Bright Lights, Big Cities : Measuring National and Sub-National Economic Growth from Outer Space in Africa, with an Application to Kenya and Rwanda

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作者：

Bundervoet, Tom

来源地址：

http://hdl.handle.net/10986/22922

关键词：

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;  Report; 

年份：

2015

出版地：

Washington,USA

语种：

English

摘要：

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).