Andrew Halpern-Manners

Panel Conditioning in Longitudinal Social Science Surveys

Social scientists usually assume that the attitudes, behaviors, and statuses of respondents to longitudinal surveys are not altered by the act of measuring them. If this assumption is false—or even if the quality of survey participants’ responses change because of measurement—then social scientists risk mischaracterizing the existence, magnitude, and correlates of changes across survey waves in respondents’ characteristics. In this article, we make the case that social scientists ought to worry more about panel conditioning biases. We also describe and demonstrate empirical strategies for estimating the magnitude of such biases in longitudinal surveys, and we provide illustrative empirical results that are germane to social science research. We end by outlining a research agenda that would generate specific information about the nature and degree of panel conditioning in specific longitudinal surveys as well as a broader understanding of the circumstances in which panel conditioning is most likely to occur.

Is the Glass Emptying or Filling Up? Reconciling Divergent Trends in High School Completion and Dropout

Conclusions about levels and trends in high school dropout differ dramatically depending on whether dropout is measured using data from the Current Population Survey (CPS) or from the Common Core of Data (CCD). Using CPS- and CCD-based drop-out measures for 16- to 19-year-olds—which differ solely in their estimates of the number of 16- to 19-year-olds holding high school credentials—the authors show that half of the differences in estimated drop-out rates are due to how private school graduates and GED recipients are counted. The other half is likely attributable to CPS respondents’ misstatements of their children’s high school completion status. The rate at which students complete (or fail to complete) high school is best measured using CCD data.

A practical approach to using multiple-race response data: a bridging method for public-use microdata.

Revised federal policies require that multiple-race responses be allowed in all federal data collection efforts, but many researchers find the multitude of race categories and variables very dif cult to use. Important comparability issues also interfere with using multiple-race data in analyses of multiple data sets and/or several points in time. These difficulties have, in effect, discouraged the use of the new data on race. We present a practical method for incorporating multiple-race respondents into analyses that use public-use microdata. Our method is a modification of the regression method developed by the National Center for Health Statistics (NCHS), which uses multiple-race respondents’ specific combination of races, as well as other individual-level and contextual characteristics, to predict the respondents’ preferred single race. In this paper we (1) apply the NCHS-generated regression coefficients to public-use microdata with limited geographic information; and (2) provide a downloadable computer program with which researchers can apply this practical and preferable method for including multiple-race respondents in a wide variety of analyses.

The effect of family member migration on education and work among nonmigrant youth in Mexico.

While academic and policy circles have given much attention to the assimilatory experiences of Mexican immigrants in the United States, less is known about those who stay behind—an especially unfortunate oversight given the increasing number of Mexican youth with migrant family members. Of the studies on this topic, most have sought to identify the effect that migration has on youths’ migratory and educational aspirations, often using qualitative methods in individual sending communities. The present article supplements this research in two ways: (1) in addition to assessing educational outcomes, the scope of the analysis is expanded to include nonmigrants’ interaction with another homeland institution of upward mobility: the labor market; and (2) using a large demographic data set, statistical techniques are employed to adjust for unobserved selectivity into the migrant family-member population, thus accounting for a potentially serious source of bias. The results suggest that youth in migrant-sending families are less likely to complete the educational transitions leading up to postsecondary school and have a lower probability of participating in the local economy. The results also indicate that unobserved factors play a “nonignorable” role in sorting youth into migrant and nonmigrant families.

Do different methods for modeling age-graded trajectories yield consistent and valid results?

Data on age-sequenced trajectories of individuals’ attributes are used for a growing number of research purposes. However, there is no consensus about which method to use to identify the number of discrete trajectories in a population or to assign individuals to a specific trajectory group. The authors modeled real and simulated trajectory data using “naïve” methods, optimal matching, grade of membership models, and three types of finite-mixture models. They found that these methods produced inferences about the number of trajectories that frequently differ (1) from one another and (2) from the truth as represented by simulation parameters. They also found that they differed in the assignment of individuals to trajectory groups. In light of these findings, the authors argue that researchers should interpret results based on these methods cautiously, neither reifying point estimates about the number of trajectories nor treating individuals’ trajectory group assignments as certain.

Measuring High School Graduation Rates at the State Level What Difference Does Methodology Make

Recent evidence makes clear that states public high school graduation rates are well measured using information from the Common Core of Data (CCD). This article investigates the substantive consequences for the results of empirical analyses of using different CCD-based measures of states’ public high school graduation rates. The authors show that substantive conclusions about the levels, correlates, and predictors of states’ public high school graduation rates are dependent on how those rates are measured using the CCD data. Warren’s (2005) estimated completion rate is the most conceptually and technically sound CCD-based measure, and that measure is improved in this study. The public high school graduation rate for the class of 2004 was about 76 percent, although that rate varied considerably by race/ethnicity and across states.

Panel Conditioning in Longitudinal Studies: Evidence From Labor Force Items in the Current Population Survey

Does participating in a longitudinal survey affect respondents’ answers to subsequent questions about their labor force characteristics? In this article, we investigate the magnitude of panel conditioning or time-in-survey biases for key labor force questions in the monthly Current Population Survey (CPS). Using linked CPS records for household heads first interviewed between January 2007 and June 2010, our analyses are based on strategic within-person comparisons across survey months and between-person comparisons across CPS rotation groups. We find considerable evidence for panel conditioning effects in the CPS. Panel conditioning downwardly biases the CPS-based unemployment rate, mainly by leading people to remove themselves from its denominator. Across surveys, CPS respondents (claim to) leave the labor force in greater numbers than otherwise equivalent respondents who are participating in the CPS for the first time. The results cannot be attributed to panel attrition or mode effects. We discuss implications for CPS-based research and policy as well as for survey methodology more broadly.

The Impact of Work and Family Life Histories on Economic Well-Being at Older Ages

Motivated by theoretical and empirical research in life course sociology, we examine relationships between trajectories of work and family roles across the life course and four measures of economic well-being in later adulthood. Using data from the Wisconsin Longitudinal Study (WLS) and multiple trajectory-generating methods, we first identify latent trajectories of work and family roles between late adolescence and age 65. We then model economic well-being at age 65 as a function of these trajectories and contemporaneously measured indicators of older adults’ work, family, and health statuses. Our central finding is that trajectories of work and family experiences across the life course have direct effects on later-life economic well-being, as well as indirect effects that operate through more proximate measures of work, family, and other characteristics. We argue that these findings have important implications for how social scientists conceptualize and model the relationship between later-life economic outcomes and people’s work and family experiences across the life course.

Panel Conditioning in the General Social Survey

Does participation in one wave of a survey have an effect on respondents’ answers to questions in subsequent waves? In this article, we investigate the presence and magnitude of “panel conditioning” effects in one of the most frequently used data sets in the social sciences: the General Social Survey (GSS). Using longitudinal records from the 2006, 2008, and 2010 surveys, we find convincing evidence that at least some GSS items suffer from this form of bias. To rule out the possibility of contamination due to selective attrition and/or unobserved heterogeneity, we strategically exploit a series of between-person comparisons across time-in-survey groups. This methodology, which can be implemented whenever researchers have access to at least three waves of rotating panel data, is described in some detail so as to facilitate future applications in data sets with similar design elements.