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Federal policies, state responses, and community college outcomes:

A test of an augmented Bennett hypothesis

Allison Frederick+, Stephen J. Schmidt*, and Lewis S. Davis+

August 18, 2010

Abstract:

We estimate the impact of increases in Federal funding, such as the recently proposed American Graduation Initiative (AGI), on the outcomes of community colleges, including enrollments, list and average tuitions, and variables related to educational quality. We develop a model of state-level education policy in which state policy makers, who may have objectives and constraints that differ from those of Federal policy makers, respond to changes in Federal policies. Our empirical specification treats all state policy variables as endogenous, and we interpret the coefficients as measuring the responses of state officials to changes in Federal policies. We simulate the effects of the AGI and find little evidence that state policy makers recapture Federal resources. We find AGI will have a significant effect on educational quality but a limited effect on enrollments. An equivalent increase in Federal student aid would have greater impact on access and enrollments, but decrease educational quality.

JEL classifications: I22, I28, H52, H75

Keywords: demand for schooling, educational finance, expenditures, grants, state and federal aid

* Corresponding author. Department of Economics, Union College, Schenectady NY USA, 12308, schmidsj@union.edu. Phone 518-388-6078, fax 518-388-6988

+ Department of Economics, Union College, Schenectady NY USA, 12308

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Section 1: Introduction

In June 2010, President Barack Obama proposed the American Graduation Initiative (AGI), a

$12 billion dollar package of Federal funding for American community colleges, in order to, in

his words, “reform and strengthen community colleges from coast to coast so they get the

resources that students and schools need -- and the results workers and businesses demand.

Through this plan, we seek to help an additional 5 million Americans earn degrees and

certificates in the next decade.”1

The proposal of the AGI raises a number of important questions. The first is how the

funding increases in the AGI would affect other important dimensions of the community college

system, such as the affordability and quality of a community college education. A second

question concerns the effects of the AGI relative to other policy options. Given that federal

student aid has long played a central role in US higher education policy, it is natural to ask

whether the AGI is more or less effective than an equivalent increase in student aid in increasing

community college enrollments and obtaining other federal policy objectives like increasing

community college affordability and quality.

Of this funding, $9.5 billion is to be used to increase graduation

rates and develop new programs, and $2.5 billion (to be matched by $7.5 billion in state and

local funds) is to be used to construct new facilities and renovate existing ones. The intention of

the program is to increase the number of Americans receiving associate degrees or higher, and

the quality of their educations, to meet the needs of a labor market where an increasing

proportion of jobs will require advanced degrees.

1 http://www.whitehouse.gov/the_press_office/Remarks-by-the-President-on-the-American-Graduation-Initiative-in-Warren-MI/

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As with much of the literature on higher education policy, our conceptual starting point is

the Bennett hypothesis. Named for former US Secretary of Education William J. Bennett

(1987), the Bennett hypothesis holds that colleges appropriate much, if not all, of any increase in

federal student aid through increases in tuition. While the subsequent evidence has not been kind

to the Bennett hypothesis, we believe it correctly raises the important question of whether the

misalignment of incentives among federal policy makers and other actors within the higher

education sector may distort or even undermine the intended effects of federal education policy.

Our approach expands on the original hypothesis in several significant respects. First, rather

than focusing exclusively on federal student aid and tuition rates, we consider a range of federal

policy instruments, including federal operating funds, federal capital grants and federal student

aid, and a range of responsive variables, including list and effective tuition rates, total

enrollment, state and local appropriations, and institutional aid. This approach allows us to

address differences in the effects of key federal policy instruments.

Second, in keeping with recent results that highlight the role of politics in setting tuition

rates at public institutions of higher education, we take state governments, which include but are

not limited to college administrators, as the primary decision makers in the community college

system. This distinction matters because state governments are likely to respond to a broader

range of economic and political incentives than college administrators alone would do.

Moreover, because they influence several dimensions of community college finances, state

governments have a wider range of options in deciding how to respond to changes in federal

education policy. For example, if an increase in federal operating funds increases the demand

for a community college education, state governments could respond by raising tuition rates,

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appropriate these funds for other uses by reducing the level of state operating funds, or shift

resources from the operating budget to other areas of community college finance.2

To better understand these relationships, we develop and estimate a model of community

college funding. In the model, state governments choose tuition rates and state funding levels to

maximize perceived net social benefits of community college spending, which depend on

community college enrollment, quality, and costs, taking as given the levels of federal policy

variables and the demand for community college education. The model produces a system of

reduced form equations describing how state governments and potential students respond to

changes in federal education policy. These equations serve as the basis for our empirical model

and forecast of the effects of AGI and an alternative policy proposal.

We estimate this system of equations using a fixed effects model and panel data from

2003 to 2008. Our results indicate that there is little or no recapture of federal operating grants

and student aid by state governments, either through tuition increases or decreases in state

funding. Most, though not all, of the federal funds devoted to community college education

reach the students they are intended reach. More generally, it does not appear that state

governments act systematically to undermine the intended effects of federal education policy.

However, our forecasts indicate that the policies embodied in the AGI will have only a

limited effect on their intended target, with community college enrollment rising by less than one

per cent. Our estimates indicate that increases in student aid are much more effective in

increasing community college enrollment. Designing an Federal education policy requires

allocating funds between funding and aid; giving funding increases educational quality but

increases enrollments only slightly, while giving student aid does more to improve access to

2 Federal operating funds are generally subject to state and local matching requirements. However, the degree to which matching is fungible is an open empirical question.

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education but dilutes its quality. President Obama’s parallel proposals to increase Pell grant

funding (which flows to four-year colleges as well as community colleges) thus helps

complement the effects of AGI by making it possible for more students to take advantage of the

resources that AGI provides to community colleges.

Section 2: Literature Review

In addressing the impact of federal education policy on community college outcomes, this paper

fills a substantial gap in the research on the economics of community colleges. Much of the

existing literature on community colleges has been concerned with estimating the private and

social returns to enrolling in a community college and the impact of community college

attendance on an individual’s subsequent educational decisions.3

In contrast, there is a large literature on the impact of federal education policy on other

segments of the higher education sector. Rizzo and Ehrenberg (2003) review the literature on the

Bennett hypothesis, finding that estimates of the impact of federal aid on public tuition level

ranges from negligible to as much as 50% of the increase in aid. However, much of this

evidence is from cross-sectional analyses and may be subject to biases from college- or state-

A sizeable literature is

concerned with the impact of state policy on community college outcomes, highlighting the

sensitivity of enrollment to the level of community college tuition, (see Kane and Rouse, 1999,

for a review). However, we are unaware of any studies that explicitly address the issue we

examine here: how state higher education policies and community college outcomes respond to

changes in federal education policy.

3 See Kane and Rouse (1999) for a recent review of the literature on community colleges, and Grubb (2002) for a review of the literature on the labor market return to community college.

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specific omitted variables. In their own analysis, Rizzo and Ehrenberg (2003) find no evidence

that in-state or out-of-state tuition rates respond to changes in the level of state need-based aid, to

changes in the level of federal Pell grants, or to changes in state-level merit based aid.

Singell and Stone (2007) find that increases in federal student aid increase tuition at

private colleges. For public universities, however, the results are more mixed. Increases in

federal aid are associated with increases in out-of-state tuition rates, but in-state tuition rates are

unaffected. In-state tuition at public universities out-of-state tuition at public colleges was not

affected. As noted above, this difference in outcomes for in-state and out-of-state tuition rates

suggests that tuition rates at public universities may respond primarily to political rather than

economic incentives.

Long (2004) examines the response of different segments of the higher education sector

to increases in state-level student aid through Georgia’s HOPE Scholarships. Like Singell and

Stone, Long finds that the response differed across private and public colleges. Private colleges

saw significant increases in tuition rates and decreases in institutional aid relative to a regional

control group. In contrast, at public universities tuition rates actually fell, but fees for room and

board rose sufficiently to capture 10% of the increase in student aid due to the HOPE

scholarships. The difference in the response of tuition rates and student fees at public

universities reported by Long suggests that it is important to consider the preferences and

incentives of different actors in the community college system. While state level officials

preferred a low tuition rate, to expand enrollments, local actors increased fees in an effort to

appropriate some of the increase in state-level student aid.

A number of these papers also address the role of state appropriations. Theory suggests

the potential for two effects. On the supply side, an increase state appropriations provide an

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alternative source of college financing, allowing a reduction in tuition rates and an increase in

enrollments. On the demand side, they may also increase demand for higher education by

increasing the actual or perceived college program quality. Both Rizzo and Ehrenberg (2003)

and Singell and Stone (2007) find that state appropriations reduce in-state tuition at public

universities. In addition, Singell and Stone (2007) find that state appropriations increase out-of-

state tuition at public universities, an outcome consistent with the quality effect discussed above.

Berger and Kostal (2002) estimate a simultaneous equations model of educational supply and

demand, and find evidence of both the supply and demand effects of state appropriations. Of the

studies that consider the impact of state appropriations on education outcomes, only a few treat

state appropriations as endogenous. Koshal and Koshal (2000) estimate a system of equations in

which both tuition and state appropriations are endogenous, and Long (2004) treats state

appropriations as endogenous, but she considers how they respond to changes in another state-

level policy variable, the introduction of Georgia’s HOPE scholarships. Of the studies that treat

state appropriations as endogenous, neither considers, as we do here, how state appropriations

respond to changes in federal policy variables.

Finally, a number of studies address the policy challenges implicit in the highly cyclical

nature of community college enrollments and state support. For example, Betts and McFarland

(1995) find that a 1% increase in the unemployment rate increases community college

enrollment by 4.5%. Similarly, Dellas and Sakellaris (2003) find that an increase in the

unemployment rate significantly increases the probability that a high school graduate enrolls in a

two-year or four-year public college, and that the increase in the probability of enrollment is

particularly large for two-year colleges. They also find evidence for the importance of other

cyclical variables in enrollment decisions, including the change in income and the level of real

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interest rates. These studies motivate our use of state unemployment rates and income levels to

control for local business cycle effects, as well as the use of period effects to control for changes

in national level variables like vary with the business cycle, such as the real interest rate, the

price level and expected inflation.

Section 3: Model

In order to measure the response of states and colleges to increased federal aid and funding, and

to predict the effects of the AGI on community colleges, we develop a simple model of

community college resource allocation. The model focuses on the interactions of three sets of

agents, federal policy makers, state education officials, and local residents, who are potential

community college enrollees.4

4 We treat college officials and other state officials as making a joint decision about state policies, making no attempt to model college administrators as agents with an independent set of objective that are distinct from those of other state officials. The clearest evidence of the divergence of state officials and school administrators comes from Long’s (2003) analysis of the impact of Georgia’s HOPE scholarships. In particular, Long finds that while tuition rates, which are set by state officials, do not rise at public universities, fees for room and board rise sufficiently to allow public universities to capture around 20% of the increase in state student aid. However, as community colleges are not residential, this effect is not relevant to our analysis. In general, it is not clear that community college administrators have sufficient financial independence to merit separate treatment in the model; we regard them as one of several actors in the state government’s decisionmaking process, which we do not explicitly model

Federal educational policies are assumed to be exogenous to the

condition of any given community college or state. The preferences of local residents are

represented by an education demand function that depends on educational quality and

affordability. State officials take the education demand function and federal policies as given,

and choose levels of state policy variables to maximize the net benefits of community college

education. . The model produces a set of reduced form equations that describe how state

officials and local residents respond to federal policies to determine a variety of community

college outcomes including funding levels, enrollments and tuition and aid variables.

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The demand for enrollment in a community college depends on the tuition rates charged

and quality of education. Since both the state and the college offer aid and other financial

assistance to students, not all students pay the same tuition. We include in the model both the list

tuition (ListTuit) which is the price paid by full-time students not receiving any kind of financial

aid, and average tuition revenue per student (AvgTuit), which represents the price paid by the

average student. We expect an increase in either of these variables to reduce enrollments. Let

demand be given by

Enroll = E(ListTuit, AvgTuit, FedAid, SIAid, Quality, X) (1)

where Enroll is demand for enrollments, and FedAid and SIAid are federal and state/institutional

student aid respectively5

Quality is the quality of education the community college provides. There is evidence of

significant differences in the quality of community college programs as indicated by their impact

on subsequent wages, e.g. Grubb (2002). While program quality is not directly observed,

perceived quality appears to be positively related to state funding levels. For example, Berger

and Kostal (2002) find that, holding tuition constant, enrollment demand is increasing in the

level of state funding. We assume quality is dependent on the amount of per-student funding:

. Holding list tuition constant, a decrease in average tuition corresponds

to greater price discrimination by community colleges.

Quality = Q(FedFunds, SLFunds) (2)

5 Note that in institutional aid does not equal the difference between list and average tuition, and in general exceeds it. As a matter of practice, much of student aid goes to cover living expenses, and are thus paid for services that are not provided by community colleges.

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where FedFunds and SLFunds represent federal and state/local funding per student, respectively,

for the community college.

X is a vector of additional variables that affect enrollment demand. We include the state

unemployment rate, which matters because it affects the opportunity cost of time spent on

education, and household income, which matters for affordability when educational loan markets

are imperfect. Betts and McFarland (1995) and Dellas and Sakellaris (2003) find that

community college enrollment are highly dependent on the unemployment rate. This is not

surprising given that Kane and Rouse (1999) report that on average wages forgone account for

over 85% of the opportunity cost of college. Enrollment demand will also depend on proxies for

the expected return to a community college education, such as the local skill premium. We

assume that all students who wish to enroll may do so, since virtually all community colleges

have open enrollment and do not select a subset of applicants for admission.

The cost of producing community college education depends positively on the level of

enrollment, the quality of the education, and a vector Z of variables corresponding to local input

prices and other variables affecting the cost of providing education:

Cost = C(Enroll, Quality, Z). (3)

Some of the costs are paid by tuition revenues, which are necessarily equal to average tuition per

student times the number of enrollments. Federal funds pay for a portion of the remaining costs,

and the state and college must fund the balance. The budget constraint is then

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SLFunds = C(Enroll, Quality, Z) - AvgTuit*Enroll – FedFunds (4)

State and college officials collectively choose a level of average tuition, educational

quality, aid, and funding that maximize their perceived net benefits from community college

education, which is increasing in enrollment and quality, and decreasing in the level of state

funding, which have a shadow cost since these could be put to other public purposes if not used

for community college education. Let the perceived benefits of community college, in dollar

value terms, be given by

Benefits = B(Enroll, Quality) (5)

and let the shadow cost of one dollar of state funds be S(W). The function S(W) indicates that

the shadow cost of funds depends on a vector of variables, such as household income levels, the

unemployment rate and political preferences, e.g. Koshal and Koshal (2000). The maximization

problem that state and college officials solve is to choose tuition, quality, and state/local

spending to maximize benefits net of the opportunity cost of funds:

B(Enroll, Quality) – S(W) * [StateFunds + StateCapFunds] (6)

Rather than model this choice structurally, we write the reduced form solution of this

optimization problem with each of the endogenous variables (except quality, which we do not

measure) on the left-hand side of its own equation, and all exogenously given variables on the

right-hand side. Because our data do not separate capital funding by source, we treat all capital

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spending as one variable, CapFunds, which is endogenous because the state/local component of

it is endogenous, and thus appears on the left-hand side of one equation. The reduced form

equations are:

Enroll = fE(FedAid, FedFunds, X, Z, S) (7a)

ListTuit = fTL(FedAid, FedFunds, X, Z, S) (7b)

AvgTuit = fTA(FedAid, FedFunds, X, Z, S) (7c)

SIAid = fA(FedAid, FedFunds, X, Z, S) (7d)

SLOpFunds = fF(FedAid, FedFunds, X, Z, S) (7e)

CapFunds = fF(FedAid, FedFunds, X, Z, S) (7f)

This model enables us to predict the reaction of states and community colleges to changes

in federal policy such as the AGI, or to changes in demand for community college education or

the cost of providing it. For example, the Bennett hypothesis is that a one-dollar increase in

federal aid produces a one-dollar increase in average tuition per student (and implicitly, has no

effect on state aid or state funding for education), and is easily tested in our framework.

Similarly, the model can predict the effects of federal funding changes, such as those in the AGI,

on enrollments, tuition (list and effective) and state and institutional finances.

By considering the role of state policy makers, the model highlights the simultaneous

determination of tuition rates, institutional aid, and state funding. In doing so, model serves to

guide our empirical specification in several ways that distinguish it from previous work in this

area. First, not only does the model suggest that there are a variety of policy instruments through

which state officials might try to appropriate increases in federal aid or federal operating or

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capital grants. An increase in federal student aid or funding may result in increased tuition (the

Bennett hypothesis) or decreases in state funding or institutional student aid. If we were to

disregard the additional instruments that state officials have under their control, we might miss

evidence that states act to appropriate funds made available under federal education policy, and

thereby blunt their impact. Second, by focusing on the role of state officials, the model provides

guidance as to which variables should be treated as endogenous. For example, our model

suggests that because state funding is endogenous, it should not be included as an independent

variable in regressions involving tuition at public universities, and that doing so may produce

estimates that are not asymptotically consistent.

Section 4: Data and Estimation

We estimate the model in (7) using a panel data set containing all community colleges in the

United States for academic years 2002/03 through 2007/08. Community college data are from

the Integrated Postsecondary Education Data System (IPEDS) from the National Center for

Education Statistics. These are augmented with state level data on income and unemployment

from the Statistical Abstract of the United States, Census Bureau. Both income and

unemployment are those of the state in which the community college is located, so they have

both cross-section and time variation. We excluded any college reporting that it did not charge

tuition, and to exclude certain outlying observations, any college reporting operating spending of

more than $50,000 per student. Our empirical results are not sensitive to reasonable changes in

these criteria for inclusion in the sample.

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Our measure of enrollment is the natural log of the total number of students enrolled at

the college. Using the natural log of enrollments allows us to interpret changes in exogenous

variables as causing percentage changes in enrollments, whose absolute impact can then vary

proportionately with the size of the college. Where the raw data is provided at the college level,

e.g. tuition revenues, we convert college-level data to per-student measures. In doing so, we

divide by the previous year’s enrollment level to avoid simultaneity problems arising from the

endogeneity of the contemporaneous enrollment level; this is appropriate if state and federal

policy makers refer to current enrollment levels in choosing policy targets for the following year.

The means and standard deviations of all variables are found in Table 1.

To estimate equation (7) we include fixed effects and year effects in the regressions in

order to capture variation that is constant across markets or over time. Since capital funds

probably have delayed effects on demand and quality, we include both one-year and two-year

lags of that variable as right-hand side variables. We also include lagged Federal operating funds

since some funds may be to develop programs that take time to start up (as is the case with some

of the AGI funding). The six estimated equations, one for each of the six endogenous variables,

are of the form:

Yit = β0 + β1*FedAidit + β2*FedFundsit + β3*FedFundsit-1 + β4*CapFundsit + (8)

β5*CapFundsit-1 + β6*HHIncomeit + β7*Unempit + δi + νt + εit

where i subscripts colleges, t subscripts time periods, δi represents college-level fixed effects,

and νt represents year effects.

Period fixed effects capture annual variation macroeconomic conditions that impact the

endogenous variables, such as the real interest rate (Dellas and Sakellaris, 2003). College-level

fixed effects are included to capture time-invariant aspects of local conditions that affect the

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educational cost and demand functions, including local wage and input prices, the return to

community college education, and the opportunity cost of enrollment, e.g. Betts and McFarland

(1995), as well as political and economic variables that affect the shadow cost of state funds, e.g.

Koshal and Koshal (2000). 6

Equations (8a-8f) are somewhat difficult to estimate because state and institutional

student aid and federal student aid are systematically correlated with one another; the two have

similar criteria for awarding aid, so the amount of Federal aid per student will be positively

related to the error in equation (8). Following the approach taken by Singell and Stone (2007),

we estimate the equations by instrumental variables, using Federal aid from the previous two

years as instruments for the current year’s Federal aid.

State-level measures of household income and unemployment are

included to capture time-variation in state conditions that affect cost and demand for education

and the shadow cost of state funds that are not captured by college and year fixed effects.

Table 2 shows the results of the estimation. An increase in federal student aid appears to

increase education demand while simultaneously changing the composition of the student body.

In particular, we find that an increase in Federal aid has a positive and significant increase on

enrollments; an increase of $100 in Federal aid per student causes an increase of 0.86% in

enrollment. This corresponds to an increase of 51.6 students at a community college of 6000

students (roughly the average size) or around 51,600 students nationwide. An increase in federal

student aid has disparate effects on the two tuition variables, increasing list tuition while

reducing average tuition. We interpret these outcomes as evidence of a shift in the composition

6 We have also estimated regressions that exclude the fixed effects and year effects, and include variables which have only cross-section or only time variance; among these variables are ethnic composition of the population, percentage urban, percent with a bachelor’s degree, national unemployment rate, wage premium for a bachelor’s degree over an associate degree, and wage premium for an associate degree over a high school diploma only. However, we do not present these results, as these models can be statistically rejected when tested against the models with fixed college and period effects. There is a great deal of unobserved variation across colleges, which distorts the results when fixed effects are not used.

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of education demand, with federal aid affecting enrollment decisions on two margins. First, it

attracts relatively poor students, who would otherwise not have enrolled, but because it increases

the affordability of attending a four-year college, it simultaneously reduces community college

enrollment among relatively well-off students. The combined effect of these changes is to

reduce the average income of community college students, which provides community colleges

with an incentive to engage in greater price discrimination. If an increase in federal student aid

also increases the share of enrolled students who apply for aid, the availability of information on

aid applications may also increase the ability of community colleges to effectively discriminate.

Our results imply that the effect on both tuition variables is relatively large: a $100

increase in federal student aid results in a $21 increase in list tuition, accompanied by $34

decrease in average tuition revenues. Federal student aid is not significant in the remaining

regressions, which measure the response of state policy variables, including the level of state and

institutional aid, state operating funds and capital funds. Thus, our results provide no evidence

that state policy makers attempt to appropriate increases in federal student aid.

Our results also suggest that an increase in federal operating funds increases education

demand, with enrollments rising both contemporaneously and in the following year. With

current and lagged coefficients taken together, our estimates suggest that a permanent $100

increase in Federal operating funds increases enrollment by .46%, which is a bit more than half

the enrollment impact of an equivalent increase in federal student aid. This suggests that if one

goal of policy is to increase enrollment at community colleges, increasing student aid is a more

cost-effective way to achieve it than is increasing Federal funds for community colleges. An

increase in Federal operating funding does not increase list tuition, though it does increase

average tuition per student by 7.3 cents per dollar of Federal funds. This suggests that students

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perceive higher Federal funding as resulting in greater education quality, for which students are

willing to pay somewhat more money in tuition. Colleges capture this willingness to pay without

significantly increasing list tuition.

Our results provide disparate results regarding the impact of federal operating funds on

the level of state and local funding. A $100 increase in federal operating funds increases state

and local funding by $95 in the same year, followed by a decrease of $20 the following year,

although this second effect is only significant at the 90% level. These results are consistent with

rules that require states to match increases in federal funds, and state attempts to recapture some

of these additional funds the following year. However, our evidence suggests that matching

rules are largely effective, with a permanent $100 increase in federal operating funds generating

a net increase of $75 in state funding levels. The crowding-in of state funds would amplify the

quality improvement and its resulting effect on tuition. It would also explain a rise in effective

tuition, if states need additional revenues to help pay for the higher costs per student. Lagged

Federal funds also increase capital funds; this may occur if, after using Federal funds to expand a

program, colleges must then increase capital funding per student to support the expansion.

Capital funding, lagged one and two years, has very little effect on operations. It does

raises average tuition revenues, by 2.5 cents per dollar with a one-year lag and another 1.6 cents

per dollar with a two-year lag, suggesting that students believe capital funds increase the quality

of education and hence the amount that students are willing to pay for it. As with Federal

operating funding, capital funding affects average tuition revenues but does not significantly

affect list tuition. Capital funding in the past also affects capital funding in the present, with

coefficients of -0.28 for the one-year lag and -0.32 for the two-year lag. This is consistent with

the discrete nature of capital spending; a college that does a large capital expenditure in one year

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is less likely to do another one in the following year or two. It is also consistent with the idea that

state governments that receive Federal capital grants recapture some of the funds by decreasing

their own capital spending in future years. Capital funding has no effect on enrollment, state and

institutional student aid, or state and local operating funding.

Both the household income level and the unemployment rate affect education and policy

decisions through multiple channels. A rise in the household income level may reduce financial

constraints on community college enrollment, but it may simultaneously increase the

attractiveness of attending a four-year school, and thus lower the demand for community college

education. In addition, states with higher incomes can raise more tax revenue and thus have a

lower shadow cost of state funds for education. Higher income levels may also indicate a rise in

the skill premium, increasing the return to both community and four-year colleges. Our results

suggest several of these effects are present, with a rise in income levels increasing demand, as

evident in the higher average tuition levels, and greater state and institutional student aid, which

is consistent with a lower opportunity cost of state funds, though both of these are more than

offset by the decrease in state operating funds.

By lowering the opportunity cost of attending college, an increase in the state

unemployment rate increases education demand and, holding average household income

constant, indicates an increase in income disparities among potential students. Our results

capture both of these effects. The increase in education demand is seen in the increase in

enrollment levels and list tuition. The increase in income disparity is seen in the evidence of

greater price discrimination: rising list tuition combined with falling average tuition, a pattern

previously identified in the coefficients on federal student aid. Not surprisingly, a rise in

unemployment also dramatically increases the level of state and institutional student aid.

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On the whole, our results are consistent with the model presented in the previous section.

Potential students are shown to respond to changes in federal student aid, unemployment and

perceived educational quality in predictable ways. In particular, all three exogenous policy

variables, federal student aid, federal operating funds and lagged capital funds, appear to increase

education demand, resulting in increases in enrollments or one of the two tuition variables. In

addition, evidence from changes in federal student aid and unemployment suggests that the

extent to which community colleges engage in price discrimination, as seen in the gap between

list and average tuition, is responsive to broader economic conditions.

From a policy perspective, our results provide at most very limited evidence in support of

an expanded Bennett hypothesis. That is, state and college officials do not appear to appropriate

increases in federal student aid or federal funds. Indeed, while increases in federal student aid

increase list tuition significantly, average tuition rates actually fall, and there is no evidence that

state officials respond to increased federal student aid by decreasing state aid or state and local

operational funding. Moreover, while an increase in federal funds results in a moderate increase

in average tuition this is more than offset by the net increase, over two years, in the level of state

funding. However, we do find some evidence of a moderate Bennett effect with respect to

capital funds, with average tuition rates rising by 4% of the increase in capital spending. Finally,

if increases in federal funds and capital funds result in greater educational quality, the additional

human capital students receive may partially offset, or more than offset, the higher cost of

receiving it.

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Section 5: Predicting the Effects of the American Graduation Initiative

The American Graduation Initiative will dramatically increase the amount of money available to

community colleges. It offers an increase of $9.5 billion over ten years in operating funds to

design new workforce training programs, improve completion rates, and reduce achievement

gaps; as well as an increase of $10 billion in capital funding to construct new facilities at

community colleges and renovate existing ones. However, state governments will respond to

these increases in Federal funding by changing their own policies, and the effects of the AGI on

community college outcomes will depend on those responses as well as on the additional Federal

funds available. In this section, we use our regression results to estimate the net effect that

President Obama’s proposals would have on enrollments, tuition rates, and state funding for

community colleges.

In order to do this, we must convert the proposed amounts of spending into per-student

terms. This task is complicated by the endogeneity of enrollments; an increase in the total

amount of Federal funding available will increase enrollments, so the ceterus paribus resulting

level of Federal funding per student is less than the increase in total funds divided by the existing

number of students. Since the regression results show how much enrollments will increase when

Federal funding rises, we can calculate the effective increase in per-student spending caused by a

fixed dollar increase in spending.7 Including this effect, an increase in Federal operating funds of

$9.5 billion over ten years implies an annual increase of $140 per student. 8

7 Similarly, an increase in Federal funding that increases enrollments will slightly reduce Federal aid per student, and conversely; our simulations also include these effects.

Similarly, an

8 Since, as discussed in the previous section,the enrollment increases from additional Federal funds are relatively small, the difference between these results and those that would be obtained without making the correction are also small. Simulations that do not make this correction, and assume that per-student spending rises in the same proportion as total spending, lead to the same substantive conclusions as the ones we report.

21

increase of $10 billion in capital funding over the same ten years implies an annual increase of

$165 per student. Table 3 shows the effects on the six endogenous variables of the AGI’s

increase in Federal operating and capital funds.9 Our calculations treat all insignificant

parameters as equal to zero, an approach that avoids attributing large effects to insignificant

variables.10

The calculations suggest that the AGI is relatively ineffective in raising enrollments,

which rise by only 0.58% in the long run. Given a population of 6.55 million community college

students, this represents an increase of about 38,000 students, at a cost of about $58,000 per

additional student. However, AGI has a second effect, which is to substantially increase funding

per student. In addition to the increase of $140 per student of Federal operating funds, it induces

a $105 increase in the level of state and local operating funds. Even though some of the Federal

capital funding is recaptured over time, equilibrium capital spending rises by $89 per student as

well. Under the interpretation that higher spending per student increases educational quality, AGI

produces a fairly substantial increase in educational quality. AGI would also increase average

tuition by $20 per student, as students are willing to pay a higher tuition to receive a higher

Because of the lag of Federal funding and the two-year lag of capital funding, the

full effects of AGI are not felt until the third year of the program; the table shows the effects in

the first two years as well as the effects of the third and subsequent years. Our discussion focuses

on the long-run, that is, third and subsequent years, impacts.

9 These calculations assume that states provide the $7.5 billion in matching funds that AGI requires them to provide, and that states do not reduce other capital expenditures on community colleges to provide the matching funds. Because our data do not distinguish between Federal and state/local capital funding, we are unable to test whether states do reduce other capital expenditures. Thus, our estimates should be taken as upper-bound estimates of the effects of AGI. Since our other findings suggest that other types of recapture are rather limited, the assumption that recapture is limited here also is perhaps not unwarranted. 10 We have also performed simulations using all point estimates, significant or not. They differ somewhat from the results reported here, but do not change the substantive conclusions of the paper. Since the simulations using point estimates with large standard errors are less reliable, we do not include them here; they are available from the authors on request.

22

quality education. Neither list tuition nor state and institutional aid per student will be

significantly affected by AGI.

If the intended goal of the AGI is to increase enrollments, it might be better to spend the

money on increased student aid, since the regression results show that a dollar of aid has a much

larger effect on enrollments than a dollar of operating funds does. To illustrate this point, we also

simulate the effect of a $19.5 billion dollar increase in student aid, with the results shown in the

second panel of Table 3. Spending the money on student aid produces an increase in enrollments

that is roughly triple the size of the increase AGI produces. The increase of 1.84% in enrollments

is equal to approximately 120,500 students, at a cost of only $16,200 per student. The increase in

student aid also results in an increase in the disparity of tuition rates paid by students, with list

tuition risings by $48 while average tuition falls by $79. These results probably reflect a shift in

the income profile of students and increase in price discrimination on the part of community

colleges. The large decrease in average tuition corresponds to a significant increase in access to a

community college education. Because per student levels of capital and operating funds are

unaffected by the increase in federal student aid, however, the fall in tuition revenues

corresponds to an overall drop in the level of funds per student available to community colleges,

and thus to a fall in educational quality. Thus, with an increase in federal student aid, the

resulting increase in enrollments and access is purchased by a decrease in educational quality.

Taken together, these simulations suggest that the choice between giving money as

student aid and given it as funding to colleges is a tradeoff between quality and quantity. Giving

operating funds to the colleges will increase enrollments – quantity – only slightly, but will

increase per student funding – quality. Giving aid to students has a much larger effect on

quantity of students, but damages quality. By adjusting the mix of operating funds and student

23

aid in actual Federal spending, policy makers can trade off greater access for higher quality

education, and vice-versa. Our results do not show what the optimal tradeoff is, since we do not

consider the returns (private or social) to such education, but they do show that the tradeoff

exists. Since AGI offers a relatively low increase in enrollments, it could be effectively

complemented by increases in student aid that would help increase enrollments and make higher-

quality education more affordability.11

The simulations also show that, contrary to the extended

Bennett hypothesis, increases in Federal aid and funding for community colleges are not fully

captured by the state and local governments, but are in large part passed on to students, either in

the form of greater access or better education or both.

Section 6: Conclusions

The effects of Federal education programs, such as the American Graduation Initiative, depend

on the manner in which state governments and individual colleges respond to them. If states or

colleges alter their behavior in an attempt to appropriate federal funds, then this may partly or

fully offset the intended effects of the these policies. In this paper we construct a model of state

and college response to changes in Federal aid and funding, test whether Federal aid and funding

increases are recaptured by states, and predict the effects of AGI on enrollments, tuition, and

spending at American community colleges.

We find little evidence of recapture of Federal resources by states and colleges. Contrary

to the expectations of the Bennett hypothesis, increases in Federal student aid to community

11 At about the same time that President Obama proposed AGI, he also proposed a major increase in the Pell grant student aid program. Because Pell grants can be used at four-year colleges as well as community colleges, it is difficult to determine how much of any Pell grant increase would end up as increased Federal aid to community college students. Hence we do not include this proposal in our simulations.

24

college students actually result in an decrease in average tuition revenue, while leaving the level

of state and institutional aid unchanged. Similarly, over two years, increases in Federal operating

funds for community colleges produce a net increase in state and local funding at the rate of 75

cents on the dollar. Although our data does not allow us to distinguish between Federal and state

capital spending, we do find that increases in total capital spending result in lower capital

spending in future years, which may reflect either the lumpy nature of capital investments or

intertemporal attempts to recapture federal capital grants after matching requirements are

relaxed.

We use our regression results to evaluate the effects of AGI on educational outcomes at

community colleges. We find that, after a transition period while lagged effects take hold, the

long-run effect of AGI is to substantially increase state spending on community colleges as well

as Federal spending, both capital and operating, and thus raises educational quality. Enrollments

rise by relatively small amounts; about 38,000 students per year, or 380,000 students over ten

years.. Spending the same amount of money on Federal student aid would produce a larger

increase in enrollments – about 120,000 students per year – and increase access, but it would

reduce per-student spending and hence reduce quality. There is a tradeoff between increasing

enrollments and increasing quality when dividing Federal spending between student aid and

direct funding of colleges. A policy that would achieve the President’s stated goals should

contain a combination of funding programs like AGI and increases in student aid, to increase

both enrollments and the quality of education students receive.

25

References

Bennett, William J. (1987) “Our Greedy Colleges,” New York Times, Feb. 18, A31. Berger, Mark C., and Thomas Kostal. (2002).Financial Resources, Regulation, and

Enrollment in US Public Higher Education. Economics of Education Review, 21, 101-110. Betts, Julian R., and Laurel L. McFarland. (1995). Safe Port in a Storm: The Impact

Of Labor Market Conditions on Community College Enrollments. Journal of Human Resources, 30, 741-765.

Dellas, Harris, and Plutarchos Sakellaris. (2003). On the Cyclicality of Schooling:

Theory and Evidence. Oxford Economic Papers 55,148-172. Grubb, W. Norton (2002) “Learning and Earning in the Middle, part 1: National Studies of pre-

Baccalaureate Education,” Economics of Education Review 21, 299-321. Kane, Thomas J., and Cecilia Elena Rouse (1999). The Community College:

Educating Students at the Margin Between College and Work. Journal of Economic Perspectives 13, 63-84.

Koshal, Rajindar K., & Koshal, Manjulika. (2000). State Appropriation and Higher

Education: What is the Relationship? Education Economics, 8, 81-89. Long, Bridget Terry. (2004). How do Financial Aid Policies Affect Colleges? The

Institutional Impact of the Georgia Hope Scholarship. The Journal of Human Resources, 39, 1045-1066.

Obama, Barack. (2009, July 14). American Graduation Initiative. Warren, Michigan. Rizzo, Michael J. and Ronald G. Ehrenberg (2003) “Resident and Non-Resident Tuition and

Enrollment at Flagship State Universities,” NBER Working Paper # 9516. Singell, Larry D., & Stone, Joe A. (2007). For Whom Pell Tolls: of University

Tuition to Federal Grants-in-Aid. Economics of Education Review, 26, 285-295.

26

Table 1. Means and standard deviations Variable Mean Std Dev Units TOTENROLL 6233 6071 Students TUIT $2,425.93 $1,433.08 Dollars EFFTUIT $1,312.58 $858.77 Dollars per student SIAID $2,395.75 $972.31 Dollars per student SLFUNDSCAP $5,354.46 $3,541.02 Dollars per student CAPFUNDSCAP $393.20 $898.07 Dollars per student FEDAID $2,767.12 $579.45 Dollars per student FEDFUNDSCAP $1,381.57 $1,672.53 Dollars per student UNEMP 4.969373 0.951917 Percentage points INCOME $47,161.81 $6,866.25 Dollars

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Table 2

IV regression results with fixed and period effects Independent Variable Dependent Variable

Log(Enroll) List Tuition

Average Tuition S/I Aid S/L Funds Cap Funds

FEDAID 0.000086 0.211609 -0.336346 0.091880 0.219471 -0.236634 0.000032 0.099731 0.100919 0.203308 0.596246 0.318819 FEDFUNDSCAP 0.000027 0.024316 0.073052 0.028878 0.952019 -0.035331 0.000006 0.018948 0.019173 0.045092 0.113279 0.060571 FEDFUNDSCAP(-1) 0.000019 0.011263 0.010035 -0.054843 -0.205594 0.166295 0.000006 0.019631 0.019864 0.046989 0.117362 0.062755 UNEMP 0.023880 36.09017 -39.06493 110.09390 92.04446 15.71071 0.005751 17.58626 17.79570 42.05979 105.1397 56.2194 INCOME 0.000001 0.001646 0.012622 0.017520 -0.069264 0.023107 0.000001 0.003529 0.003571 0.008438 0.0211 0.011283 CAPFUNDSCAP(-1) 0.000001 -0.004943 0.024692 -0.010230 -0.015751 -0.280311 0.000003 0.007722 0.007814 0.020074 0.046167 0.024686 CAPFUNDSCAP(-2) 0.000004 -0.003191 0.015587 0.005097 0.028422 -0.321266 0.000003 0.007894 0.007988 0.021798 0.047193 0.025235 C 7.846208 1465.3403 1680.3100 835.9590 6778.871 -89.96327 0.119251 368.7190 373.1102 781.0747 2204.393 1178.714 Mean of DV 8.296729 2338.13 1303.595 2417.966 5562.042 417.2427 Bold coefficients significant at 5% level; italics at 10%

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Table 3. Simulation results

Effects of AGI Year 1 Year 2 Year 3 and later Enrollment 0.31% 0.58% 0.58% List Tuition -1.69 -1.69 -1.69 Average tuition 12.92 16.99 19.56 State/inst aid 0.00 0.00 0.00 State/local funds 133.28 104.50 104.50 Capital funds 165.00 142.03 89.02

Effects of equivalent spending on aid Year 1 Year 2 Year 3 and later Enrollment 1.89% 1.84% 1.84% List Tuition 48.25 48.25 48.25 Average tuition -78.66 -78.86 -78.98 State/inst aid 0.00 0.00 0.00 State/local funds -25.70 -20.15 -20.15 Capital funds -8.00 -10.25 -7.68