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1 College Aid Policy and Competition for Diversity Despite substantial increases in the enrollment and college completion rates among African American and Hispanic students in the last three decades (Snyder, Dillow, & Hoffman, 2007, Table 267), a college completion gap persists between minority students and White and Asian/Pacific Islander students (ACE, 2008; Carey, 2004). A number of factors help determine college persistence and attainment (Tinto, 1993) but two factors strongly associated to baccalaureate attainment are: access to financial aid (Dynarski, 2002; Heller & Nelson Laird, 2000; Turner, 2004) and access to elite education 1 (Alon & Tienda, 2005; Alon & Tienda, 2007; Author, 2008; Author, forthcoming; Bowen & Bok, 1998; Horn, 2007). Students who attain a baccalaureate degree from an elite institution with low debt have several advantages including the opportunity to pursue a graduate degree (Eide, Brewer, & Ehrenberg, 1998) and/or to enter the labor market and start receiving the benefits of college education such as higher earnings and middle class status (Cabrera, Burkum, & La Nasa, 2004; Mortenson, 2006). In recent decades, a permanent increase of tuition above the cost of living coupled with a decrease in the real value of Federal Pell Grants, a shift from federal grants towards federal loans (College Board, 2006), a decrease in state appropriations for higher education (Hovey, 2002), and colleges increasing movement from need-based to meritbased financial aid (Ehrenberg, Zhang, & Levin, 2006; Heller & Nelson Laird, 2000) have left both low- and middle-income families struggling to pay for education. The increasing costs coupled with the changes in financial aid are probably associated with 1 Elite education is defined as access to prestigious and highly ranked private institutions as well as public flagships.

2 the lower rates of college enrollment and attainment of low-income and minority students compared to their high-income and non-minority peers (Astin & Oseguera, 2004; Bowen, Chingos & McPherson, 2009). Some evidence suggests that the decrease in enrollment of low-income minority students may also be associated to the passing of anti-affirmative action policies in some states (Carnevale & Rose, 2003; Long, 2004a). For example, according to Horn & Flores (2003), since the ban on affirmative action policies, the proportion of low-income minorities attending elite institutions in California, Florida, and Texas has decreased, and the percentile plans (i.e. ten percentage plan in Texas) instituted by these states have not been as successful as hoped in attracting low-income minority students. Furthermore, proponents of affirmative action policies argue that restriction on considering race in the admissions process has hampered the ability of public flagship institutions to attract high-achieving low-income minorities (Alon & Tienda, 2005; Bowen & Bok, 1998; Kane, 1998). Most of the studies that have tried to explain the factors associated with the relatively low participation and attainment rates of lowincome and minority students have focused on exploring the impact of the different types of financial aid (Dynarski, 2002; Long 2004b), or on the positive effects of attending more selective institutions (Alon & Tienda, 2005; Bowen & Bok, 1998; Author, 2008; Author, forthcoming). However, to the best of our knowledge no study has explored how financial aid policies in combination with the banning of affirmative action policies have also restricted public flagship institutions to compete for high-achieving low-income minorities. One of the main reasons for the lack of research in this area is that information on financial aid packages provided to students is not publicly available. This study 2

3 College Aid Policy and Competition for Diversity overcomes this limitation by taking advantage of a unique dataset compiled as part of the Gates Millennium Scholarship (GMS) program funded by the Bill & Melinda Gates Foundation. The foundation collected student self-reported data on the different types of financial aid that the students received their first year (i.e., grants, loans, parental contribution, and work study). The main objective of this study is to create a typology of the most common financial aid packages offered to students, and to test for differences in the packages offered to high-achieving low-income minorities by institutional control (ownership) and selectivity. Given that the GMS program was geared only to minority students, we complement the data with the National Postsecondary Aid Survey (NPSAS) to test for differences in the types of financial aid received between minority and white students. Two research questions guide this inquiry: 1) Are financial aid packages with a higher proportion of grants more prevalent at private as opposed to public institutions, selective as opposed to non-selective institutions, and private selective as opposed to public selective institutions? 2) Are financial aid packages with a higher proportion of grants more prevalent for high-achieving low-income minority than for high-achieving low-income white students? An implicit assumption of our study is that it is preferable for students to receive financial aid packages with a higher proportion of financial aid in the form of grants. In reality, the best packages are those that minimize the unmet need, and in the case of lowincome students the expected family contribution (EFC). Given that this information is very limited in our dataset, we have to rely on the proportion of grants in the package as an approximation of a more attractive financial aid package. If the data confirms that the financial aid packages with a larger proportion of grants are more prevalent at the elite 3

4 privates, and that the proportion of institutional aid in the form of grants is larger for minority than white students at the private institutions, this would confirm that institutions are strategically using resources to compete for high-achieving low-income students. Our work is grounded in the economics of higher education theory that assumes that colleges act as competitive firms in the market for higher education. Colleges want to have an academically prepared diverse student body, and financial aid policies are the instrument to obtain the desired composition. To obtain a quality diverse student population, a college must bid for it with a sufficient subsidy. In the present market environment, a high-achieving minority student is more likely to enroll in response to a higher subsidy. To be able to offer this higher subsidy, a college must be able to legally make this differentiated offer and to have resources to finance it. The results of the study suggest that indeed elite private colleges offered a financial aid package with a larger proportion of grants to attract low-income high achieving minority students. A potential explanation for this result is that elite private colleges usually have higher endowments that they can use to recruit their desired freshmen classes, and also, they are less restricted by the law to use race/ethnicity as one of their criteria used to allocate the funds. This suggests that elite private colleges are able to exercise their financial and policy advantages in competing for the high-achieving lowincome minority students and that this hampers the ability of public colleges to attract these students. Operating in a legal environment where minority students cannot be targeted with institutional subsidies, public schools lose in this competition for diversity. 4

5 College Aid Policy and Competition for Diversity In the sections that follow, we situate the context of our study in the existing literature; describe the analytical strategy, data and our sample; explain our methodology; report the results; and finish with conclusions and policy implications. Literature Review In this study we draw on several strands of the existing literature in economics, education, and sociology that have explored different factors associated with recruitment and enrollment decisions of students in postsecondary institutions. The economics literature has developed extensions of traditional economics models of the firm to illustrate the production function of non-for-profit postsecondary institutions (Winston, 1999). As described in more detail below, these models are used to estimate the appropriate level of tuition discounting that different types of institutions should offer to maintain quality and remain economically viable (Martin, 2002; 2004). The models are also used to estimate probabilities of enrollment of students with desirable characteristics to maximize the prestige of the institution as well as the mission for the public good (Epple, Romano, &Sieg, 2006; Ehrenberg & Sherman, 1984; Epple, Romano, & Sieg, 2008). The education and sociology literature have contributed to the field by documenting that traditional economic assumptions of perfect information does not hold in higher education. Specifically, using qualitative and quantitative strategies they demonstrate how low-income and racial/ethnic minority students tend to over-estimate the costs of education, and under-estimate the subsidies. This has important policy implications in the sense that specific types of postsecondary institutions that are more responsive to these groups of students are more successful in recruiting and enrolling them. 5

6 Economics Literature A series of papers in economics establishes a foundation for our work. Winston (1999) defines colleges as competitive market entities. He points out that peer quality is an input in education production that contributes to students education and that is costly for a college to obtain. Finding a relationship between a school s resources and its ability to pay for student quality with high institutional subsidies, Winston illustrates the vast donative resource advantage private selective colleges possess compared to public colleges. Institutions operating in this competitive market have embarked on a series of tuition discounting practices to attract high quality students with the objective of maximizing the prestige of the institution. Martin (2004) presents empirical evidence that illustrates that when institutions do not take into account the opportunity costs of aggressive student subsidies, they run deficits. He develops an intuitive model that connects the actual institutional discount rate with the resulting deficit or a surplus. He concludes that if institutions continue to engage in aggressive discounting practices subsidizing students from tuition waivers rather than from the endowment, they cannot remain financially viable. In addition, he argues that the common practice for institutions has been to increase enrollment until they reach full capacity. He argues that institutions take into account the marginal cost of a student instead of the average cost, and this is a serious miscalculation that results in institutions giving subsidies to high-income students, lowering the quality of the institutions, and running deficits. He advocates for institutions to be more financially responsible, and increase tuition discount with flexible funds from the endowment, and increasing enrollment of high-achieving low-income students. 6

7 College Aid Policy and Competition for Diversity There is also empirical evidence that private colleges provide much higher levels of institutional aid in the form of grants and have more sophisticated tuition discounting practices (Horn & Peter, 2003; Baum & Lapovsky, 2006; College Board, 2008). From 2002 to 2007, the institutional share in grant aid of private colleges has risen by 42 percent (College Board, 2008, Figure 5). From to , about 70 percent of all institutional grants were awarded to undergraduates at private four-year colleges. About 70 percent of all private institutional grants were need-based, compared to just 44 percent of public institutional grants (College Board, 2008, Figure 14a). Another strand of the economics literature has focused on the supply side, and has developed general equilibrium models to simulate changes in financial aid and affirmative action policies (Epple, Romano, &Sieg,2006; Ehrenberg & Sherman, 1984; Epple, Romano, & Sieg (2008). Ehrenberg & Sherman (1984) model a set of optimal financial aid policies for a private selective university. Their results suggest that minority students should be offered larger aid packages because holding all else equal, they have a lower propensity to enroll. Epple, Romano, and Sieg (2008) go a step further, and they explicitly model the consequences of the affirmative action ban in college admissions and financial aid policies. Their model implies that under affirmative action, minority students pay less for college and that a ban on affirmative action results in a decline of minority student population in more selective colleges. The results of these studies suggest that given the competitive market in higher education, institutions with larger donative resources have an advantage in terms of competing for low-income high-achieving minorities. There is also evidence that a 7

8 subsidy to low-income minorities will be positive in the sense that it will increase their probability of enrollment. Education and Sociology Literature The emerging education and sociology literature provides some evidence that the perception of college costs and financial aid availability varies by socioeconomic status and race and ethnicity. De La Rosa (2006) finds that students perceptions of their college opportunities are grounded in family background and school culture and, as such, are limited by the families understanding of the college and financial aid application process. Horn, Chen, and Chapman (2003) also document racial/ethnic and socioeconomic inequalities in both the probability of estimating tuition cost and parents ability to estimate tuition costs accurately. In a similar vein, Grodsky and Jones (2007) use a national representative dataset to estimate differences in perceptions and conclude that low-income and minority parents are less likely to provide estimates of college tuition, and when they provide estimates, tend to make larger errors. These results suggest that low-income students might be vulnerable to what is known as sticker price shock given that they tend to over-estimate the costs and are not as informed of the financial aid options available to them. Perna (2006) argues that simply making information available to these students and their parents is insufficient to promote enrollment. Indeed, Venegas (2006) ascertains that even though low-income students may have access to computers, they lack the skills necessary to navigate the available financial aid resources online. McDonough and Calderone (2006) further assert that even though many families lack basic understanding of financial aid (including the difference between grants and loans), they are keenly aware of the high college costs due to the high sticker price particularly of 8

9 College Aid Policy and Competition for Diversity private selective institutions. The authors quote a counselor at a private high school speaking about the fact that many of her low-income minority students have received better aid packages at private schools because they [the private colleges] want the kids... as opposed to state schools. The emerging education and sociology literature indicates that private colleges may be more sensitive to the informational deficiencies faced by low-income minority college-aspiring youth and can be more proactive than public institutions in offering more generous financial aid packages to counteract student uncertainty about college affordability. In summary, our work is grounded in the economics of higher education theory that assumes that colleges act as competitive firms in the market for higher education. Colleges want to maximize the quality of their student body, and financial aid policies are the instrument to obtain the desired composition. In addition, colleges want to craft a class that reflects the socio-economic and racial/ethnic diversity of the country. To obtain a quality diverse student population, a college must bid for it with a sufficient subsidy. In the present market environment, a high-achieving minority student is more likely to enroll in response to a higher subsidy. To be able to offer this higher subsidy, a college must be able to legally make this differentiated offer and to have resources to finance it. In the following section, we describe our analytical strategy, data, and methodology. Analytical Strategy, Data and Sample One of the reasons for the lack of research on the postsecondary institutional financial aid is the lack of publicly available data. As mentioned above, this study uses a unique dataset that enables us to create a typology or categories for the most common 9

10 financial aid packages received by the students. For our study, the primary goal has been to identify the most common financial aid packages offered to the students, and then to test for the resulting differences by institutional control and selectivity. Because there is little literature that would directly inform our method -- constructing the packages ex-post with the student self-reported data -- it was first necessary for us to employ a non-causal approach to establish the descriptive facts. Future studies can use quasi-experimental approaches merging institutional level data from the Integrated Postsecondary Education Data System (IPEDS) to explore the association between institutional endowment and financial aid offers and college persistence and attainment. In the following section we briefly describe the Gates Millennium Scholars (GMS) program focusing on the data and sample used in this study. Data In 1999, the Bill and Melinda Gates Foundation funded the Gates Millennium Scholars Program (GMS), a $1 billion twenty-year scholarship initiative. The scholarship is a capping grant, supplementing a student s financial aid award by substituting grants for loans and work study up to the total cost of attendance. The GMS was designed to broaden access to higher education for minorities, particularly African Americans, American Indians/Alaska Natives, Asian Pacific Islander Americans, and Hispanic Americans who were also low income. The first GMS cohort was funded in 2000, and the GMS Program s goal is to fund about 20,000 minority students by To assess the impact of the scholarship program, the Bill & Melinda Gates Foundation asked the National Opinion Research Center at the University of Chicago (NORC) to follow selected cohorts of GMS recipients (scholars) and comparison samples of nonrecipients as they enter and progress through college and beyond. This study includes 10

11 College Aid Policy and Competition for Diversity recipients and non-recipients who were undergraduates in the first and third cohorts of GMS and who entered college in the and academic years. NORC s study design involved conducting baseline and follow-up interviews of all recipients and selected non-recipients. For the first cohort, they began in 2002 and tracked the students between survey rounds through 2006 (NORC, 2003, Table 1.1 and Exhibit 1). For the third cohort, they began in 2003 with a follow-up survey in 2005 (NORC, 2004, Table 1.1 and Exhibit 1). There are several advantages of using this unique dataset. First, the GMS data provide a large sample of low-income minority students. Studies that have used other data such as the NPSAS (Epple, et al., 2008) to study financial aid targeted at minority students in elite colleges, have to work with a very small and homogenous sample. Second, since GMS is selective, its participants are not only college ready, but also high achieving, comparable in ability and academic preparation to their non-minority peers in elite colleges. Third, we also employ a unique feature of the GMS program -- the selection of participants based on a number of non-traditional criteria positively correlated with college persistence (Sedlacek, 2004). This selection increases the chances that GMS scholars are more similar to the non-recipients peers in terms of traditionally unobservable characteristics. Fourth, we benefit from the availability of a comparison group consisting of GMS non-recipients. Having a comparable sample of non-treated applicants to the GMS program is important because the observed ex-post differences in students financial aid 11

12 packages cannot be attributed to the ex-ante variations in student characteristics due to self-selection into the program. GMS data share a common limitation with most other student-level datasets in that they are largely self-reported. This may be problematic in the context of reporting financial aid information because students may not provide the exact monetary quantities received. We lessen the consequences of this possible measurement error by constructing the types of financial aid packages in terms of relative aid proportions, rather than absolute amounts or their ratios (see Methodology for a detailed explanation). Sample The final sample of this study is composed of 1,634 GMS recipients and nonrecipients from Cohort 1 and Cohort 3 who participated in the base and follow-up surveys and who provided information for all the relevant variables included in the study. This was about 61 percent of the original sample. The original Cohort 1 sample provided by NORC was composed of 1,108 individuals. The original sample for Cohort 3 provided by NORC was composed of 1,592 individuals. We removed American Indians from our sample because their number was very low. A few notable considerations pertain to Cohorts 1 and 3 student data. In the first year of GMS, the scholars were notified of the award after they had already accepted an offer from a postsecondary institution. This created a unique benefit for using Cohort 1 data because the GMS award was unexpected for both the recipients and the institutions they would attend. The institutions were not able to anticipate students GMS awards, thus could not modify their initial financial aid packages accordingly. Theoretically, the institutions should not be able to alter their initial aid offer in expectation of a GMS award. Rather, GMS is calculated on the basis of the initial award letter. However, an 12

13 College Aid Policy and Competition for Diversity institution that enrolls GMS recipients on a regular basis can, in principle, anticipate that a predictable number of GMS recipients will apply and get early signs about GMS receipt from student applicants. Also, the students were not familiar enough with the scholarship program to be able to request an increase in their financial aid budgets to cover additional costs such as expected family contribution (EFC). There is some anecdotal evidence on students manipulation of GMS funds eligibility rules. Scholars quickly learn about being able to request increases in their financial aid budgets to obtain additional funding for certain expenses. Some institutions have established their own rules regarding the frequency with which the students can request increase in their budgets. These idiosyncratic features of the GMS Cohort 1 data are helpful in minimizing endogenous variations in financial aid offers and awards due to unobservable characteristics of students and institutions. An additional advantage associated with the first cohort is that one can expect a much higher percentage of scholars enrolled at lessselective schools given that they were informed of the award during their freshmen year. This benefits our study because the resulting set of colleges is more varied in terms of selectivity and produced a more heterogeneous set of financial aid packages. Because the creation of the program database was in its inception, not all data fields were readily populated for Cohort 1 data. For example, the information in the students EFC field is lacking and the detail on the types of loans is incomplete. Cohort 3 data was collected when the program was in its full inception, so the financial aid information is much more complete. Methodology 13

14 In this section we describe the methodology that we used to construct the financial aid packages we study in this paper, the characteristics of the postsecondary institutions which awarded the financial aid packages, and the characteristics of the students who received this aid. Financial Aid Packages We considered two important points in constructing the models of student financial aid packages that are the focus of our study. First, as discussed above, our sample is unique in that it is composed of highly motivated and high achieving minority students who enrolled in college right after high school graduation. Therefore, as we expected, many of the students in our sample enrolled in selective or highly-selective institutions and received generous financial aid packages containing substantial grants. Consequently, the grant share in the financial aid packages for the students in our samples was much higher than the 60 percent grant share in an average financial aid package for a full-time full-year undergraduate (Snyder & Tan, 2005). Second, we faced a common problem arising in studies of student financial aid: we only had information on disbursed, not offered, aid. Because disbursed aid is contingent upon students decision to attend, endogeneity issues arise from potential changes in aid packages due to students decisions to persist or drop out. To avoid these issues in our study we used only information on freshman year financial aid packages. We started by identifying distributional patterns of the major components in student financial aid packages. First, we calculated the totals for grants, loans, parental contribution, and work study for each student. Then, we estimated the proportion of each component (e.g., the proportion of grants in the total financial aid received in freshman year). The next step was to calculate the lowest (25 th ), the mean, and the highest (75 th ) 14

15 College Aid Policy and Competition for Diversity percentiles of the relative proportions of grants, loans, parental contribution, and work study. For example, when we computed the grant share of student financial aid packages for the students in Cohort 1, the 1 st quartile package (lowest 25 th percentile was composed of 37 percent grants, the mean had 64 percent grants, and the last quartile package (highest 75 th percentile) had 86 percent grants. For the students in Cohort 3, the distribution was 30, 58 and 85 percent respectively. The percentile distribution for the other types of financial aid for Cohort 1 was as follows: loans were 0, 11 (mean), and 19 percent; while parental contribution was 0, 12 (mean), and 16 percent. For the students in Cohort 3, the distribution was 0, 11(mean), and 16 for loans; and 0, 9(mean), and 10 for parental contribution. We closely examined the resulting distribution of financial aid components to determine the most common combinations received by the students in our sample. From this, we have constructed six possible combinations of financial aid packages: (1) Highest percentage in the form of grants. This variable includes all grants reported by a student, such as a Federal Pell Grant, any institutional or state grant, and grant money from the Gates Foundation. This variable identifies the packages with the highest (in the 75 th percentile) proportion of grants (about $14,000 for Cohort 1 and about $11,000 for Cohort 3). These packages have average or below average proportions of loans, hours worked per week, and parental contribution. (2) Highest percentage in the form of loans. This variable includes all loans reported by a student. The variable identifies the packages with the highest (in the 75 th percentile) proportion of loans (about $2,700 for 15

16 Cohort 1 and about $2,000 for Cohort 3). These packages have average or below average levels in the form of grants, hours worked per week, and parental contribution. Even though GMS replaces loans and work study in students financial aid packages, the students may still take out loans to cover their EFC or unmet need, which is the difference between the student s cost of attendance (COA) and the awarded aid. Each institution may calculate EFC differently for a given student for the purposes of awarding aid. Institutions, particularly private selective ones, may employ their own methodology (often called Institutional Methodology [IM]) to determine a student s eligibility for institutional aid. The magnitude of unmet need is largely dependent not only on EFC and the many components of the financial aid package, but also on factors like student residency. Thus, out-of-state students in public universities may face larger unmet need. Larger loan amounts can be borrowed either against a student s EFC, or unmet need, or both. (3) Highest percentage in the form of parental contribution. This variable identifies the packages with the highest (in the 75 th percentile) proportion of parental contribution (about $3,000 for Cohort 1 and about $1,500 for Cohort 3). These packages have average or below average levels in the form of loans, grants, and hours worked per week. (4) Highest percentage in the form of grants and parental contribution. This variable identifies the packages with the highest (in the 75 th percentile) proportion of grants and parental contribution. These packages have average or below average levels in the form of loans and hours worked per week. (5) Highest percentage in the form of loans and parental contribution. 16

17 College Aid Policy and Competition for Diversity This variable identifies packages with the highest (in the 75 th percentile) proportion of loans and parental contribution. These packages have average or below average levels in the form of grants and hours worked per week. (6) Highest percentage in the form of grants, loans, parental contribution, and hours worked per week. This variable identifies packages with the highest (in the 75 th percentile) proportion of grants, loans, parental contribution, and hours worked per week. Analyses We present descriptive statistics illustrating the characteristics of the individual as well as the characteristics of the postsecondary institutions that they attended. After defining the typology of financial aid packages we used conventional statistical methods such as chi-square tests of independence, to test whether the observed differences in the types of packages by selected institutional characteristics were statistical significant (Howell, 2009). We tested for differences in types of financial aid packages received in freshman year by: institutional control, institutional selectivity, and a combination of control and institutional selectivity. In the following part we define the institutional and individual characteristics in more detail. Postsecondary Institutional Characteristics Based on the studies described in our literature review, we have chosen to concentrate on two institutional characteristics: institutional control (ownership) and selectivity. We categorized all institutions as either public or private non-profit. We constructed institutional selectivity to reflect the quality of the institution attended by the student. We first categorized institutions between selective and less selective. We then 17

18 provided a fine-grain categorization composed of most selective, highly selective, selective, and less selective. (A list of all the postsecondary institutions is available from the authors upon request.) Given that students could have attended more than one institution, we used the selectivity of either the graduating institution, the current institution, or the institution last attended by the student as the main institution attended. We calculated the selectivity measure of this institution using the SAT scores of the freshman entrant class reported in Barron s Profiles of American Colleges and Universities. To better understand the quality match between our students and the institutions, we have calculated a proxy variable that we called peer-effects. We estimated this by subtracting individual SAT scores of the students in our sample from the corresponding average SAT scores of the entrant freshmen class at the last institution attended. We also identified the institution s Carnegie Classification code (i.e Doctoral/Research Comprehensive Extensive, Doctoral/Research Comprehensive Intensive, Master Comprehensive I, Master Comprehensive II, Baccalaureate College - Liberal Arts, Baccalaureate College General, and Other), as well as the major field of study last reported by the students. Student Characteristics Background student characteristics include: female, African American and Hispanic and Asian/Pacific Islander, and age. Three proxies for socioeconomic status are: Pell Grant recipient; father attained a B.A. or higher; mother attained a B.A. or higher. The student cognitive characteristics are: average SAT scores, number of advanced placement (AP) exams taken, attended a private high school (as opposed to a public one), baccalaureate expectations of students by high school. Students non- 18

19 College Aid Policy and Competition for Diversity cognitive characteristics are captured in the variable containing a summary measure of all non-cognitive variables included in GMS surveys. Limitations Even though we have a unique dataset that enabled us to create a typology of financial aid packages received by low-income high-achieving minority students, the data has a number of limitations. First, the data was collected from surveys and is selfreported by the students. This is problematic because the data is less accurate than institutional records. Second, the ideal dataset to answer the questions in our study would be the financial aid packages offered, and the financial aid received by the students after enrollment. Having information on the total tuition and fee costs, the expected family contribution (EFC), the different types of financial aid used to cover the total cost of attendance (COA), as well as the unmet need would really enable us to calculate the best packages and determine the type of institutions that are offering them. Fourth, in addition, it would be helpful to have information describing the type of funding (i.e., subsidized or unsubsidized loans, parental contribution) that the students used to cover the expected family contribution (EFC) and unmet need. Even though the Bill & Melinda Gates Foundation collected some of the information described above, it collected it only for the Scholars, and it is partially complete only for the scholars in Cohort 3. Despite the limitations described above, the analyses described below uses all the information from the surveys and institutional records of the foundation to present an accurate picture of the funding packages offered to this unique group of students. Finally, one of the major limitations of the data is our inability to identify the proportion of the financial assistance that was given as need- 19

20 based aid and merit-based aid. It is important to mention that our sample qualified for both, and it would be really interesting to see how public and private institutions allocate their institutional resources according to these criteria. Results Student Profile To give the reader a better understanding of our student sample, we present descriptive statistics for the student sample of GMS recipients and non-recipients for the combined cohorts (see Table 1). The minority students in our sample possess four distinctive characteristics: they are indeed low-income and high-achieving, they attend a mix of public and private mostly selective institutions, and they receive generous subsidies. Consistent with recent national college enrollment trends, a majority of the participants in the sample are females. The Gates Foundation s efforts to achieve even representation of African Americans, Asian American/Pacific Islanders, and Hispanic Americans are clear: each group represents about one third of the sample. As noted in Table 1, there were some missing responses for Cohort 3 students, so as a consequence only 50 percent of the students in our sample indicated their participation in the Federal Pell Grant Program. We have reasons to believe that the data underestimate the percentage of low-income students. This is further confirmed by the relatively low percentage of students with parents with a college degree. The average SAT score for the students in our sample was 1,167. This average was higher than the re-centered scores of 1,016 of the sample of test takers in 1999 (College Board, 1999; College Board, 2007). The relatively high number of AP courses taken in high school (2.34), as well as their high level of college aspirations (

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