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The paper presents the first major update of the international "USD 1 a day" poverty line, first proposed in 1990 for measuring absolute poverty by the standards of the world's poorest countries. In a new data set of national poverty lines we find that a marked economic gradient only emerges when consumption per person is above about USD 2.00 a day at 2005 purchasing power parity. Below this, the average poverty line is USD 1.25, which we propose as the new international poverty line. Relative poverty appears to matter more to developing countries than has been thought. Our proposed schedule of relative poverty lines is bounded below by USD 1.25, and rises at a gradient of USD 1 in USD 3 when mean consumption is above USD 2.00 a day.

Absolute poverty --- Global poverty --- International poverty line --- National poverty --- National poverty lines --- Poor --- Poor countries --- Poor person --- Poverty line --- Poverty measurement --- Poverty Reduction --- Rural Development --- Rural Poverty Reduction

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Brazil, China and India have seen falling poverty in their reform periods, but to varying degrees and for different reasons. History left China with favorable initial conditions for rapid poverty reduction through market-led economic growth; at the outset of the reform process there were ample distortions to remove and relatively low inequality in access to the opportunities so created, though inequality has risen markedly since. By concentrating such opportunities in the hands of the better off, prior inequalities in various dimensions handicapped poverty reduction in both Brazil and India. Brazil's recent success in complementing market-oriented reforms with progressive social policies has helped it achieve more rapid poverty reduction than India, although Brazil has been less successful in terms of economic growth. In the wake of its steep rise in inequality, China might learn from Brazil's success with such policies. India needs to do more to assure that poor people are able to participate in both the country's growth process and its social policies; here there are lessons from both China and Brazil. All three countries have learned how important macroeconomic stability is to poverty reduction.

Consumption expenditures --- Economic growth --- Household consumption --- Household surveys --- Impact on poverty --- Income --- Income distribution --- Inequality --- Macroeconomic stability --- National poverty --- National poverty line --- National poverty lines --- Poor --- Poor people --- Poverty line --- Poverty measures --- Poverty Reduction --- Pro-Poor Growth --- Regional Economic Development --- Rural --- Rural areas --- Rural Development --- Rural Poverty Reduction --- Social policies

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China has seen a huge reduction in the incidence of extreme poverty since the economic reforms that started in the late 1970s. Yet, the growth process has been highly uneven across sectors and regions. The paper tests whether the pattern of China's growth mattered to poverty reduction using a new provincial panel data set constructed for this purpose. The econometric tests support the view that the primary sector (mainly agriculture) has been the main driving force in poverty reduction over the period since 1980. It was the sectoral unevenness in the growth process, rather than its geographic unevenness, that handicapped poverty reduction. Yes, China has had great success in reducing poverty through economic growth, but this happened despite the unevenness in its sectoral pattern of growth. The idea of a trade-off between these sectors in terms of overall progress against poverty in China turns out to be a moot point, given how little evidence there is of any poverty impact of non-primary sector growth, controlling for primary-sector growth. While the non-primary sectors were key drivers of aggregate growth, it was the primary sector that did the heavy lifting against poverty.

Absolute poverty --- Agricultural growth --- Agricultural land --- Counterfactual --- Economic growth --- Extreme poverty --- Impact on poverty --- Income --- Inequality --- Land rights --- National poverty --- National poverty line --- Poor --- Poor people --- Poverty impact --- Poverty measures --- Poverty Reduction --- Pro-Poor Growth --- Regional Economic Development --- Rural --- Rural areas --- Rural Development --- Rural economic growth --- Rural Poverty Reduction

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This paper uses the night lights (satellite imagery from outer space) approach to estimate growth in and levels of subnational 2013 gross domestic product for 47 counties in Kenya and 30 districts in Rwanda. Estimating subnational gross domestic product is consequential for three reasons. First, there is strong policy interest in how growth can occur in different parts of countries, so that communities can share in national prosperity and not get left behind. Second, subnational entities want to understand how they stack up against their neighbors and competitors, and how much they contribute to national gross domestic product. Third, such information could help private investors to 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, the approach may underestimate economic activity in sectors that are largely unlit notably agriculture. For Kenya, the results of the analysis affirm that Nairobi County is the largest contributor to national gross domestic product. However, at 13 percent, this contribution is lower than commonly thought. For Rwanda, the three districts of Kigali account for 40 percent of national gross domestic product, 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, it is important to estimate subnational gross domestic product using standard approaches (production, expenditure, income).

Agricultural output --- Agricultural performance --- Agricultural sector --- Agriculture --- Annual growth --- Annual growth rate --- Cities --- City --- Coefficients --- Consumption --- Criteria --- Development indicators --- Development policy --- Diseconomies of scale --- Distribution of income --- District --- District administrations --- District level --- District-level --- Economic activity --- Economic decline --- Economic downturns --- Economic growth --- Economic theory & research --- Economics --- Elasticity --- Empirical model --- Estimation method --- Financial crisis --- Fiscal management --- Fixed effects --- GDP --- GDP per capita --- Gross domestic product --- Growth --- Growth rate --- Growth rates --- Household surveys --- Incentives --- Incidence of poverty --- Indicators --- Informal economy --- Inputs --- Long-term growth --- Macroeconomics --- Macroeconomics and economic growth --- National poverty line --- Policy research --- Poverty --- Poverty impact evaluation --- Poverty levels --- Poverty line --- Poverty reduction --- Pro-poor growth --- Provinces --- Real GDP --- Resource allocation --- Revenue --- Revenue allocation --- Revenue sharing --- Revenue sharing formula --- Revenue-raising capacity --- Subnational entities --- Subnational governments --- Subnational unit --- Surveys --- Tax --- Underestimates --- Urban areas --- Wealth