Contents lists available at ScienceDirect Agricultural Systems journal homepage: www.elsevier.com/locate/agsy Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: A multivariate empirical (MVE) approach Ibrahim L. Kadigi a,b, *, James W. Richardson c , Khamaldin D. Mutabazi a , Damas Philip a , Jean-Claude Bizimana c , Sixbert K. Mourice d , Betty Waized a a School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, P.O. Box 3007, Morogoro, Tanzania b Soil-Water Management Research Group, Sokoine University of Agriculture, P.O. Box 3003, Morogoro, Tanzania c Department of Agricultural Economics, Texas A&M University, College Station, TX 77845, United States d Department of Crop Science and Horticulture, Sokoine University of Agriculture, P.O. Box 3005, Morogoro, Tanzania ARTICLEINFO Keywords: Cereal crops MVE probability distribution Stochastic simulation Semi-arid area Sub-humid area Simetar ABSTRACT 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 in- creasing 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 depen- dence 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. 1. Introduction Maize (Zea mays L.), sorghum (Sorghum bicolor L. Moench) and rice (Oryza sativa) are major staple food crops in Sub Saharan Africa (SSA) consumed by people with varying food preferences and socio-economic backgrounds (Waithaka et al., 2013). The three staple crops are grown in diverse agro-ecological zones and farming systems and account for the largest share of calories and protein consumed in SSA (Macauley and Ramadjita, 2015). However, recent productivity trends and current performance of food crops in SSA are progressively less able to meet the needs of its rapidly increasing population. The low productivity of these crops in SSA is attributed to many constraints including high depen- dence on rain-fed agriculture, drought, floods, pest and diseases, and inadequate application of improved seed and fertilizers leading to food insecurity in rural areas (Ziervogel et al., 2006; Cooper et al., 2008; Ziervogel and Ericksen, 2010; URT, 2013; Kahimba et al., 2015; Wilson and Lewis, 2015). As the population of SSA is likely to grow to around 1.7 billion by 2050, demand for food to feed the population also increases (Waithaka et al., 2013). In the African Union (AU), recommitments have been https://doi.org/10.1016/j.agsy.2019.102693 Received 18 October 2018; Received in revised form 2 August 2019; Accepted 11 September 2019 ⁎ Corresponding author at: School of Agricultural Economics and Business Studies, Sokoine University of Agriculture, P.O. Box 3007, Morogoro, Tanzania. E-mail address: ibrahim.kadigi@sua.ac.tz (I.L. Kadigi). Agricultural Systems 180 (2020) 102693 Available online 20 December 2019 0308-521X/ © 2019 Elsevier Ltd. All rights reserved. T