Bright Lights, Big Cities
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World Bank, Washington, DC
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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).
Palabras clave
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
