Keeping it Simple: Impact of FAFSA Simplification on Federal and State Student Aid Eligibility SHEEO August 2011

Current Federal and State Issues Pell Grant program expenditures have doubled since Increases not sustainable Federal budget deficit threatens cuts in Pell Grant and other federal aid programs Student loan subsidies Campus-based aid Economic downturn has resulted in cuts in state funding to higher education and to need-based grants President Obama has set a goal for increasing college completion by 2020

Early Awareness and Simplicity An effective federal and state student aid system is key to meeting college completion goals The current student aid system is complex (process and programs) Low- and moderate-income students are more likely to prepare academically if they understand financial aid A simple, predictable, well-targeted student aid system will lead to more efficient use of taxpayer dollars College Board’s Rethinking Student Aid (RSA) recommendations are based on this premise

Simplification: Progress to Date HR 3221 passed but never considered by Senate Only data available from IRS used to determine federal aid eligibility; families with assets above legislated cap ineligible for federal aid Similar proposal in President Obama’s FY 2012 budget Administration committed to further FAFSA simplification

State Need-Based Aid Study Goals of study Help states understand impact of a simplified federal aid process on state grant programs Support institutions’ ability to plan for a simpler FAFSA Build state support for a simplified process to ensure that students will benefit Evidence about benefits of simplifying the application and increasing predictability of grant aid is compelling Help states advocate for a streamlined system that will enable them to distribute need-based aid equitably and efficiently May require changes to underlying Federal Methodology

Our Approach Selected a representative group of pilot states based on criteria for eligibility & aid determination Kentucky Minnesota Ohio Texas Vermont Using state’s or FAFSA and award data, simulated impact of potential federal data and formula changes on state grant awards

Our Methodology: Multiple Simulations 1. Remove Worksheet A items (new baseline for comparison) — previously eliminated in FM 2. Eliminate all assets 3. Eliminate untaxed income and income adjustments ( Worksheets B and C items) 4. Use only IRS data (similar to HR 3221 language) No employment allowance FICA based on AGI/total earnings IRS data included AGI, taxes paid, number of exemptions

Reviewing the Results Focus today on 2 states Minnesota (Shared Responsibility Model) Kentucky (EFC cut-off, first come/first-served) Ohio completed but results more complex Limited data make results difficult to compare to other states Vermont process very different from other 4 states Requires additional application form Considers asset data, noncustodial parent financial information Analysis of Texas data incomplete

Impact of Removing Assets on EFC Average EFCs decline for all applicants Largest declines among dependent applicants from highest income households (more likely to have significant assets) In MN dependent students from families with incomes > $75K would see average EFC decreases of $2,540 (10%); similar results in KY In MN dependent students from families with incomes between $45K and $60K would see average EFC decreases of $530; in KY average EFCs for this group decline by $636 Lowest income students (incomes below $30K) would see average declines in EFC < $200 in both states Small decreases in EFC for independent students Unlikely to have significant assets; little impact when assets removed

Impact of Removing Assets on State Grants and Pell Grants Minimal impact on average state grant in MN, OH, KY Targeted at students from low- and moderate-income backgrounds who are less likely to have significant assets MN: average grant would increase by $10 per applicant; total expenditures by $1M or.6% (Shared Responsibility model) KY: eligibility would increase on average by $27; total expenditures by $2.9 million or 3% (if program were fully funded) More significant increases to average Pell Grant in both states ($87 per filer in MN and KY)

Using Only IRS Data: Impact on Dependent Filers Average EFCs would decline for most applicants Largest impact among those from higher income families; more likely to have complex financial situations In MN, average decrease in EFC of $3,323 for FAFSA filers with family income > $75,000; $2,569 drop in KY In MN, average EFC declines by about $600 for filers with family income between $45K and $60K; by about $750 in KY In MN average decrease in EFC of about $300 for lowest-income (< $30K); similar pattern in KY Small impact on Pell Grants and state grants which are targeted at students from lower income backgrounds MN: Average Pell Grant per filer would increase by $23; average state grant would decrease by $6 KY: Average Pell Grant would increase by $47; average state grant eligibility would increase by $22 Institutional need would increase significantly, particularly at institutions that award need-based aid to higher income applicants

Using Only IRS Data: Impact on Independent Filers Independent students without dependents Average EFCs would decrease modestly: in MN by $323 on average, in KY by $46 on average Small increases in Pell and state grants for lowest income filers, but small decreases for those with higher incomes Independent students with dependents Average EFCs would increase for all but lowest income filers as a result of elimination of employment allowance In MN EFCs would increase by $70 on average; in KY average EFCs would increase by $15; slight EFC decreases for lowest- income filers in both states Small decreases in Pell and state grants as a result of EFC increases

Additional Modeling Activities White House Council of Economic Advisers (CEA) National ISIR sample Simulated impact of HR 3221 on Pell Grants Segmented results by state to support College Board study Small samples for most states Income distribution based on sample State tax allowance based on national average (2-3%) Simulated impact on EFC, PC and Pell for families with EFCs below $25,000

What We Learned from CEA Model National analysis using only IRS data Dependent students 61% change in Pell Grant < $250 36% increase > $250 Independent students 90% change in Pell Grant < $250

Average EFC Changes: Minnesota

Minimizing the Impact of Fewer Data Elements Make modest changes to the underlying need analysis formula Achieve EFC results closer to current level while simplifying the application for students Modeled impact of changing the adjusted available income assessment rates Parameters in current system are arbitrary and not based on economic research Increase marginal tax rates by 3% Modify Adjusted Available Income (AAI) bands Achieved EFC levels similar to those in effect in

FM AAI Assessment Rates Adjusted Available Income (AAI) Assessment Rate Applied to AAI Less than -$3,409 -$750 -$3,409 to $13,400 22% of AAI $13,401 to $16,800 $2, % of AAI over $13,400 $16,801 to $20,200 $3, % of AAI over $16,800 $20,201 to $23,700 $4, % of AAI over $20,200 $23,701 to $27,100 $5, % of AAI over $23,700 $27,101 or more $7, % of AAI over $27,100

Minimizing the Impact of Fewer Data Elements If only IRS data were used to determine federal aid eligibility, why couldn’t more detailed IRS data be provided to institutions and perhaps to states? Identify tax filers with negative AGI Impute assets based on interest and dividend income Create more effective need analysis system than exists today Model still under review, but opens up possibilities Would require support from Administration and perhaps legislation

Policy Considerations Given the evidence related to the effect of a simpler student aid system on increasing enrollment and graduation rates among low-income students, would states and institutions support a move to a system based only on IRS data? Would states and institutions be supportive of modifications to the federal need analysis system to reduce impact of less federal data? Would states and institutions support a proposal to develop a new need analysis formula that relied on more detailed IRS data?

We’re Interested in Hearing From You Sandy Baum Kathie Little