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Journal Issue: Opportunity in America Volume 16 Number 2 Fall 2006

The Role of Higher Education in Social Mobility
Robert Haveman Timothy Smeeding

Endnotes

  1. National Center for Education Statistics, Digest of Education Statistics (U.S. Department of Education, 2002), table 382.
  2. M. Lindsay Morris, “Low-Income Women and the Higher Education Act Reauthorization,” On Campus with Women (Association of American Colleges and Universities) 3, no. 3 (Spring–Summer 2004), www.aacu.org/ocww/volume33_3/national.cfm (accessed on April 25, 2006).
  3. Michael Kirst, “Overcoming Educational Inequality: The Role of Elementary and Secondary Education Linkages with Broad Access to Postsecondary Education,” paper presented to the conference on Economic Inequality and Higher Education: Access, Persistence and Success, Maxwell School of Syracuse University, September 23–24, 2005 (hereafter, Maxwell School conference on Economic Inequality and Higher Education).
  4. National Center for Education Statistics, The Condition of Education, NCES 2003-067 (U.S. Department of Education, 2003), table 18-1.
  5. Thomas J. Kane, “College Going and Inequality,” in Social Inequality, edited by Kathryn Neckerman (New York: Russell Sage Foundation, 2004); Pell Institute, Indicators of Opportunity in Higher Education (Washington: Pell Institute, 2004).
  6. Thomas G. Mortenson, “Students from Low-Income Families and Higher Educational Opportunity,” Postsecondary Education Opportunity 78 (1998): 1–2.
  7. National Center for Education Statistics, National Education Longitudinal Study, 1988 (U.S. Department of Education, 2002); National Center for Education Statistics, The Condition of Education 2000 (U.S. Department of Education, 2002), table 382.
  8. Melanie E. Corrigan, “Beyond Access: Persistence Challenges and the Diversity of Low-Income Students,” New Directions for Higher Education 121 (2003): 25–34.
  9. National Center for Education Statistics, The Condition of Education (U.S. Department of Education, 2001); John Wirt and others, The Condition of Education 2004, NCES 2004-077 (U.S. Department of Education, National Center for Education Statistics, 2004), table 19-2, p. 143.
  10. John Goldthorpe, “Education-Based Meritocracy: The Barriers to Its Realization,” paper presented to the Center for Policy Research, Maxwell School of Syracuse University (April 2002), www.cpr.maxwell.syr.edu/ seminar/spring05/goldthorpe.pdf.
  11. The effect of higher education on social mobility depends on both the effect of family income on schooling and the effect of schooling on offspring income. In our discussion, we emphasize the first of these components. However, we also provide some evidence on the latter linkage—that between schooling attainment and earnings.
  12. Goldthorpe, “Education-Based Meritocracy” (see note 10).
  13. Lars Osberg, Timothy M. Smeeding, and Jonathan Schwabish, “Income Distribution and Public Social Expenditure: Theories, Effects, and Evidence,” in Social Inequality, edited by Kathryn Neckerman (New York: Russell Sage Foundation, 2004), pp. 821–59. See also Susan Mayer, “How Did the Increase in Eco nomic Inequality between 1970 and 1990 Affect American Children's Educational Attainment?” unpublished manuscript, University of Chicago and Russell Sage Foundation (2005), on the effects of economic segregation on educational attainment.
  14. Susan Mayer, “How Economic Segregation Affects Children's Educational Attainment,” unpublished manuscript, Russell Sage Foundation (2005).
  15. While there is no empirical estimate of the effect of the higher education system on social mobility, English social researchers suggest that, relative to parental socioeconomic status, the education sector explains 20 percent of the variance in the status of offspring in that country.
  16. While our policy discussion recognizes the possibility that efforts to intervene in the development of human capital before the secondary and postsecondary levels may be more effective in attaining increased social mobility, we conclude that policies targeted on the higher education system are necessary to enable “college-qualified” youth to access and complete postsecondary schooling.
  17. Robert D. Mare, “Change and Stability in Educational Stratification,” American Sociological Review 46 (1981): 72–87; Robert Hauser, “Trends in College Entry among Whites, Blacks, and Hispanics,” in Study of Supply and Demand in Higher Education, edited by Charles Clotfelter and Michael Rothschild (University of Chicago Press, 1993), pp. 61–104.
  18. For an economic treatment of this issue, see Igal Hendel, Joel Shapiro, and Paul Willen, “Educational Opportunity and Income Inequality,” Journal of Public Economics 89 (2005): 841–70.
  19. Some would argue that in the face of the advantages enjoyed by youth from higher-income families, the higher education sector should target its services on those youth who lack these genetic and family-based advantages. We do not address this issue here, but note that the argument cannot easily be ignored if a goal of the higher education system is to promote social mobility.
  20. David Ellwood and Thomas J. Kane, “Who Is Getting a College Education: Family Background and the Growing Gaps in Enrollment,” in Securing the Future: Investing in Children from Birth to College, edited by Sheldon Danziger and Jane Waldfogel (New York: Russell Sage Foundation, 2000). Ellwood and Kane also report such gaps for students with similar mathematics test scores. For example, while 59 percent of high-income youth in the middle two quartiles of test scores attend a four-year college, only 33 percent of youth from the lowest income quartile and with test scores in this range attend these institutions. See also Paul Barton, “Toward Inequality: Disturbing Trends in Higher Education” (Princeton, N.J.: Educational Testing Service, 1997).
  21. Over the period covered by these two cohorts, the earnings return to college-going also increased substantially. It appears that youth from high-income families responded strongly to these increased returns from higher schooling and (of more concern) will reap the gains of these returns in their future careers.
  22. The High School and Beyond survey was sponsored by the National Center for Education Statistics to study the educational, vocational, and personal development of young people, beginning with their elementary or high school years and following them over time as they begin to take on adult roles and responsibilities. The survey included two cohorts: the 1980 senior and sophomore classes. Both cohorts were surveyed every two years through 1986, and the 1980 sophomore class was also surveyed in 1992.
  23. The Barron indicator of college selectivity is from Barron's Profiles of American Colleges.
  24. Susan Dynarski finds that even after controlling for ability, as measured by test scores, the college participation gap between youth in families in the top and bottom quartiles is 22 percentage points; without controlling for ability, the gap was 30 percentage points. See Susan Dynarski, “Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion,” Working Paper 7422 (Cambridge, Mass.: National Bureau of Economic Research, 1999).
  25. The estimates in table 1 reflect the efforts of Ellwood and Kane, “Who Is Getting a College Education?” (see note 20) to measure parental family income in a consistent way across data sources (see p. 320).
  26. The family income levels reported on student aid application forms (that is, supplied by parents) are generally substantially higher than the income levels reported by the students themselves in response to survey questions.
  27. This distinction is also very important if one wishes to infer more than correlation between family income and higher education attainment. A number of recent studies have found that permanent household income is a significant determinant of both college attendance decisions by youth and the level of family investments in children, while transitory income is not. See Michael P. Keane and Kenneth I. Wolpin, “The Effect of Parental Transfers and Borrowing Constraints on Educational Attainment,” International Economic Review 42, no. 4 (2001): 1051–103; Steven Cameron and James Heckman, “Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males,” Journal of Political Economy 106 (1998): 262–332; David Blau, “The Effect of Income on Child Development,” Review of Economics and Statistics 81, no. 2 (1999): 261–76; Pedro Carneiro and James Heckman,“The Evidence on Credit Constraints in Post-Secondary Schooling,” Economic Journal 112, no. 482 (2002): 705–34.
  28. Robert Haveman and Kathryn Wilson, “Economic Inequality in College Access, Matriculation, and Graduation,” paper presented to the Maxwell School conference on Economic Inequality and Higher Education.
  29. The estimates are similar when wealth is used as the indicator of economic position.
  30. Anthony P. Carnevale and Stephen J. Rose, “Socioeconomic Status, Race/Ethnicity, and Selective College Admissions,” in America's Untapped Resource: Low-Income Students in Higher Education, edited by Richard D. Kahlenberg (New York: Century Foundation Press, 2004), pp. 101–56.
  31. Gordon Winston and Catharine Hill, “Access to the Most Selective Private Colleges by High-Ability, Low- Income Students: Are They Out There?” paper prepared for the Macalester-Spencer Forum, 2005.
  32. Kirst, “Overcoming Educational Inequality” (see note 3).
  33. See Thomas Kane and Peter Orszag, “Higher Education Spending: The Role of Medicaid and the Business Cycle,” Policy Brief 124 (Brookings, September 2003).
  34. Note that the focus here is on the completion of postsecondary schooling, and the data in figure 1 refer to degree attainment, not college attendance, per se. There have been increases in the extent of college-going in the United States over past decades. Susan Dynarski reports that “in 1968, 36 percent of 23-year-olds had gone to college. By 2000, that figure had grown to 55 percent. Over the same period, the share of young people with a college degree has risen relatively slowly.” The reason for the disparity is the growth in college dropouts—students who start but do not complete college. Dynarski states that “in the 2000 Census, just 57 percent of those age 22 to 34 with any college experience had completed an associate's or bachelor's degree.” See Susan Dynarski, “Building the Stock of College-Educated Labor,” Working Paper 11604 (Cambridge, Mass.: National Bureau of Economic Research, 2005), www.nber.org/papers/w11604.
  35. In the future, it may be possible to study the linkage between family economic position and educational attainment using new data sources, for example, the Trends in International Mathematics and Science Study (TIMSS; http://nces.ed.gov/timss/) and the OECD's Program for International Student Assessment (PISA; http://nces.ed.gov/surveys/pisa), in a cross-national context. These data sources have information on the test scores that are a precursor to college-going, thus enabling study of the linkage between family position and test scores. Ludger Woessmann makes an initial foray into these data and finds that although family background has a strong effect on student test scores, there is little variation across countries. However, in France and Flemish Belgium the effect of family background on test scores is smaller than average and in Germany and England it is larger, representing respectively greater and lesser degrees of inequality of educational opportunity. See Ludger Woessmann, “How Equal Are Educational Opportunities? Family Background and Student Achievement in Europe and the United States,” Discussion Paper 1284 (Bonn, Germany: IZA, 2004).
  36. Orley Ashenfelter, Colm Harmon, and Hessel Oosterbeek, “A Review of Estimates of the Schooling/Earnings Relationship, with Tests for Publication Bias,” Labour Economics 6 (1999). Ashenfelter, Harmon, and Oosterbeek distinguished the studies by model, sample, extent of control for relevant variables, and the nature of the labor market (such as country). For example, across all of the studies the estimated rate of return to schooling averages 7.9 percent (S.D. = .036). When direct controls for schooling are employed, the average return drops to 6.6 percent (S.D. = .026); when data using twins are employed, the average return is 9.2 percent (S.D. = .037); when an instrumental variable approach is employed, the average return is 9.3 percent (S.D. = .041).
  37. Thomas J. Kane and Cecilia Elena Rouse, “Labor-Market Returns to Two- and Four-Year College,” American Economic Review 85, no. 3 (1995): 600–14.
  38. Dominic Brewer, Eric R. Eide, and Ronald G. Ehrenberg, “Does It Pay to Attend an Elite Private College? Cross-Cohort Evidence on the Effects of College Type on Earnings,” Journal of Human Resources 34, no. 1 (1999): 104–23. The study controls for selection on unobservables.
  39. Stacy Berg Dale and Alan B. Krueger, “Estimating the Payoff to Attending a More Selective College: An Application of Selection on Observables and Unobservables,” Quarterly Journal of Economics 117, no. 4 (2002), pp. 1491–527.
  40. Jeff Grogger and Eric Eide, “Changes in College Skills and the Rise in the College Wage Premium,” Journal of Human Resources 30, no. 2 (1995): 280–310.
  41. Mayer, “How Economic Segregation” (see note 14); Kirst, “Overcoming Educational Inequality” (see note 3).
  42. 42. National Center for Education Statistics, Digest of Education Statistics (U.S. Department of Education, 2002).
  43. Kirst, “Overcoming Educational Inequality” (see note 3); P. Michael Timpane and Arthur M. Hauptman, “Improving the Academic Preparation and Performance of Low-Income Students in American Higher Education,” in America's Untapped Resources: Low-Income Students in Higher Education, edited by Richard D. Kahlenberg (New York: Century Foundation Press, 2004); Vincent Tinto, “Economic Inequality and Higher Education: Access, Persistence, and Success,” comments delivered at the Maxwell School conference on Economic Inequality and Higher Education.
  44. Kane, “College Going and Inequality” (see note 5), contains an excellent discussion of these issues.
  45. Thomas Kane and Cecilia Rouse, “The Community College: Educating Students at the Margin between College and Work,” Journal of Economic Perspectives 13, no. 1 (1999): 63–84; Amanda Pallais and Sarah E. Turner, “Access to Elites: The Growth of Programs to Increase Opportunities for Low Income Students at Selective Universities,” paper presented to the Maxwell School conference on Economic Inequality and Higher Education; Michael McPherson, “Comments,” presented to the Maxwell School conference on Economic Inequality and Higher Education.
  46. Timpane and Hauptman, “Improving the Academic Preparation” (see note 43).
  47. Much of the following discussion rests on Lawrence E. Gladieux, “Low-Income Students and the Affordability of Higher Education,” in America's Untapped Resources: Low-Income Students in Higher Education, edited by Richard D. Kahlenberg (New York: Century Foundation Press, 2004), which includes a number of important recommendations for reform of federal, state, and institutional student financial aid. Many of these focus on increasing the targeting of assistance on students from low-income families.
  48. College Board, Trends in College Pricing, 2001 (New York, 2001).
  49. For analysis of the causal impact of college costs on attendance, see Thomas J. Kane, “College Entry by Blacks since 1970: The Role of College Costs, Family Background, and the Returns to Education,” Journal of Political Economy 102, no. 5 (1994): 878–911; Susan Dynarski, “Hope for Whom? Financial Aid for the Middle Class and Its Impact on College Attendance,” National Tax Journal 53, no. 3 (2000): 629–61; Susan Dynarski, “Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion,” American Economic Review 93, no. 1 (2003): 279–88; Susan Dynarski, “The New Merit Aid,” in College Choices: The Economics of Where to Go, When to Go, and How to Pay for It, edited by Caroline Hoxby (University of Chicago Press, 2004). For a review of this literature, see Susan Dynarski, “The Behavioral and Distributional Implications of Aid for College,” American Economic Review 92, no. 2 (2002): 279–85.
  50. Advisory Committee on Student Financial Assistance, Access Denied: Restoring the Nation's Commitment to Equal Educational Opportunity (Washington, 2001).
  51. Amy Ellen Schwartz, “The Cost of College and Implications for Income Inequality,” paper presented to the Maxwell School conference on Economic Inequality and Higher Education.
  52. Leonard E. Burman and others, “The Distributional Consequences of Federal Assistance for Higher Education: The Intersection of Tax and Spending Programs,” Discussion Paper 26 (Washington: Urban Institute Tax Policy Center, 2005), summarize the last decade of federal policy developments in this area as follows: “Since 1997, federal higher education subsidies have increasingly been delivered through the tax code rather than through traditional direct spending programs, such as grants, loans, and work study . . . and have been directed toward students from middle- and upper-middle-income families.” Using a microdata simulation model developed for estimating the distributional effects of higher education policies, they find that while two-fifths of Pell program expenditures flow to students in tax units with adjusted gross income (AGI) of less than $10,000, the tax provisions provide little benefit to households at the lower end of the income distribution and concentrate the bulk of their benefits within the broad middle- and uppermiddle class, with roughly $50,000 to $100,000 in cash income. They find that tax units in this income range receive almost 42 percent of the benefit from the various tax provisions, and that about one-seventh of the total tax benefit flows to tax units with cash incomes of $100,000 or more.
  53. Century Foundation, “Left Behind: Unequal Opportunity in Higher Education” (Washington, 2004).
  54. Michael McPherson and Morton Owen Schapiro, The Student Aid Game: Meeting Need and Rewarding Talent in American Higher Education (Princeton University Press, 1998).
  55. Michael McPherson and Morton Owen Schapiro, “Watch What We Do (and Not What We Say): How Student Aid Awards Vary with Financial Need and Academic Merit,” draft paper for presentation at the conference on Opening Opportunity or Preserving Privilege, Chicago, 2005.
  56. Congressional Budget Office, “H.R. 609, College Access and Opportunities Act of 2005,” presented to the House Committee on Education and the Workplace (July 25, 2005).
  57. Dynarski, “Building the Stock” (see note 34).
  58. This behavioral response is often referred to as the “Bennett hypothesis,” after former secretary of education William Bennett, who argued that “increases in financial aid in recent years have enabled colleges and universities blithely to raise their tuitions.” See William J. Bennett, “Our Greedy Colleges,” New York Times, February 18, 1987, p. A31. For rather different conclusions on this response, see Bridget Long, “The Institutional Impact of the Georgia HOPE,” Journal of Human Resources 39 (2004): 1045–66; and Benjamin Scafidi and others, “Merit-Based Financial Aid and College Tuition: The Case of Georgia's Hope Scholarships,” unpublished manuscript, Georgia State University (2003).
  59. Kane and Rouse, “The Community College” (see note 45).
  60. Dan Goldhaber and Gretchen Kiefer, “Higher Education and Inequality: The Increasingly Important Role Community Colleges Play in Higher Education,” paper presented to the Maxwell School conference on Economic Inequality and Higher Education.
  61. Eric P. Bettinger and Bridget Terry Long, “The Role of Institutional Responses to Reduce Inequalities in College Outcomes: Remediation in Higher Education,” paper presented to the Maxwell School conference on Economic Inequality and Higher Education.
  62. Goldhaber and Kiefer, “Higher Education and Inequality” (see note 60).
  63. Ibid.; Kane and Rouse, “The Community College” (see note 45); Thomas Kane, The Price of Admission: Rethinking How Americans Pay for College (Brookings, 1999).
  64. Bettinger and Long, “The Role of Institutional Responses” (see note 61).
  65. Thomas Bailey, Gregory Kienzl, and Dave E. Marcotte, “The Return to a Sub-Baccalaureate Education: The Effects of Schooling, Credentials and Program Study on Economic Outcomes” (Institute on Education and the Economy and the Community College Research Center, Teachers College, Columbia University, 2004).
  66. Thomas Bailey and others, “Educational Outcomes of Occupational Postsecondary Students” (Institute on Education and the Economy and the Community College Research Center, Teachers College, Columbia University, 2004).
  67. Debbie Sydow, comments presented to the Maxwell School conference on Economic Inequality and Higher Education.
  68. Jane Wellman, “State Policy and Community College—Baccalaureate Transfer” (National Center for Public Policy and Higher Education, Stanford University, August 2002); Kirst, “Overcoming Educational Inequality” (see note 3).
  69. Richard Romano and Martin Wisniewski, “Tracking Community College Transfers Using National Student Clearinghouse Data,” Working Paper 36 (Cornell Higher Education Research Insititute, 2003).
  70. Ibid.
  71. Goldhaber and Kiefer, “Higher Education and Inequality,” table 1, p. 19 (see note 60), show that nearly half of all community college enrollment is in five large states—California, Florida, Illinois, Texas, and New York—and in all but New York, community college enrollments exceed enrollments in public four-year colleges. California alone has 24.4 percent of the nation's community college students, but only 9.2 percent of the nation's public four-year college enrollees.
  72. Tinto, “Economic Inequality” (see note 43).
  73. Pallais and Turner, “Access to Elites” (see note 45).
  74. Kirst, “Overcoming Educational Inequality” (see note 3). Of course, were we to create policies to promote retention and persistence to a degree for low-income and low-qualification students, per student costs would be likely to increase.
  75. Despite the positive impact of remediation on educational outcomes, these authors note that the institutional variation they exploit to obtain their results necessitates excluding from their sample the lowest ability students, who would be in remediation at any institution. The impact of remediation on these students is unknown. Bettinger and Long, “The Role of Institutional Responses” (see note 61); Eric P. Bettinger and Bridget Terry Long, “Addressing the Needs of Under-Prepared Students in Higher Education: Does College Remediation Work?” Working Paper 11325 (Cambridge, Mass.: National Bureau of Economic Research, 2005).
  76. Mayer, “How Economic Segregation” (see note 14); Pell Institute, Indicators of Opportunity (see note 5); Haveman and Wilson, “Economic Inequality” (see note 28).
  77. Thomas Garrett and William Poole, “Stop Paying More for Less: Ways to Boost Productivity in Higher Education,” Regional Economist (Federal Reserve Bank of St. Louis, January 2006).
  78. Pallais and Turner, “Access to Elites” (see note 45); McPherson, “Comments” (see note 45).
  79. Bruce Chapman and Chris Ryan, “The Access Implications of Income Contingent Charges for Higher Education: Lessons from Australia,” Economics of Education Review 24, no. 5 (2005): 491–512. In early 1993, the Clinton administration introduced broad-based reforms to student loan programs, including an option for students to adopt income-contingent repayments for some part of their student loan obligations, up to 20 percent of an agreed income. See Evelyn Brody, “Paying Back Your Country through Income-Contingent Student Loans,” San Diego Law Review 31 (1994): 449–518.