Tax Benefits for Graduate Education: Incentives for. Whom?

Transcription

1 Tax Benefits for Graduate Education: Incentives for Whom? Steven Bednar and Dora Gicheva March 2012 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 From and , employees could receive $5,250 worth of tax-exempt graduate or undergraduate tuition assistance from their employer. During the rest of the period, this exemption was in place only for college courses. Using the October supplements of the CPS, we find that graduate enrollment rates among full-time workers were higher when this tax exemption was available. Using the National Postsecondary Student Aid Study, we find that individuals enrolled in full-time Master s programs are more likely to receive employer aid when the tax exemption was available compared to individuals in full-time undergraduate programs. While full-time Master s students also reported an increase in the amount of tuition subsidies, graduate students in both part-time and full-time programs paid an average tuition even greater than the additional employer-provided assistance. Keywords: Educational Finance, Tax Code, Graduate Education, Employer- Provided Tuition Subsidies JEL Classification Codes: H52, I22, I28, J32 Preliminary draft. Comments are welcome. Please do not cite. Department of Economics, Elon University. sbednar@elon.edu. Department of Economics, University of North Carolina at Greensboro. d gichev@uncg.edu. 1

2 1 Introduction There are several reasons why it is important to understand the degree to which different groups of students respond to government-provided financial incentives for education, in particular ones available through the tax code. In the academic year alone, close to $15 billion of student aid was in the form of federal education tax credits and deductions; about 10 percent of this amount was used by graduate students (College Board 2011). In addition, in 2010, the government lost an estimated $690 million in revenue due to tax exemptions for employer-provided educational assistance (Office of Management and Budget 2010). Understanding how such benefits are likely to affect the recipients who are targeted, as well as those who may not be, can help in the cost-benefit analysis of government spending on education. Responses to changes in the tax treatment of employer-provided tuition assistance can also provide a better understanding of firm-provided general training. Additionally, there is still a lot to be learned about the price elasticity of demand for graduate education. This paper examines how the tax code and government education policies affect graduate enrollment rates as well as how students fund their graduate education. Over the past twenty years, the United States government has enacted several federal policies with the goal of increasing graduate education enrollment. One important policy has been allowing a tax exemption for employer-provided tuition assistance. Our identification strategy relies on the fact that the tax exemption has been in place for undergraduate courses during the whole period we study ( ), but employer assistance for graduate education was not exempt prior to 1991 and between 1996 and While numerous studies have examined the enrollment responses of traditional un- 2

3 dergraduate students to the introduction of government-provided tuition subsidies 1, far less attention has been devoted to graduate students and nontraditional undergraduate students. 2 There is more room for increase in enrollment among older students because their attendance rates are considerably lower than the attendance rates of recent high school graduates. The incentives that older students face are likely to be very different from the driving forces behind the postsecondary enrollment of more typical college students. Older students are most likely to pay for the education themselves, rather than rely on parental transfers, so it is important to focus on personal, rather than parental income. In addition, individuals in their twenties and thirties have to balance work, family, and, potentially, school, both financially and in terms of time. For the reasons mentioned above, one s own employment status, among other factors, should have a strong impact on schooling decisions. In our study, employment status is given even more importance, as our identifying variation is linked to employer-provided education subsidies. We use the exogenous changes in the tax exemption of employer-provided graduate tuition assistance to examine any accompanying changes in graduate enrollment. The nature of the policy change allows us to use two different control groups: college graduates who are unemployed or out of the labor force and current and potential undergraduate students. Neither of these two groups should have been affected by the tax 1 Programs whose effects on enrollment have been studied recently include the Georgia Hope Scholarship (Dynarski 2000, Cornwell, Mustard and Sridhar 2006), the CalGrant program in California (Kane 2003), the Washington, D.C. Tuition Assistance Grant Program (Abraham and Clark 2006, Kane 2007) and, most notably, the Tax Relief Act of 1997 (Long 2004, Chenevert 2010, Turner 2011). Dynarski (2003) is among the few studies who focus on the enrollment effects of the elimination of a program (the Social Security Student Benefit Program in 1982). See the overview in Dynarski (2002) for a list of other papers that use the quasi-experimental approach to estimate the elasticity of demand for college education. 2 Two exceptions are Seftor and Turner (2002), who examine how changes in the Pell Grant Program impact the college enrollment rates of individuals in their twenties and thirties, and LaLumia (2011), who studies the impact of the Tax Relief Act of 1997 on older college students. 3

4 code changes under consideration. Furthermore, we believe that the incentive was not large enough to induce individuals without an undergraduate degree to complete college in order to have access to the graduate tuition assistance exemption, or to lower workers reservation wages. We focus on two age groups, 23 to 30 and 31 to 40, in order to account for the possibility that potential students price sensitivity changes as their returns to more education decrease with age. It is also likely that other important factors, such as the opportunity cost of time, are different for older individuals, who are more likely to have a family or a higher-paying job. The quasi-experimental approach that we adopt avoids many of the problems of a cross-sectional study in which schooling outcomes are expressed as a function of individual characteristics, aid eligibility and the available tax incentives because the latter two are likely to be correlated with unobservables that affect schooling. Using the October supplements of the Current Population Survey, we find that graduate enrollment rates among full-time workers are higher when the tax exemption is available. We do not see this relationship in the case of undergraduate enrollment. We then examine the proportion of students in the National Postsecondary Student Aid Study who use educational assistance from their employer. We find that use of employer aid for individuals enrolled part-time in graduate programs increases relative to similar students enrolled part-time in undergraduate programs. This finding is contrary to the CPS finding, so we investigate whether the overall results are driven by students in different programs. When we separate individuals into program type we find that full-time Master s students are more likely to report employer aid when the tax exemption is in place and that the results from part-time students are driven by individuals receiving law degrees. While part-time graduate students also reported receiving a larger aver- 4

5 age amount of assistance, part-time and full-time graduate students reported paying higher tuition compared to similar undergraduate students when the tax exemption was in place. It is unclear, however, if this comes from universities increasing tuition or if students enroll in more expensive universities when the tax exemption is in place. The rest of the paper is organized as follows. Section 2 provides more information about the most commonly used federal tax subsidies for higher education along with other popular sources of graduate aid; section 3 describes the data and empirical methodology; section 4 provides the results and section 5 concludes. 2 Tax Benefits and Other Sources of Education Finance According to a provision in the IRS tax code known as Section 127, 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, 3 as long as the employer has a qualified educational assistance program. 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 March 2007, 49 percent of workers had access to work-related educational assistance through their firm, and non-work related assistance was available to 15 percent of employees. These numbers are higher for management and professional workers, full-time and unionized employees, as well as those who earn higher 3 Amounts greater than $5,250 can be exempt only if they qualify as a working condition fringe benefit, meaning that the amount could have been deducted as an employee business expense (i.e. Section 132 benefit). 5

6 wages and work in larger establishments. There are also small geographic differences in the incidence of education assistance programs (U.S. Bureau of Labor Statistics 2007). Employers can deduct the full cost of educational assistance from their annual income if the firm has a tuition reimbursement plan. Section 127 has been extended several times, but the only amendments made since 1986 have been the inclusion or exclusion of graduate education. 4 In 1990, Section 127 was amended and the $5,250 exemption was applied to graduate education undertaken after January 1, A 1996 amendment excluded graduate education from Section 127 after June 30 of that year, but graduate courses were included again starting in January of We are not aware of any specific reason for which any of the changes were made. For more information on Section 127, see Levine and Lyke (2002) and Levine (2008). The tuition assistance deduction was the main tax incentive for higher education until the Tax Relief Act of 1997 was passed. Its two most significant provisions were the Hope Credit and the Lifetime Learning Credit (LLC) (both introduced in 26 U.S.C. 25A(b)). The Hope Credit benefits only 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 for own schooling expenditures or for a taxpayer s spouse or children s education. The Lifetime Learning Credit 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 Unlike the Hope Credit, the LLC covers 20% of the qualifying expenses. Both the LLC and the Hope Credit are subject to the same 4 Levine (2008) lists in detail all Section 127 extensions and their provisions. 6

7 income eligibility requirements and neither is refundable meaning that the amount of the credit received is also capped at the amount of taxes owed. This makes very low-income households ineligible for these credits if their income is below the taxable minimum. Another important provision was introduced starting with the 2002 tax year, when 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. The benefit is available to both graduate and undergraduate students, their spouses and dependents, but it may not be used concurrently with the Hope Credit or LLC. This deduction is again aimed at the middle class because households who do not owe income tax are not eligible (or are eligible for less than the full amount if the sum they owe is less than the maximum deduction), and there exist upper income limits that exclude households with income over $80,000 (if single) or $160,000 (if filing jointly). 5 The timing and changes for the tax benefits for which graduate students are eligible are summarized in Figure 1. 6 Tax benefits constitute a small portion of the total aid received by graduate students, with the majority (69% in the academic year) coming from federal loans. Most loans are taken out under the Stafford Loan Program. Graduate students can accrue up to $138,500 in debt from subsidized and unsubsidized Stafford loans. Perkins Loans are not available at all institutions and account for less than one percent of total federal loans for graduate students. Limits and eligibility for the federal loan program increased most substantially after the 1992 reauthorization of the Higher Education Act (HEA) of 5 These amounts were lower prior to Other tax incentives for education introduced with the Tax Relief Act of 1997 include a student loan interest deduction, the Coverdell Education Savings Account and a tax exception for early IRA distributions used to cover schooling expenses. We do not focus on these provisions because the timing of the incentives they create is unclear and the latter two are more likely to be used by parents for their children s college education. Furthermore, in our empirical work we include some controls for the provisions of the Tax Relief Act of 1997, which should account at least partly for the aforementioned benefits. 7

8 1965, so to account for any effects of this change on enrollment in our empirical models we include an indicator for the post-1992 period. 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 by other forms of aid (College Board 2011). Graduate students are not eligible for Federal Pell Grants, Federal Supplemental Educational Opportunity Grants (FSEOG), Academic Competitiveness Grants (ACG), and SMART Grants, but can receive institutional and private, in addition to employer, grants. An overview of the benefits described in this section is available in Table 1. 3 Data and Empirical Specification 3.1 Current Population Survey We use the October supplements of the Current Population Survey to examine any changes in enrollment rates associated with Section 127. 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 in 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: year-olds and individuals between the ages of 31 and 40. We exclude people younger than 23 because our study is directed at graduate 8

9 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 (available on request) 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 in the relevant age groups. 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 2 show that 6.4 percent of respondents in the 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 2). 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 being enrolled such classes at the interview date. Family income is reported as a categorical variable in the CPS data, which introduces much noise in our measure of income and makes it hard to determine respondents eligibility for many of the tax benefits. Thus, we do not draw any firm conclusions about the enrollment effects of income-contingent benefits, such as the LLC. Since the 9

10 income 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 aims to include individuals whose income is too low to be taxable, which would make the tax benefits inapplicable. The high income category is constructed to include respondents whose income is above the eligibility cutoff for many of the benefits. The descriptive statistics in Table 2 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 30 with no college degree, only 9 percent have high family income, and 19 percent have low income. Income increases with age, with the increase being more pronounced for the college sample. We reestimated the specifications varying the cutoffs for the income categories, but the main findings were robust 7. We further interact the three income categories with an indicator for t These variables are intended to capture any income-contingent effects on enrollment of the Tax Relief Act. The rest of the descriptive statistics in Table 2 indicate that respondents in the sample of college graduates are more predominantly Asian than those in the less educated sample, more likely to have been enrolled in school a year before the October interview, and less likely to be married before the age of 30 but slightly more likely to be married between the ages of 31 and 40. In our empirical specifications we include three binary variables that indicate Section 127 availability and eligibility. First, we construct a 7 Results available upon request 10

11 variable that equals 1 in years and These are all years for which Section 127 benefits could be applied to graduate classes taken during 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 use the CPS labor force and part-time/full-time definitions; workers who are employed but currently absent from work are counted as employed. Table 2 shows that college graduates are more likely to be employed full-time. The difference is most pronounced in the younger subsample, where it is 10 percentage points. Respondents without a Bachelor s degree are slightly more likely to be employed part-time, but also more likely to be unemployed or out of the labor force. Finally, we use one year lagged state-level annual unemployment rates for all workers 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, Johnson 2011). 3.2 National Postsecondary Student Aid Study We use the , , , , and waves of the National Postsecondary Student Aid Study to analyze how graduate students finance their education. 8 NPSAS surveys individuals who are enrolled in the given school year about their finances and supplements these data with individual-level institutional records. 9 There is information for both undergraduate and graduate students in each 8 The tax exemption was not available for respondents in the and samples but was available in the other years. 9 NPSAS is not longitudinal and it is not clear how many years the student had been enrolled in the program at the time of the interview. 11

12 year. The survey includes detailed and accurate accounts of the number of dollars of different types of grants, including employer tuition assistance, loans, and other sources of income, as well as the amount of tuition paid to the institution. Whether a student is enrolled part-time or full-time and the number of hours worked outside of the university allow us to examine the impact of the tax exemption on different types of students. Table 3 shows NPSAS summary statistics of the rates at which graduate students in the data use different types of aid described in Section 2. The numbers represent the percent of total aid that comes from each category. Most of the trends are similar to the ones reported by the College Board (2011). Employer tuition assistance has stayed close to 20% of total funding for graduate students as a whole, but grants have made up a smaller portion of funding over time, being replaced by loans, especially from the Stafford program. In 2010, loans made up roughly 54% of total funding. Graduate students do not make much use of work-study. Comparing demographic characteristics of the NPSAS data in Table 4 to those in the CPS in Table 2, 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. 12

13 3.3 Empirical Specifications 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 in the CPS and education financing in the NPSAS. This approach has been used in Dynarski (2000) to evaluate the impact of Georgia s HOPE Scholarship on college attendance, 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. Using the available employment information in the CPS data, we estimate a model of the form Enroll it =f{x it β + γ 1 (Sec127 t ) + γ 2 (Sec127 t Empl FT it ) + γ 3 (Sec127 t Empl PT it ) + η 1 (Empl FT it ) + η 2 (Empl PT it ) + (Income it )δ + ε it }, (1) where X i contains demographic information, a quadratic in time, indicators for enrollment in the previous year and for t 1993, 10 as well as the one-year lag of the state unemployment rate. The income vector consists of indicators for the low and middle income categories (the high income category is excluded), and the interactions of each of our three binary income variables with an indicator for t 1998, which should account for some of the changes in enrollment that are due to the Tax Relief Act of Our 10 In 1992, Congress reauthorized the Higher Education Act of 1965, expanding substantially the limits and eligibility for federal student loans beginning in Our estimation strategy allows for enrollment trends to change upon the HEA reauthorization, but the estimated coefficients are small and not statistically significant. 11 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. 13

14 treatment group is comprised of employed college graduates, who would be affected by the changes in the Section 127 treatment of graduate tuition assistance if they decided to use employer-provided grant aid. In this case the estimated coefficients of interest γ 2 and γ 3 measure the intention to treat. We estimate equation (1) for four separate groups: college graduates between the ages of 23 and 30, college graduates aged 31-40, high school graduates between the ages of 21 and 30, and year-old high school graduates. In the latter two groups, high school graduates refers to respondents who do not have a Bachelor s degree. The purpose of splitting the sample by education is to compare the Section 127 enrollment effects of potential graduate students, who should be affected by the changes, and potential undergraduate students, who should not be affected. Another approach would be to combine the high school and college graduates samples and estimate a triple-difference model. We chose to estimate two separate models in order to allow all of the coefficients to vary by education status. We combine the samples in the NPSAS estimations because we do not have appropriate employment data that we can use to construct a control group. We estimate equation (1) by probit. We estimate the model separately for each enrollment variable (full-time, part-time and vocational courses). 12 The coefficients that we report are average marginal effects, which we estimate using the person-specific weights in the CPS. 12 We also estimated a multinomial logic model of the joint decision of full-time or part-time attendance with a base outcome of no schooling; the results were virtually identical. The last outcome, vocational training, is not mutually exclusive with the first two because respondents can be enrolled in a degree program and take vocational courses at the same time. 14

15 The model that we estimate using the NPSAS data is given by EmployerAid it =f{x it β + γ 1 (Sec127 t ) + γ 2 (Sec127 t Graduate it ) + η 1 (Graduate it ) + ε it }, (2) where the vector X includes race, age, marital status, number of children, income, the one-year lag of the state unemployment rate and a quadratic in time. Since on-campus employment is prevalent in the NPSAS data, using employment status is a very noisy way to differentiate between the treatment and control groups. Thus, we pool the samples of graduate and undergraduate students and use undergraduates as a control group and graduate students as the treatment group. Because all respondents in the sample are currently enrolled in school and we use the actual aid that they receive from their employers as a dependent variable, the coefficient of interest γ 2 in this case is a measure of the treatment effect on the treated. The sample is split using the same age cutoffs as in the CPS regressions. We estimate the model in equation (2) using different forms of the dependent variable. First, we estimate a probit model in which the outcome of interest is an indicator for any employerprovided tuition assistance received during the academic year when the interview took place. An increase in the proportion of graduate students who use employer-provided tuition reimbursement during periods when Section 127 applies to this type of aid could indicate one of two things. On the one hand, it is possible that graduate enrollment increases, and marginal individuals who would not have undertaken the education without the deduction, enroll when the cost drops by the tax deduction amount. On the other hand, we cannot distinguish this scenario from the case in which enrollment remains the same, but students shift towards using more employer-provided aid either because its 15

16 value increases or because more firms start offering this benefit. Thus, it is important to consider both the CPS and NPSAS results. Using the NPSAS detailed information on program level (undergraduate, Master s or PhD) and type (MBA, law or education for example), we estimate a specification similar to the one in (2) separately for each program: EmployerAid it = f{x it β + γ 1 (Sec 127 Available t ) + ε it }. (3) Note that this is no longer a difference-in-difference framework. This approach allows us to see how Section 127 availability may have affected different types of programs. We also estimate equation (2) by tobit with a dependent variable that measures the amount (in 2009 dollars) of employer aid that each respondent used. The direction in which the amount of employer-provided aid might vary with changes in the Section 127 provisions depends on the incidence of the tax credit. The incidence 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 the assistance offered 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 its labor costs. Researchers have also pointed out that educational institutions may increase tuition costs or lower the amount of aid they offer in response to the introduction or expansion of education tax benefits (e.g. Long 2004, Turner 2012). We therefore estimate equation (2) by tobit with a dependent variable that measures the amount (in 2009 dollars) of tuition paid. An increase in tuition for graduate students 16

17 relative to undergraduates when the tax exemption is in place can reflect institutions increasing tuition or it could be that students enroll in more expensive programs when the tax exemption is in place. We are unable to distinguish between these two cases but it will be relevant to examine whether there is a change in the amount of tuition paid. The critical assumption for our difference-in-difference estimator to be valid is that use of tuition assistance, amount of tuition assistance and tuition paid would trend similarly for the two groups in the absence of the tax exemption. We do not use information on traditional undergraduate students, those aged 18-22, who are unlikely to use tuition assistance. Instead, we compare individuals enrolled in graduate and undergraduate programs within two age groups, and Results 4.1 CPS We begin with a graphical illustration of the trends that we are interested in. We estimate a modified version of equation (1), in which we replace the income interactions and time trend with a full set of year dummies interacted with employment status, and we combine the two age groups. We graph the point estimates of the year and employment interactions in Figures 2 and 3. These graphs should show how the relationship between employment status and enrollment varies over time. The three darker vertical lines on each graph correspond to the points in time when the Section 127 rules changed. We also include a vertical line that marks the year when the Tax Relief Act came into effect. The graduate enrollment trends in Figure 2 suggest that enrollment rates among fulltime workers were lowest when neither Section 127, nor the Lifetime Learning Credit 17

18 were available ( ). We see a general downward trend prior to 1998 and an upward trend after 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 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). Employed individuals enrollment increased slightly immediately after the Tax Relief Act was introduced, but that was followed by a decline until the early 2000s. Table 5 shows equation (1) estimation results for graduate enrollment. The dependents variables in the first three columns are 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 the sample of older college graduates. We find a much stronger relationship between Section 127 availability and full-time or vocational education than between Section 127 and part-time enrollment. Among year-olds, we see more full-time employees enrolling full-time or taking vocational classes in periods when graduate students can use the tuition assistance deduction; the estimated marginal effects equal and 0.015, respectively, and are highly significant. The enrollment rates of respondents who are out of work decrease by 1.2 and 1 percentage points, respectively. The vocational enrollment rates of part-time employees increase by 1.3 percentage points, and this estimate is significant at the 10 percent level, but the coefficients are closer to zero and not significant in columns 1 and 2. The only Section 18

19 127 coefficients that are significant for the older sample indicate that the tax deduction increases full-time enrollment by slightly less than half a percentage point for full-time workers and decreases it by 0.3 percentage points for individuals who are not working. 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. The results in Table 5 suggest that the lagged state-level unemployment rate does not have a statistically significant impact on enrollment rates in these samples. 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 part of the effects, since our income variable is noisy, and employment status tends to be highly correlated with income. As a comparison, we re-estimate the equation (1) probit model on the sample of high school graduates with no college degree. The dependent variables in these models are indicators for attendance of a part-time (columns 1 and 4) or full-time (columns 2 and 5) undergraduate program or vocational courses (columns 3 and 6). Three of the four coefficients on the Section 127 interactions with employment in the vocational training models in Table 6 are negative and significant at the 5 percent level; the fourth one is negative but not significant. In addition, the coefficient on 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 college-educated workers is crowding out employer-provided tuition assistance for undergraduate education in periods 19

20 when Section 127 is available for graduate education. On the other hand, we estimate a positive and weakly significant coefficient on the interaction with full-time employment in column 5, but the magnitude of the marginal effect is small ( ). 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. There is a slight increase in full-time and vocational enrollment among the younger group and just vocational coursework among the older group for respondents who are unemployed or out of the labor force at the time of their interview. Table 6 suggests that the Tax Relief Act had a stronger impact on individuals with no Bachelor s degree. The program shifted low-income individuals enrollment from fulltime to part- time. Part-time and vocational enrollment increased slightly for the older middle-income sample. The coefficient on the interaction with high income is negative and marginally significant in column 1 and positive and significant in column 3, with magnitudes of about 1 percentage point. An explanation consistent with the observed trends is that the newly introduced tax benefits incentivized some people to switch program intensity. The lagged unemployment rate has a positive impact on all three types of enrollment for the older sample. 4.2 NPSAS We examine the probability that an individual uses employer tuition assistance as a source of finance for their graduate education in Table 7. The first two columns look at part-time and full-time students respectively in the age group. The third and fourth column examines part-time and full-time students in the older age group. The 20

21 difference-in-difference coefficient of interest is on the interaction of Grad and Section 127 Available. The results indicate that the tax exemption is more important for part-time education than full-time education. The probability of using any employer assistance increases by 1.5 percentage points for the younger group relative to similar aged undergraduates and by 3.3 percentage points for the older group relative to similar age undergraduate students when the exemption is in place. This is contrary to the CPS findings that indicate a stronger enrollment response for full-time than part-time enrollment. The NPSAS data has information about degree type, such as undergraduate, Master s or PhD, as well as detailed information about the program of study such as MBA, law or education. It is possible that our results are driven by specific programs so we estimate our specification for programs separately according to equation (3). We estimate this equation with probit and present marginal effects in Table 8 for undergraduates, undergraduate business majors, all Masters students, all PhD students, MBA, Law and Education degrees for each age group and full-time and part-time separately. The only significant coefficient on the tax emeption variable in the part-time regressions is for older students in law programs. The effect is large, indicating an 18 percentage point increase in the probability of having any employer tuition assistance when the tax exemption is in place. It is possible that this is driving the results of part-time programs in the pooled regressions. Turning to the full-time programs, the younger group and older group of undergraduates are about 1 and 1.5 percentage points more likely to report employer tuition assistance respectively when the tax exemption is in place. Master s, PhD and Education students in the younger age group are 2.7, 3.8 and 5.1 percentage points more likely 21

22 to report employer tuition assistance. Only PhD students in the older age group see a statistically significant increase in the probability of reporting tuition assistance when the exemption is in place. Pooling the degree types together may cause us to miss which groups are truly affected by the tax exemption as some degree programs are unlikely to have any students with employer sponsorship. The results of the regressions by degree type are more in line with the CPS results. In addition to the incentive for individuals to acquire additional education when the tax exemption is in place, universities may increase tuition to capture the incidence of the subsidy. Alternatively, students can afford a more expensive education so they may enroll in a university with a higher tuition. Table 9 displays the results of Equation 2 where the dependent variable is the amount of tuition paid. Relative to undergraduate students, both part-time and full-time graduate report paying a higher tuition when the tax exemption is in place. The impact on tuition for full-time students is larger than that for part-time students. Full-time students pay roughly two to three thousand dollars more in tuition whereas part-time students pay roughly one thousand more dollars in tuition. Full-time tuition is often more expensive than part-time tuition, so it is possible that universities increase tuition by the same percentage. In any case it is unclear whether the response is due to students or employers and we leave untangling this effect to future work. Interestingly, income is not a significant predictor of tuition. The tax exemption is equivalent to giving an individual more income to spend on their education, so a lack of significance on the income variable provides some evidence that it is universities that are changing their behavior. Finally, the response in the amount of tuition assistance received is investigated in Table 10. Pooling part-time and full-time students together reveals a similar pattern to 22

23 the impact of the tax exemption on the probability of reporting any assistance. That is, part-time students in both age groups report a significantly higher amount, roughly $1,000, than their undergraduate counterparts when the tax exemption is in place. Fulltime students do not report a significantly higher amount of tuition assistance. When this result is broken down by degree type, however, different patterns emerge. 13 Both full-time undergraduates and graduate students report a statistically significant increase in amount of employer aid. The change is larger for graduate students than undergraduates. There are also several degree types that report no change, which eliminates the effect when all groups are pooled together. The lagged unemployment rate has a negative impact on both the probability of receiving any aid and on the average amount of aid received. If individuals are not employed they cannot use employer assistance, so this is consistent with a story of individuals receiving mroe education when the unemployment rate is high. 5 Conclusion In this paper we examine how changes in the tax code affect enrollment in and financing of graduate education. We focus on the six-year lapse in exemptions for employerprovided graduate tuition assistance. Using the October supplements of the CPS, we find that full-time graduate enrollment among year-old employed college graduates increases by almost 2 percentage points in years when the tuition reimbursement tax exemption is available. Even though the treatment samples are different, this result is comparable to the findings of previous studies that use exogenous changes in education financing policies to study the effect of aid on college attendance (e.g. Dynarski 2000, 13 Table available upon request. 23

24 Cornwell et al. 2006, Kane 2003, Seftor and Turner 2002). The enrollment effects we estimate are lower for older students and for part-time employees. In terms of financing graduate education, we find differential responses to the tax exemption by program type. Part-time law students and full-time Masters, PhD and Education degree students are more likely to report receiving any employer assistance during the years of preferential tax treatment to tuition assistance. Although the literature up to date has mostly focused on the elasticity of demand for college education, mostly among recent high school graduates, it is important when doing program evaluation to keep in mind that financial aid policies may have a different effect on graduate students. This paper provides a look at one such policy that is targeted at employed college graduates whose firms offer educational assistance. Our treatment group is not fully representative of all potential graduate students, but the fact that we find a response to changes in the cost of graduate education suggests that other programs are also likely to have a nontrivial impact on graduate enrollment. It is also necessary to examine in more detail how firms respond to changes in Section 127 in terms of the tuition assistance offered for both graduate and undergraduate courses, and whether educational institutions increase the effective cost to students when federal aid policies for graduate students are more generous. We find that students report receiving a larger amount of tuition assistance and pay more in tuition during tax exempt years. However, we are unable to tell whether this comes from employers being more generous or more employees making use of existing programs. While students report paying more in tuition it is not clear whether universities are increasing tuition or if individuals choose to attend more expensive programs. We offer an initial insight but leave untangling these effects for future work. 24

25 Figure 1: Tax Treatment Schedule Tax Relief Act of 1997 signed Grad courses eligible for Sec 127 Grad courses eligible for Sect Max LLC = $1K Max LLC = $2K 1992 Reauthorization of HEA Loan limits increased Tuition deduction = $3K Tuition deduction = $4K 25

26 0.07 Full Time Graduate Enrollment Figure 2: Full-Time Graduate Enrollment Employed FT Full Time Graduate Enrollment Employed PT Full Time Graduate Enrollment Unemployed/Out of labor force The plotted values are the coefficients of the full set of year dummies interacted with employment status from linear regressions of the full-time graduate enrollment indicator that also include as independent variables age and age squared, race, gender, marital status, the state unemployment rate, last year s school enrollment status, the natural log of household income (constructed from the CPS categorical measure), and state indicators. The sample consists of college graduates; 1989 t 2009; 23 Age 40. The thinner lines represent 95% confidence intervals. 26

27 0.035 Full Time Undergraduate Enrollment Figure 3: Full-Time Undergraduate Enrollment Employed FT Full Time Undergraduate Enrollment Employed PT Full Time Undergraduate Enrollment Unemployed/Out of labor force The plotted values are the coefficients of the full set of year dummies interacted with employment status from linear regressions of the full-time undergraduate enrollment indicator that also include as independent variables age and age squared, race, gender, marital status, the state unemployment rate, last year s school enrollment status, the natural log of household income, and state indicators. The sample consists of high school graduates without a college degree; 1989 t 2009; 23 Age 40. The thinner lines represent 95% confidence intervals. 27

28 Table 1: 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 ( ) or $10K ( ) Phase-out income: $40K/$80K to $50K/$100K ( ) $50K/$100K to $60K/$120K (2009) Interest Deduction Deduction up to $A of adjusted gross income for interest payments on student loans; : Limited to first 60 months of interest payments (2000), $2,500 ( ) A =$1,000 (1998), $1,500 (1999), $2,000 Phase-out income: $40K/$60K to $55K/$75K ( ) $55K/$110K to $70K/$140K (2007) Deduction up to $A for postsecondary tuition and fees A=$3K ( ) or $4K ( ) 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 ( ) $80K/$160K ( ) A =$5,250 ( , ) or 0 ( , ) A = $5K ( ) or $6K ( ) B = $30K ( ) or $40K ( ) A = $7.5K ( ), $8.5K ( ) B = $54.75K ( ), $65.5K ( ) A = $4K ( ) or $10K ( ) B = $73K ( ) 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. 28