We use randomized grants to generate shocks to capital stock for a set of Sri Lankan microenterprises. We find the average real return to capital in these enterprises is 4.6%–5.3 % per year), substantially higher than market interest rates. We then examine the heterogeneity of treatment effects. Returns are found to vary with entrepreneurial ability and with household wealth, but not to vary with measures of risk aversion or uncertainty. Treatment impacts are also significantly larger for enterprises owned by males; indeed, we find no positive return in enterprises owned by females. I.

I n what turned out to be a rhetorical master-move, the 1990 World Develop-ment Report from the World Bank defined the “extremely poor ” people ofthe world as those who are currently living on no more than $1 per day per person, measured at the 1985 purchasing power parity (PPP) exchange rate. In 1993, the poverty line was updated to $1.08 per person per day at the 1993 PPP exchange rate, which is the line we use in this paper. Poverty lines have always existed—indeed $1 per day was chosen in part because of its proximity to the poverty lines used by many poor countries.1 However the $1-a-day poverty line has come to dominate the conversations about poverty to a remarkable extent. But how actually does one live on less than $1 per day? This essay is about the economic lives of the extremely poor: the choices they face, the constraints they grapple with, and the challenges they meet. The available evidence on the eco-nomic lives of the extremely poor is incomplete in many important ways. However, a number of recent data sets and a body of new research have added a lot to what we know about their lives, and taken together there is enough to start building an image of the way the extremely poor live their lives. Our discussion of the economic lives of the extremely poor builds on house-

Theoretically, measures of household wealth can be reflected by income, consumption or expenditure information. However, the collection of accurate income and consumption data requires extensive resources for household surveys. Given the increasingly routine application of principal components analysis (PCA) using asset data in creating socio-economic status (SES) indices, we review how PCAbased indices are constructed, how they can be used, and their validity and limitations. Specifically, issues related to choice of variables, data preparation and problems such as data clustering are addressed. Interpretation of results and methods of classifying households into SES groups are also discussed. PCA has been validated as a method to describe SES differentiation within a population. Issues related to the underlying data will affect PCA and this should be considered when generating and interpreting results.

Woolcock, and Manfred Zeller for helpful comments on an earlier draft of this paper. Thanks are also due to the participants of seminars at Cornell University, the International Food Policy Research Institute (IFPRI), and the IRIS Center at the University of Maryland. Management and processing of the data was expertly handled

AIDS deaths could have a major impact on economic development by affecting the human capital accumulation of the next generation. We estimate the impact of parent death on primary school partici-pation using an unusual fi ve-year panel data set of over 20,000 Kenyan children. There is a substantial decrease in school participation following a parent death and a smaller drop before the death (presum-ably due to pre-death morbidity). Estimated impacts are smaller in specifi cations without individual fi xed effects, suggesting that estimates based on cross-sectional data are biased toward zero. Effects are largest for children whose mothers died and, in a novel fi nding, for those with low baseline aca-demic performance. ore than one in nine children under age 18 in sub-Saharan Africa have lost a parent, and the HIV/AIDS pandemic is the leading cause (UNAIDS, UNICEF, and USAID 2004).1 HIV/AIDS deaths today could have major long-term effects on economic development by affecting the human capital accumulation of the next generation. While some have argued that HIV/AIDS is the key development issue facing Africa (UNAIDS 2000), and children orphaned by AIDS have received considerable international media coverage,2 surprisingly little systematic empirical research has estimated the impact of parent death on children’s

As recent discussions have made clear, the apparent lack of poverty reduction in the face of historically high rates of economic growth—both in the world as a whole and in specific coun-tries (most notably India)—provides fuel for the argument that economic growth does little to reduce poverty. How confident can we be that the data actually support these inferences? At the international level, the regular revision of purchasing power parity exchange rates plays havoc with the poverty estimates, changing them in ways that have little or nothing to do with the actual experience of the poor. At the domestic level, the problems in measuring pov-erty are important not only for the world count but also for tracking income poverty within individual countries. Yet, in many countries, there are large and growing discrepancies be-tween the survey data—the source of poverty counts—and the national accounts—the source of the measure of economic growth. Thus economic growth, as measured, has at best a weak relationship with poverty, as measured. The World Bank prepares and publishes estimates of the number of poor people in the world. Although these numbers should be taken with a pinch of salt, they are arguably important. In an institution where the reduction of poverty is the para-

The last several years have seen a growth in the number of publications in economics that use principal component analysis (PCA) in the area of welfare studies. This paper explores the ways discrete data can be incorporated into PCA. The effects of discreteness of the observed variables on the PCA are reviewed. The statistical properties of the popular Filmer and Pritchett (2001) procedure are analyzed. The concepts of polychoric and polyserial correlations are introduced with appropriate references to the existing literature demonstrating their statistical properties. A large simulation study is carried out to compare various implementations of discrete data PCA. The simulation results show that the currently used method of running PCA on a set of dummy variables as proposed by Filmer and Pritchett (2001) can be improved upon by using procedures appropriate for discrete data, such as retaining the ordinal variables without breaking them into a set of dummy variables or using polychoric correlations. An empirical example using Bangladesh 2000 Demographic and Health Survey data helps in explaining the differences between procedures. 1.

Abstract. Impact of insecticide-treated bednets (ITNs) on preventing malaria may be minimized if they are not used by vulnerable populations. Among ITN-owning households from 15 standardized national surveys from 2003 to 2006, we identify factors associated with ITN use among children younger than 5 years of age and make comparisons of ITN use among children and pregnant women across countries. Within ITN-owning households, many children and pregnant women are still not using them. Between-country analysis with linear regression showed child ITN use increases as intra-household access to ITNs increases ( P = 0.020, R 2 = 0.404), after controlling for season and survey year. Results from within-country logistic regression analyses were consistent with between-country analysis showing intra-household access to ITNs is the strongest and most consistent determinant of use among children. The gaps in ITN use and possession will likely persist in the absence of achieving a ratio of no more than two people per ITN.

Shapiro, Rebecca Thornton, Alwyn Young and participants in seminars at BREAD, Harvard University, the University of Chicago and SITE provided helpful comments. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.

This paper uses individual and household level data to explore empirically the associations between household wealth and the incidence and treatment of fever, as an indicator of malaria, among children in sub-Saharan Africa. The data used are from Demographic and Health Surveys collected in the 1990s from 22 countries where malaria is prevalent. The results suggest that the incidence of fever and its treatment are related to poverty in sub-Saharan Africa. Incidence is typically lower at the very top of the wealth distribution. The relationship, however, is not strong, especially after controlling for potentially confounding factors. Treatment patterns are strongly related to poverty as wealthier households are more likely to seek care or advice. While it is perhaps unsurprising that treatment from private sources increases with household wealth, government services – despite their public nature – are typically also used more by wealthier households. While general results hold for many of the countries, there is sufficient variation across countries that any policy seeking to reform the health sector in order to better cater to the poor needs to be informed by country-specific work. Key words: fever, malaria, inequality, child health