performing poorly due to many constraints, including poor agricultural practices and climate variability. In addressing the challenge, the government is making substantial investments to speed the agriculture transformation into a more modernized, commercial, and highly productive and profitable sector. Our objective was to apply a Monte Carlo simulation approach to assess the economic feasibility of alternative rice farming systems operating in Tanzania while considering risk analysis for decision-makers with different risk preferences to make better management decisions. The rice farming systems in this study comprise rice farms using traditional practices and those using some or all of the recommended system of rice intensification (SRI) practices. The overall results show 2% and zero probability of net cash income (NCI) being negative for partial and full SRI adopters, respectively. Meanwhile, farmers using local and improved seeds have 66% and 60% probability of NCI being negative, correspondingly. Rice farms which applied fertilizers in addition to improved seeds have a 21% probability of negative returns. Additionally, net income for rice farms using local seeds was slightly worthwhile when the transaction made during the harvesting period compared to farms applied improved varieties due to a relatively high price for local seeds. These results help to inform policymakers and agencies promoting food security and eradication of poverty on the benefits of encouraging improved rice farming practices in the country. Despite climate variability, in Tanzania, it is still possible for rice farmers to increase food production and income through the application of improved technologies, particularly SRI management practices, which have shown a promising future.

Keywords: rice; management practices; risk; Monte Carlo simulation; stochastic variables; Tanzania (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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