- 9.2% of our annual attendance records for students aged 19-22 were not in the 1098-T data and appeared only in the NSLDS Pell data. Using our most-attended college attendance measure, 4.1% of the students in our analysis sample were not in the 1098-T data and originally appeared only in the NSLDS Pell data. The NSLDS Pell data has a smaller impact at the student level than the student-year level because many students attend a given college for multiple years and receive a 1098-T form in at least one of those years.
Paper not yet in RePEc: Add citation now
Andrews, R., S. Imberman, and M. Lovenheim (2016). Recruiting and Supporting Low-Income, High-Achieving Students at Flagship Universities. NBER Working Paper No. 22260.
Angrist, J., D. Autor, S. Hudson, and A. Pallais (2014). Leveling Up: Early Results from a Randomized Evaluation of Post-Secondary Aid. NBER Working Paper No. 20800.
- As discussed in Section II.D, we impute income statistics and attendance for colleges with missing data for the 1980-82 cohorts using data from the 1983 and 1984 cohorts. We use this procedure to impute data for 597 (27%), 519 (24%), and 408 (19%) colleges in cohorts 1980-1982, respectively, accounting for 570,000 additional students (9.1% of college attendees and 5.0% of all children). For the remaining 105 colleges that are missing data for either the 1983 or 1984 cohorts, we do not impute any values. This leaves us with 11.3 million children in our core sample underlying our main analysis.
Paper not yet in RePEc: Add citation now
- Average Faculty Salary. This variable measures the average salary for full-time faculty members on 9-month equated contracts in the academic year 2001-02, as reported in the IPEDS Delta Cost Project Database.
Paper not yet in RePEc: Add citation now
Avery, C., C. Hoxby, C. Jackson, K. Burek, G. Pope, and M. Raman (2006). Cost Should Be No Barrier: An Evaluation of the First Year of Harvard’s Financial Aid Initiative. NBER Working Paper No. 12029.
Avery, C., M. Glickman, C. Hoxby, and A. Metrick (2013). A Revealed Preference Ranking of U.S. Colleges and Universities. Quarterly Journal of Economics 128(1), 425–467.
- Barron’s Educational Series, College Division (Ed.) (2008). Barron’s Profiles of American Colleges 2009. Hauppage, NY: Barron’s Educational Series, Inc.
Paper not yet in RePEc: Add citation now
Black, D. and J. A. Smith (2004). How Robust Is the Evidence on the Effects of College Quality? Evidence from Matching. Journal of Econometrics 121(1-2), 99–124.
- Both points use the success rate for the 1980-82 cohorts as the y-axis coordinate. The solid circles and triangles use access for the 1980 cohort (who are 20 in 2000) as the x-axis variable; the open circles and triangles use access for the 1991 cohort (who are 20 in 2011) as the x-axis variable. The curves show isoquants of mobility rates at the 10th, 50th, and 90th percentiles in the cross-sectional sample, taken directly from Figure Va. We also report the mean enrollment-weighted mobility rate for each group of colleges in 2000 and 2011, measured as the product of success rates for the 1980-82 cohorts with access in either the 1980 or 1991 cohorts.
Paper not yet in RePEc: Add citation now
- Bowen, W. G. and D. Bok (1998). The Shape of the River: Long-Term Consequences of Considering Race in College and University Admissions. Princeton, NJ: Princeton University Press.
Paper not yet in RePEc: Add citation now
Chetty, R., N. Hendren, P. Kline, and E. Saez (2014). Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States. Quarterly Journal of Economics 129(4), 1553–1623.
- Cilke, J. (1998). A Profile of Non-Filers. U.S. Department of the Treasury, Office of Tax Analysis Working Paper No. 78.
Paper not yet in RePEc: Add citation now
- College Board (2016). Annual Survey of Colleges. Available at https://professionals.collegeboard. org/higher-ed/recruitment/annual-survey.
Paper not yet in RePEc: Add citation now
- college’s Employer Identification Number (EIN) and its ZIP code. We use 1098-T data for students during calendar years 1999-2013.
Paper not yet in RePEc: Add citation now
- Congress has changed both the Maximum Pell Grant and the EFC formula over time, although the changes to the Maximum Pell Grant have been most consequential. The series in solid circles in Appendix Figure IXa plots the Maximum Pell Grant (in real 2015 dollars) over our sample period.
Paper not yet in RePEc: Add citation now
- Dale, S. and A. B. Krueger (2002). Estimating the payoff to attending a more selective college.
Paper not yet in RePEc: Add citation now
- Data Sources. We combine two data sources to measure student-level college attendance: Form 1098-T records and National Student Loan Data System (NSLDS) Pell grant recipient records. Note that neither data source relies on the student or the student’s family to file a tax return, and neither data source contains information on course of study or degree attainment.
Paper not yet in RePEc: Add citation now
- Declining Real Household Incomes. The second factor that drives a wedge between trends in Pell shares and our percentile-based measures of access is the well-known fact that real incomes have fallen for low-income households in recent years (e.g., Piketty et al. 2016). For example, in our data, the 40th percentile of the income distribution among parents with college-age children fell from $45,600 for parents of children in the 1980 cohort to $36,300 in the 1991 cohort. This implies that the fraction of parents with incomes below the thresholds for Pell eligibility has increased, driving up Pell shares irrespective of any changes in colleges’ policies.
Paper not yet in RePEc: Add citation now
- definition to every NSLDS Pell record and ever 1098-T record, we use information from the NSLDS on dates of attendance to impute missing 1098-T data, thereby yielding comprehensive attendance records by calendar year from 1999-2013.
Paper not yet in RePEc: Add citation now
- Deming, D. and C. Walters (2017). The Impacts of Price and Spending Subsidies on U.S. Postsecondary Attainment. Working Paper.
Paper not yet in RePEc: Add citation now
- Deming, D. and S. Dynarski (2010). Into College, Out of Poverty? Policies to Increase the Postsecondary Attainment of the Poor, pp. 283–302. University of Chicago Press.
Paper not yet in RePEc: Add citation now
Deming, D. J., C. Goldin, L. F. Katz, and N. Yuchtman (2015). Can Online Learning Bend the Higher Education Cost Curve? American Economic Review Papers and Proceedings 105(5), 496–501.
Deming, D., C. Goldin, and L. F. Katz (2012). The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators? Journal of Economic Perspectives 26(1), 139–64.
- Details on Income Definitions. As discussed in Section II, in our baseline analysis, we measure children’s earnings as the sum of individual wage income and net self-employment income (if positive) for year 2014. Here we provide further details regarding those definitions, which are more complex than our parent income definitions because we must apportion total income reported on the tax return across individuals to measure income at the individual level.
Paper not yet in RePEc: Add citation now
- Endowment per Student. We compute the endowment per student by dividing the ending value of endowment assets in 2000, which are taken from IPEDS’ Delta Cost Project Database, by the total undergraduate enrollment in the fall of 2000, taken from IPEDS Fall Enrollment survey.
Paper not yet in RePEc: Add citation now
- Enrollment Counts for Attendance Measures. The steps described above yield a student-collegeyear level dataset that provides a complete record of college attendance in the U.S. during calendar years 1999-2013 for children born between 1980-1991. This dataset contains 207.6 million observations.
Paper not yet in RePEc: Add citation now
- Enrollment. We measure enrollment as the sum of total full-time and part-time undergraduate students enrolled in the fall of 2000 using data from the IPEDS Fall Enrollment survey.
Paper not yet in RePEc: Add citation now
Espenshade, T. J., C. Y. Chung, and J. L. Walling (2004). Admission Preferences for Minority Students, Athletes, and Legacies at Elite Universities. Social Science Quarterly 85(5), 1422–1446.
- Expenditures per Student. Following the approach of Deming and Walters (2017), we compute the instructional expenditure per student for a college in 2000 as the total expenditure for instruction excluding operations and maintenance and interest for the year divided by the total enrollment in the fall of 2000 using data from IPEDS.
Paper not yet in RePEc: Add citation now
- F. Changes in Low-Income Access: Pell Shares vs. Percentile-Based Measures In this appendix, we reconcile our findings on trends in access with prior work that has used the share of students eligible for Pell grants as a proxy for low-income access. For example, many elite private colleges have cited their rising Pell share as evidence of success in attracting a more economically diverse student body. Ivy-Plus colleges, for instance, have seen their average Pell share increase from 12.1% to 16.8% between 2000 and 2011. The Pell share has also been used to measure access more broadly, for instance in the New York Times College Access Index (2017).
Paper not yet in RePEc: Add citation now
- FIGURE III: Relationship Between Children’s and Parents’ Ranks within Colleges A. Selected Colleges 30 40 50 60 70 80 Child Rank 0 20 40 60 80 100 Parent Rank National (Slope: 0.288) UC Berkeley (Slope: 0.060) SUNY Stony Brook (Slope: 0.041) Glendale CC (Slope: 0.027) B. By College Tier 30 40 50 60 70 80 Child Rank 0 20 40 60 80 100 Parent Rank National (Slope: 0.288) Elite Colleges (Slope: 0.065) Other Four-Year Colleges (Slope: 0.095) Two-Year (Slope: 0.110) Notes: This figure shows the relationship between children’s income ranks and parents’ income ranks for children in the 1980-82 birth cohorts. Panel A plots the mean child rank in each parent income ventile (5 percentile point bin) vs.
Paper not yet in RePEc: Add citation now
- For each child, we define the parent(s) as the person(s) who claim the child as a dependent on a 1040 tax form in the year the child turns 17. Note that the parent(s) of the child are not necessarily biological parents, as it is possible for custodians (regardless of family status) to claim a child if the child resides with them.54 If parents are married but filing separately, we assign the child both parents. We identify children’s parents at age 17 because our goal is to measure the economic resources of the child’s family around the time he or she attends college. We do not match children to parents at later ages (e.g., 18 or 19) because many children leave home after age 17 (at differential rates across income groups), creating scope for selection bias.
Paper not yet in RePEc: Add citation now
- Form 1098-T is an information return that is submitted by colleges to the U.S. Treasury Department.
Paper not yet in RePEc: Add citation now
- Fourth, we describe how we identify and remove a small set of colleges who have incomplete 1098-T data. Finally, we summarize annual enrollment counts for our college attendance definitions.
Paper not yet in RePEc: Add citation now
Goodman, J. (2008). Who Merits Financial Aid? Massachusetts’ Adams Scholarship. Journal of Public Economics 92(10), 2121–2131.
- Graduation Rate. We measure the graduation rate as of the year 2002. This variable comes from the IPEDS Delta Cost Project Database, which is a longitudinal database derived from IPEDS survey data. It measures the percentage of full-time, first-time, degree/certificate-seeking under55 graduate students graduating within 150 percent of normal time at four-year and two-year institutions.
Paper not yet in RePEc: Add citation now
Haider, S. and G. Solon (2006). Life-Cycle Variation in the Association between Current and Lifetime Earnings. American Economic Review 96(4), 1308–1320.
Hastings, J., C. Neilson, and S. Zimmerman (2013). Are Some Degrees Worth More than Others? Evidence from college admission cutoffs in Chile. NBER Working Paper No. 19241.
Hill, C., D. D.-V. Atta, R. Gambhir, and G. Winston (2011). Affordability of Highly Selective Private Colleges and Universities II. Williams Project on the Economics of Higher Education. Discussion Paper No. 73.
Hoekstra, M. (2009). The Effect of Attending the Flagship State University on Earnings: a Discontinuity-Based Approach. Review of Economics and Statistics 91(4), 717–724.
- Hout, M. (1988). More Universalism, Less Structural Mobility: The American Occupational Structure in the 1980s. American Sociological Review 93(6), 1358–1400.
Paper not yet in RePEc: Add citation now
Hoxby, C. and C. Avery (2013). The Missing â€ÂOne-Offsâ€Â: The Hidden Supply of High-Achieving, Low-Income Students. Brookings Papers on Economic Activity 2013(1), 1–65.
- Hoxby, C. and S. Turner (2013). Expanding College Opportunities for High-Achieving, Low-Income Students. Stanford Institute for Economic Policy Research Discussion Paper No. 12-014.
Paper not yet in RePEc: Add citation now
- Hoxby, C. M. (2015). Computing the Value-Added of American Postsecondary Institutions. Working Paper.
Paper not yet in RePEc: Add citation now
- If the college had submitted 1098-Ts on behalf of a given Pell student whose enrollment period began in calendar year t, the college would likely have submitted a 1098-T for the student in calendar year t (had it been required to do so). Thus, for every NSLDS Pell student with Super OPEID x and an enrollment start date in calendar year t, we impute a 1098-T for the student with Super OPEID x and calendar year t.
Paper not yet in RePEc: Add citation now
- King, J. E. (2004). Missed Opportunities: Students Who Do Not Apply for Financial Aid. American Council on Education Issue Brief .
Paper not yet in RePEc: Add citation now
- Looney, A. (2017). A Comparison between the College Scorecard and Mobility Report Cards. Accessed on May 19, 2017. https://www.treasury.gov/connect/blog/Pages/ A-Comparison-between-the-College-Scorecard-and-Mobility-Report-Cards.aspx.
Paper not yet in RePEc: Add citation now
Marx, B. and L. Turner (2015). Borrowing Trouble? Student Loans, the Cost of Borrowing, and Implications for the Effectiveness of Need-Based Grant Aid. NBER Working Paper No. 20850.
- Mobility rates are the fractions of children who have parents in the bottom income quintile and whose own earnings place them in either the top 20% or top 1% of their own age-specific income distribution. The trend statistics are coefficients from enrollment-weighted univariate regressions of the share of parents from the bottom 20% or 60% on student cohort, multiplied by 11; the statistics can therefore be interpreted as the trend change in access over the 1980-1991 cohorts.
Paper not yet in RePEc: Add citation now
- Most colleges file a 1098-T for every student, regardless of whether the student’s tuition has been waived. However, some colleges do not file a 1098-T for students who pay no tuition. Almost all such students with American parents are from low-income families, are eligible for a Pell grant from the federal government, and are required by their colleges to acquire a Pell grant in order to receive their tuition waiver.
Paper not yet in RePEc: Add citation now
- Net Cost for Low-Income Students. The net cost for low-income variable is taken from Department of Education’s College Scorecard for the year 2013. This variable captures the average net cost of attendance for full-time, first-time degree/certificate seeking undergraduates who receive Title IV aid and are in the bottom quintile of the income distribution ($0-$30,000 family income).
Paper not yet in RePEc: Add citation now
- Note that this metric is only available in the Scorecard starting in the academic year 2009-10.
Paper not yet in RePEc: Add citation now
- Online Appendices A. Sample Construction and Income Definitions Sample Definition. Our primary sample is very similar to the “extended sample†analyzed in Chetty et al. 2014, and much of this appendix is therefore taken directly from Chetty et al. (2014, Online Appendix A).
Paper not yet in RePEc: Add citation now
- ONLINE APPENDIX FIGURE IX Trends in Eligibility for Pell Grants, 2000-20111 A. Maximum Pell Grant Amounts and Pell Shares at Ivy-Plus Colleges 12 13 14 15 16 17 %
Paper not yet in RePEc: Add citation now
- ONLINE APPENDIX FIGURE VII Trends in College Attendance for Children in Low-Income Families 0 10 20 30 40 Percentage Attending College 2000 2002 2004 2006 2008 2010 Year when Child was 20 4-Year Elite 4-Year Selective 4-Year Selective, Non-Elite 2-Year For-Profit Notes: This figure presents a stacked area graph of the percentage of children from families in the bottom income quintile who attend colleges in different tiers, in each cohort in our extended analysis sample (1980-1991). For ease of interpretation, the x-axis shows the year in which children in the relevant cohort turn 20 (e.g., 2000 corresponds to data from the 1980 birth cohort). See notes to Figures II and IX for definition of college tiers.
Paper not yet in RePEc: Add citation now
- ONLINE APPENDIX FIGURE VIII Trends in Bottom 60% Access, 2000-2011 A. By College Tier 0 20 40 60 80 100 Percent of Parents in the Bottom 60% 2000 2002 2004 2006 2008 2010 Year When Child was 20 All Colleges For-Profit Colleges 2-Year Colleges Other 4-Year Colleges Other Elite Ivy-Plus B. At Selected Colleges 0 20 40 60 80 Percent of Parents in the Bottom 60% 2000 2002 2004 2006 2008 2010 Year When Child was 20 Glendale CC SUNY Stony Brook UC Berkeley Stanford Harvard Notes: This figure replicates Panels A and B of Figure X, showing trends (in Panel A) and the specific values for certain colleges (Panel B) in the fraction of students from the bottom three quintiles instead of the bottom quintile. See notes to Figure X for further details.
Paper not yet in RePEc: Add citation now
Pallais, A. and S. Turner (2006). Opportunities for Low-Income Students at Top Colleges and Universities: Policy Initiatives and the Distribution of Students. National Tax Journal 59(2), 357–386.
- Parents' incomes are measured at the household level when children are between the ages of 15 and 19, while children's incomes are measured at the individual level in 2014. See notes to Table I for futher details on income definitions and how children are assigned to colleges. Median Parent Income ($) Median Child Earnings ($) WithinCollege Rank-Rank Slope Num. of Colleges (80-82 cohorts) Num. of Students (80-82 cohorts) Mobility Rate Success Rate Sample: Sons Daughters Dependent Variable: Individual Earnings Rank Working HH Earn. Rank Married HH Inc.
Paper not yet in RePEc: Add citation now
- Pell Recipients at Ivy-Plus Colleges 4500 5000 5500 6000 Maximum Pell Grant (2015$) 2000 2002 2004 2006 2008 2010 Year When Child Was 20 Maximum Pell Grant Pell Share at Ivy-Plus Colleges B. Percent Eligible for Pell Grants by Parent Income, 2000 vs. 2011 0 15 30 45 60 75 90 %
Paper not yet in RePEc: Add citation now
Piketty, T., E. Saez, and G. Zucman (2016). Distributional National Accounts: Methods and Estimates for the United States. NBER Working Paper. No. 22945.
- Public. This indicator provides a classification of whether a college is operated as public institution or as a private college that derives its funding from private sources. We use the Integrated Postsecondary Education Data System’s (IPEDS) Institutional Characteristics survey in 2013 to create this indicator. For colleges aggregated in a cluster, we assign the cluster the type of the institution with the largest enrollment in that cluster.
Paper not yet in RePEc: Add citation now
- Removing College-Years with Incomplete 1098-T Data. A small number of college-year observations have incomplete 1098-T data, either because of errors in administrative records or because of changes in EIN’s and reporting procedures.63 We discard these defective college-years by flagging them using two methods based on counts of total students. The counts described below are con63 Most of these cases are college-year cells with zero 1098-Ts in the database. For example, in the years when the 1098-T first began to be collected (1999-2002), a number of small universities do not have any records at all in the database. In addition, some universities switch from reporting data separately for each campus to using a single EIN-ZIP for all their campuses, which creates inconsistencies in their data across years.
Paper not yet in RePEc: Add citation now
Rothstein, J. and A. H. Yoon (2008). Affirmative Action in Law School Admissions: What Do Racial Preferences Do? The University of Chicago Law Review 75(2), 649–714.
- Sander, R. H. (2004). A Systemic Analysis of Affirmative Action in American Law Schools. Stanford Law Review, 367–483.
Paper not yet in RePEc: Add citation now
- SAT Scores. We compute average SAT scores as the mean of the 25th and 75th percentile SAT scores on the math and verbal sections reported by colleges in IPEDS in 2001 and 2013, scaled to 1600. For colleges aggregated in a cluster, we compute this and all other measures below as the enrollment-weighted mean of the variable for the colleges in the cluster.
Paper not yet in RePEc: Add citation now
Solon, G. (1992). Intergenerational Income Mobility in the United States. American Economic Review 82(3), 393–408.
Solon, G. (1999). Intergenerational Mobility in the Labor Market. In O. Ashenfelter and D. Card (Eds.), Handbook of Labor Economics, Volume 3, pp. 1761–1800.
- STEM Major Share. This variable measures the percentage of degrees awarded in communication technologies, computer and information services, engineering, engineering related technologies, biological sciences, mathematics, physical sciences and science technologies in the year 2000, using data from IPEDS.
Paper not yet in RePEc: Add citation now
- Sticker Price. We compute this measure as the sum of tuition for in-state undergraduate fulltime, full-year students and in-state undergraduate fees from IPEDS for the academic year 2000-01.
Paper not yet in RePEc: Add citation now
- structed using the total counts of forms 1098-T and Pell grants for all children born in 1980-1991, regardless of a successful link to parents and regardless of whether the student attends several institutions.
Paper not yet in RePEc: Add citation now
- Tebbs, J. and S. Turner (2005). Low-Income Students a Caution about Using Data on Pell Grant Recipients. Change: The Magazine of Higher Learning 37(4), 34–43.
Paper not yet in RePEc: Add citation now
- The 1999 1098-T data lack the ZIP code of the college, so in that year only, we assign Super OPEID using the subset of EINs from the Super OPEID crosswalk that map to a single Super OPEID regardless of ZIP code.
Paper not yet in RePEc: Add citation now
- The cap increased by more than 33% between 2000 and 2011. The largest changes were an increase from $3,300 in 2000 to $4,000 in 2002 and from $4,310 in 2007 to $5,500 in 2010. These increases, in turn, expanded significantly the range of parental incomes at which students could qualify for Pell grants. The series in open circles in Appendix Figure IXa plots the fraction of students receiving Pell grants at the twelve Ivy-Plus colleges. The changes in observed Pell shares closely track the maximum Pell grant amount, suggesting that at least part of the increase in Pell shares is due to the changes in federal eligibility rules rather than changes in colleges’ policies.
Paper not yet in RePEc: Add citation now
- The decline in real incomes accounts for roughly a 2.5 pp increase in Pell-eligible students at Ivy-Plus colleges between 2000 and 2011.70 In sum, we estimate that the changes in the Pell eligibility thresholds and the decline in real incomes together lead to roughly a 5.4 pp increase in the share of Pell-eligible students at IvyPlus colleges. This predicted change is similar to the observed increase of 4.7 pp. The Pell data thus imply that there was no significant change in the parental income distribution of students at Ivy-Plus colleges between 2000-2011, consistent with our conclusions in Figure Xa.
Paper not yet in RePEc: Add citation now
- The New York Times (2017, May). College Access Index. Accessed May 31, 2017. https://www. nytimes.com/interactive/2017/05/25/sunday-review/opinion-pell-table.html.
Paper not yet in RePEc: Add citation now
- The series in triangles plots the fraction of students in each parental income percentile with a college attendance record in the 1098-T data only. The series in solid circles plots the fraction who attend college based on the union of the NSLDS and 1098-T data, the measure of attendance we use in our empirical analysis.
Paper not yet in RePEc: Add citation now
- Theil, H. (1972). Statistical Decomposition Analysis. With Applications in the Social and Administrative Sciences. Amsterdam: North-Holland Pub. Co.
Paper not yet in RePEc: Add citation now
- There are no public measures of calendar-year Pell attendance that can be used to directly validate the imputation procedure described above. However, indirect validation methods suggest a high degree of fidelity. The share of our students on a Pell grant in the average calendar year is very highly correlated with, and similar in levels to, approximations to annual Pell student shares based on publicly available data. Moreover, at colleges with substantial numbers of students on Pell grants, the imputation algorithm adds almost no net students to 1098-T attendance records – consistent with these colleges issuing 1098-T forms for all students regardless of their tuition billing status and with our algorithm only imputing 1098-Ts in calendar years that the student was in fact enrolled.
Paper not yet in RePEc: Add citation now
- To construct the age-20 definition, we restrict the full dataset to attendance at age 20, which leaves 30.5 million records. If a student attends multiple colleges at age 20, we weight the studentcollege -level records using the method described in Section II.B such that each student carries a total weight of one, leaving 27.3 million effective records for 26.1 million students. After bringing in non-college goers under this definition, restricting to birth cohorts 1980-1982, and restricting to students matched to parents with weakly positive income, we have 11.0 million records for 10.8 million children. Finally, we impute income statistics and attendance for colleges with missing data for the 1980-82 cohorts as described above, leaving us with a 11.3 million person sample underlying our age-20 analysis.
Paper not yet in RePEc: Add citation now
- To construct the most-attended definition, we first restrict the full dataset to attendance between ages 19-22, which leaves 114.6 million records. Condensing the student-college-year data to the student level using the most-attended definition (see Section II.B) leaves 33.1 million student-level records. Eliminating students we cannot match to parents or whose parents had negative income leaves 31.0 million records. Finally, restricting to birth cohorts 1980-1982 (as we do in our main analysis) leaves 6.7 million records; including non-college goers in this sample yields a sample size of 10.8 million children.
Paper not yet in RePEc: Add citation now
- To quantify the impacts of these trends in real incomes on Pell shares, we hold fixed Pell eligibility rules at the 2000 levels and calculate the fraction of students who would have been eligible for Pell grants based on the national parental income distributions for each cohort from 1980-1991. We assume that the share of students who attend Ivy-Plus colleges within each parental income ventile remains fixed at the level observed for the 1980 cohort, thereby isolating the impacts of national trends in income inequality (holding fixed colleges’ selection of students from that distribution).
Paper not yet in RePEc: Add citation now
- Trend in Success Rates (1980-84 Birth Cohorts, pp) -8-4 0 4 8 Trend in Access (1980-84 Birth Cohorts, pp) B. Projected Changes in Mobility Rates For Selected Colleges 0 20 40 60 80 100 Success Rate: P(Child in Q5 |
Paper not yet in RePEc: Add citation now
- Turner, S. (2014.). Providing Information, Avoiding Distortions: Challenges for the Postsecondary Information Rating System. EdPolicyWorks Working Paper Series No. 21..
Paper not yet in RePEc: Add citation now
- U.S. Department of Education (2015). The College Scorecard. https://collegescorecard.ed.gov/ data/.
Paper not yet in RePEc: Add citation now
- Using this dataset, we construct the three measures of college attendance – the most-attended college (our primary measure), age-20 college, and first-attended college – following the definitions given in Section II.B. In what follows, we document the impact of the restrictions imposed in each definition on sample sizes and report the share of observations obtained from the 1098-T vs. NSLDS datasets.
Paper not yet in RePEc: Add citation now
- We begin with the universe of individuals in the Death Master (also known as the Data Master1) file produced by the Social Security Administration. This file includes information on year of birth and gender for all persons in the United States with a Social Security Number or Individual Taxpayer Identification Number (ITIN).53 To construct our sample of children, we begin from the set of individuals born in the 1980-1991 cohorts. We measure parent and child income, college attendance, and all other variables using data from the IRS Databank, a balanced panel covering all individuals in the Death Master file who were not deceased as of 1996.
Paper not yet in RePEc: Add citation now
- We implement this calculation in three steps. First, we calculate the shares of children at each absolute level of parental income (measured in 2015 dollars) who received a Pell grant in 2000, as in Appendix Figure IXb. We then use these estimates to calculate the fraction of students who would receive Pell grants (under Pell eligibility rules from 2000) in each parent income ventile in subsequent years. Finally, we calculate the predicted Pell-share at Ivy-Plus colleges for each cohort as the mean of these parent-ventile-specific Pell shares, weighting by the fraction of students from each parental income ventile at Ivy-Plus colleges in 2000. Appendix Figure IXc shows that there is an increasing trend in the fraction of Pell-eligible students at Ivy-Plus colleges that is generated purely by national trends in the income distribution.
Paper not yet in RePEc: Add citation now
- We map the NSLDS data to calendar years as follows. For every NSLDS Pell student at a Super OPEID x and a Pell award enrollment start date lying in calendar year t, we impute a 1098-T for the student at Super OPEID x in calendar year t. Then, for every NSLDS Pell student at a Super OPEID x and a Pell enrollment start date in the second half of calendar year t and with a Pell grant amount equal to more than 50% the student’s maximum eligible Pell amount in the award year, we additionally impute a 1098-T for the student at Super OPEID x in calendar year t + 1. Finally, we remove duplicate records. The remainder of this subsection explains the logic underlying this imputation strategy further. The NSLDS Pell data contain the start date of the enrollment period covered by the Pell grant.
Paper not yet in RePEc: Add citation now
- We therefore supplement the 1098-T records with records from the administrative NSLDS Pell records. The NSLDS contains information on every Pell grant awarded, including the college receiving the Pell payment (Pell grant payments are remitted directly from the federal government to the college the student attended). The NSLDS Pell data are indexed by award years, defined as the spring of the academic year beginning on July 1. We use NSLDS Pell data for all students in award years 1999-2014, comprising Pell awards for enrollment spells that began between the dates July 1, 1999, and June 30, 2014 (roughly academic years beginning in calendar years 19992013) . Colleges are indexed in the NSLDS Pell data by the six-digit federal OPEID (Office of Postsecondary Education Identification) identifier.
Paper not yet in RePEc: Add citation now
- We use the NSLDS Pell data to impute missing 1098-T data and thereby construct comprehensive student-college-year attendance records 1999-2013.58 Doing so requires homogeneous college and time-period definitions across the two data sources, but the two data sources differ in these definitions. The next two subsections detail our methods for homogenizing those definitions and constructing comprehensive student-college-year attendance records.
Paper not yet in RePEc: Add citation now
Zimmerman, S. D. (2014). The Returns to College Admission for Academically Marginal Students. Journal of Labor Economics 32(4), 711–754.