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This paper provides evidence from eight developing countries of an inverse relationship between poverty and city size. Poverty is both more widespread and deeper in very small and small towns than in large or very large cities. This basic pattern is generally robust to the choice of poverty line. The paper shows, further, that for all eight countries, a majority of the urban poor live in medium, small or very small towns. Moreover, it is shown that the greater incidence and severity of consumption poverty in smaller towns is generally compounded by similarly greater deprivation in terms of access to basic infrastructure services, such as electricity, heating gas, sewerage and solid waste disposal. We illustrate for one country – Morocco – that inequality within large cities is not driven by a severe dichotomy between slum dwellers and others. Robustness checks are performed to assess whether the findings in the paper hinge on a specific definition of “urban area”; are driven by differences in the cost of living across city-size categories; by reliance on an income-based concept of well-being; or by the application of small-area estimation techniques for estimating poverty rates at the town and city level. [ABSTRACT FROM PUBLISHER]

Governments and international development agencies have intensified efforts to promote small-scale enterprises as an engine of propoor growth. In Brazil, however, small- scale industries may also be responsible for the bulk of air pollution emissions. Although employees of polluting small-scale industries in Brazil are not disproportionately poor, simulations suggest that stringent environmental regulation resulting in widespread closures of pollution-intensive small-scale industries would result in a nonnegligible increase in poverty among employees of these firms. The results suggest that the enthusiasm for small-scale enterprises needs to be tempered by awareness of the potential environmental costs imposed by this sector. [ABSTRACT FROM AUTHOR]

Communities differ in important ways in their needs, capacities, and circumstances. Because central governments are not able to discern these differences fully, they seek to achieve their policy objectives by relying on decentralized mechanisms that use local information. Household and individual characteristics within communities can also vary substantially. A growing body of theoretical literature suggests that inequality within communities can influence policy outcomes in ways that are either harmful or helpful, depending on the circumstances. Until recently, empirical investigations into the impact of inequality have been held back by a lack of systematic evidence on community-level inequality. This study uses household survey and population census data to estimate per capita consumption inequality within communities in three developing economies. It finds that communities vary markedly in their degree of inequality. It also shows that there should be no presumption that inequality is less severe in poor communities. The kind of community-level inequality estimates generated here can be used in designing and evaluating decentralized antipoverty programs. [ABSTRACT FROM AUTHOR]

The article explores how sample survey data can be combined with census data to yield predicted poverty rates for population covered by the census using the case of Ecuador. It is stated that poverty maps provide information on spatial distribution of living standards which is used by policymakers to allocate transfers and inform policy design. Poverty map development is notably hampered by scarcity of disaggregated data that is not generally available for a sufficient number of households.

Assessments of the distributional effects of public spending reforms have generally been based on average rates of program participation by income or expenditure group. This practice can be deceptive because the socioeconomic composition of participants can change as a social program expands or contracts. The geographic variation found in 1993–94 household survey data for rural India is used to estimate the marginal odds of participating in schooling and antipoverty programs. The results suggest early capture of these programs by the nonpoor. It is shown that conventional methods for assessing benefit incidence underestimate the gains to the poor from higher public outlays and underestimate the losses from cuts. [ABSTRACT FROM AUTHOR]