For-Profit Higher Education Responsiveness to Price Shocks:
An Investigation of Changes in the Post 9-11 GI Bill Allowed Maximum Tuitions
Matthew Baird, Michael S. Kofoed, Trey Miller, and Jennie Wenger
RAND and United States Military Academy
BACKGROUND/RESEARCH QUESTIONS
Service members and For-Profit Colleges
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Previous to the 2011 policy change, there was variation across states regarding how much could be reimbursed.
Thus the the policy change caused variation in the change in benefit to a veteran in a given state.
In 2008, Congress passed the Post 9/11 Veterans Educational Assistance Act (PGIB) that expanded tuition
benefits beyond those provided by the Montgomery GI Bill. New benefits included increased tuition
reimbursements, eliminated buy in requirements, and allowed veterans to transfer benefits to a spouse or
dependents.
Policymakers are concerned about how veterans use their benefits and how institutions respond to
increases/decreases in the maximum tuition rates set by PGIB.
Former Secretary of Education William J. Bennett first proposed that increases in student financial aid may give
incentives for institutions to increase their “sticker price” tuition levels to capture this aid. One concern is that
for-profit universities may be changing their sticker prices to take advantage of increased PGIB aid.
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RESULTS: BY POLICY DIRECTION
CHANGES IN THE POST 9/11 GI BILL REIMBURSEMENT (CONT.)
VARIABLES
First Max
Pos × Diff × Post2011
Observations
R-squared
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Exogenous variation allows us to examine how the direction and magnitude of a change in financial aid benefits
affects pricing of for-profit universities.
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Research Question:
Do exogenous changes in the maximum GI Bill reimbursement benefit
affect the “sticker price” tuition at for-profit universities?
PREVIOUS LITERATURE
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Financial Aid as a form of Price Discrimination
Turner (2014) uses a regression kink identification and finds that colleges respond to increases in Pell Grants by
lowering institutional merit aid and thus increasing the price of college that students actually pay (a form of price
discrimination).
Cellini and Goldin (2012) compare for-profit colleges that are eligible for federal financial aid to those institutions
that are just below the eligibility cutoff. The authors find that for-profit universities that are eligible for federal
funds have higher sticker price tuition as compared to those colleges not eligible for programs like subsidized
student loans or Pell Grants.
Cellini (2010) finds that the number of for-profit institutions that opened in a given county increased when certain
aid programs such as Pell Grants, Cal Grants, and GI Bill were also increased in California.
Long (2004) examines changes in Georgia college and universities given the introduction of the HOPE scholarship
and finds that four year institutions did increase tuition pricing after the introduction of HOPE.
The Effects of the PGIB on Veteran Outcomes
Barr (2015) shows that the PGIB increased college enrollment of veterans by fifteen to twenty percent and
increased the number of veterans enrolled at (relatively expensive) four year institutions.
Barr (2016) shows that increased state, merit aid programs reduce military enlistments thus showing an interesting
trade-off between college enrollment and military enlistments.
TIMELINE OF POLICY CHANGE
Figure: Timeline for Changes in PGIB
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yjst = β1diffst + β2post2011 + β3(diffst × post2011) + φ1Xjst + jst
(2)
where diff is the difference between the state-specific maximum tuition rate and the post 2011 national amount.
Other variables in equation (2) are similar to equation (1).
We also want to account for differences in behavior between institutions in states that received a positive change in
aid to states that saw PGIB decreased. To ensure that the results in equations (1) and (2) are not driven by
institutions decreasing tuition in response to less aid, we estimate the following model:
Positive × Post 2011 621.537 *
(377.40)
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CHANGES IN THE POST 9/11 GI BILL REIMBURSEMENT
State & Year FEs
Exog Vars
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The unique policy change created a situation where some states saw a dramatic increase or decrease in the
maximum aid that the VA would reimburse.
Figure: States by Increase or Decrease in Aid
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SE Cluster Level
Observations
R-squared
Diff
No
405.164
(358.67)
508.305
(336.61)
508.305*
(269.46)
Yes
Yes
Yes
No
No
Yes
Yes
State
11,201
0.005
State
11,201
0.159
State
11,201
0.171
Institution
11,201
0.171
(1)
(2)
(3)
Tuition Tuition
Tuition
-0.027 -0.035*** -0.030***
(0.022) (0.002)
(0.007)
(4)
Tuition
-0.030
(0.019)
(3)
-147.683 974.696*** 1129.58*** 1129.58***
(195.83) (250.09) (310.21) (235.75)
Diff × Post 2011
0.016*
(0.009)
0.093
(0.007)
0.012*
(0.006)
0.012*
(0.007)
State & Year FEs
No
Yes
Yes
Yes
Exog Vars
No
No
Yes
Yes
State
11201
0.006
State
11201
0.159
State
11201
0.171
Institution
11201
0.171
SE Cluster Level
Observations
R-squared
-0.013 -0.105
(0.027) (0.079)
0.002 -0.019
(0.048) (0.118)
1,154
0.197
Diff × Post 2011
0.012*
(0.006)
0.034***
(0.009)
0.012**
(0.006)
State & Year FEs
Yes
Yes
Yes
Yes
Yes
11,201
1,848
0.171
0.345
Standard Errors Clustered by State
Yes
9,353
0.202
Check to see how the number of veterans in a state influences price discrimination:
(1)
All
First Max
-0.020*
(0.010)
-0.007
(0.010)
0.000
(0.009)
0.007
(0.012)
Diff
Diff × Post2011
Neg × Diff × Post2011
Pos × Diff × Post2011
Neg × Diff × Post2011 × Above Median
Pos × Diff × Post2011 × Above Median
Observations
R-squared
(2)
All
(3)
4 Year
(4)
(5)
2 Year <2 Year
-0.015 0.000 -0.058*** 0.052
(0.011) (0.013) (0.021) (0.034)
-0.006 -0.007 -0.010
0.031
(0.010) (0.014) (0.013) (0.023)
-0.005 -0.008
0.013
-0.012
(0.010) (0.011) (0.022) (0.062)
-0.003
(0.015)
0.054
(0.033)
0.009
(0.0207)
0.012
(0.036)
-0.001
(0.015)
0.104**
(0.047)
0.021
(0.0225)
-0.044
(0.044)
11,481 11,481 5,604
0.138 0.138
0.079
Standard Errors Clustered by State
-0.042***
(0.010)
-0.010
(0.052)
0.066***
(0.0217)
0.022
(0.055)
0.127
(0.174)
0.013
(0.133)
-0.300*
(0.171)
0.046
(0.053)
4,723
0.078
1,154
0.234
CONCLUSION
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Post 2011
0.009
(0.013)
0.055*
(0.029)
0.715**
(0.300)
VARIABLES
(1)
(2)
(3)
(4)
Tuition
Tuition
Tuition
Tuition
-963.307 -3407.69*** -2098.60*** -2098.60 **
(651.62)
(134.34)
(458.15)
(919.41)
755.068***
(282.10)
0.006
(0.014)
0.041
(0.027)
2.263***
(0.239)
First Max × (2008-2011)
755.068*
(383.56)
0.060
(0.039)
0.027
(0.023)
0.034
(0.087)
1.130***
(0.310)
Exog Vars
Observations
R-squared
RESULTS:FOR-PROFIT
-608.783** 673.799*
(289.39)
(375.43)
-0.045**
(0.022)
-0.013
(0.013)
0.003
(0.025)
(1)
(2)
(3)
Full Sample Above Max Benefit Below Max Benefit
-0.030***
-0.183***
-0.008***
(0.002724)
(0.003614)
(0.002773)
Post 2011
Where FirstMaxst is the total maximum reimbursement before the 2011 policy change in a given state in year t.
In this model, our coefficients of interest are β5 and β6 which represent heterogeneous treatment effects for a
positive or negative change in the PGIB benefit.
Post 2011
0.009
(0.015)
-0.008
(0.015)
-0.007
(0.010)
11,481 11,481 5,604 4,723
0.128
0.128 0.070 0.067
Standard Errors Clustered by State
Diff
yjst = β1positivest + β2post2011 + β3(positivest × post2011) + φ1Xjst + jst
(1)
Where yjst is the “sticker price” tuition rate, positivest is whether veterans in state s experienced a positive
increase in the PGIB, post2011 is a dummy for whether the rate was set after the policy change in 2011, and Xjst
includes a host of institution characteristics along with year and state fixed effects. In our empirical model, β3 is
the coefficient of interest since it represents the change in tuition rates in states with an increase in benefit after
the policy change.
To calculate the “pass through” of the increased financial aid to the for-profit college via increased tuition, we
estimate the following model:
Positive Increase
-0.005
(0.011)
-0.009
(0.010)
-0.005
(0.010)
We check to see if results are robust by whether tuition was originally at or above the state’s maximum amount as
a proxy for already occurring price discrimination.
Using data from IPEDS, we study the effect of the change from a state specific maximum tuition reimbursement
to a federally uniform rate on the “sticker price” tuition at for-profit colleges, we estimate the following empirical
models:
yjst = β1FirstMaxst + β2Diff + β3FirstMax × Post2011 + β4(Diff × Post2011)
+ (β5Neg + β6Pos)(Diff × Post2011) + φ1Xjst + jst
(3)
(4)
(5)
4 Year 2 Year <2 Year
ROBUSTNESS CHECKS
EMPIRICAL MODELS
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(2)
All
-0.007
(0.011)
Diff
-0.009
(0.010)
First Max × (2008-2011) -0.002
(0.00853)
Diff × Post2011
0.015
(0.010)
Neg × Diff × Post2011
Figure: States by Increase or Decrease in Aid
One reason for this behavior is to comply with the “90-10” rule where a maximum of 90% of an institutions’ revenues can come from
Title IV funds. However, the Department of Education does not consider PGIB benefits as Title IV.
From 2008 to 2011, the PGIB reimbursed active duty service members and veterans attending private and
for-profit colleges the highest tuition charged for a program located at a public university in a given state. In 2010,
Congress amended the PGIB to switch these amounts to one federal maximum of $17,500. This policy change
creates exogenous variation in the amounts of aid received by veterans.
For profit colleges are of great concern to the Departments of Defense and Veteran Affairs. In fact, in the first year
of the Post 9-11 GI Bill, nearly 36.5 percent of all benefits were claimed by students at for-profit universities while
enrolling only 23.3 percent of PGIB beneficiaries (Health Education, Labor, and Pensions Committee, 2010, p. 4;
Deming et al. 2012).
(1)
All
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We find in states where the PGIB was increased that for-profit colleges increase “sticker price” tuition for all
students (not just veterans) by $508.31.
We also find that this magnitude creates as 1.2 percent. “pass through” for the GI Bill. However, at institutions
that were already charging the maximum reimbursement rate, this “pass through” increased to 3.4 percent.
Our results are driven by institutions that are located in states with a positive increase and institutions that offer
four year degree programs.
In states with high veteran populations, the “pass through” almost doubles to around ten percent.
Disclaimer
The views expressed herein are those of the authors and do not reflect the position
of the United States Military Academy, the Department of the Army,
or the Department of Defense.
[email protected]; [email protected]; [email protected]; [email protected]