A fundamental premise of absolute poverty lines is that they represent the same level of utility through time and space. Disturbingly, a series of recent studies in middle and low-income economies show that even carefully derived poverty lines rarely satisfy this premise. This paper proposes an information theoretic approach to estimating cost of basic needs (CBN) poverty lines that are utility-consistent. Applications to date illustrate that utility-consistent poverty measurements derived from the proposed approach and those derived from current CBN best practices often differ substantially with the current approach tending to systematically overestimate (underestimate) poverty in urban (rural) zones. Estimating Utility-Consistent Poverty Lines withApplications to Egypt and Mozambique I. IntroductionPoverty reduction has become one of the primary objectives of development assistance, and changes in poverty have become the dominant yardsticks by which development assistance and accompanying government action are measured. The stakes are high. In many poor countries, failure to reduce measured poverty levels over the medium term, either nationally or in significant sub-regions, would very likely catalyze widespread calls for major policy reform as well as country program reviews by donor organizations, including a reassessment of the overall level of assistance. In this environment, reasonably precise measures of poverty levels across space and changes in poverty levels through time are essential.Poverty measurement is a complex and contentious subject, with a large literature. This paper concentrates on methods for setting consumption-based poverty lines. Poverty lines serve not only as a dividing line between the poor and nonpoor, but also as cost of living indices, permitting interpersonal welfare comparisons when the cost of acquiring basic needs varies over time or space (Ravallion, 1998). Demand systems estimation constitutes a direct approach to setting poverty lines; however, formidable practical barriers have implied that this approach is rarely applied. 1 Instead, two major approaches to setting poverty lines are commonly used: the Food Energy Intake (FEI) approach (Dandekar and Roth, 1971;Greer and Thorbecke, 1985, 1986) and the Cost of Basic Needs (CBN) approach (Ravallion, 1994(Ravallion, , 1998 Ravallion and 1 Dorosh, del Ninno, and Sahn (1994) estimate poverty rates via demand systems estimation.Meyerhoeffer, Ranney, and Sahn (2005) provide an overview of the issues associated with demand systems estimation and propose a new approach when panel data is available.

No abstract

Important differences exist between communities with respect to their needs, capacities and circumstances. As central governments are not able to discern these differences fully, they seek to achieve their policy objectives by relying on decentralized mechanisms that utilize local information. However, household and individual characteristics within communities can also vary substantially. A growing theoretical literature suggests that inequality within communities can influence policy outcomes, and that this influence could be harmful or helpful, depending on the circumstances. Empirical investigations into the impact of inequality have, to date, been held largely back by a lack of systematic evidence on community-level inequality. This paper uses household survey and population census data to estimate per capita consumption inequality within communities in three developing countries. Communities are found to vary markedly from one another in terms of the degree of inequality they exhibit. We also show that there should be no presumption that inequality is less severe in poor communities. We argue that the kind of community-level inequality estimates generated in this paper can be utilized in designing and evaluating decentralized antipoverty programs. IntroductionGovernments in developing countries commonly implement decentralized antipoverty programs that are designed to distribute assets or cash to individuals or households.In many such cases, the central government first distributes its poverty reduction budget to communities, and these are then left to decide how to allocate that budget across individuals.Social Funds projects provide a well-known example from the family of community based development (CBD) initiatives, in which poor communities are required to identify, apply for funding, design, implement and manage their projects (Mansuri and Rao, 2003 (2003) provides a recent attempt to proxy local inequality on the basis of easily observed correlates of household income.5 outcomes combining the detailed information available from a household survey with the large-scale representation of the population census. We suggest that meaningful estimates of income or expenditure inequality for small areas can be obtained for many countries on the basis of these techniques. Second, we show that there is great heterogeneity in inequality across these communities in each country. We find that this heterogeneity in local inequality levels is still present when we focus our attention on the poorest communities in rural areas. The combined implication of these findings is that information on local inequality is available for use by program implementers and that this information can help to categorize communities even after conditioning on local poverty and type of area. How Can Local Inequality Affect Welfare Outcomes?Mansuri and Rao ( A detailed case study of the north Indian village of Palanpur provides one illustration of the manner in which local elites are able to appropriate for their own purposes ...

Using 1996-97 and 2002-03 nationally representative household surveys, we examine the extent to which growth in Mozambique has been pro-poor. While all sections of society enjoyed a rapid annual increase in consumption between the sample periods, the rate of growth in consumption was slightly higher for richer households.This has led to a moderate increase in inequality at the national level, as demonstrated by the rise in the Gini coefficient from 0.40 to 0.42. However, this slight increase in inequality is not statistically significant, and its impact on poverty reduction efforts is small: the poverty headcount would have been 53.0 percent in 2002-03 if all sections of society had enjoyed the mean growth rate in consumption, compared with the 54.1 percent at which it actually stood. Interestingly, the use of the entropy class of inequality measures indicates that inequality in real consumption between provinces and regions has diminished over time, in contrast to popular claims. Maputo City continues to have the highest rates of inequality in the country; it witnessed a significant increase in inequality between 1996-97 and 2002-03 (the Gini coefficient rose from 0.44 to 0.52).

IFPRI's Discussion Papers contain preliminary material and research results. They have not been subject to formal review by IFPRI's Publications Review Committee. They are circulated in order to stimulate discussion and critical comment.