Tax Benefits for Graduate Education

Tax Benefits for Graduate Education Steven Bednar and Dora Gicheva November 2011 Abstract This paper examines how changes in the tax treatment of graduate tuition affect enrollment in and financing of graduate education. We examine the period of 1993-2010. From 1993-1996 and 2002-2010, employees could receive $5,250 worth of tax exempt graduate tuition assistance from their employer. From 1996-2001 this exemption was not in place. Using the October supplements of the CPS we find that enrollment rates among full time workers were lowest when this tax exemption was not available. Using the National Postsecondary Student Aid Study we find that individuals aged 31-40 enrolled in Master s or Doctoral programs receive more of their funding from employers when the tax exemption is in place. However, individuals aged 23-30 do not see a significant increase. We control for features of the Tax Relief Act of 1997. Keywords:Educational Finance, Tax Code JEL Classification Codes:H52, I22 Preliminary draft. Comments are welcome. Please do not cite. Department of Economics, Elon University. E-mail: sbednar@elon.edu. Department of Economics, University of North Carolina at Greensboro. E-mail: d gichev@uncg.edu. 1

In 2011, aggregate student debt eclipsed credit card debt (Lewin 2011). The national unemployment rate has hovered around nine percent meaning that college graduates are having a harder time landing jobs than in the past and thus being less able to pay down their student debt. Kahn (2010) finds that students who graduate in worse national economies are less likely to find a high paying job so they either complete more education or stick with a lower paying job. Lifetime earnings of those that graduate in a down economy are therefore lower than those that graduate during a good economy. The state of the economy can also affect decisions about whether to start a graduate degree. Johnson (2011) finds that enrollment of females in master s programs is countercyclical and male enrollment in graduate programs in general is acyclical. In addition to taking into account the state of the economy at the time of enrollment and completion of a degree, individuals must consider how they will fund the education. This paper examines how the state of the economy, the tax code and government education policies affect graduate enrollment rates as well as how students fund their graduate education. It is important to understand the degree to which different groups of students respond to tax incentives for education in order to be able to conduct cost-benefit analysis of the government spending on such benefits. In the 2009-10 academic year alone, $1 billion of graduate student aid was in the form of federal education tax credits and deductions (Baum and Payea 2010). While numerous studies have examined the enrollment responses of traditional undergraduate students to changes in the tax treatment of tuition payments 1, far less attention has been devoted to graduate students and older undergraduate students, who are most likely to pay for the education themselves and who have to balance work, family, and education expenditures. It is likely that tax 1 See for example Susan Dynarski s work, including Dynarski (2000), Dynarski (2003) and the overview in Dynarski (2002), as well as Long (2004) and Kane (2003),Kane (2007), Abraham and Clark (2006), among others. 2

benefits affect such students differently than more traditional undergraduate students. Responses to changes in the tax treatment of employer-provided tuition assistance can also help us understand firm-provided general training better. Over the past twenty years the United States government has enacted several federal policies with the goal of increasing graduate education enrollment. Notable policies include allowing a tax exemption for employer provided tuition assistance and allowing for a non-refundable tax credit linked to tuition payments made by the individual. We examine how graduate enrollment and the proportion of total aid that comes from employers relates to these policies. Both policies lower the cost of graduate education which should lead to an increase in enrollment. The incidence of the tax credit will fall on firms if they change the amount of tuition assistance offered in response to the change in the tax code. For example, suppose a firm provides $5,000 in tuition assistance of which the student must pay $1,000 in taxes (assuming a 20 percent average tax rate) if the tuition assistance is not exempt. When the assistance becomes exempt, the employer could decrease their assistance to $4,000 and the student could pay $1,000 to cover the difference. The student is thus no better or worse off but the firm has reduced the amount it pays. Using the October supplements of the CPS we find that enrollment rates among full time workers were lowest when the tax exemption was not available. We then examine the amount of total aid that comes from employers in the National Postsecondary Student Aid Study. We find that individuals aged 31-40 enrolled in master s or Doctoral programs receive more of their funding from employers when the tax exemption is in place. However, individuals aged 23-30 do not see a significant increase. Part-time M.B.A. students report that over half of their total student aid comes from employers, 3

but this does not change when the exemption is in place. The rest of the paper is organized as follows. Section 1 describes in detail the sources of student aid and provides some summary statistics about trends in student aid, section 2 describes the data, section 3 provides the results and section 4 concludes. 1 Sources of Education Finance 1.1 Loans and Grants From 1994 to 2010, graduate students had about two dollars worth of loans for every dollar received in grants (Baum and Payea 2010). 2 The majority of graduate student loans come from the federal Stafford Loan Program. Interest begins accruing immediately with unsubsidized Stafford Loans whereas the government covers the interest while a student is enrolled in school under a subsidized loan. Subsidized Stafford Loans are need based whereas anyone can borrow from an unsubsidized loan. Graduate students can accrue a combined $138,500 across these two types of loans. The NPSAS data do not distinguish between subsidized and unsubsidized Stafford Loans. The interest rate is capped at 8.25 percent but is variable and remained much lower than this cap during the 2000s. Perkins Loans are administered through universities. Loan repayment begins nine months after graduation and the interest rate is set at five percent. Perkins Loans are not available at all institutions and account for only about one percent of total aid for graduate students in the NPSAS samples. Finally, students have been able to take out private loans since 1995 and starting in July 2006 graduate students are able to borrow through the PLUS program to cover additional tuition costs that are not covered 2 Employer tuition assistance is counted as a grant in Table 1, explaining the difference between the Department of Education finding reported in Baum and Payea (2010) and our results from NPSAS data. 4

by other forms of aid. PLUS loans have a set 7.9 percent interest rate. Graduate students are not eligible for Federal Pell Grants, Federal Supplemental Educational Opportunity Grants (FSEOG), Academic Competitiveness Grants (ACG), and SMART Grants. As seen in Table 1, graduate students receive very little of their total aid, typically less than one percent, in the form of federal or state grants. Instead, the majority of graduate student grants come from institutions and employers. As discussed below, employer provided tuition assistance has been subject to differential tax treatment during the past twenty years. 1.2 Tax Benefits An incentive for employers to offer tuition assistance and for workers to seek sponsorship comes from the fact that it is associated with significant tax benefits. Employers can deduct the full cost of educational assistance if the firm has a tuition reimbursement plan. According to a provision known as Section 127 Benefits, employer contributions towards tuition are treated like other fringe benefits. They are reported on employees W2 forms but are tax exempt up to $5,250. The course work does not need to be related to the job for the tax benefit to come into effect, but education involving sports, games and hobbies is not eligible, unless directly related to the job. Expenditures that are included in the exemption are tuition, fees, books, supplies, and equipment, but not meals, room and board, and transportation. In 1990, Section 127 was amended and the $5,250 exemption was applied to graduate education undertaken after January 1, 1991. A July 1996 amendment excluded graduate education from Section 127, but graduate courses were included again starting in January of 2002. For more information on Section 127, see Levine (2008) and Levine and Lyke (2002). 5

The Tax Relief Act of 1997 increased the available tax benefits for higher education beyond employer-provided training. The HOPE Credit (introduced in 26 U.S.C. 25A(b)) benefits undergraduate students in the first two years of their postsecondary schooling. It covers the first $1,000 of tuition and fee expenditures, as well as half of the next $1,000. The maximum credit is thus $1,500, and can be claimed by the individual undertaking schooling or their spouse s or children s education. The Lifetime Learning Credit (also part of 26 U.S.C. 25A(b)) is aimed at a different group of students. It covers tuition and fees for any postsecondary education, including graduate degrees and course work that is not part of a degree program. The maximum credit was $1,000 when first introduced, but increased up to $2,000 in 2003. Unlike the HOPE Credit, the LLC covers 20% of the qualifying expenses. Both the LLC and the HOPE Credit are subject to the same income eligibility requirements and neither is refundable meaning that the amount of the credit received is also capped at the amount of taxes owed. See Long (2004) for more details. A summary of the benefits described in this section is available in Table 2. Starting in 2002, students could deduct up to $3,000 from their taxable income for postsecondary tuition and fees. In 2004 the limit was increased to $4,000. There are income limits for this deduction and the point was to give a tax break for the middle class. The timing and changes for all of the tax benefits are summarized in Figure 1. 6

2 Data 2.1 Current Population Survey We use the 1989-2009 October supplements of the Current Population Survey to examine any changes in enrollment rates associated with Section 127 and the Tax Relief Act of 1997. The CPS offers fairly large samples, which are representative of the U.S. population. We focus our attention on the October surveys because they contain school enrollment information for the current and previous years. We restrict the estimation to the CPS reference person and his or her spouse. It is not clear how relevant the family income variable reported by the CPS is with regards to the schooling decisions of other household members. For example, an adult child of the reference person may be financially independent but living in the same household. We focus on two main age groups: 23-30 year-olds and individuals between the ages of 31 and 40. We exclude people younger than 23 because our study is directed at graduate education, and we are mainly interested in the incentives created by tax benefits for financially independent individuals. It is likely that schooling decisions are going to be different for the two age groups referenced above, since the basic human capital model predicts that optimal education decisions change with age. Some preliminary robustness checks (not reported here) suggest that varying the age cutoff does not change the results substantially. We estimate two sets of models. For graduate enrollment, the samples consist of all college graduates. To compare these trends to trends in undergraduate enrollment, we also show undergraduate enrollment estimates for high school graduates with less than a Bachelor s degree. The descriptive statistics in Table 3 show that 6.4 percent of respondents in the 7

younger sample of college graduates were attending a part-time graduate program at the time when they were interviewed, while this number is somewhat lower (4 percent) for the older sample. The difference in full-time enrollment is even bigger: 7.8 and 1.9 percent, respectively. The numbers are similar for undergraduate enrollment in the high school sample (columns 3 and 4 of Table 3). In addition to part-time and full-time programs, we also consider another variable, which measures whether an individual reported taking vocational classes. Since the Lifetime Learning Credit and Section 127 cover course work that may not lead to a degree, the vocational studies variable is relevant in this context. About 3 percent of respondents in all four subsamples report taking such classes. Family income is reported as a categorical variable in the CPS data, so there is going to be a lot of noise in our measure of income and, consequently, eligibility for many of the tax benefits. Since the categories do not change over time (with the exception of an additional category at the top of the distribution starting with the 2003 survey), it is also not possible to systematically account for inflation. The income measure that we use consists of three categories: low income (less than $10,000 for single respondents and less than $20,000 if married), middle income ($10,000-$49,999 if single; $20,000-$74,999 if married) and high income (all others). The low income category should roughly correspond to individuals whose income is too low to be taxable, which would make the tax benefits inapplicable. The high income category is constructed to include those whose income is too high to make them eligible for many of the benefits. The descriptive statistics in Table 3 show that among college graduates between the ages of 31 and 40, 77 percent of the sample falls in either the middle or high income category, with each getting a roughly equal share. Among high school graduates between the ages of 23 and 8

30 with no college degree, only 9 percent have high family income, and 19 percent have low income. We experimented with the cutoffs for the income categories, but the main findings were robust 3. The rest of the descriptive statistics in Table 3 indicate that the sample of college graduates is more predominantly Asian, more likely to have been enrolled in school a year before the October interview, and, not surprisingly, with higher family income. Income also increases with age, with the increase more pronounced for the college sample. There are three binary variables that indicate Section 127 availability and eligibility. First, we construct a variable that equals 1 in years 1991-1995 and 2002-2009. These are all years for which Section 127 benefits could be applied to graduate classes in the month of October. Next, we interact this variable with part-time and full-time employment status, since individuals who are unemployed or out of the labor force cannot take advantage of this benefit. We interact the three income categories with an indicator for t 1998. These variables are intended to capture any income-contingent effects on enrollment of the Tax Relief Act. While we do not show the results here, we also estimated the models with a set of two interactions for each income variable, one for 1998 t < 2003 and another for t 2003 in order to account for changes in the Lifetime Learning Credit maximum and the introduction of tuition deductions as another tax benefit. This introduced more noise in the estimates but did not change the main findings. Finally, we use state-level unemployment rates from the Local Area Unemployment Statistics series provided by the BLS. There is evidence that unemployment may have an effect on postsecondary educational enrollment and the return to postsecondary degrees (Betts and McFarland 1995, Bedard and Herman 2008, Kahn 2010). 3 Results available upon request 9

2.2 National Postsecondary Student Aid Study We use the 1992-1993, 1995-1996, 1999-2000, 2003-2004 and 2007-2008 waves of the National Postsecondary Student Aid Study to analyze how graduate students finance their education. NPSAS surveys individuals that are enrolled in the given school year about their finances and also has access to individual level institutional records. Results are weighted to be nationally representative. NPSAS is not longitudinal and it is not clear how many years the student had been enrolled in their program at the time of the interview. Comparing demographic characteristics of the NPSAS data in Table 4 to those in the CPS in Table 3, we find that students are slightly younger than the average population in both age categories and that whites make up fewer of graduate students than the general population. In both data sets half of the younger aged group and two-thirds of the older aged group of college graduates enrolled in graduate school are in part time programs. Individuals in the younger aged group are less likely to be married than those in the older aged group, and graduate students are less likely to be married than the general population. Students receive grants and loans from the federal government, state governments, their institution and outside sources. One particular source of interest is employer provided tuition assistance and is described in detail in section 1.2. Older and part-time students are more likely to receive employer provided tuition assistance. Students can also receive work-study assistance. Finally, graduate institutions offer teaching and research assistant opportunities. Table 1 shows the sources of total graduate aid for each of the years listed above. One clear trend is that education grants have made up a smaller portion of total aid over 10

time and loans have played an increasing role in graduate education finance. Decreasing institutional grant support has made up the majority of this fall and it appears that students are compensating by taking out private loans. Individuals that attend M.B.A. programs are more likely to receive employer provided tuition assistance, and in particular employer tuition assistance makes up a greater share of total aid for individuals enrolled in part-time programs as shown in Table 5 and Table 6. This is a well documented fact and is explored in Gicheva (forthcoming). It is interesting to note that employer tuition assistance for part-time M.B.A. programs has made up a smaller fraction of total aid over time. 3 Results 3.1 Current Population Survey We adopt a difference-in-difference style approach in order to examine how changes in the tax treatment of employer-provided tuition assistance and the Tax Relief Act affect enrollment rates. This approach has been used in Dynarski (2000) to evaluate the impact of Georgia s HOPE Scholarship on college attendace, and by Dynarski (2003) to examine the 1982 elimination of the Social Security Benefits Program for students with a deceased parent. Kane (2003) and Long (2004) use a similar approach to evaluate how the CalGrant program and the HOPE and Lifetime Learning Credits, respectively, affected college enrollment. 11

We estimate models of the form Enroll i = fx i β + γ 1 (Sec127) + γ 2 (Sec127 Employed FT) + γ 2 (Sec127 Employed PT) + δ 1 (Post-1997 Low Income) + δ 2 (Post-1997 Middle Income) + δ 3 (Post-1997 High Income) + η 1 (Employed FT) + η 2 (Employed PT) + η 3 (Low Income) + η 4 (Middle Income) + ε, (1) where X i contains demographic information, a quadratic in time, indicators for enrollment in the previous year and for t 1993 4, as well as the state unemployment rate during the year when the respondent was interviewed. For an illustration of the trends that we are interested in, Figures 2 and 3 show the point estimates from a modified version of Equation (1), in which we drop the income interactions and time trend but include year dummies interacted with employment status in order to graph the point estimate over time. The graduate enrollment trends in Figure 2 suggest that enrollment rates among full time workers were lowest when neither Section 127, nor the Lifetime Learning Credit were available. We see an upward trend after 1998. The pattern is similar for part-time workers, but very different for those who are unemployed or out of the labor force: enrollment rates show an increase after graduate classes were removed from Section 127 in 1996, and a decrease after 1998. Since we are not interacting the year dummies with income, the unemployed sample of respondents is likely to include many of the low-income individuals whose tax-exempt status made them effectively ineligible for the Lifetime Learning Credit. There is no pronounced pattern for undergraduate enrollment (Figure 3). There is a slight increase in employed 4 In 1992, Congress reauthorized the Higher Education Act of 1965, expanding substantially the limits and eligibility for federal student loans beginning in 1993. Our estimation strategy allows for enrollment trends to change upon the HEA reauthorization, but the estimated coefficients are small and not statistically significant. 12

individuals enrollment immediately after the Tax Relief Act was introduced, but it was followed by a decline until 2002 or 2003. Seftor and Turner (2002) notes that most of the literature on educational attainment focuses on recent high school graduates. They find that the introduction of the Pell Grant program had a larger effect on college enrollment of individuals ages 22-35 than those aged 18-22. In order to pursue a graduate degree an individual must have completed a college degree. With some graduate programs, like an M.B.A., students will often work for a few years between college graduation and graduate school enrollment. For some other degrees students might be more likely to continue their education without such a break. We split our sample to look at individuals that are likely to be recent college graduates and those that are more likely to have an extended break between college graduation and graduate school enrollment. We estimate Equation (1) by probit; Table 7 shows the average marginal effects for graduate enrollment estimated using the individual weights that the CPS provides. The first three columns show results for part-time, full-time and vocational enrollment, respectively. The sample for these models is limited to college graduates between the ages of 23 and 30. Columns 4-6 use the same dependent variables, but are estimated on a sample of older college graduates. The results suggest that the state-level unemployment rate increases enrollment rates only for part-time students over the age of 30. The post- 1997 interactions are significant only for the low-income group, and their sign is negative in the full-time enrollment models and positive in Column 3. One interpretation of these estimates is that the introduction of the Lifetime Learning Credit had little effect on graduate education, but it could also be the case that the Section 127 variables are picking up any potential effects, since our income variable is noisy, and employment 13

status tends to be highly correlated with income. The results in Table 7 suggest that part-time employment status has a weakly positive correlation with the attendance rates of the younger group, but the effect of full-time enrollment is much more pronounced. The coefficients in Columns 2, 3 and 5 are positive and statistically significant. In the younger sample, the availability of Section 127 increases full-time workers probability of full-time attendance by 1.9 percentage points and of taking vocational classes by 1.5 percentage points. The effect on full-time enrollment in the older sample is smaller: 0.4 percentage points. The result that full-time employees are more likely to make use of the Section 127 benefits compared to part-time employees is consistent with the idea that employers are more likely to provide tuition assistance to their full-time labor force. As a comparison, we re-estimate the Equation (1) probit model on the sample of high school graduates with no college degree. The dependent variable in these models is attendance of an undergraduate program or vocational courses. Table 8 shows that the Tax Relief Act had a stronger effect on this group. It appears to shift low-income individuals enrollment from full time to part time. Part-time and vocational enrollment increased for the older middle-income sample. The coefficient on the interaction with high income is negative and significant in Column 1 and positive and significant in Column 3, with roughly the same magnitude (about 1 percentage point). Again, it is possible that the newly introduced tax incentives made people switch from part-time attendance to vocational courses. Three of the four coefficients on the Section 127 interactions with employment in the vocational training models in Table 8 are negative and significant at the 5 percent level; the fourth one is negative but not significant. In addition, the coefficient on 14

the interaction with part-time employment is negative and significant in Column 2. This may mean that the increased interest in pursuing graduate education by collegeeducated workers is crowding out employer-provided tuition assistance for undergraduate education in periods when Section 127 is available for graduate education. On the other hand, we estimate a positive and significant coefficient on the interaction with full-time employment in column 5, but the magnitude of the marginal effect is small (0.00261). Another possibility is that some employers expand their tuition assistance programs in periods when the $5,250 exemption is available to graduate students, and some of the older full-time workers in these firms are able to take advantage of this to enroll in an undergraduate program. Both Tables 7 and 8 suggest that higher-income individuals and full-time employees are less likely to be attending school full-time, which is intuitive. Low-income individuals are more likely to be enrolled part-time than full-time. 3.2 NPSAS We examine the extent to which individuals finance their graduate education with employer assistance in Table 9. We regress the percent of total aid that comes from employer tuition assistance on a set of demographic controls, the lagged unemployment rate, a time trend and an indicator for whether the tuition assistance exemption was in place using pooled OLS. The top panel of Table 9 refers to graduate students aged 23-30 and the bottom panel examines graduate students aged 31-40. We evaluate separately the impact of the tuition assistance exemption for master s, doctoral and professional degrees as well as part-time and full-time M.B.A. degrees. For the younger group of graduate students, the coefficient on the tuition exemption 15

variable is small and not significant at the five percent level for any of the degree types. For the older group, this variable is significant and large for doctoral students but not for any other degree type. This is surprising because doctoral programs are typically longer than masters or professional degree programs. Further work is needed to identify whether the results are driven by one particular type of doctoral degree that is commonly funded in part by employers. In our sample, employer tuition assistance makes up over half of all student aid for part-time M.B.A. students and a much smaller fraction of aid for those in a full-time program. However, the tax exemption appears to have no effect on the proportion of financing that comes from employers. Coupled with results from the CPS data on enrollment rates, we believe that the tax exemption increases the number of individuals that use tuition assistance for part-time M.B.A. programs but does not lead the employer to offer any more or less assistance. While not statistically significant, one could argue that the negative coefficient on the tax exemption variable for part-time M.B.A. students means that employers decrease tuition assistance because of the tax saving. That is, the incidence of the tax credit falls on both students and firms. For both age groups, individuals with larger incomes during the year before the interview financed their graduate education with slightly more tuition assistance from employers. This could be picking up that these individuals were more likely to be full time employees or that higher paying firms are more likely to offer tuition assistance. The negative coefficient on the lagged unemployment rate indicates that firms are less likely to offer tuition assistance during bad economies. Finally, it is curious that when controlling for income, age, marital status and features of the economy, black students receive a smaller proportion of total aid in the form of graduate tuition assistance from 16

an employer. In the raw data, a smaller percentage of black students receive any tuition assistance from an employer than white students, but those that do receive a larger nominal amount that white students. 4 Conclusion In this paper we examine how changes in the tax code affect enrollment in and financing of graduate education. We consider the Tax Relief Act of 1997 that established tax credits against tuition payments. As the credits are non-refundable, only those with a large enough income to have positive tax liability qualify for the benefit. We also examine the six year lapse in exemptions for employer provided tuition assistance. We find that enrollment rates for full time workers are highest when the tax exemption is in place. In terms of financing graduate education, we find that the percent of total aid that comes from employers increases when the exemption is in place for older workers enrolled in doctoral and masters programs, but there is not a significant change for younger workers. At this point we do not formally model the firm s decision about providing tuition assistance and the individual s decision about obtaining a graduate degree. It does appear, however, that firms are not decreasing the amount of tuition assistance that they provide in reaction to the decreased tax liability of the worker. This implies that the incidence of the tax benefit falls on the worker. The policy appears successful at decreasing the cost of graduate education and increasing enrollment in graduate education programs. 17

Tax Relief Act of 1997 signed Grad courses eligible for Sec 127 Grad courses eligible for Sect 127 01-89 01-91 10-94 07-96 08-97 07-98 01-02 10-02 01-03 01-04 10-09 Max LLC = $1K Max LLC = $2K 1992 Reauthorization of HEA Loan limits increased Tuition deduction = $3K Tuition deduction = $4K Figure 1: Tax Treatment Schedule 18

Full Time Graduate Enrollment 0.08 0.085 Employed FT 0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125 Full Time Graduate Enrollment 0.04 Employed PT 0.03 0.02 0.01 0 0.01 0.02 Full Time Graduate Enrollment 0.02 0.015 Unemployed/Out of labor force 0.01 0.005 0 0.005 0.01 0.015 0.02 Figure 2: Full-Time Graduate Enrollment 19

Full Time Undergraduate Enrollment 0.04 0.045 Employed FT 0.05 0.055 0.06 0.065 0.07 0.075 Full Time Undergraduate Enrollment 0.04 Employed PT 0.03 0.02 0.01 0 0.01 0.02 Full Time Undergraduate Enrollment 0.03 0.025 0.02 Unemployed/Out of labor force 0.015 0.01 0.005 0 0.005 0.01 0.015 0.02 Figure 3: Part-Time Graduate Enrollment 20

Table 1: NPSAS Aid Statistics, All Students 1993 1996 2000 2004 2008 Grants 0.413 0.392 0.432 0.366 0.359 Federal 0.015 0.003 0.006 0.004 0.004 State 0.019 0.008 0.011 0.008 0.009 Institution 0.204 0.167 0.180 0.115 0.122 Employer 0.152 0.209 0.198 0.206 0.205 Private 0.023 0.024 0.037 0.033 0.019 Loans 0.405 0.409 0.426 0.485 0.504 Stafford 0.282 0.384 0.378 0.426 0.402 Perkins 0.014 0.008 0.007 0.013 0.006 Other Federal 0.051 0.002 0.023 State 0.005 0.001 0.002 0.000 0.001 Institution 0.008 0.003 0.005 0.003 0.001 Private 0.020 0.009 0.030 0.041 0.072 Work Study 0.024 0.010 0.008 0.005 0.004 Other Aid 0.158 0.189 0.134 0.144 0.133 Teaching 0.053 0.051 0.055 0.056 0.052 Research 0.052 0.043 0.052 0.052 0.050 Other School Assistantship 0.019 0.006 0.023 0.022 Veteran s Benefits 0.018 0.008 0.012 0.012 0.009 Total Federal 0.397 0.405 0.399 0.448 0.436 Total State 0.031 0.013 0.013 0.009 0.010 Total Institution 0.359 0.342 0.306 0.251 0.248 Total Other 0.213 0.240 0.282 0.292 0.306 Data Source: NPSAS 21

Table 2: Education Benefits Overview Benefit Eligibility Amount Lifetime Learning Credit Available for course work; can be claimed for net tuition and fees (less grant aid) for taxpayer, spouse, dependent; 20% credit against total tax liability for first $A per household of qualified tuition and expenses A = $5K (1998-2002) or $10K (2003-09) Phase-out income: $40K/$80K to $50K/$100K (1998-2001) $50K/$100K to $60K/$120K (2009) Interest Deduction Deduction up to $A of adjusted gross income for interest payments on student loans; 1998-2001: Limited to first 60 months of interest payments (2000), $2,500 (2001-07) A =$1,000 (1998), $1,500 (1999), $2,000 Phase-out income: $40K/$60K to $55K/$75K (1998-2001) $55K/$110K to $70K/$140K (2007) Deduction up to $A for postsecondary tuition and fees A=$3K (2002-03) or $4K (2004-07) Tuition and Fees Deduction Section 127 Tax-free status of employer-provided subsidy up to $A for graduate courses Perkins Loan Fixed-rate (5%) loan; annual limit of $A and aggregate limit of $B for graduate students Subsidized Variable interest rate; annual limit of $A and aggregate limit of Stafford Loan $B for graduate students Unsubsidized Stafford Loan Annual limit of $A and aggregate limit of $B for graduate students Income limits: $65K/$130K (2002-03) $80K/$160K (2004-09) A =$5,250 (1994-95, 2002-07) or 0 (1996-2001) A = $5K (1995-98) or $6K (1999-2007) B = $30K (1995-98) or $40K (1999-2007) A = $7.5K (1987-93), $8.5K (1994-2007) B = $54.75K (1987-92), $65.5K (1993-2007) A = $4K (1986-94) or $10K (1995-2007) B = $73K (1994-2007) Graduate students are not eligible for the HOPE credit, Federal Pell Grants, Federal Supplemental Educational Opportunity Grants (FSEOG), Academic Competitiveness Grants (ACG), and SMART Grants. 22

Table 3: CPS Summary Statistics College graduates HS, No Bachelor s 23-30 31-40 23-30 31-40 Enrolled part-time 0.0643 0.0403 0.0520 0.0312 Enrolled full-time 0.0782 0.0192 0.0595 0.0178 Taking vocational classes 0.0319 0.0297 0.0322 0.0266 Age 27.1382 35.5986 26.8377 35.6211 White 0.8421 0.8383 0.8186 0.8317 Asian 0.0758 0.0779 0.0222 0.0239 Female 0.5518 0.5096 0.5443 0.5284 Married, spouse present 0.5858 0.7778 0.6354 0.7374 Was enrolled in school last year 0.2091 0.0827 0.1175 0.0529 Low income 0.0713 0.0332 0.1911 0.1243 Middle income 0.6358 0.4816 0.7206 0.7166 High income 0.2929 0.4852 0.0882 0.1590 N 52,265 102,654 113,757 200,685 Summary statistics using CPS individual weights. Table 4: NPSAS Summary Statistics Ages 23-30 Ages 31-40 Part Time 0.503 0.703 Full Time 0.493 0.294 Age 26.1 34.9 Masters 0.600 0.634 PhD 0.111 0.135 Professional 0.171 0.061 Married 0.287 0.588 Kids 0.145 0.523 White 0.735 0.726 Black 0.072 0.109 Asian 0.088 0.068 Income $29,442 $52,569 Employer Assistance 0.139 0.288 Summary statistics using NPSAS individual weights. 23

Table 5: NPSAS Aid Statistics, Full-Time MBA Students 1993 1996 2000 2004 2008 Grants 0.314 0.353 0.366 0.295 0.323 Federal 0.000 0.000 0.000 0.000 0.000 State 0.026 0.019 0.003 0.003 0.002 Institution 0.192 0.153 0.155 0.056 0.092 Employer 0.092 0.178 0.202 0.231 0.217 Private 0.003 0.010 0.018 0.005 0.012 Loans 0.502 0.484 0.519 0.628 0.589 Stafford 0.321 0.450 0.431 0.540 0.422 Perkins 0.008 0.009 0.003 0.004 0.003 Other Federal 0.094 0.000 0.029 State 0.006 0.000 0.000 0.000 0.000 Institution 0.032 0.013 0.018 0.000 0.000 Private 0.023 0.012 0.067 0.084 0.134 Work Study 0.005 0.021 0.010 0.003 0.003 Other Aid 0.179 0.142 0.105 0.074 0.084 Teaching 0.070 0.027 0.030 0.011 0.029 Research 0.004 0.014 0.037 0.031 0.020 Other School Assistantship 0.051 0.006 0.021 0.015 Veteran s Benefits 0.018 0.012 0.026 0.011 0.021 Total Federal 0.442 0.466 0.434 0.547 0.455 Total State 0.032 0.020 0.003 0.003 0.002 Total Institution 0.390 0.303 0.258 0.119 0.158 Total Other 0.136 0.211 0.305 0.331 0.384 Data Source: NPSAS 24

Table 6: NPSAS Aid Statistics, Part-Time MBA Students 1993 1996 2000 2004 2008 Grants 0.679 0.757 0.732 0.588 0.532 Federal 0.005 0.000 0.000 0.000 0.000 State 0.011 0.008 0.002 0.002 0.006 Institution 0.096 0.029 0.067 0.036 0.040 Employer 0.543 0.719 0.662 0.537 0.481 Private 0.024 0.014 0.009 0.013 0.004 Loans 0.266 0.189 0.229 0.353 0.415 Stafford 0.195 0.186 0.210 0.338 0.359 Perkins 0.008 0.000 0.001 0.000 0.000 Other Federal 0.019 0.000 0.004 State 0.006 0.000 0.002 0.000 0.000 Institution 0.010 0.001 0.000 0.000 0.001 Private 0.013 0.002 0.015 0.015 0.050 Work Study 0.015 0.001 0.005 0.002 0.000 Other Aid 0.039 0.053 0.035 0.058 0.054 Teaching 0.000 0.013 0.008 0.010 0.011 Research 0.000 0.003 0.003 0.016 0.012 Other School Assistantship 0.021 0.000 0.012 0.009 Veteran s Benefits 0.012 0.011 0.022 0.018 0.022 Total Federal 0.243 0.186 0.212 0.339 0.364 Total State 0.024 0.008 0.004 0.003 0.006 Total Institution 0.140 0.071 0.083 0.076 0.073 Total Other 0.593 0.735 0.702 0.583 0.557 Data Source: NPSAS 25

Table 7: CPS Results - Graduate Enrollment 23 Age 30 31 Age 40 PT FT Voc PT FT Voc State unemployment rate -0.00032 0.00096 0.00008 0.00095* -0.00042-0.00013 (0.00096) (0.00082) (0.00077) (0.00052) (0.00034) (0.00054) Low income and t 1998-0.00120-0.01249** 0.01422** 0.00813-0.00500* -0.00379 (0.00940) (0.00632) (0.00695) (0.00669) (0.00290) (0.00636) Middle income and t 1998 0.00541-0.00655 0.00286 0.00390-0.00033 0.00135 (0.00538) (0.00498) (0.00433) (0.00301) (0.00208) (0.00300) High income and t 1998 0.00554-0.00757 0.00568 0.00352 0.00308 0.00047 (0.00675) (0.00746) (0.00527) (0.00319) (0.00249) (0.00308) Section 127 available -0.00961-0.01187*** -0.00909* 0.00029-0.00303* 0.00285 (0.00776) (0.00390) (0.00489) (0.00388) (0.00158) (0.00349) Section 127 and employed FT 0.00866 0.01871*** 0.01500*** -0.00212 0.00421** -0.00415 (0.00790) (0.00456) (0.00509) (0.00396) (0.00183) (0.00361) Section 127 and employed PT 0.00046 0.00538 0.01252* -0.00715 0.00204-0.00400 (0.00995) (0.00531) (0.00737) (0.00518) (0.00219) (0.00494) Employed FT 0.05231*** -0.12726*** -0.00988** 0.02481*** -0.03205*** 0.00582* (0.00625) (0.00377) (0.00410) (0.00325) (0.00160) (0.00303) Employed PT 0.03492*** -0.00323-0.01090* 0.01505*** -0.00121 0.00354 (0.00774) (0.00426) (0.00593) (0.00408) (0.00173) (0.00401) Low income -0.03190*** 0.04637*** -0.00415-0.01713*** 0.02183*** 0.00394 (0.00676) (0.00632) (0.00514) (0.00408) (0.00216) (0.00380) Middle income -0.00047 0.02019*** -0.00006 0.00310* 0.00829*** -0.00222 (0.00460) (0.00577) (0.00346) (0.00187) (0.00172) (0.00182) * p<0.10, ** p<0.05, *** p<0.01. The reported coefficients are weighted average marginal effects from probit models. The sample consists of college graduates, 1989 t 2009. The controls include quadratics in age and t, race, gender, marital status, state dummies and indicators for enrollment last year and for t 1993 (post-hea reauthorization). 26

Table 8: CPS Results - Undergraduate Enrollment 23 Age 30 31 Age 40 PT FT Voc PT FT Voc State unemployment rate 0.00075 0.00040-0.00054 0.00111*** 0.00028 0.00068* (0.00059) (0.00052) (0.00055) (0.00034) (0.00024) (0.00037) Low income and t 1998 0.00800* -0.00671* 0.00426 0.00957*** -0.00522*** -0.00110 (0.00435) (0.00351) (0.00371) (0.00296) (0.00170) (0.00286) Middle income and t 1998 0.00297 0.00077 0.00445 0.00389** -0.00041 0.00477** (0.00323) (0.00309) (0.00293) (0.00181) (0.00138) (0.00190) High income and t 1998-0.00934* 0.00451 0.01096** 0.00199 0.00133 0.00187 (0.00541) (0.00650) (0.00552) (0.00247) (0.00225) (0.00267) Section 127 available -0.00009 0.00471** 0.00672** 0.00012-0.00101 0.00569*** (0.00334) (0.00217) (0.00264) (0.00189) (0.00092) (0.00193) Section 127 and employed FT -0.00006 0.00048-0.00708** -0.00054 0.00261** -0.00772*** (0.00350) (0.00274) (0.00286) (0.00198) (0.00122) (0.00205) Section 127 and employed PT 0.00148-0.01151*** -0.00427 0.00145 0.00128-0.00841*** (0.00462) (0.00310) (0.00419) (0.00271) (0.00145) (0.00288) Employed FT 0.02807*** -0.07099*** -0.00306 0.00921*** -0.02942*** 0.00183 (0.00286) (0.00234) (0.00244) (0.00161) (0.00109) (0.00174) Employed PT 0.01671*** 0.01284*** -0.00434 0.00574*** -0.00516*** 0.00581** (0.00369) (0.00249) (0.00344) (0.00214) (0.00116) (0.00232) Low income -0.03535*** 0.02039*** 0.00391-0.02162*** 0.00803*** -0.00321 (0.00449) (0.00567) (0.00472) (0.00221) (0.00187) (0.00224) Middle income -0.01648*** 0.00759 0.00494-0.00498*** 0.00405** -0.00356* (0.00412) (0.00559) (0.00452) (0.00169) (0.00176) (0.00188) * p<0.10, ** p<0.05, *** p<0.01. The reported coefficients are weighted average marginal effects from probit models. The sample consists of high school graduates without college degree, 1989 t 2009. The controls include quadratics in age and t, race, gender, marital status, state dummies and indicators for enrollment last year and for t 1993 (post-hea reauthorization). 27

Table 9: NPSAS Results - Percent of Aid as Employer Tuition Assistance Age 23-30 All Masters Doctoral Professional Part Time MBA Full Time MBA Section 127 available 0.00830 0.02008 0.02742 0.01325* -0.09562-0.06543 (0.01375) (0.02260) (0.01835) (0.00793) (0.09239) (0.04854) Black -0.04358*** -0.06866*** -0.02861*** -0.00928*** -0.14159** -0.10128*** (0.00971) (0.01355) (0.00752) (0.00332) (0.05756) (0.02069) Income (10,000s) 0.04176*** 0.04658*** 0.01084*** 0.00344*** 0.05643*** 0.01872** (0.00313) (0.00471) (0.00320) (0.00106) (0.00603) (0.00809) Lagged Unemployment Rate -0.00712** -0.01041** -0.00534 0.00166 0.00244-0.00206 (0.00296) (0.00478) (0.00412) (0.00151) (0.02323) (0.01254) Constant -0.12732** -0.15450* -0.08497-0.08230** 0.64944** -0.06944 (0.05491) (0.08942) (0.05423) (0.04013) (0.32621) (0.20971) Observations 19441 7719 4533 5973 777 531 Age 31-40 All Masters Doctoral Professional Part Time MBA Full Time MBA Section 127 available 0.10492*** 0.08272* 0.09091*** 0.03605-0.02739 0.25118 (0.03186) (0.04349) (0.02862) (0.03265) (0.09231) (0.15338) Black -0.09582*** -0.09993*** -0.09084*** -0.03932** -0.17862** -0.06782 (0.02171) (0.02872) (0.01654) (0.01743) (0.07537) (0.09341) Income (10,000s) 0.02493*** 0.02488*** 0.01708*** 0.01129*** 0.01444*** 0.01180 (0.00297) (0.00394) (0.00259) (0.00336) (0.00525) (0.00933) Lagged Unemployment Rate -0.02088*** -0.01757* -0.02132*** -0.00412 0.00068-0.09084** (0.00685) (0.00991) (0.00750) (0.00889) (0.02142) (0.04016) Constant 0.07381 0.24493-0.02724-0.07688 0.54187 0.83652 (0.11227) (0.15251) (0.13986) (0.14694) (0.37335) (0.62739) Observations 7646 3571 2255 1145 499 241 * p<0.10, ** p<0.05, *** p<0.01. The reported coefficients are weighted OLS results. The sample consists of individuals enrolled in a graduate program. The controls include age, a quadratic in t, marital status, whether the individual has children and the amount of Lifetime Learning Credit that the individual is eligible for. 28

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