Prepared by James Thurlow

1. COVID-19 and Rural-Urban
Poverty in Developing Countries
Lessons Learned, Remaining Questions
James Thurlow (IFPRI, Washington D.C.)
Workshop on “Rurbanomics and Common Prosperity” | September 24, 2021

2. Flattening the Curve (Rise of Models for Foresight Analysis)
Q1-Q2
2020
Q3-Q4 Q1-Q2
2021
Q3-Q4
Lockdowns Build back better
Relief & recovery
2022 2030
Longer-term analysis
Short-term analysis
Modeling short vs. long-term economic impacts
Case study countries
Modeling outbreaks

3. Short-Term Impacts (Early Model Estimates)
National GDP Changes
Large impacts, but smaller losses in agri-food systems (AFS)
Household Income Changes
Larger income losses for urban and non-poor households
Myanmar
Asia
Asia
Africa
Asia
Africa
Rural & urban (%)
Poor & non-poor (%)
Pakistan
Indonesia
Cambodia
Bangladesh
India
Rwanda
Nigeria
Ghana
Ethiopia
Malawi
Mali
Africa

4. Moving to Longer-Term Analysis
• Data sources
• Early IFPRI estimates (2020-2021)
• World Bank GDP projections (ends 2023, but no Delta!)
• Considerations
• How many future waves? (duration)
• Will future waves be less severe? (severity)
• Scenarios
• World Bank projection (no Delta)
• WB + Delta
• WB + Delta + Future Waves(in 2022, 2023, 2024 and/or 2025)
• Assumptions
• Future waves are scaled versions of past waves
• Economies & societies are adapting (i.e., similar-sized
outbreaks lead to smaller economic losses over time)
WB GDP Growth Projections (Jun 2021 vs. Jan 2020)
South Asia
Sub-Saharan Africa

5. Ethiopia | Modeled GDP Impacts
Deviations in GDP from “No COVID” baseline
-9%
-8%
-7%
-6%
-5%
-4%
-3%
-2%
-1%
0%
2019 20 21 22 23 24 25 26 27 28 29 2030
Total GDP
Agriculture
Industry
Services
-6%
-4%
-2%
0%
2%
4%
2019 20 21 22 23 24 25 26 27 28 29 2030
Total GDP
Agriculture
Industry
Services
WB + Delta scenario
GDP growth rates
lower than pre-COVID
expectations until
after 2022
Growth rates recover
but cumulative losses
remain (“lost years”)
Agriculture less affected
than other sectors
Deviation in GDP growth rates from baseline
Cumulative deviation in GDP from baseline
WB + Delta scenario

6. -1.9%
-2.3%
-0.4%
0.7%
1.3% 1.1%
0.5%
0.2%
-2.8%
-4.6%
-2.5%
0.4%
3.1%
3.4%
1.7%
0.6%
2020 2021 2022 2023 2024 2025 2026 2027
Rural Urban
Ethiopia | Modeled Consumption & Inequality Impacts
Consumption
Deviation in consumption growth
rate from No-COVID baseline
Inequality
National inequality index (Theil)
WB + Delta scenario
0.14
0.15
0.16
0.17
0.18
0.19
0.20
2019 20 21 22 23 24 25 26 27 28 29 2030
No-C19 baseline
With delta
Delta + 2022-25
Urban consumption levels fall by more than
rural consumption, but also recovers more
quickly once the COVID waves end
Inequality initially falls as the rural-urban gap
narrows, but both rural and urban households
experience falling consumption levels
WB projection | WB + Delta | WB + Delta plus annual waves until 2025

7. Ethiopia | Modeled Poverty Impacts
Deviations in poverty from “No COVID” baseline
WB + Delta scenario
WB + Delta scenario
Deviation in poverty headcount rate from No-COVID baseline
0%
1%
2%
3%
4%
5%
2019 20 21 22 23 24 25 26 27 28 29 2030
National
Rural
Urban
0
1
2
3
4
5
2019 20 21 22 23 24 25 26 27 28 29 2030
National
Rural
Urban
Increase in number of poor people due to COVID (millions)
Urban poverty rates
rise more than rural
poverty rates
But urban poverty
also recovers faster
Larger rural
population means
most of the absolute
increase in poverty is
in rural areas

8. Ethiopia | Considerable Uncertainty
Deviations in from “No COVID” baseline
Future waves would
mean much larger
GDP losses
Poverty could
continue to worsen
& undermine
development goals
Cumulative GDP losses caused by COVID
-10%
-8%
-6%
-4%
-2%
0%
2019 20 21 22 23 24 25 26 27 28 29 2030
WB projection
With delta
Delta + 2022 wave
Delta + 2022-23
Delta + 2022-24
Delta + 2022-25
Duration scenarios
Increase in poor people due to COVID (millions)
0
1
2
3
4
5
2019 20 21 22 23 24 25 26 27 28 29 2030
Latest projection
With delta
Delta + 2022
Delta + 2022-23
Delta + 2022-24
Delta + 2022-25
Duration scenarios

9. Other Countries | Modeled GDP & Poverty Impacts
Bangladesh Nigeria
-12%
-10%
-8%
-6%
-4%
-2%
0%
2019 20 21 22 23 24 25 26 27 28 29 30
Total GDP
Agriculture
Industry
Services
Cumulative deviation in GDP from baseline
WB + Delta scenario
-12%
-10%
-8%
-6%
-4%
-2%
0%
2019 20 21 22 23 24 25 26 27 28 29 2030
Total GDP
Agriculture
Industry
Services
Cumulative deviation in GDP from baseline
WB + Delta scenario
0.0
0.5
1.0
1.5
2.0
2.5
3.0
2019 20 21 22 23 24 25 26 27 28 29 2030
National
Rural
Urban
Increase in number of poor people due to COVID (millions)
Increase in number of poor people due to COVID (millions)
WB + Delta scenario
WB + Delta scenario
0.0
1.0
2.0
3.0
4.0
5.0
6.0
2019 20 21 22 23 24 25 26 27 28 29 2030
National
Rural
Urban

10. Lessons Learned, Remaining Questions
From Vulnerability to Recovery
• What did our early modeling get right?
• Agric. was less affected, but agri-food system still vulnerable
• Smaller income losses for rural households
• Agric. functioned as a “safety net” for many countries
• New insights (needing further study)
• More integrated food systems increase agric. & rural households’
exposure to COVID losses (e.g., Bangladesh)
• Urban households may recover quicker than rural households
• Avoiding future waves may be more important today than
building short-term resilience
• Remaining questions
• What is the role of policy in accelerating recovery?
• What determines the private sector’s ability to recover?
• Will COVID responses in urban areas crowd-out rural investment?
Recovery [2] driven by…
1. Policies and public investments
2. Private sector’s own actions