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Contents -- About the Authors -- Acknowledgments -- Chapter 1. Introduction -- Chapter 2. Creating New Hope -- Chapter 3. Participants -- Chapter 4. The Evaluation -- Chapter 5. Work and Poverty -- Chapter 6. Children -- Chapter 7. Families -- Chapter 8. New Hope's Lessons -- Chapter 9. New Hope and National Policy -- Appendix. New Hope Program Impacts -- Afterword -- Notes -- References -- Index

AbstractDemography's population perspective, and the sampling methods that help produce it, are powerful but underutilized research tools. The first half of this article makes the case for more vigorous promotion of a population perspective throughout the sciences. It briefly reviews the basic elements of population sampling and then provides examples from both developed and developing countries of how population sampling can enrich random-assignment policy experiments, multisite studies, and qualitative research. At the same time, an ill-considered application of a population perspective to the problem of causal inference can hinder social and behavioral science. The second half of the article describes the "slippery slope" by which some demographic studies slide from providing a highly useful description about the population to using regressions to estimate causal models for that population. It then suggests that causal modeling is sometimes well served by a highly selective look at small subsets of a population with interesting variability in independent variables of interest. A robust understanding of causal effects, however, rests on convergence between selective and population-wide perspectives.

Offers personal reflections on the origins & development of the Panel Study of Income Dynamics (PSID) since the author's initial involvement with it as a graduate student in 1972. The origins of the project in then-President Lyndon Johnson's "War of Poverty" & its growth as one of the main instruments used to assess the economic health of the nation's households are chronicled. Stages in the processes of goal setting, proposal writing, questionnaire development, & data collection & analysis are outlined; methodological changes over the years are also documented. The wealth of data provided by the PSID on family composition, residential location, income sources & amounts, & employment patterns have provided fresh insights into the nature & trajectory of the family life cycle, as well as been used to compare patterns on the bases of gender, race, & other sociodemographic variables. Policy & programmatic uses of the PSID findings are described, along with encouraging efforts by other countries to replicate the PSID panel design in their own socioeconomic research. The author's application of economic & policy insights from her PSID experience to her new research on human development is recounted. 5 Tables, 37 References. K. Hyatt Stewart

This article considers whether the disparate socioeconomic circumstances of families in which white, black, and Hispanic children grow up account for the racial and ethnic gaps in school readiness among American preschoolers. It first reviews why family socioeconomic resources might matter for children's school readiness. The authors concentrate on four key components of parent socioeconomic status that are particularly relevant for children's well-being—income, education, family structure, and neighborhood conditions. They survey a range of relevant policies and programs that might help to close socioeconomic gaps, for example, by increasing family incomes or maternal educational attainment, strengthening families, and improving poor neighborhoods.

Their survey of links between socioeconomic resources and test score gaps indicates that resource differences account for about half of the standard deviation—about 8 points on a test with a standard deviation of 15—of the differences. Yet, the policy implications of this are far from clear. They note that although policies are designed to improve aspects of "socioeconomic status" (for example, income, education, family structure), no policy improves "socioeconomic status" directly. Second, they caution that good policy is based on an understanding of causal relationships between family background and children outcomes, as well as cost-effectiveness.

They conclude that boosting the family incomes of preschool children may be a promising intervention to reduce racial and ethnic school readiness gaps. However, given the lack of successful large-scale interventions, the authors suggest giving only a modest role to programs that address parents' socioeconomic resources. They suggest that policies that directly target children may be the most efficient way to narrow school readiness gaps.

Cet article explique de quelle façon des expériences sociales à grande échelle faisant appel à une assignation aléatoire, comme le Projet d'autosuffisance du Canada, permettent d'aborder d'importantes questions sociologiques et développementales. Nous expliquons d'abord comment la répartition aléatoire résout le problème de biais qui se retrouve dans la plupart des recherches fondées sur des enquêtes. Nous passons ensuite en revue les méthodes et résultats de deux séries d'expériences récentes faisant appel à une répartition au hasard, l'une qui manipulait la situation économique des familles et l'autre qui manipulait les conditions du quartier. En conclusion, nous analysons les forces et faiblesses de cette approche expérimentale.

This article explains how large-scale random-assignment social experiments such as the Canadian Self-Sufficiency Project can address important sociological and developmental issues. The authors begin with an explanation of how random assignment solves the bias problem that plagues most research based on sample surveys. They then review methods and results from two recent sets of random-assignment experiments, one manipulating family economic conditions and the other manipulating neighborhood conditions. The authors conclude with a discussion of the strengths and weaknesses of the experimental approach.