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Household Crowding During Childhood and Long-Term Education Outcomes

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Demography

Abstract

Household crowding, or having more household members than rooms in one’s residence, could potentially affect a child’s educational attainment directly through a number of mechanisms. We use U.S. longitudinal data from the Panel Study of Income Dynamics to derive new measures of childhood crowding and estimate negative associations between crowding during one’s high school years and, respectively, high school graduation by age 19 and maximum education at age 25. These negative relationships persist in multivariate models in which we control for the influence of a variety of factors, including socioeconomic status and housing-cost burden. Given the importance of educational attainment for a range of midlife and later-life outcomes, this study suggests that household crowding during one’s high school years is an engine of cumulative inequality over the life course.

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Notes

  1. Deep poverty is usually defined as income below half the federal poverty threshold (Shaefer and Edin 2013).

  2. In 2009, the poverty threshold for a family of three with one adult and two children was $17,285 (U.S. Census Bureau n.d.).

  3. Each interviewed family in the PSID was assigned a head of household. The head was at least 16 years old and had the primary financial responsibility within the family. In nearly all cases, the head was male. Although the children born into the PSID could have various relationships with the head (e.g., a grandchild, a niece/nephew), the vast majority were the head’s children. For instance, among those born in 1968, 81 % were children of the head, and 13 % were grandchildren, nieces, or nephews. For the remaining 6 %, the relationship status was not reported. For simplicity, we use the terms head of household and parent interchangeably.

  4. The PSID question asks the respondent to report the number of rooms in the household for the “family.” Some respondents may adjust their count of rooms to take into account the presence of nonfamily members in the household. However, we have no means to ascertain the extent to which that is the case.

  5. The PSID recorded the Census Needs Standard using a schedule reported by the U.S. Census Bureau based on the size of the family and number of children. This schedule is available online (http://www.census.gov/hhes/www/poverty/data/threshld/index.html).

  6. More details on the official definition can be found online (http://www.census.gov/hhes/www/poverty/about/overview/measure.html).

  7. The PSID started collecting information on the “Spanish or Hispanic descent” of the heads of household in 1985. We created a variable for Hispanic that overlaps with the racial categories (i.e., among Hispanic respondents, some are white, some are African American, and the rest fall into the “other race” category).

  8. Most housing cost burden measures include, in addition to annual mortgage payments or rent, mortgage interest, property taxes, the cost of utilities, and housing (or rental) insurance (see, e.g., Newman and Holupka 2014a). In selected years, the PSID measured some of these variables, but only the mortgage or rental payment was consistently measured throughout the period of our study.

  9. We ran several preliminary logistic regression models to determine whether model choice changed our findings, and found that the results were substantively identical.

  10. Another potential modeling option that would reduce omitted variable bias is a family fixed-effects model. In such a model, one compares the crowding experienced between (among) siblings to reduce bias in the crowding coefficients. Factors that are common among siblings, such as parental supervision, are removed from the estimation process and cannot bias coefficient estimates. These models are predicated on variation in crowding between siblings. Unfortunately, ever-crowding does not vary much between siblings. For example, only 14 % of the cases had variation in crowding (measured as a HCR > 1) between ages 15 and 18. Even a continuous measure of crowding showed very little variation. Given this low level of variation, we chose not to use a family fixed-effects model.

  11. In supplemental analyses, we estimated these models separating the respondents into four quartiles based on their INTR and found no evidence of heterogeneous effects by SES.

  12. In supplemental analyses, we estimated models to determine whether crowding mattered at specific ages in the high school years. Our results suggest that the effects are constant from ages 15 to 18 and do not surface before age 15.

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Acknowledgments

We thank Emily Cardon, Maddy Hamlin, and Mary Stottele for their research assistance on this project.

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Authors and Affiliations

  1. Department of Public Administration and International Affairs, and Center for Policy Research, Maxwell School of Citizenship & Public Affairs, Syracuse University, 426 Eggers Hall, Syracuse, NY, 13244-1020, USA

    Leonard M. Lopoo

  2. Department of Sociology, Aging Studies Institute, and Center for Policy Research, Maxwell School of Citizenship & Public Affairs, Syracuse University, 307C Lyman Hall, Syracuse, NY, 13244-1020, USA

    Andrew S. London

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Correspondence to Leonard M. Lopoo.

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Lopoo, L.M., London, A.S. Household Crowding During Childhood and Long-Term Education Outcomes. Demography 53, 699–721 (2016). https://doi.org/10.1007/s13524-016-0467-9

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