The Association of Advanced Math Course-Taking by American Youth on Subsequent Receipt of Public Assistance
DOI:
https://doi.org/10.18060/23866Keywords:
Income support, public assistance, advanced mathematics, work-firstAbstract
Helping people move to independence is often cited as a primary goal of public assistance policies in the United States. Over the past several decades, welfare reform efforts in the US have promoted the idea of a work-first approach. Research shows that this approach has discouraged or at least made it harder for some students to attend college while meeting the work requirements for aid. How can those students who need public assistance increase their chances of finding a sustainable job and thus not need to rely on the public support system after high school? To address this question, this study used a sample of 3,384 student responses from the National Longitudinal Study of Adolescent to Adult Health and a recursive bivariate probit model to analyze the association between advanced math course-taking in high school and the probability of subsequent receipt of public assistance. The empirical results suggest that taking advanced math courses in high school is associated with a lower probability of receiving public assistance for recent graduates. These findings are particularly important for school social workers who work in conjunction with teachers and school counselors to help at-risk students improve their chances of future financial independence.
References
Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. Department of Education. https://www2.ed.gov/rschstat/research/pubs/toolboxrevisit/toolbox.pdf
Altonji, J. G. (1995). The effects of high school curriculum on education and labour outcomes. The Journal of Human Resources, 30(3), 409-438.
Altonji, J. G., Blom, E., & Meghir, C. (2012). Heterogeneity in human capital investments: High school curriculum, college major, and careers. Annual Review of Economics, 4(1), 185-223. https://doi.org/10.3386/w17985
Angrist, J., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton University Press. https://doi.org/10.1515/9781400829828
Attewell, P., & Domina, T. (2008). Raising the bar: Curricular intensity and academic performance. Educational Evaluation and Policy Analysis, 30(1), 51-71. https://doi.org/10.3102/0162373707313409
Boalar, J. (2011). Changing students’ lives through the de-tracking of urban mathematics classrooms. Journal of Urban Mathematics Education, 4(1), 7-14.
Brauner, S., & Loprest, P. (1999). Where are they now? What states’ studies of people who left welfare tell us. Washington, DC: Urban Institute. http://webarchive.urban.org/UploadedPDF/anf32.pdf
Burnett, N. (1997). Gender economics courses in liberal arts colleges. Journal of Economic Education, 28(Fall), 369-377. https://doi.org/10.2307/1183420
Burris, C., Heubert, J., & Levin, H. (2006). Accelerating mathematics achievement using heterogeneous grouping. American Educational Research Journal, 43(1), 103-134. https://doi.org/10.3102/00028312043001105
Byun, S., Irvin, M.J., & Bell, B. A. (2015). Advanced math course taking: Effects on math achievement and college enrollment. Journal of Experimental Education, 83(4), 439-468. https://doi.org/10.1080/00220973.2014.919570
Catsambis, S. (1994). The path to math: Gender and racial-ethnic differences in mathematics participation from middle school to high school. Sociology of Education, 67(3), 199-215. https://doi.org/10.2307/2112791
Center on Budget and Policy Priorities. (2020, February 6). Policy brief: Temporary Assistance for Needy Families. https://www.cbpp.org/research/family-income-support/temporary-assistance-for-needy-families
Chavkin, N. (1996). Social work and mathematics: Strange bedfellows or productive partners? The Clearing House, 69(6), 327-329. https://doi.org/10.1080/00098655.1996.10114331
Chen, P., & Chantala, K. (2014). Guidelines for analyzing Add Health data. Carolina Population Center University of North Carolina at Chapel Hill. http://cdr.lib.unc.edu/downloads/1v53k016h
Common Core State Standards Initiatives. (2020). About the standards. http://www.corestandards.org/about-the-standards/
Dave, D. M., Corman, H., & Reichman, N. E. (2012). Effects of welfare reform. Journal of Labor Research, 33(2), 251-282. https://doi.org/10.1007/s12122-012-9130-4
Davenport, E. C., Jr., Davison, M. L., Kuang, H., Ding, S. Kim, S., & Kwak, N. (1998). High school mathematics course-taking by gender and ethnicity. American Educational Research Journal, 35(3), 497-514. https://doi.org/10.3102/00028312035003497
Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R.D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82(1), 405-432. https://doi.org/10.1111/j.1467-8624.2010.01564.x
Goodman, J. (2012). The labor of division: Returns to compulsory math coursework. Faculty Research Working Paper Series. Harvard Kennedy School. https://doi.org/10.3386/w23063
Greenberg, M. (2001). Welfare reform and devolution: Looking back and forward. Brookings Institution Press. https://doi.org/10.2307/20080986
Greene, W. (1998). Gender economics courses in liberal arts colleges: Further Results. Journal of Economic Education, 29(4), 291-300. https://doi.org/10.1080/00220489809595921
Greene, W. (2000). Econometric analysis (4th ed.). Prentice Hall.
Hamilton, L. S., Stecher, B. M., & Yuan, K. (2008). Standards-based reform in the United States: History, research, and future directions. RAND Corporation. https://www.rand.org/content/dam/rand/pubs/reprints/2009/RAND_RP1384.pdf
Hassrick, E., & Schneider, B. (2009). Parent surveillance in schools: A question of social class. American Journal of Education, 155(2), 195-225. https://doi.org/10.1086/595665
Hays, S. (2003). Flat broke with children. Oxford University Press.
Hotz, J. V., Imbens, G. W., & Klerman, J. A. (2006). Evaluating the differential effects of alternative welfare-to-work training components: A reanalysis of the California GAIN program. Journal of Labor Economic, 24(3), 521-566. https://doi.org/10.3386/w11939
Jacobs, J. A., & Winslow, S. (2003). Welfare reform and enrollment in postsecondary education. The Annals of the American Academy, 586(1), 194-217.
Joensen, J., & Nielsen, H. (2009). Is there a causal effect of high school math on labor market outcomes? Journal of Human Resources, 44(1), 171-198. https://doi.org/10.3368/jhr.44.1.171
K12Academics. (2004-2020). Education reform. https://www.k12academics.com/education-reform
Klopfenstein, K. (2004). Advanced placement: Do minorities have equal opportunity? Economics of Education Review, 23(2), 115-131. https://doi.org/10.1016/s0272-7757(03)00076-1
Knapp, L.G., & Seaks, T.G. (1998). A Hausman Test for a dummy variable in probit. Applied Economics Letters, 5(5), 321-323.
Levine, P., & Zimmerman, D. (1995). The benefit of additional high-school math and science classes for young men and women. Journal of Business & Economic Statistics, 13(2), 137-149. https://doi.org/10.2307/1392368
Long, M. C., Iatarola, P., & Conger, D. (2009). Explaining gaps in readiness for college-level math: The role of high school courses. Education Finance and Policy, 4(1), 1-33. https://doi.org/10.1162/edfp.2009.4.1.1
Long, M. C., Conger, D., & Iatarola, P. (2012). Effects of high school course-taking on secondary and postsecondary success. American Educational Research Journal, 49(2), 285-322. https://doi.org/10.3102/0002831211431952
Loprest, P. (1999). Families who left welfare: Who are they and how are they doing? Urban Institute. http://webarchive.urban.org/UploadedPDF/discussion99-02.pdf
National Center for Education Statistics. (2011). Youth indicators 2011 America’s youth: Transition to adulthood. https://nces.ed.gov/pubs2012/2012026/tables/table_32.asp
National Commission on Excellence in Education. (1983). A nation at risk. U.S. Government Printing Office. https://www.edreform.com/wp-content/uploads/2013/02/A_Nation_At_Risk_1983.pdf
Personal Responsibility and Work Opportunity Reconciliation Act of 1996, Pub. L. No. 104-193, 110 Stat. 2105.
Peterson, J., Song, X., & Jones-DeWeever, A. (2002). Life after welfare reform: Low-income single parent families, pre- and post-TANF (No. D446). Institute for Women’s Policy Research Publication. https://files.eric.ed.gov/fulltext/ED469527.pdf
Riegle-Crumb, C. (2006). The path through math: Course sequences and academic performance at the intersection of race/ethnicity and gender. American Journal of Education, 113(1), 1-17. https://doi.org/10.1086/506495
Rivers, D., & Vuong, Q. (1988). Limited information estimators and exogeneity tests for simultaneous probit models. Journal of Econometrics, 39(November), 347-366. https://doi.org/10.1016/0304-4076(88)90063-2
Rose, H., & Betts, J. (2004). The effect of high school courses on earnings. Review of Economics and Statistics, 86(2), 497-513. https://doi.org/10.1162/003465304323031076
Sawhill I. V., & Haskins, R. (2002). Welfare reform and the work support system. Policy Brief No. 17, Brookings Institution Press, Washington, DC. https://www.brookings.edu/research/welfare-reform-and-the-work-support-system/
Semuels, A. (2016, April 1). The End of Welfare as We Know It. America’s once-robust safety net is no more. The Atlantic. https://www.theatlantic.com/business/archive/2016/04/the-end-of-welfare-as-we-know-it/476322/
Sklad, M., Diekstra, R., De Ritter, M., Ben, J., & Gravestein, C. (2012). Effectiveness of school-based universal social, emotional, and behavioral programs: Do they enhance students’ development in the area of skill, behavior, and adjustment? Psychology in the Schools, 49(9), 892-910. https://doi.org/10.1002/pits.21641
Sosa, A. (2016). Impact of mathematics course taking during high school on earnings: Evidence from shocks to teachers' supply. Working Paper, https://aefpweb.org/sites/default/files/webform/41/AlfredoSosa_coursetaking2016-03-01Draft3.pdf
Ujifusa, A. (2018, July 31). Donald Trump signs first major education policy bill of his presidency. Education Week. https://www.edweek.org/ew/articles/2018/07/31/donald-trump-signs-career-technical-education-bill.html
United States Census Bureau. (2015, May 28). 21.3 percent of U.S. Population participates in government assistance programs each month. https://www.census.gov/newsroom/press-releases/2015/cb15-97.html
White House. (2018, April 10). Executive Order Reducing Poverty in America by Promoting Opportunity and Economic Mobility. Social Programs. https://www.whitehouse.gov/presidential-actions/executive-order-reducing-poverty-america-promoting-opportunity-economic-mobility/