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DOI	10.1016/j.agsy.2019.102693
	Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: A multivariate empirical (MVE) approach
	Kadigi, Ibrahim L.1,2; Richardson, James W.3; Mutabazi, Khamaldin D.1; Philip, Damas 1; Bizimana, Jean-Claude 3; Mourice, Sixbert K.4; Waized, Betty 1
通讯作者	Kadigi, Ibrahim L.
来源期刊	AGRICULTURAL SYSTEMS
ISSN	0308-521X
EISSN	1873-2267
出版年	2020
卷号	180
英文摘要	Maize (Zea mays L.), sorghum (Sorghum bicolor L. Moench) and rice (Oryza sativa) are essential staple crops to the livelihoods of many Tanzanians. But the future productivity of these crops is highly uncertain due to many factors including overdependence on rain-fed, poor agricultural practices and climate change and variability. Despite the multiple risks and constraints, it is vital to highlight the pathways of cereal production in the country. Understanding the pathways of cereals helps to inform policymakers, so they can make better decisions to improve the viability of the sector and its potential to increase food production and income for the majority population. In this study, we employ a Monte Carlo simulation approach to develop a multivariate empirical (MVE) distribution model to simulate stochastic variables for main cereal crops in Tanzania. Eleven years (2008-2018) of yields and prices data for maize, sorghum and rice were used in the model to simulate and forecast yields and prices in Dodoma and Morogoro regions of Tanzania for a seven-year period, from 2019 to 2025. Dodoma and Morogoro regions represent semi-arid and sub-humid agro-ecological zones, respectively. The simulated yields and prices were used with total costs and total area harvested for each crop to calculate the probable net present value (NPV) for each agro-ecological zone. The results on crop yield show a slightly increasing trend for all three crops in Dodoma region. Likewise, rice yield is expected to marginally increase in Morogoro with a decreasing trend for maize and sorghum, meanwhile, the prices for the three crops all are projected to increase for the two regions. Generally, the results on economic feasibility in terms of NPV revealed a high probability of success for all the crops in Dodoma despite a higher relative risk for rice. The results in Morogoro presented a high probability of success for rice and sorghum with maize indicating the highest relative risk, and a 2.41% probability of negative NPV. This study helps to better understand the outlook of the main cereal crop sub-sectors in two agro-ecological zones of Tanzania over the next seven years. With high dependence on rain-fed agriculture, production of main cereals in Tanzania are likely to face a high degree of risk and uncertainty threatening livelihoods, incomes and food availability to the poor households.
英文关键词	Cereal crops MVE probability distribution Stochastic simulation Semi-arid area Sub-humid area Simetar
类型	Article
语种	英语
国家	Tanzania ; USA
收录类别	SCI-E
WOS记录号	WOS:000524975500009
WOS类目	Agriculture, Multidisciplinary
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/313929
作者单位	1.Sokoine Univ Agr, Sch Agr Econ & Business Studies, POB 3007, Morogoro, Tanzania; 2.Sokoine Univ Agr, Soil Water Management Res Grp, POB 3003, Morogoro, Tanzania; 3.Texas A&M Univ, Dept Agr Econ, College Stn, TX 77845 USA; 4.Sokoine Univ Agr, Dept Crop Sci & Hort, POB 3005, Morogoro, Tanzania
推荐引用方式 GB/T 7714	Kadigi, Ibrahim L.,Richardson, James W.,Mutabazi, Khamaldin D.,et al. Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: A multivariate empirical (MVE) approach[J],2020,180.
APA	Kadigi, Ibrahim L..,Richardson, James W..,Mutabazi, Khamaldin D..,Philip, Damas.,Bizimana, Jean-Claude.,...&Waized, Betty.(2020).Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: A multivariate empirical (MVE) approach.AGRICULTURAL SYSTEMS,180.
MLA	Kadigi, Ibrahim L.,et al."Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: A multivariate empirical (MVE) approach".AGRICULTURAL SYSTEMS 180(2020).