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Articles

Experimental Estimates of Impacts of Cost-Earnings Information on Adult Aspirations for Children’s Postsecondary Education

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Pages 486-511 | Received 21 Nov 2017, Accepted 24 Jun 2018, Published online: 03 Aug 2018
 

ABSTRACT

Economic information may close aspiration disparities for postsecondary education across socioeconomic, ethnic, and partisan divides. In 2017, we estimated impacts of information on such disparities by means of a survey experiment administered to a nationally representative sample of 4,214 adults. A baseline group was asked whether they preferred a 4-year degree, a 2-year degree, or no further education for their oldest child younger than the age of 18 years (or the option they would prefer if they had a child younger than 18 years). Before 3 other randomly selected segments of our sample were asked the same question, they were given either information about (a) both net costs and returns, (b) net costs, or (c) returns to a 2-year and 4-year degree. Information about both costs and returns did not reduce socioeconomic-status disparities but did affect ethnic and partisan divides. The findings suggest that reductions in socioeconomic inequalities in educational opportunity require more than simple changes in the dissemination of information aimed at altering economic cost–benefit calculations. Sustained effort that mitigates deeper-seated cultural and social barriers seems necessary.

Supplementary data

Supplemental data for this article can be accessed at http://hdl.handle.net/1811/86102

Notes

1. We refer to estimates without controls to facilitate comparison to income differentials in enrollment reported by Bailey and Dynarksi (Citation2011).

2. Almost half of the U.S. Hispanic population in 2016 was foreign-born, and 72.4% of Hispanics older than age 5 years lived in households where Spanish was the language spoken at home (U.S. Census Bureau, Citation2016).

Additional information

Funding

This work was funded in great part by National Science Foundation Grant No. 0732233, “Learning Progressions for Scientific Inquiry: A Model Implementation in the Context of Energy.”

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