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Spatial Heterogeneity of COVID-19 Impacts on Urban Household Incomes : Between- and Within-City Evidence from Two African Countries (English)

This paper examines spatial heterogeneity in the impacts of the early days of the COVID-19 pandemic on urban household incomes in Ethiopia and Kinshasa, Democratic Republic of Congo. Combining new panel household surveys with spatial data, the fixed-effects regression analysis for Ethiopia finds that households in large and densely populated towns were more likely to lose their labor incomes in the early phase of the pandemic, and their recovery was slower than other households. Disadvantaged groups, such as female, low-skilled, self-employed, and poor, particularly suffered in those towns. In Kinshasa, labor income-mobility elasticities are higher among workers—particularly female and/or low-skilled workers—who live in areas that are located farther from the city core area or highly dense and precarious neighborhoods. The between- and within-city evidence from two Sub-Saharan African countries points to the spatial heterogeneity of COVID-19 impacts, implying the critical role of mobility and accessibility in urban agglomerations.

Details

  • Author

    Batana,Yele Maweki, Nakamura,Shohei, Rajashekar,Anirudh Venkatanarayan, Viboudoulou Vilpoux,Mervy Ever, Wieser,Christina

  • Document Date

    2021/08/30

  • Document Type

    Policy Research Working Paper

  • Report Number

    WPS9762

  • Volume No

    1

  • Total Volume(s)

    1

  • Country

    Ethiopia,

    Congo, Democratic Republic of

  • Region

    Africa East,

  • Disclosure Date

    2021/08/30

  • Disclosure Status

    Disclosed

  • Doc Name

    Spatial Heterogeneity of COVID-19 Impacts on Urban Household Incomes : Between- and Within-City Evidence from Two African Countries

  • Keywords

    labor income; Poverty and Equity; female-headed household; travel to work; urban household; lack of written contract; income loss; large town; urban labor market; household fixed effect; income reduction; state of emergency; high population density; impacts on employment; central business district; city core area; movement data; mobility index; household characteristic; accessibility to job; land use management; Work Remotely; private sector wage; time per day; freedom of movement; parameter of interest; Ownership Share Type; low population density; effect on employment; social security payment; urban agglomeration economy; terms of consumption; household head; household income; low-skilled worker; regression analysis; residential location; standard error; estimation result; labor outcomes; population size; urban economics; high probability; household size; consumption quintile; building density; urban worker; consumption level; coefficient estimate; poor household; spatial mismatch; robustness check; transport subsidy; income shock; national statistical; employment rate; welfare impact; household level; enumeration area; time-invariant variable; econometric model; zip code; conceptual framework; job opportunities; job opportunity; employment outcome; transport service; econometric analysis; public economics; regression model; phone number; high frequency; dependency ratio; large population; state service; female workers; urban population; Learning and Innovation Credit; coping strategy; disadvantaged worker; education level; household survey; recycled materials; retail trade; population characteristic; business cycle; sheet metal; casual laborers; job loss; steep slope; federal system; industrial area; Young Workers; massive layoff; older worker; school closure; income impact; economic sector; urban resident; agricultural jobs; empirical analysis; urban entity; mitigation measure; educational activities; agricultural worker; employment dynamic; employment information; human settlement; summary statistic; survey sample; european commission; baseline survey; increased income; telephone call; market garden; undeveloped areas; health emergency; administrative boundary; survey methodology; environmental features; city government; central market; Grocery Store; rural area; high share; confirmed case; employment type; parameter estimate; movement restriction; social distance; estimate impact; ppp terms; recent studies; employment condition; individual characteristic; transport development; casual worker; tight restriction; Cash Transfer; research design; phone penetration; regression results; measurement error; positive coefficient; disadvantaged household; female head; workers experience; in economics; youth unemployment; search cost; quantitative evidence; living standard; open access; development policy; poverty status; panel data; short-term impact; Research Support; short term impact; human mobility; social consequence; containment policy; job displacement; real time; emergency food; spatial structure; marital status; national emergency; estimated elasticity; income elasticity; quarantine facility; protective equipment; public assistance; survey period; liquidity injection; forbearance measure; Financial Sector; government restriction; big data; low-income worker; african americans; household labor; subnational levels; consumer spend; productivity gain; density variable; limited mobility; residential area; metropolitan area; physical accessibility; geographic level

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Citation

Batana,Yele Maweki Nakamura,Shohei Rajashekar,Anirudh Venkatanarayan Viboudoulou Vilpoux,Mervy Ever Wieser,Christina

Spatial Heterogeneity of COVID-19 Impacts on Urban Household Incomes : Between- and Within-City Evidence from Two African Countries (English). Policy Research working paper,no. WPS 9762,COVID-19 (Coronavirus) Washington, D.C. : World Bank Group. http://documents.worldbank.org/curated/en/673551630347904909/Spatial-Heterogeneity-of-COVID-19-Impacts-on-Urban-Household-Incomes-Between-and-Within-City-Evidence-from-Two-African-Countries