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Parental Resources, Schooling Achievements, and Gender Schooling Gaps: Evidence of Change over 25 years in Rural Guatemala

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Abstract

We use village census data and linear regression models to examine changes between 1975 and 2002 in the associations of parental resources with boys’ and girls’ schooling in four rural Guatemalan villages. Levels of schooling in 1975 were universally low for children 7–17 years. Large increases in schooling achievements occurred between 1975 and 2002. By 2002, schooling levels were comparable for younger boys and girls (7–12 years, N = 3,525) and favored older boys compared to older girls (13–17 years, N = 2,440) by about 0.5 grades. The associations of household standard of living and maternal schooling with schooling among girls diminished over time and became more comparable with these associations among boys, and the associations of household standard of living with schooling among older boys declined and became more comparable with these associations among girls. Thus, as increased social investments reduce the costs of schooling or increase the supply and quality of schooling to families, the magnitudes of the associations between parental resources and children’s schooling decline and become more gender equitable at all ages. However, our results show that older boys may benefit more than older girls from social investments in schooling. These changes suggest potential needs to monitor gender gaps in schooling retention among older children, to insure gender equitable access to social investments in schooling, and to encourage parents to invest in schooling as joint measures to achieve greater schooling achievements of girls and boys.

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Notes

  1. Following Glasser and Smith (2008), we use the term gender gap to describe changes in or even reversals over time in the relative schooling achievements of boys and girls as well as changes over time in the associations of parental resources with the schooling achievements of sons and daughters. Evidence of either set of changes would support the idea that gaps in the schooling achievements of boys and girls are, at least in part, socially constructed.

  2. The data for the present study do not permit us to investigate such possibilities, so we explore associations, rather than causal relationships, among the study variables.

  3. The choices of children, given prior investments in them and prior opportunities available to them, also influence their schooling attainments (Haveman and Wolfe 1995). We argue that in poor settings where norms of collectivism and parental authority are stronger and children are relatively young at the time of schooling attainment decisions (because levels of schooling attainment are lower), parents are more likely than children to control decisions about investing in schooling.

  4. This model ignores the possibility that parents can collectively influence societal or governmental decisions about schooling.

  5. The gross enrollment ratio is the ratio (in percent terms) of all children in school, regardless of age, to the population of school-age children. Net enrollment is the ratio of school-age appropriate children to the population of school-age children.

  6. A nuclear family was defined as (1) a couple (including their children, if any), regardless of whether they lived on their own or with others such as parents, or (2) a single adult, with children and/or pregnant, regardless of whether s/he lived on their own or with others, or (3) a single adult living alone.

  7. All models also control for the small percentage of missing data on these parental and household attributed with dummy variables indicating for an observation when a value is missing and has been replaced with the median for that village and census year.

  8. In an environment such as this characterized by deficient public resources for schooling, indicators such as teachers per grade and grades offered are likely to be critical determinants of schooling. We considered other village-level measures for social investments in school quality, such as the student–teacher ratio. Yet, this measure is less likely to have been measured well and was never significant in our analyses.

  9. We also assessed the potential influence of migration on our estimates by limiting the sample of older children to those 13–15 years. The results, which are available upon request, corroborate those for children 13–17 years, suggesting that selection is not substantially affecting the results.

  10. We estimated linear probability models for the binary indicator ever-schooling due to the loss of observations for “perfect prediction” when we estimated probit models with interactions between census year and other variables. This problem can arise when the right-side variables define many subgroups. So, OLS was considered the preferred estimation strategy; the results are qualitatively similar to those derived from probit estimations.

  11. We also include, but do not report, interactions of census year with missing parental resource variables, the migration indicators, and the individual age dummies. We tested interactions with other variables in H (such as living in a two-parent household) but these interactions were rarely significant, and so were not controlled for in the results presented.

  12. Estimates for maternal and paternal grade attainment in both census years are based on cases with the relevant data. Although the share of children with missing data on paternal schooling is higher than the share of children with missing data on maternal schooling for all ages, census years, and genders, the share of children with missing data on maternal and paternal schooling does not vary significantly either by the child’s gender (within census years) or over time (within the child’s gender).

  13. Because the distributions of boys and girls 7–12 and 13–17 years did not differ across study villages, there were no significant differences by child’s gender in any of the indicators for parental or village resources in either 1975 or 2002.

  14. As in lower-income settings, the association of maternal schooling with children’s schooling outcomes was stronger than that of paternal schooling, but significantly so only for the progression ratio and grades attained for girls (results available upon request).

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Authors and Affiliations

  1. Hubert Department of Global Health, Emory University, 1518 Clifton Road, NE, Atlanta, GA, 30322, USA

    Kathryn M. Yount & Usha Ramakrishnan

  2. Department of Sociology, Emory University, 1555 Dickey Drive, Atlanta, GA, 30322, USA

    Kathryn M. Yount

  3. Department of Economics, Middlebury College, Warner Hall 502B, Middlebury, VT, 05753, USA

    John A. Maluccio

  4. Department of Economics, University of Pennsylvania, 3718 Locust Walk, 229 McNeil, Philadelphia, PA, 19104-6297, USA

    Jere R. Behrman

  5. International Food Policy Research Institute, 2033 K Street, NW, Washington, DC, 20006-1002, USA

    John Hoddinott & Alexis Murphy

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  1. Kathryn M. Yount
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Yount, K.M., Maluccio, J.A., Behrman, J.R. et al. Parental Resources, Schooling Achievements, and Gender Schooling Gaps: Evidence of Change over 25 years in Rural Guatemala. Popul Res Policy Rev 32, 495–528 (2013). https://doi.org/10.1007/s11113-013-9270-0

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