Income and Child Well-Being. THIRTY-FOURTH GEARY LECTURE, 2005

My topic this afternoon is the link between family income and the well-being of children. While it is easy to document the better health and higher achievement of children who have grown up in richer as opposed to poorer families, it is much harder to isolate the causal impact of income itself. Children growing up in higher income families are advantaged in many other ways, including having parents who have completed more formal schooling and are embedded in higher-status social networks, and whose genetic endowments may provide cognitive and health-related advantages

The importance of poverty early in childhood

Introduction: Using a poverty line set at 60% of New Zealand’s median national income, nearly one in five New Zealand children (19%) was poor in 2011. This poverty rate is considerably less than that of the United States and Canada, similar to that of Australia, the United Kingdom, Germany and France, and much greater that in Scandinavian countries. These rates are far from immutable; New Zealand’s child poverty rate was much higher in 2004 before social policies were enacted which focused, in part, on the country’s child poverty problem

"Whither the Middle Class'? A Dynamic View"

Research using cross-sectional survey 'snapshots' of household income taken over the past quarter century reveals a growing inequality in the distribution of annual money income of households in the United States (Thurow, 1987; Levy, 1987; Levy and Michel, 1991; Michel, 1991; Karoly, 1990; Center on Budget and Policy Priorities, 1990; Easterlin, MacDonald and Macunovich, 1990), prompting some to argue that the U.S. middle class is disappearing (Phillips, 1990; Bradbury, 1986). Aggregate data from the National Accounts and from wealth surveys (Wolff, 1989; Eargle, 1991) reinforce this conclusion by showing a growing share of income from capital, a falling share for earnings, and a slightly increasing concentration of wealth among upper-income groups. Also well-documented is greater inequality in the size distribution of earnings and wages in the late 1980s as compared to one or two decades before (GottschaLk and Danziger, 1989; Burtless, 1989; Blackbum et al., this volume). Despite the consistency of these results, their almost universal reliance on data drawn from cross-sectional snapshots leaves unanswered many important questions regarding the nature of the changes taking place in the distribution of income and wealth. Most importantly, cross-sectional snapshots provide information only on net changes in economic position and thus reveal little about the extent and nature of movement into and out of the middle class.. Are increasing numbers of families 'falling from grace', as Katherine Newman (1988) puts it? If so, who are they and what events are linked to their income losses? Or is mobility into the middle class declining? And, if so, does this affect in particular young families? What avenues for upward mobility are disappearing? These are the types of questions we seek to address for adults crossing either the lower or the upper boundary of the middle class. A second set of issues we address involves linkages between changes in income and changes in wealth. We analyze trends in the transitions of prime age (25-54 years old) adults into and out of the middle class using 22 years of data from the Panel Study of Income Dynamics. We begin by reviewing the methodology and measurement procedures that we employ to define the middle class and transitions into and out of middle-class status. Next we present our basic findings which, in fact, show a persistent 'withering' of the middle class since about 1980. We then search for clues as to who moved into and out of the middle-income groups and the source of such changes. Because notions of 'class' are usually based on measures of wealth as well as income, we also investigate longitudinal changes in the wealth distribution in the 1980s for these same individuals. Our findings on wealth reinforce those based on income. The paper concludes with a brief discussion of the policy implications of our findings.

Measurement Error In Cross-Sectional and Longitudinal Labor Market Surveys: Results From Two Validation Studies

This paper reports evidence on the error properties of survey reports of labor market variables such as earnings and work hours. Our primary data source is the PSID Validation Study, a two-wave panel survey of a sample of workers employed by a large firm which also allowed us access to its very detailed records of its workers earnings. etc. The second data source uses individuals' 1977 and 1978 (March Current Population Survey) reports of earnings, matched to Social Security earnings records. In both data sets, individuals: reports of earnings are fairly accurately reported, and the errors are negatively related to true earnings. The latter property reduces the bias due to measurement error when earnings are used as an independent variable, but (unlike the classical-error case) leads to some bias when earnings are the dependent variable. Measurement-error-induced biases when change in earnings is the variable of interest are larger, but not dramatically so. Various measures of hourly earnings were much less reliable than annual earnings. Retrospective reports of unemployment showed considerable under-reporting, even of long spells.

Optimal indicators of socioeconomic status for health research

Objectives: This paper examines the relationship between various measures of SES and mortality for a representative sample of individuals. ; Methods: Data are from the Panel Study of Income Dynamics. Sample includes 3,734 individuals aged 45 and above who participated in the 1984 interview. Mortality was tracked between 1984 and 1994 and is related to SES indicators using Cox event-history regression models. ; Results: Wealth has the strongest associations with subsequent mortality, and these associations differ little by age and sex. Other economic measures, especially family-size-adjusted household income, have significant associations with mortality, particularly for nonelderly women. ; Conclusions: By and large, the economic components of SES have associations with mortality that are at least as strong as, and often stronger than, more conventional components (e.g., completed schooling, occupation).Income distribution

Moving At-Risk Teenagers Out of High-Risk Neighborhoods: Why Girls Fare Better Than Boys

neighborhood effects; social experiment; mixed methods; youth risk behavior