Winners from the Food Security Simulator Kenya Blog Competition
CGIAR Initiative on National Policies and Strategies
On July 19, 2023, the CGIAR Research Initiative on National Policies and Strategies initiated a blog competition, inviting all attendees of the Food Security Simulator Kenya demonstration to participate. The competition winner would be eligible for a short-term industrial attachment/mentorship at IFPRI’s Kenya office and the top three blogs would be published on the CGIAR Research Initiative on National Policies and Strategies site. After receiving numerous submissions, our panel of judges composed of international and country experts has chosen the top three blogs below:
- Winner! Dorah Kwamboka Momanyi, Short-Term Effects of Food Price Shocks Ensuing Expiration of the Black Sea Grain Deal: A Food Security Simulation
- Moses Mahugu, The Widening Food Gap in Kenya amid Serious Drought: A Cry for Policy Reforms on Food Security
- Kefa Simiyu, From Income and Food Price Shocks to Food [In]security in Kenya: A Simulated Scenario Analysis
*Any opinions stated in the blog are those of the author(s) and are not necessarily representative of or endorsed by the CGIAR.
Short-Term Effects of Food Price Shocks Ensuing Expiration of the Black Sea Grain Deal: A Food Security Simulation
By Dorah Kwamboka Momanyi
Russia’s invasion of Ukraine has disrupted agriculture and trade, jeopardizing global food security, and, along with other factors, causing food prices to skyrocket globally – especially for wheat.
Wheat Outlook in Kenya
According to the 2023 Food Balance Sheet (FBS) published by the Kenya National Bureau of Statistics (KNBS), per capita consumption of wheat was 42.1 kilograms (kg), making it the third most important food crop after starchy roots and maize. However, Kenya’s average wheat production of roughly 0.3 million metric tons (MT) is often affected by drought and already high outlays for inputs must be increased to meet domestic wheat demand. In order to meet this deficit, Kenya imports 1.8 million MT, roughly 40 percent of which come from war-torn countries (FAOSTAT, 2022). Thus, Kenya is vulnerable to this global geopolitical crisis.
The Black Sea Grain Initiative
In July 2022, the United Nations supported the brokering of a deal between Ukraine, Turkey, and Russia that would allow Ukraine to ship 32.9 MT of food to 45 countries through the Black Sea. Up until August 2023, about 1 million MT and 6 million MT of food was exported directly to low- and lower-middle-income countries, respectively, with Kenya receiving tons. The World Food Programme has chartered 725,000 tons to countries most vulnerable to severe hunger, including 25,000 tons to Kenya.
Expiration of the Black Sea Grain Initiative
As of July 17, 2023, the rare diplomatic agreement ended. Exports of about 2.1 million MT in June dropped to just 0.2 tons in July. Coupled with the effects of climate change and COVID-19, the urban population in Kenya will be the hardest hit, due to over-reliance on market purchases.
Food Security Simulator Kenya Methodology
The Food Security Simulator Kenya (FSSK) was used to assess the short-term effects of urban wheat price shocks on urban food poverty, the prevalence of undernourishment, and diet-quality-related indicators, as shown in Table 1. The simulation used the Kenya Integrated Household Budget and Survey (KIHBS, 2015/16) household survey data. A 10 percent positive wheat price shock resulting from changes in wheat prices was used as an input in the tool. Wheat prices were derived from daily market indicators from Kenya’s Ministry of Agriculture.
Table 1: Simulation of the effects of rising wheat prices on poverty rates and the prevalence of undernourishment at urban and national levels
|Total||Change from baseline (%)|
|Residential area||Food poverty rate (%)||Prevalence of under-nourishment (%)||Food poverty rate (%)||Prevalence of under-nourishment (%)||Food poverty rate (%)||Prevalence of under-nourishment (%)|
Effects on Poverty Rates and Food Consumption
The simulation resulted in a 0.2 percent and 0.1 percent reduction in urban and national food poverty rates, respectively. Intuitively, food costs are expected to reduce disposable incomes during food inflation, resulting in higher poverty levels. In previous studies, however, they may have failed to account for the heterogeneous household preferences. The cross-price elasticities of demand, expressed by households and used in the FSSK, may lead to increases in the price of one food (such as wheat) leading to more consumption of other foods. And indeed, this is what the FSSK shows us, with households increasing consumption of fruits and vegetables while decreasing wheat consumption.
This is corroborated by simulation results from the FSSK tool for food consumption expenditure per capita, which increases by 1.1 percent and 0.5 percent at the urban and national levels, respectively. This finding is consistent with the household switching their preferences away from wheat as a source of calories, to somewhat more expensive sources of calories (such as vegetables), and thus increasing their net food expenditure.
The simulation also resulted in a 0.1 percent and 0.2 percent decrease in the prevalence of undernutrition in urban areas and at the national level, respectively. The simulation results also show a 0.5 percent improvement in the diet quality indicator and a 0.2 percent increase in the consumption of various food groups. These are all consistent with household preference switching into more diverse sources of calories following a price increase in wheat.
In the short term, Kenya could investigate alternate import sources, such as the United States and Canada, to meet short-term wheat deficits. Even though some wheat producers have limited or banned wheat exports completely, Kenya can leverage its diplomatic relationships to avert the looming hunger crisis.
In the long term, food system stakeholders should enact policies that enhance local wheat production. Implementation of the Kenyan government’s Bottom-Up Economic Transformation Agenda (BETA) prioritizes reduction in wheat imports and leverages the Africa Crop Production model (AfCP) developed by Akademiya2063. The model has earmarked the top five wheat-producing sub-counties expected to produce over 270,000 tons of wheat in 2022. In the face of climate change, the government may consider investing in collecting high-frequency accurate, disaggregated, and timely data to predict, track, and advise on wheat production patterns.
In conclusion, food price shocks caused by the Russia-Ukraine war and other global disruptions will continue to threaten global food security. The FSSK is thus a critical tool for rapid analyses of direct, household-level outcomes of food price and household income shocks, and policy responses. Kenya should prioritize using the tool and executing policy options to meet immediate and long-term wheat domestic demand.
Dorah Kwamboka Momanyi (firstname.lastname@example.org) is the winner of the CGIAR Research Initiative on National Policies and Strategies blog competition and a Young Professional at the Kenya Institute of Public Policy Research and Analysis (KIPPRA).
The Widening Food Gap in Kenya amid Serious Drought: A Cry for Policy Reforms on Food Security
By Moses Mahugu
The Global Hunger Index report ranked Kenya as one of the most at-risk countries in the world. Earlier in the year, the state of food insecurity in Kenya became conspicuously apparent following the effects of the war in Ukraine and intense drought, which destabilized the supply of staple foods and their prices. These shifts heavily impacted consumption practices in both rural and urban households. Dryland communities in Northern Kenya, for example, caved into pressures of drought, the intensity of which had not been seen in the last 40 years. There was a dire need to bridge the supply gap in staples, with the maize deficit alone reaching approximately 10 million 90kg bags. The public generally expected the national government to purchase available supply from farmers before resorting to imports. However, this alternative was not considered favorable even though it would guarantee adequate volumes in the short run while making economic savings. This decision was met with resentment from farmer groups and organizations that support small-scale farmers.
The Food Security Simulator-Kenya tool (FSSK)
This decision to import staple foods evoked pleas for the government to “make it, make sense” as ardent social media users would put it. This article analyzes the government’s decision and quantifies its potential implications. To understand the arguments that informed the government’s decision, I utilized the Food Security Simulator-Kenya (FSSK) tool to create evidence-based food security outcomes informed by changes in food prices and household incomes. The tool was created through a partnership of the Kenya Institute of Public Policy Research and Analysis (KIPPRA), the University of Nairobi, the International Food Policy Research Institute (IFPRI), and CGIAR.
Potential Gains in the Short Run from Importing Staples
The decision to import was based on the benefit of economies of scale and also the anticipated ripple effects to the population that would result from a reduction in the price of maize by 25 percent from 200 Kenyan shillings (Ksh) to Ksh150. Inputting this price decrease into the FSSK, resulted in a positive shift in various food security indicators.
For instance, the decision to import would improve access to food, which is indicated by a decrease in rates of food poverty and undernourishment by 1.4 percent and 3.5 percent, respectively (Table 1). Interestingly, urban households would be less food-poor than rural households. This may be explained by the difference in consumption patterns between urban and rural populations, where the former primarily consume maize in the form of packaged flour.
Table 1: Food Poverty and Undernourishment
|Simulated Impact (%)||Change from Baseline (% points)|
|Food poverty rate||National||21.7%||-1.4%|
|Prevalence of under-nourishment||National||31.4%||-3.5%|
Lower food prices will stimulate an increase in household expenditures. Remarkably, people in the low- to middle-income brackets would see an average increase in their food budget by 1.4 percent. Additionally, people within the same income groups will consume more energy-giving foods with an average increase in calorie intake of 6.8 percent. This projection is related to the trend in starch deprivation, which declines from 21 percent to 13.7 percent.
Table 2: Food expenditure, consumption, and dietary outcomes
|Change from Baseline (% points)|
|Food consumption expenditure per capita (KSh/day)||National||0.5%||1.9%||1.5%||0.9%||0.2%||-0.1%|
|Calorie consumption amount per adult equivalent (kcal/day)||National||5.0%||7.1%||7.1%||6.2%||4.6%||2.9%|
|Change from Baseline|
|Diet quality indicator||National||0.5%||0.7%||0.9%||0.4%||0.5%||0.0%|
|Average adequate food groups||National||8.7%||17.7%||12.9%||9.5%||2.6%||5.9%|
|Share of deprived households with sufficient food consumption||National||3.7%||2.0%||3.8%||4.0%||5.7%||2.8%|
Imports of food supplies will also drive an increase of approximately 4.9 percent in food sufficiency for rural households previously labelled food-deprived. However, only 1.3 percent of urban households of similar income will become food sufficient.
The potential increase in food consumption can also be perceived through the diet quality indicator. The tool predicts that urban households will spend 2.1 percent more money on food due to their preference for high-quality diets. Furthermore, they will consume a wider variety of foods (9.2 percent) compared to rural households (8.4 percent).
Thus, evidence shows that the decision to import is justified due to the improved access, availability, stability, and use of food by the wider population. Analysis from the FSSK tool does not necessarily argue for importation, but rather, increased supply of staples in the country. Therefore, policymakers should create policies that encourage farmers to increase production of staple crops by not only subsidizing production but also guaranteeing market access. Doing so would impact households’ food security, health and wellbeing, and the economy as a whole.
About the author:
Moses Mahugu (email@example.com)
From Income and Food Price Shocks to Food [In]security in Kenya: A Simulated Scenario Analysis
By Kefa Simiyu
The interplay between the COVID-19 pandemic, below average harvests, and the Russia-Ukraine war jeopardized households’ resilience to negative shocks while simultaneously heightening food insecurity. Negative disruptions of global food supply chains, amidst general declines in agricultural output in Kenya, have contributed to food inflation. As average incomes declined during the pandemic, purchasing power among poor and moderately-rich households declined. Yet, the extent to which these food price and income shocks affected Kenya’s food poverty is under-researched. It is against this backdrop that this blog analyzes how rural and urban food poverty are joint affected by income and price shocks using the new Food Security Simulator Kenya (hereafter, the FSSK) developed by the International Food Policy Research Institute (IFPRI) and partners.
DATA AND METHODOLOGY
The FSSK requires inputs of income shocks and/or price shocks. For the income changes, I leverage three datasets from nationwide household-level surveys that shed light on recent income trajectories. These datasets are the 2019 and 2021 Fin-Access Households Survey (Fin-Access) and the 2022 Kenya Demographic and Health Survey (KDHS). These datasets allow for household disaggregation based on income and residence. Similarly, households’ income trajectories can be analyzed over time using cross-sectional data. This is because I adopt a measure of annualized growth that does not necessarily require panel data (see Ray & Genicot (2023) for discussion). Price shocks are proxied by year-on-year inflation using data for selected food commodities retrieved from the Consumer Price Index (CPI).
Households are disaggregated into poor and nonpoor based on the upper-middle-income poverty line (see World Bank’s Poverty & Equity Brief). This is important since food poverty and income dynamics vary across social classes. Average incomes and annualized growth are reported in Table 1. Despite a general post-COVID (2021–2022) recovery, average incomes among the rural poor did not fully recover, as suggested by negative 2019–2022 annualized growth. In this analysis, annualized growth offers a benchmark for income shocks, thereby ensuring that simulation statistics are data-backed.
Table 1: Historical average incomes and annualized income growth
|Household group||Average income (Kenya shilling)||Annualized income growth|
Note: A household in group m experiences annualized income growth equal to from year z to z+l.
Annualized growth and inflation data are subsequently utilized in the FSSK. The FSSK enables one to analyze how people’s diets and food consumption are affected by shocks to household incomes and food prices in a partial equilibrium model. Baseline poverty rates are calculated using the 2015/16 Kenya Integrated Households Budget Survey (KIHBS) and show 23.2 percent of households were food poor, although the food poverty rate among rural households was higher (26.0 percent) than urban (19.3 percent).
I investigate two scenarios informed by the historical data: (1) a reduction in average income alongside price increases for potatoes, sugar, kale, and beef, as was observed in the data, and (2) an increase in average income alongside price inflation of fortified maize flour, salad oil, fresh packaged cow milk, kale, and beef with bones, to explore the counterfactual of income growth.
In the first scenario (in the Table 2 below), an additional 3.0 percent and 4.6 percent of rural and urban households, respectively, fall below the food poverty line in the microsimulation. In the second scenario, income and price shocks have a negligible impact on rural and urban food poverty. In particular, an additional 0.3 percent of rural households become food nonpoor whereas 0.2 percent of urban households become food poor.
Table 2: Simulation results
|Food poverty rate|
|Baseline (%)||Scenario 1||Scenario 2|
|Simulated Impact (%)||Change from Baseline (% points)||Simulated Impact (%)||Change from Baseline (% points)|
These findings suggest that food price inflation and negative income shocks reinforce each other in raising food poverty. Urban food poverty rises more than rural food poverty. These findings further indicate that positive income shocks counterbalance food price inflation, such that rising incomes compensate households for inflation-induced changes in their purchasing power. This blogpost supports Mutea et al. (2022) and Onyango et al. (2021). Utilizing KIHBS, the logit estimates in Mutea et al. (2022) suggested that negative income shocks raised Kenya’s food insecurity. Relying on the 2017 Hungry Cities Partnership Survey, and employing the generalized linear mixed model, Onyango et al. (2021) revealed that Nairobi’s food security significantly declined in food price increments.
CONCLUSIONS AND RECOMMENDATIONS
By analyzing the effects of food prices and income shocks on urban and rural food poverty in Kenya, I conclude that while falling incomes and rising food prices raise both rural and urban food poverty, rising food prices are counterbalanced by positive income growth. To address food insecurity in Kenya, I recommend the following:
- Expansion of the Hunger Safety Net Program and increases of cash transfer initiatives that target vulnerable groups by the national government.
- The roll-out of farm subsidies within Kenya’s arable rural lands by the Ministry of Agriculture in order to increase agricultural production and reduce rural food poverty.
- Economic diversification within the Bottom-Up Economic Transformation Agenda to raise household incomes and buffer households against food price inflation.
About the author
Kefa Simiyu (firstname.lastname@example.org)
The CGIAR Research Initiative on National Policies and Strategies (NPS) was launched with national and international partners to build policy coherence, respond to policy demands and crises, and integrate policy tools at national and subnational levels in countries in Africa, Asia, and Latin America. CGIAR centers participating in NPS are The Alliance of Bioversity International and the International Center for Tropical Agriculture (Alliance Bioversity-CIAT), International Food Policy Research Institute (IFPRI), International Livestock Research Institute (ILRI), International Water Management Institute (IWMI), International Potato Center (CIP), International Institute of Tropical Agriculture (IITA), and WorldFish. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund.