Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda
The authors use the night lights (satellite imagery from outer space) approach to estimate subnational 2013 GDP growth and levels for 47 counties in Kenya and 30 districts in Rwanda. Estimating subnational GDP is consequential for three reasons: Fi...
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| Language: | English en_US |
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World Bank, Washington, DC
2015
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| Online Access: | http://documents.worldbank.org/curated/en/2015/10/25160952/republic-kenya-bright-lights-big-cities-measuring-national-sub-national-economic-growth-outer-space-africa-application-kenya-rwanda http://hdl.handle.net/10986/22922 |
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okr-10986-229222021-04-23T14:04:12Z Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda Bundervoet, Tom Maiyo, Laban Sanghi, Apurva EXPENDITURE GROWTH RATES SUB-NATIONAL CONSUMPTION REVENUE SHARING POVERTY LINE DISECONOMIES OF SCALE EQUAL SHARES ECONOMIC GROWTH NATIONAL ACCOUNTS ESTIMATION METHOD CITY POVERTY LEVELS COEFFICIENTS FINANCIAL CRISIS INCOME VALUE DEPENDENT VARIABLE REVENUE ALLOCATION NATIONAL POVERTY LINE ECONOMIC DECLINE ANNUAL GROWTH RATE REAL GDP DISTRICT ADMINISTRATIONS GDP PER CAPITA RESOURCE ALLOCATION NATIONAL INCOME ELASTICITY URBAN AREAS DISTRIBUTION OF INCOME AGRICULTURAL SECTOR AGRICULTURE INCENTIVES DISTRICT- LEVEL SUBNATIONAL UNITS PROVINCES ANNUAL GROWTH TAX INPUTS CITIES WEALTH SURVEYS ECONOMICS AGRICULTURAL OUTPUT FIXED EFFECTS SUBNATIONAL ECONOMIC ACTIVITY SUB- NATIONAL PRO-POOR GDP LONG-TERM GROWTH GROWTH RATE INFORMAL ECONOMY POVERTY SUBNATIONAL GOVERNMENTS REVENUE-RAISING CAPACITY ECONOMIC DOWNTURNS DISTRICT INCIDENCE OF POVERTY REVENUE AGRICULTURAL PERFORMANCE CRITERIA UNDERESTIMATES POOR TAX BASE DISTRICT-LEVEL HOUSEHOLD SURVEYS INDICATORS EMPIRICAL MODEL DISTRICT LEVEL GROSS DOMESTIC PRODUCT REVENUE SHARING FORMULA DEVELOPMENT INDICATORS DISTRICTS EXPENDITURE NEEDS ECONOMIC CONDITIONS SUBNATIONAL ENTITIES SUB-NATIONAL UNIT GROWTH The authors use the night lights (satellite imagery from outer space) approach to estimate subnational 2013 GDP growth and levels for 47 counties in Kenya and 30 districts in Rwanda. Estimating subnational GDP is consequential for three reasons: First, there is strong policy interest in seeing how growth can occur in different parts of countries, so that communities can share in national prosperity and not get left behind. Second, sub-nationals themselves want to understand how they stack up against their neighbors and competitors, and how much they contribute to national GDP. Third, such information could help private investors to better assess where to undertake investments. Using night lights has the advantage of seeing a new (and more accurate) estimation of informal activity, and being independent of official data. However it may underestimate economic activity in sectors that are largely unlit (notably agriculture). Indeed, we find that the association between nightlights and GDP is stronger where unlit agriculture accounts for a smaller part of overall economic activity. With these caveats in mind, our analysis yields some interesting results. For Kenya, our results affirm that Nairobi County is the largest contributor to national GDP. However, at 13 percent, this contribution is lower (of 60 percent) as commonly thought. For Rwanda, the three Districts of Kigali account for 40 percent of national GDP, underscoring the lower scale of economic activity in the rest of the country. To get a composite picture of subnational economic activity, especially in the context of rapidly improving official statistics in Kenya and Rwanda, the authors note the importance of estimating subnational GDP using standard approaches (production, expenditure, income). 2015-11-09T23:00:35Z 2015-11-09T23:00:35Z 2015-10-16 Report http://documents.worldbank.org/curated/en/2015/10/25160952/republic-kenya-bright-lights-big-cities-measuring-national-sub-national-economic-growth-outer-space-africa-application-kenya-rwanda http://hdl.handle.net/10986/22922 English en_US CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo/ World Bank World Bank, Washington, DC Economic & Sector Work Economic & Sector Work :: General Economy, Macroeconomics, and Growth Study Africa Kenya |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English en_US |
| topic |
EXPENDITURE GROWTH RATES SUB-NATIONAL CONSUMPTION REVENUE SHARING POVERTY LINE DISECONOMIES OF SCALE EQUAL SHARES ECONOMIC GROWTH NATIONAL ACCOUNTS ESTIMATION METHOD CITY POVERTY LEVELS COEFFICIENTS FINANCIAL CRISIS INCOME VALUE DEPENDENT VARIABLE REVENUE ALLOCATION NATIONAL POVERTY LINE ECONOMIC DECLINE ANNUAL GROWTH RATE REAL GDP DISTRICT ADMINISTRATIONS GDP PER CAPITA RESOURCE ALLOCATION NATIONAL INCOME ELASTICITY URBAN AREAS DISTRIBUTION OF INCOME AGRICULTURAL SECTOR AGRICULTURE INCENTIVES DISTRICT- LEVEL SUBNATIONAL UNITS PROVINCES ANNUAL GROWTH TAX INPUTS CITIES WEALTH SURVEYS ECONOMICS AGRICULTURAL OUTPUT FIXED EFFECTS SUBNATIONAL ECONOMIC ACTIVITY SUB- NATIONAL PRO-POOR GDP LONG-TERM GROWTH GROWTH RATE INFORMAL ECONOMY POVERTY SUBNATIONAL GOVERNMENTS REVENUE-RAISING CAPACITY ECONOMIC DOWNTURNS DISTRICT INCIDENCE OF POVERTY REVENUE AGRICULTURAL PERFORMANCE CRITERIA UNDERESTIMATES POOR TAX BASE DISTRICT-LEVEL HOUSEHOLD SURVEYS INDICATORS EMPIRICAL MODEL DISTRICT LEVEL GROSS DOMESTIC PRODUCT REVENUE SHARING FORMULA DEVELOPMENT INDICATORS DISTRICTS EXPENDITURE NEEDS ECONOMIC CONDITIONS SUBNATIONAL ENTITIES SUB-NATIONAL UNIT GROWTH |
| spellingShingle |
EXPENDITURE GROWTH RATES SUB-NATIONAL CONSUMPTION REVENUE SHARING POVERTY LINE DISECONOMIES OF SCALE EQUAL SHARES ECONOMIC GROWTH NATIONAL ACCOUNTS ESTIMATION METHOD CITY POVERTY LEVELS COEFFICIENTS FINANCIAL CRISIS INCOME VALUE DEPENDENT VARIABLE REVENUE ALLOCATION NATIONAL POVERTY LINE ECONOMIC DECLINE ANNUAL GROWTH RATE REAL GDP DISTRICT ADMINISTRATIONS GDP PER CAPITA RESOURCE ALLOCATION NATIONAL INCOME ELASTICITY URBAN AREAS DISTRIBUTION OF INCOME AGRICULTURAL SECTOR AGRICULTURE INCENTIVES DISTRICT- LEVEL SUBNATIONAL UNITS PROVINCES ANNUAL GROWTH TAX INPUTS CITIES WEALTH SURVEYS ECONOMICS AGRICULTURAL OUTPUT FIXED EFFECTS SUBNATIONAL ECONOMIC ACTIVITY SUB- NATIONAL PRO-POOR GDP LONG-TERM GROWTH GROWTH RATE INFORMAL ECONOMY POVERTY SUBNATIONAL GOVERNMENTS REVENUE-RAISING CAPACITY ECONOMIC DOWNTURNS DISTRICT INCIDENCE OF POVERTY REVENUE AGRICULTURAL PERFORMANCE CRITERIA UNDERESTIMATES POOR TAX BASE DISTRICT-LEVEL HOUSEHOLD SURVEYS INDICATORS EMPIRICAL MODEL DISTRICT LEVEL GROSS DOMESTIC PRODUCT REVENUE SHARING FORMULA DEVELOPMENT INDICATORS DISTRICTS EXPENDITURE NEEDS ECONOMIC CONDITIONS SUBNATIONAL ENTITIES SUB-NATIONAL UNIT GROWTH Bundervoet, Tom Maiyo, Laban Sanghi, Apurva Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda |
| geographic_facet |
Africa Kenya |
| description |
The authors use the night lights
(satellite imagery from outer space) approach to estimate
subnational 2013 GDP growth and levels for 47 counties in
Kenya and 30 districts in Rwanda. Estimating subnational GDP
is consequential for three reasons: First, there is strong
policy interest in seeing how growth can occur in different
parts of countries, so that communities can share in
national prosperity and not get left behind. Second,
sub-nationals themselves want to understand how they stack
up against their neighbors and competitors, and how much
they contribute to national GDP. Third, such information
could help private investors to better assess where to
undertake investments. Using night lights has the advantage
of seeing a new (and more accurate) estimation of informal
activity, and being independent of official data. However it
may underestimate economic activity in sectors that are
largely unlit (notably agriculture). Indeed, we find that
the association between nightlights and GDP is stronger
where unlit agriculture accounts for a smaller part of
overall economic activity. With these caveats in mind, our
analysis yields some interesting results. For Kenya, our
results affirm that Nairobi County is the largest
contributor to national GDP. However, at 13 percent, this
contribution is lower (of 60 percent) as commonly thought.
For Rwanda, the three Districts of Kigali account for 40
percent of national GDP, underscoring the lower scale of
economic activity in the rest of the country. To get a
composite picture of subnational economic activity,
especially in the context of rapidly improving official
statistics in Kenya and Rwanda, the authors note the
importance of estimating subnational GDP using standard
approaches (production, expenditure, income). |
| format |
Report |
| author |
Bundervoet, Tom Maiyo, Laban Sanghi, Apurva |
| author_facet |
Bundervoet, Tom Maiyo, Laban Sanghi, Apurva |
| author_sort |
Bundervoet, Tom |
| title |
Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda |
| title_short |
Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda |
| title_full |
Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda |
| title_fullStr |
Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda |
| title_full_unstemmed |
Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda |
| title_sort |
bright lights, big cities : measuring national and sub-national economic growth from outer space in africa, with an application to kenya and rwanda |
| publisher |
World Bank, Washington, DC |
| publishDate |
2015 |
| url |
http://documents.worldbank.org/curated/en/2015/10/25160952/republic-kenya-bright-lights-big-cities-measuring-national-sub-national-economic-growth-outer-space-africa-application-kenya-rwanda http://hdl.handle.net/10986/22922 |
| _version_ |
1764452427214356480 |