Publication: Predicting Food Crises
Loading...
Files in English
2,328 downloads
Date
2020-09
ISSN
Published
2020-09
Author(s)
Editor(s)
Abstract
Globally, more than 130 million people are estimated to be in food crisis. These humanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. The existing outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in their temporal frequency and ability to look beyond several months. This paper presents a statistical forecasting approach to predict the outbreak of food crises with sufficient lead time for preventive action. Different use cases are explored related to possible alternative targeting policies and the levels at which finance is typically unlocked. The results indicate that, particularly at longer forecasting horizons, the statistical predictions compare favorably to expert-based outlooks. The paper concludes that statistical models demonstrate good ability to detect future outbreaks of food crises and that using statistical forecasting approaches may help increase lead time for action.
Link to Data Set
Citation
“Spencer, Phoebe; Kraay, Aart; Wang, Dieter; Andree, Bo, Pieter Johannes. 2020. Predicting Food Crises. Policy Research Working Paper;No. 9412. © World Bank. http://hdl.handle.net/10986/34510 License: CC BY 3.0 IGO.”
Associated URLs
Associated content
Other publications in this report series
Publication The Future of Poverty(Washington, DC: World Bank, 2025-07-15)Climate change is increasingly acknowledged as a critical issue with far-reaching socioeconomic implications that extend well beyond environmental concerns. Among the most pressing challenges is its impact on global poverty. This paper projects the potential impacts of unmitigated climate change on global poverty rates between 2023 and 2050. Building on a study that provided a detailed analysis of how temperature changes affect economic productivity, this paper integrates those findings with binned data from 217 countries, sourced from the World Bank’s Poverty and Inequality Platform. By simulating poverty rates and the number of poor under two climate change scenarios, the paper uncovers some alarming trends. One of the primary findings is that the number of people living in extreme poverty worldwide could be nearly doubled due to climate change. In all scenarios, Sub-Saharan Africa is projected to bear the brunt, contributing the largest number of poor people, with estimates ranging between 40.5 million and 73.5 million by 2050. Another significant finding is the disproportionate impact of inequality on poverty. Even small increases in inequality can lead to substantial rises in poverty levels. For instance, if every country’s Gini coefficient increases by just 1 percent between 2022 and 2050, an additional 8.8 million people could be pushed below the international poverty line by 2050. In a more extreme scenario, where every country’s Gini coefficient increases by 10 percent between 2022 and 2050, the number of people falling into poverty could rise by an additional 148.8 million relative to the baseline scenario. These findings underscore the urgent need for comprehensive climate policies that not only mitigate environmental impacts but also address socioeconomic vulnerabilities.Publication Exports, Labor Markets, and the Environment(Washington, DC: World Bank, 2025-07-14)What is the environmental impact of exports? Focusing on 2000–20, this paper combines customs, administrative, and census microdata to estimate employment elasticities with respect to exports. The findings show that municipalities that faced increased exports experienced faster growth in formal employment. The elasticities were 0.25 on impact, peaked at 0.4, and remained positive and significant even 10 years after the shock, pointing to a long and protracted labor market adjustment. In the long run, informal employment responds negatively to export shocks. Using a granular taxonomy for economic activities based on their environmental impact, the paper documents that environmentally risky activities have a larger share of employment than environmentally sustainable ones, and that the relationship between these activities and exports is nuanced. Over the short run, environmentally risky employment responds more strongly to exports relative to environmentally sustainable employment. However, over the long run, this pattern reverses, as the impact of exports on environmentally sustainable employment is more persistent.Publication The Macroeconomic Implications of Climate Change Impacts and Adaptation Options(Washington, DC: World Bank, 2025-05-29)Estimating the macroeconomic implications of climate change impacts and adaptation options is a topic of intense research. This paper presents a framework in the World Bank's macrostructural model to assess climate-related damages. This approach has been used in many Country Climate and Development Reports, a World Bank diagnostic that identifies priorities to ensure continued development in spite of climate change and climate policy objectives. The methodology captures a set of impact channels through which climate change affects the economy by (1) connecting a set of biophysical models to the macroeconomic model and (2) exploring a set of development and climate scenarios. The paper summarizes the results for five countries, highlighting the sources and magnitudes of their vulnerability --- with estimated gross domestic product losses in 2050 exceeding 10 percent of gross domestic product in some countries and scenarios, although only a small set of impact channels is included. The paper also presents estimates of the macroeconomic gains from sector-level adaptation interventions, considering their upfront costs and avoided climate impacts and finding significant net gross domestic product gains from adaptation opportunities identified in the Country Climate and Development Reports. Finally, the paper discusses the limits of current modeling approaches, and their complementarity with empirical approaches based on historical data series. The integrated modeling approach proposed in this paper can inform policymakers as they make proactive decisions on climate change adaptation and resilience.Publication The Asymmetric Bank Distress Amplifier of Recessions(Washington, DC: World Bank, 2025-07-11)One defining feature of financial crises, evident in U.S. and international data, is asymmetric bank distress—concentrated losses on a subset of banks. This paper proposes a model in which shocks to borrowers’ productivity dispersion lead to asymmetric bank losses. The framework exhibits a “bank distress amplifier,” exacerbating economic downturns by causing costly bank failures and raising uncertainty about the solvency of banks, thereby pushing banks to deleverage. Quantitative analysis shows that the bank distress amplifier doubles investment decline and increases the spread by 2.5 times during the Great Recession compared to a standard financial accelerator model. The mechanism helps explain how a seemingly small shock can sometimes trigger a large crisis.Publication Impact of Heat Waves on Learning Outcomes and the Role of Conditional Cash Transfers(Washington, DC: World Bank, 2025-07-14)This paper evaluates the impact of higher temperatures on learning outcomes in Peru. The results suggest that 1 degree above 20°C is equivalent to 7 and 6 percent of a standard deviation of what a student learns in a year for math and reading tests, respectively. These results hold true when the main specification is changed, splitting the sample, collapsing the data at school level, and using other climate specifications. The paper aims to improve understanding of how to deal with the impacts of climate change on learning outcomes in developing countries. The evidence suggests that conditional cash transfer programs can mitigate the negative effects of higher temperatures on students’ learning outcomes in math and reading.
Journal
Journal Volume
Journal Issue
Collections
Related items
Showing items related by metadata.
Publication Stochastic Modeling of Food Insecurity(World Bank, Washington, DC, 2020-09)Recent advances in food insecurity classification have made analytical approaches to predict and inform response to food crises possible. This paper develops a predictive, statistical framework to identify drivers of food insecurity risk with simulation capabilities for scenario analyses, risk assessment and forecasting purposes. It utilizes a panel vector-autoregression to model food insecurity distributions of 15 Sub-Saharan African countries between October 2009 and February 2019. Statistical variable selection methods are employed to identify the most important agronomic, weather, conflict and economic variables. The paper finds that food insecurity dynamics are asymmetric and past-dependent, with low insecurity states more likely to transition to high insecurity states than vice versa. Conflict variables are more relevant for dynamics in highly critical stages, while agronomic and weather variables are more important for less critical states. Food prices are predictive for all cases. A Bayesian extension is introduced to incorporate expert opinions through the use of priors, which lead to significant improvements in model performance.Publication Pollution and Expenditures in a Penalized Vector Spatial Autoregressive Time Series Model with Data-Driven Networks(World Bank, Washington, DC, 2019-02)This paper introduces a Spatial Vector Autoregressive Moving Average (SVARMA) model in which multiple cross-sectional time series are modeled as multivariate, possibly fat-tailed, spatial autoregressive ARMA processes. The estimation requires specifying the cross-sectional spillover channels through spatial weights matrices. the paper explores a kernel method to estimate the network topology based on similarities in the data. It discusses the model and estimation, focusing on a penalized Maximum Likelihood criterion. The empirical performance of the estimator is explored in a simulation study. The model is used to study a spatial time series of pollution and household expenditure data in Indonesia. The analysis finds that the new model improves in terms of implied density, and better neutralizes residual correlations than the VARMA, using fewer parameters. The results suggest that growth in household expenditures precedes pollution reduction, particularly after the expenditures of poorer households increase; that increasing pollution is followed by reduced growth in expenditures, particularly reducing the growth of poorer households; and that there are significant spillovers from bottom-up growth in expenditures. The paper does not find evidence for top-down growth spillovers. Feedback between the identified mechanisms may contribute to pollution-poverty traps and the results imply that pollution damages are economically significant.Publication Machine Learning Guided Outlook of Global Food Insecurity Consistent with Macroeconomic Forecasts(World Bank, Washington, DC, 2022-10)Motivated by the deterioration in global food security conditions, this paper develops a parsimonious machine learning model to derive a multi-year outlook of global severe food insecurity from macro-economic projections. The objective is to provide forecasts that are internally consistent with wider economic assessments, allowing both food security policies and economic development policies to be informed by a cohesive set of expectations. The model is validated on holdout data that explicitly test the ability to forecast new data from history and extrapolate beyond observed intervals. It is then applied to the World Economic Outlook database of April 2022 to project the severely food insecure population across all 144 World Bank lending countries. The analysis estimates that the global severely food insecure population may remain above 1 billion through 2027 unless large-scale interventions are made. The paper also explores counterfactual scenarios, first to investigate additional risks in a downside economic scenario, and second, to investigate whether restoring macroeconomic targets is sufficient to revert food insecurity back to pre-pandemic levels. The paper concludes that the proposed model provides a robust and low-cost approach to maintain reliable long-term projections and produce scenario analyses that can be revised systematically and interpreted within the context of available economic outlooks.Publication Environment and Development(World Bank, Washington, DC, 2019-02)This paper revisits the issue of environment and development raised in the 1992 World Development Report, with new analysis tools and data. The paper discusses inference and interpretation in a machine learning framework. The results suggest that production gradually favors conserving the earth's resources as gross domestic product increases, but increased efficiency alone is not sufficient to offset the effects of growth in scale. Instead, structural change in the economy shapes environmental outcomes across GDP. The analysis finds that average development is associated with an inverted $U$-shape in deforestation, pollution, and carbon intensities. Per capita emissions follow a $J$-curve. Specifically, poverty reduction occurs alongside degrading local environments and higher income growth poses a global burden through carbon. Local economic structure further determines the shape, amplitude, and location of tipping points of the Environmental Kuznets Curve. The models are used to extrapolate environmental output to 2030. The daunting implications of continued development are a reminder that immediate and sustained global efforts are required to mitigate forest loss, improve air quality, and shift the global economy to a 2°pathway.Publication Comparative Analysis of AI-Predicted and Crowdsourced Food Prices in an Economically Volatile Region(Washington, DC: World Bank, 2024-04-23)High-frequency monitoring of food commodity prices is important for assessing and responding to shocks, especially in fragile contexts where timely and targeted interventions for food security are critical. However, national price surveys are typically limited in temporal and spatial granularity. It is cost prohibitive to implement traditional data collection at frequent timescales to unravel spatiotemporal price evolution across market segments and at subnational geographic levels. Recent advancements in data innovation offer promising solutions to address the paucity of commodity price data and guide market intelligence for diverse development stakeholders. The use of artificial intelligence to estimate missing price data and a parallel effort to crowdsource commodity price data are both unlocking cost-effective opportunities to generate actionable price data. Yet, little is known about how the data from these alternative methods relate to independent ground truth data. To evaluate if these data strategies can meet the long-standing demand for real-time intelligence on food affordability, this paper analyzes open-source daily crowdsourced data (104,931 datapoints) from a recently published data set in Nature Journal, relative to complementary ground truth sample. The paper subsequently compares these data to open-source monthly artificial intelligence–generated price data for identical commodities over a 36-month period in northern Nigeria, from 2019 to 2022. The results show that all the data sources share a high degree of comparability, with variation across commodity and market segments. Overall, the findings provide important support for leveraging these new and innovative data approaches to enable data-driven decision-making in near real time.
Users also downloaded
Showing related downloaded files
Publication Making Devolution Work for Service Delivery in Kenya(Washington, DC: World Bank, 2022-02)Kenya adopted a new constitution and began the process of devolution in 2010, ceding many formerly national responsibilities to new county governments. As an institutional response to longstanding grievances, this radical restructuring of the Kenyan state had three continuing main objectives: decentralizing political power, public sector functions, and public finances; ensuring a more equitable distribution of resources among regions; and promoting more accountable, participatory, and responsive government at all levels. The first elections under the new constitution were held in 2013 and led to the establishment of 47 new county governments. Each county government is made up of a county executive, headed by an elected governor, and an elected County Assembly that legislates and provides oversight. Making Devolution Work for Service Delivery in Kenya takes stock of how devolution has affected the delivery of basic services to Kenyan citizens nine years after the “devolution train” left the station. Whereas devolution was driven by political reform, the ensuing institutions and systems were expected to deliver greater socioeconomic equity through devolved service delivery. Jointly coordinated by the government of Kenya and the World Bank, the Making Devolution Work for Service Delivery (MDWSD) study is the first major assessment of Kenya’s devolution reform. The study provides key messages about what is working, what is not working, and what could work better to enhance service delivery based on currently available data. It provides an independent assessment of service delivery performance in five sectors: agriculture, education, health, urban services, and water services. This assessment includes an in-depth review of the main pillars of devolved service delivery: accountability, human resource management, intergovernmental finance, politics, and public financial management. In addition to its findings for the present, the MDWSD study provides recommendations on how Kenya can improve its performance in each of these pivotal areas in the future.Publication Ten Steps to a Results-Based Monitoring and Evaluation System : A Handbook for Development Practitioners(Washington, DC: World Bank, 2004)An effective state is essential to achieving socio-economic and sustainable development. With the advent of globalization, there are growing pressures on governments and organizations around the world to be more responsive to the demands of internal and external stakeholders for good governance, accountability and transparency, greater development effectiveness, and delivery of tangible results. Governments, parliaments, citizens, the private sector, Non-governmental Organizations (NGOs), civil society, international organizations, and donors are among the stakeholders interested in better performance. As demands for greater accountability and real results have increased, there is an attendant need for enhanced results-based monitoring and evaluation of policies, programs, and projects. This handbook provides a comprehensive ten-step model that will help guide development practitioners through the process of designing and building a results-based monitoring and evaluation system. These steps begin with a 'readiness assessment' and take the practitioner through the design, management, and importantly, the sustainability of such systems. The handbook describes each step in detail, the tasks needed to complete each one, and the tools available to help along the way.Publication Fiscal Incidence Analysis for Kenya(World Bank, Washington, DC, 2018-06-29)Kenya has made satisfactory progress in reducing poverty and inequality in recent years. Economic growth in Kenya between 2005-06 and 2015-16 averaged around 5.3 percent, exceeding the average growth of 4.9 percent observed for Sub-Saharan Africa. This robust economic growth resulted in a reduction in poverty, whether measured by the national or international poverty line. The proportion of the population living beneath the national poverty line fell from 46.8 percent in 2005-06 to 36.1 percent in 2015-16, showing a modest improvement in the living standards of the Kenyan population. Similarly, poverty under the international poverty line of US$ 1.90 a day declined from 43.6 percent in 2005-06 to 35.6 percent in 2015-16. At this level, poverty in Kenya is below the average in sub-Saharan Africa and is amongst the lowest in the East African Community (World Bank, 2018b). However, the proportion of the population living in poverty remains comparatively high in Kenya and the rate at which growth translated into poverty reduction was lower than elsewhere. At twice the average, Kenya’s poverty rate is still high for a lower-middle income country, a group that Kenya joined only in 2015. In addition, the Kenya’s growth elasticity of poverty reduction, the percentage reduction in the poverty rate associated with a one-percent increase in mean per capita income is only 0.57, lower than in Tanzania, Ghana, or Uganda (World Bank, 2018b). This leads to the obvious question of what can be done to make economic growth more pro-poor in Kenya. This study assesses the distributional consequences of Kenya’s system of taxes and transfers, covering 60 percent of revenue and between 25 and 30 percent of government spending. The analysis of fiscal incidence and distributional consequences of Kenya’s tax and transfer system is an important input for designing pro-poor policies and potentially for influencing the rate at which economic growth translates into poverty reduction. In this study, direct taxes and transfers, indirect taxes (VAT and excise duties), as well as public health and education spending are assessed in terms of their distributional impacts. Overall, these taxes and transfers account for about 60 percent of revenue and between 25 and 30 percent of government spending.Publication Nigeria Development Update, June 2021(World Bank, Washington, DC, 2021-06)In 2020, Nigeria experienced its deepest recession in four decades, but growth resumed in the fourth quarter as pandemic restrictions were eased, oil prices recovered, and the authorities implemented policies to counter the economic shock. As a result, in 2020 the Nigerian economy experienced a smaller contraction (-1.8 percent) than had been projected when the pandemic began (-3.2 percent). As part of its response, the government carried out several long-delayed policy reforms, often against vocal opposition. Notably, the government (1) began to harmonize exchange rates; (2) began to eliminate gasoline subsidies; (3) started adjusting electricity tariffs to more cost-reflective levels; (4) cut nonessential spending and redirected resources to COVID-19 (coronavirus) responses at both the federal and the state levels; and (5) enhanced debt management and increased public-sector transparency, especially for oil and gas operations. By creating additional fiscal space and maximizing the impact of the government’s limited resources, these measures were critical in protecting the economy against a much deeper recession and in laying the foundation for earlier recovery. However, several critical reforms are as yet incomplete, which threatens Nigeria’s nascent recovery. In the baseline scenario, Nigeria’s economy is expected to grow by 1.8 percent in 2021. Despite the current favorable external environment, with oil prices recovering and growth in advanced economies, reform slippages would hinder the renewed economic expansion and undermine progress toward Nigeria’s development goals. In a risk scenario, in which the government fails to sustain recent macroeconomic and structural reforms, the pace of economic recovery would slow, and GDP growth couldbe just 1.1 percent in 2021.Publication Managing County Assets and Liabilities in Kenya(Washington, DC : World Bank, 2022)Public entities around the world possess an enormous volume of assets and wealth, which includes land, buildings, historic sites, parks, and infrastructure networks, among many others. Good management of such assets is a catalyst for accelerating development and expanding services; poor asset management generates enormous losses, including lost opportunities to build wealth. Private enterprises increasingly use computerized systems to manage assets such as fleets and buildings. Many city leaders in developing countries, however, are unaware of asset management or feel they lack the time or money to undertake it. Managing County Assets and Liabilities in Kenya: Postdevolution Challenges and Responses can help them begin or maintain their efforts to manage assets sustainably. This book helps readers understand the basic concept of asset management; explains systems, tools, and procedures; and provides models and guidance. Kenya has achieved much since its 2013 devolution of governance and management to new counties. However, counties, which are the local governments in Kenya, are still working toward establishing systems and procedures, creating asset and liability registers, verifying and valuing assets, using assets strategically, and resolving disputes surrounding inherited assets and liabilities. This book provides glimpses into the Kenyan devolution process and asset transfer challenges, draws lessons, and explores options relevant to both Kenya and other nations. Ample studies discuss various aspects of municipal asset management, such as managing infrastructure, fixed assets, water services, building properties, roads, or fleets. This book is unique among asset management studies in three ways: it discusses all sorts of assets and liabilities and their interlinkages, exemplifies the close connection between financial results and asset management of municipalities, and reveals the political economy challenges in transferring assets and liabilities across public entities.