CGIAR Initiative on Foresight

Permanent URI for this collectionhttps://hdl.handle.net/10568/117889

Part of the CGIAR Action Area on Systems Transformation

Primary CGIAR impact area: Poverty reduction, livelihoods and jobs

https://www.cgiar.org/initiative/24-foresight-and-metrics-to-accelerate-inclusive-and-sustainable-agrifood-system-transformation/

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Now showing 1 - 20 of 419

Global Handbook of Rice Policies
(Book, 2024) Antonio, Ronald Jeremy; Valera, Harold Glenn; Durant-Morat, Alvado; Hoang, Hoa; Diagne, Mandiaye; Malakhail, Fazal; Pede, Valerien
The objective of this Handbook is to summarize global coverage of recent information on policy instruments used by governments to realize objectives related to rice production and supply, rice markets, and trade. Unlike previous work that focuses only on Asia, this Handbook attempts to provide a more comprehensive documentation of rice policies for Asia, Africa, the Americas, Europe, and the Middle East. Rice policies remain quite significant in many countries in these regions. Rice continues to play a significant role in food security in Asia and Africa, where rice production contributes 89% and 5% to global rice production, respectively. The changing role of rice in these two regions dramatically intensifies the need for information among policymakers who attach great weight to national food security imperatives in the crafting of rice programs. Similar to the United States and exporting countries in Asia, Latin America is also highly relevant for the world rice market since it houses some key rice exporters (i.e., Argentina, Brazil, and Uruguay). Likewise, rice is an important traded commodity in the Middle East, accounting for 13% of the world’s rice imports based on USDA estimates for 2023. Overall, this Handbook covers 70 countries and regions, which collectively account for 99% of global rice production and 98% of consumption.
Kenya tax model: Value added tax simulation analysis
(Brief, 2024) Shibia, Adan; Omune, Lensa; Mbuthia, Juneweenex; Diao, Xinshen; Oguso, Alex; Omwenga, Walter; Kiptoo, Elvis; Ali, Jecinta; Laichena, Joshua
Taxation can be used as a policy tool to influence economic behaviour, promote equity and achieve developmental goals. However, taxation can result in undesired outcomes if not well designed and implemented. Distortionary tax may adversely affect consumption, private sector investment (Adam and Bevan, 2014) and household welfare (de la Feria and Swistak, 2024). Kenya faces a similar trade-off between generating sufficient tax revenue to finance government programmes such as the Bottom-Up Economic Transformation Agenda (BETA) and mitigating potential adverse effects on domestic production and household welfare. The Value Added Tax (VAT) contributes about 30 per cent of Kenya’s total tax revenue (National Treasury, 2024). The average share of VAT to GDP for Kenya was 4.6 per cent between 2013/14 and 2023/24, comparable to that of East African Community (EAC) countries and Sub-Saharan African at 4.5 per cent (World Bank, 2024; East Africa Revenue Authorities Technical Committee, 2024), but lower than the 6.7 per cent for South Africa and the 5.2 per cent for lower-middle-income economies. VAT is a broad-based consumption tax, with tax incidence largely falling on the final consumers, and therefore any VAT policy changes have potential economy-wide implications. This is compounded by the fact that VAT is a regressive tax, meaning that low-income households spend a higher proportion of their income on vatable products compared to high income earners. The VAT in Kenya is currently imposed at a standard rate of 16 per cent, with certain essential goods, particularly primary agricultural produces, and services as VAT exempt or zero-rated.
A scalable crop yield estimation framework based on remote sensing of solar-induced chlorophyll fluorescence (SIF)
(Journal Article, 2024-04) Kira, Oz; Wen, Jiaming; Han, Jimei; McDonald, Andrew J.; Barrett, Christopher B.; Ortiz-Bobea, Ariel; Liu, Yanyan; You, Liangzhi; Mueller, Nathaniel D.; Sun, Ying
Projected increases in food demand driven by population growth coupled with heightened agricultural vulnerability to climate change jointly pose severe threats to global food security in the coming decades, especially for developing nations. By providing real-time and low-cost observations, satellite remote sensing has been widely employed to estimate crop yield across various scales. Most such efforts are based on statistical approaches that require large amounts of ground measurements for model training/calibration, which may be challenging to obtain on a large scale in developing countries that are most food-insecure and climate-vulnerable. In this paper, we develop a generalizable framework that is mechanism-guided and practically parsimonious for crop yield estimation. We then apply this framework to estimate crop yield for two crops (corn and wheat) in two contrasting regions, the US Corn Belt US-CB, and India's Indo–Gangetic plain Wheat Belt IGP-WB, respectively. This framework is based on the mechanistic light reactions (MLR) model utilizing remotely sensed solar-induced chlorophyll fluorescence (SIF) as a major input. We compared the performance of MLR to two commonly used machine learning (ML) algorithms: artificial neural network and random forest. We found that MLR-SIF has comparable performance to ML algorithms in US-CB, where abundant and high-quality ground measurements of crop yield are routinely available (for model calibration). In IGP-WB, MLR-SIF significantly outperforms ML algorithms. These results demonstrate the potential advantage of MLR-SIF for yield estimation in developing countries where ground truth data is limited in quantity and quality. In addition, high-resolution and crop-specific satellite SIF is crucial for accurate yield estimation. Therefore, harnessing the mechanism-guided MLR-SIF and rapidly growing satellite SIF measurements (with high resolution and crop-specificity) hold promise to enhance food security in developing countries towards more effective responses to food crises, agricultural policies, and more efficient commodity pricing.
Pathways to resilient dryland food systems in Africa: Strategic and tactical choices for accelerated impacts
(Report, 2024) Marenya, Paswel P.; Narmandakh, Davaatseren; Kirui, Leonard; Odhong, Jonathan A.; Sanni Abdulrahman; Aboudoulaye, Soule B.; Adam, Mamadou; Alex, Gerald; Belko, Marème N.; Bett, Charles; Dembele, Bandiougou; Derik, Sakatali P.; De Pee, Eric; Diatta, Cyril; Faye, Ndeye F.; Gichuru, Lilian; Kone, Bouréma; Kazombo, Samson F.M.; Kisilu, Rachael; Mchau, Devotha; Martey, Edward; Mbulwe, Lloyd; Ndubi, Jerika M.; Templer, Noel A.; Ouédraogo, Nofou; Opie, Hellen; Puozaa, Doris K.; Reoungel, Djinodji; Salegua, Venancio; Sawadogo-Compaoré, Eveline; Sime, Mekonnen; Zemedu, Lemma
Africa’s drylands form vital food systems, supporting a significant portion of its population and agricultural activity. However, they face persistent challenges with low productivity, limited market integration, and acute vulnerability to climate shocks. These issues contribute to structural poverty and high rates of undernourishment, highlighting the need for investments to improve rural incomes, enhance resilience, and foster economic growth.
Modeling crop-livestock interactions in semi-subsistence economies
(Poster, 2024-08-04) Aragie, Emerta A.; Thurlow, James
Climate and weather shocks pose significant threats to crop-livestock systems. Examine interactions and dynamic adjustments within the crop and livestock systems: Weather/climate shocks. Evaluate effectiveness of alternative adaptation strategies. Using spatially disaggregated Ethiopia data.
Informing food system transformation with foresight: Partners adopting the use of foresight and metrics tools
(Video, 2024-04) Mohan, Anisha; Anisimova, Evgeniya; Wolday, Tsega
Better-informed national policy choices – Governments and other decision makers in at least five countries contribute to and use foresight analysis to better reflect climate and other risks in policy dialogues and decision-making, including policies and investments designed to make food, land, and water systems more resilient, while recognizing synergies and trade-offs with other goals relating to nutrition, livelihoods, equity, and the environment. The videos are the result of three years established partnership with technical partners in three regions and six countries. The videos showcase on how the partnership established over the years have yielded the outcome expected. Together with these partners we have co-created and scaled our tools that are now widely used by the partners. In April 2024, the CGIAR Initiative on Foresight and the Institute for Integrated Development Studies (IIDS, Nepal) held the Foresight Partnership Forum and Training in Kathmandu, Nepal. The four-day event brought together key Initiative partners from across Asia, Africa, and Latin America to share insights on the multifaceted challenges affecting food, land, and water systems and strengthen local foresight and policy modeling capacity. During the event, we interviewed the Foresight Initiative partners from Argentina, Brazil, China, India, Indonesia, and South Africa and asked them to answer two questions: “Why did you join the Foresight Initiative and how is this partnership helping you in addressing the food systems issues in your countries?” and “How is the use of Foresight models helping you in advancing/informing strategies in your country?” *The letter of agreements with our partners can be available upon request.
Agrifood value chains in India: A state-level analysis using a social accounting matrix
(Working Paper, 2025-01-27) Pal, Barun Deb; Thurlow, James; Pauw, Karl; Diao, Xinshen; Ajmani, Manmeet Singh
This study describes disparities in per capita income, in the structure of the economy, and in agrifood systems (AFS) across states in India. We use the gross value added (GVA) obtained from state-specific agrifood value chains (AVCs) to describe the size and structure of the AFS in each state of India. This study also presents the size of employment and variability in labor productivity within the AFS across states. A special focus is given to female and youth employment in the state specific AVCs. The 2017/18 state-level social accounting matrix (SAM) for India is the primary data source for estimating statewise GVA from the AFS. Periodic Labor Force Survey data are used to estimate the size of AFS employment. Our results reveal that the bottom half of the Indian population has an average per capita income of US$1,019, 2.5 times lower than that of the top half. India’s AFS is valued at $756 billion, or 31 percent of its GVA. Primary agriculture comprises 59 percent of the AFS, and off-farm activities the rest. The share of off-farm activities in the AFS rises moving from lower-income states to higher-income states, corroborating the theory of structural transformation. The national average share of female workers in total employment is 23 percent and the majority of women who do work are engaged in primary agriculture. The share of women employed in the primary agriculture sector does not change between low- and high-income states in India. In contrast, the share of youth in primary agriculture declines between lower- and higher-income states. Since state governments in India are empowered to design their own policy and development strategies, this study provides an important policy insight to both the federal (central) and state governments.
Spatial downscaling of future food demand
(Presentation, 2024-11-22) Song, Chun; Yego, Francis; Petsakos, Athanasios; Gotor, Elisabetta
Building Ethiopia’s food security resilience to climate and hydrological change
(Journal Article, 2025-03) Murgatroyd, Anna; Thomas, Timothy S.; Koo, Jawoo; Strzepek, Kenneth M.; Hall, Jim
Historically Ethiopia's food security has been sensitive to climatic variability, but changes in future weather and climate could lead to overall reductions and increased variability in agricultural production, without further adaptation. We present an integrated modelling assessment framework which combines climate, crop, and hydrological modelling to quantify future risks to Ethiopia's food security. We explore the impacts of 2°C and higher climate change scenarios on water availability and crop yields and simulate how future climate shocks may impact Ethiopia's food. We consider three adaptations to agricultural management practices (improved seed varieties, increased use of nitrogen fertilizer and supplementary irrigation) and quantify their effectiveness in enhancing the resilience of Ethiopia's food system to climate and hydrological change by 2050. Results show that, without policy intervention, climate change creates a risk of declining Meher season crop yields across Ethiopia. Under the worst climate change scenario, teff (−12.0%), barley (−6.7%), and wheat (−4.4%) are projected to have the largest decline in average yields, whilst maize (−0.1%) and sorghum (+0.9%) yields are less impacted thanks to more favourable growing conditions. However, the results also indicate that the adaptation options have a bigger beneficial effect than the climate impact. Of the policies evaluated, improved seeds have a relatively greater effect than increased fertilizer use. Supplementary irrigation could help to mitigate increases in crop water requirements under warmer climate conditions and is most effective in drought prone basins and for drought-vulnerable crops. Overall, the results show that locally relevant agricultural policies are necessary to build Ethiopia's food system resilience to climate and hydrological change by the mid-century.
Ups and downs in the world rice market
(Newsletter, 2024-07-02) Pede, Valerien; Dawe, David
International rice prices have risen substantially. Over the past year, the main factors driving world market prices have been El Niño and the export restrictions from India, the world’s largest rice exporter. Since January 2024, however, prices have declined as El Niño conditions have ended. Fertilizer prices have declined substantially from their peaks in mid-2022 and have stabilized over the past year. These factors give grounds for optimism that international rice prices will stabilize or decline further in the near future.
World rice market update: more trade, better weather, lower prices
(Newsletter, 2024-12-14) Dawe, David; Pede, Valerien Olivier; Antonio, Ronald Jeremy
Good news: the recent developments in the global rice trading environment and improved weather conditions have lowered world market prices. As these factors lead to lower domestic prices, consumers will find it easier to afford a healthy diet. Improved trade World prices are now back to levels last seen before India’s restrictions were imposed in July 2023 (see the latest data point in Figure 1). This shift is largely influenced by the major rice trade policy changes in both the world’s largest exporter (India) and the world’s largest importer (the Philippines) in the past months. Beginning in late September and continuing over the succeeding weeks, India removed nearly all restrictions on rice exports in the face of large domestic stocks and prospects for an excellent forthcoming crop. These restrictions included a ban on non-basmati non-parboiled rice exports (with some exceptions for countries that needed imports for food security), a minimum export price on basmati rice and an export tax on parboiled rice, paddy, and husked rice.
Simulated Future Climates for Ethiopia Using MIT-IGSM HFDs Based on CMIP5
(Dataset, 2024-12-30) International Food Policy Research Institute; Massachusetts Institute of Technology
The dataset consists of high-resolution climate projections spanning 50 years, capturing spatial and temporal variations in temperature, precipitation, and extreme weather events. These climate inputs were combined with agricultural models to simulate the frequency, intensity, and impact of weather events on the yields of key crops, such as maize, in Ethiopia. It integrates hybrid frequency distributions (HFDs) from the Massachusetts Institute of Technology Integrated Global Systems Model (MIT-IGSM) with detrended gridded historical climates from Princeton Global Forcings. Using a Gaussian quadrature routine, 455 representative climate scenarios were selected for Ethiopia under each emissions scenario (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). This comprehensive dataset provides critical insights into the risks posed by climate change to food security and serves as a valuable resource for researchers and policymakers aiming to develop adaptive strategies for sustainable agriculture.
Introduction to spatial econometrics and its application in foresight initiative
(Presentation, 2024-06-13) Song, Chun
Foot-and-mouth Disease Management in Rwanda's Cattle Sector: A Multi-Model Approach Integrating Livestock Dynamics, Epidemiology, and Economic Analysis
(Brief, 2024-12-20) Jean-Pierre, Ralph; Enahoro, Dolapo K.; Bahta, Sirak T.; Aragie, Emerta A.; Rich, Karl M.
Water conflict in Africa: Understanding the impact of climatic and institutional factors
(Presentation, 2024-08-01) Song, Chun; Petsakos, Athanasios; Gotor, Elisabetta
Expert validation of the intrinsic productivity growth rates for cassava in Africa
(Report, 2024-12) Mjuma, A.; Gbegbelegbe, S.; Alene, A.
Expert validation of the intrinsic productivity growth rates for cowpea in West & Central Africa
(Report, 2024-12) Mjuma, A.; Gbegbelegbe, S.; Alene, A.
Dashboard for ex-ante, foresight, and impact assessment studies of food systems
(Website, 2024-12-13) Andrade, Robert; Orjuela Ramirez, Guillermo; Ossa Arias, Luis Miguel; Guerrero, Samuel; Esponda, Maria Del Mar; Rivera, Tatiana
The AgriForesight Dashboard offers bibliometric data on scientific publications, covering studies on Ex-ante, Foresight, and Impact Assessment in the field of food systems. It enables users to explore conceptual and social structures of knowledge.
GitHub training
(Presentation, 2024-07-31) Mishra, Abhijeet; Singh, Vartika
The presentation was given at IFPRI's New Delhi Office Office on July 31, 2024. There is an accompanying training document detailing the steps to utilize GitHub.
Bangladesh: Systematic analysis of climate and world market shocks
(Brief, 2024-12-30) Mukashov, Askar; Jones, Eleanor; Thurlow, James
This study explores Bangladesh’s vulnerability to economic and climatic shocks and identifies those contributing most to economic uncertainty. The Bangladesh Computable General Equilibrium (CGE) model was employed to simulate a range of potential economic outcomes under various shock scenarios sampled using historical data to capture domestic agricultural yield volatilities and world market price uncertainty for traded goods. Data mining and machine learning methods were applied to quantify the contribution of each shock to the uncertainty of economic outcomes (gross domestic product [GDP], private consumption, poverty, and undernourishment). Our findings suggest that potential variation in Bangladesh’s GDP ranges from +0.8 to -1.0 percent to baseline, with domestic climate shocks accounting for 53.7 percent of uncertainty, and remaining 41.7 percent are explained by the volatility of world market prices and Foreign Exchange (FX) flows. At the same time, private con sumption is more uncertain (from +4.0 to -3.5 percent to base), and external factors are the most important risk contributors (70.1 percent is world prices and 2.9 percent is FX flows). Similarly, external factors contribute roughly two-thirds to the potential variation of national poverty and undernourishment rates that fluctuate from -2.4 to +1.8 and –2.2 to +1.9 relative to the baseline rates percentage points respectively. Understanding how potential shocks might impact various segments of the Bangladesh economy and population is a critical first step in facilitating a discussion on risk mitigation strategies that include increasing sectoral productivity or diversifying production to reduce reliance on high-risk sectors.

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