1

Postsecondary Performance Funding Plans

Cheyenne, WyomingFebruary 20, 2014

Matt Gianneschi, Ph.D.Vice President of Policy and ProgramsEducation Commission of the States

2

Patterns of U.S. High School and College Participation and Completion by Age

High School Participation

Undergraduate College Participation – Peaks at Age 19, Levels off at Age 30

Earn High School Diploma or Equivalent – Levels off at Age 21

Complete Undergraduate College Degree –

Peaks and Levels off at Age 31

0%

20%

40%

60%

80%

100%

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

AGENote: Includes associate and bachelor’s degrees, but not certificates.

Source: U.S. Census Bureau, 2005-07 American Community Survey (Public Use Microdata Sample); prepared by the National Center for Higher Education Management Systems

3

9.0

7.9

7.5

7.5

7.2

7.1

6.6

6.4

6.2

6.2

6.1

6.1

6.1

5.8

5.7

5.6

5.4

5.4

5.3

5.3

5.1

5.1

5.0

4.8

4.7

4.7

4.6

4.6

4.5

4.4

4.3

3.6

3.5

3.4

3.2

3.1

3.0

3.0

2.8

2.8

2.5

2.5

2.4

2.4

2.2

2.0

1.7

1.3

1.1

0.5

-0.6

-2

0

2

4

6

8

10

Nev

ada

Ala

ska

Loui

sian

aA

rkan

sas

Texa

sA

rizo

naTe

nnes

see

New

Mex

ico

Geo

rgia

Kent

ucky

Idah

oW

est

Vir

gini

aM

issi

ssip

piO

klah

oma

Ala

bam

aCa

lifor

nia

Del

awar

eSo

uth

Caro

lina

Flor

ida

Mai

neO

rego

nM

ichi

gan

Nor

th C

arol

ina

Ohi

oM

onta

naU

nite

d St

ates

Indi

ana

Wyo

min

gM

isso

uri

Wis

cons

inW

ashi

ngto

nM

aryl

and

Haw

aii

Penn

sylv

ania

Illin

ois

Colo

rado

Uta

hVe

rmon

tKa

nsas

Neb

rask

aV

irgi

nia

Rhod

e Is

land

New

Jers

eySo

uth

Dak

ota

Iow

aCo

nnec

ticu

tN

ew Y

ork

Min

neso

taN

ew H

amps

hire

Mas

sach

usett

sN

orth

Dak

ota

Data File Provided by Patrick Kelly (NCHEMS, 2010)

Additional Average Annual Degree Production Needed to Achieve Lumina’s Goal (60%)

4

9.1

7.7

7.2

7.1

7.0

6.8

6.7

6.6

6.6

6.6

6.2

6.0

6.0

6.0

5.7

5.7

5.6

5.6

5.5

5.4

5.2

5.1

5.1

5.1

5.0

5.0

4.8

4.8

4.7

4.6

4.6

4.5

4.5

4.5

4.5

4.5

4.4

4.4

4.3

4.2

4.0

3.8

3.6

3.4

3.3

3.2

3.2

3.2

3.1

2.7

0.5

0

1

2

3

4

5

6

7

8

9

10

Iow

aN

ew Y

ork

Virg

inia

Sout

h Da

kota

Mai

neW

est V

irgin

iaPe

nnsy

lvan

iaKe

ntuc

kyN

orth

Dak

ota

Mis

sour

iVe

rmon

tM

assa

chus

etts

Illin

ois

Arka

nsas

Indi

ana

New

Jers

eyM

inne

sota

Mar

ylan

dM

onta

naKa

nsas

Ohi

oLo

uisi

ana

Uni

ted

Stat

esCa

lifor

nia

Mis

siss

ippi

Nev

ada

Okl

ahom

aU

tah

Ore

gon

Sout

h Ca

rolin

aId

aho

Texa

sFl

orid

aAr

izon

aRh

ode

Isla

ndN

orth

Car

olin

aTe

nnes

see

New

Ham

pshi

reAl

abam

aW

isco

nsin

Was

hing

ton

Neb

rask

aCo

nnec

ticut

Mic

higa

nH

awai

iAl

aska

Wyo

min

gCo

lora

doN

ew M

exic

oG

eorg

iaDe

law

are

Sources: U.S. Census Bureau, Decennial Census and American Community Survey; prepared by the National Center for Higher Education Management Systems (2013)

Change in College Attainment from 2000 to 2011 by State – 25- to 34-year-olds

5

Examples of State-level Performance Funding Plans

• Tennessee• Complete College Tennessee Act of 2010• 100% Outcomes-based funding for HIED• Performance is built into initial allocation formula• Formula is weighted according to pre-determined outcomes priorities

• Oregon• Creation of the Oregon Education Investment Board• Alignment of all systems to accomplish the state’s 40/40/20 goal.• Funding to institutions is allocated through performance “compacts”• Each board—K-12 districts, community colleges, and universities—negotiates a compact with the OEIB.

• Colorado• Performance contracts for each separate governing board, based on role and mission• Performance is self-referencing (institutions “compete” against their own current productivity)• The state identified priority goals—completion, student support, underserved populations, and fiscal

prudence—and the campuses selected their own metrics aligned with the state goals.

6

Suggestions for Measuring and Monitoring Performance

1. Focus on Annual, Achievable, Incremental Change Rather than Benchmarks 2. Measure Change Within Institutions (rather than performance against others)

3. To the Extent Possible, Focus on Activities Institutions Can Influence

4. Maintain Short List of High Priority Goals

5. Ensure That Metrics Are Not in Conflict With One Another

6. Use Existing Data Whenever Practicable

7. Consider “Smoothing” the Effect of Year-over-year Changes (i.e., 3-year averaging)

Suggestions for Developing Effective Performance Metrics

7

• Productivity (degrees/FTE enrollment)– Instead of “graduation rates”

• Credit Hour/Threshold Completion (15/30/60)– Instead of retention

• Gateway Course Completion (English, math, history, biology, etc.)– Instead of passing remedial courses

• Expenditures (by institution) or Costs (to students) per Degree– Rather than tuition rates

• Consider Alternative Measures of Completion, Such as Successful “Transfer-out” and Dual Enrollment Course Completions.

• Credit Hours at Completion– Rather than “time” to degree.

Options for Performance Metrics That Are Sensitive to Campus Differences

8

Tennessee Metrics (2014-15)

9

Example of Productivity Option

Statewide 2009 2010 2011

Degrees 30,557 32,913 35,431

FTE 133,729.40 147,416.60 154,560.00Degrees per 100 Students 22.85 22.33 22.92*Excludes Private IHEs

Example of Productivity Metric

10

Does it Work?• Evidence of programmatic efficacy is just now emerging, but consider:

– Kentucky (fastest growth in degree attainment in SREB)– Tennessee – dramatic innovations in remedial education and course redesign– Colorado – Overhaul of financial aid policy to align with state priorities

• Probably not useful to look at historical trends, as the conditions were very different.

• Consider the “criticality” and magnitude of performance funding.

• Theory of the Firm (foundation of micoeconomics)– Firms employ factors of production (producers)– Operate in markets (and markets are dynamic)– Firms are assumed to make consistent decisions relative to the market and internal

operations– Are profit maximizers (always seek to maximize marginal utility)

Does it Work?

11

Theories That Help Explain Higher Education

• Revenue Theory of Expenditures– Howard Bowen (1980)– Colleges are “prestige maximizers” and will find infinite uses

of revenue– Expenditures are determined by revenues, not markets

• Resource Dependency Theory (J. Pfeffer)– Organizations are dependent on certain sources of revenues. – These “buyers” influence decisions made within

organizations, including structure and products.– “He who pays the piper calls the tune”

Theories that Help Explain Higher Education

12

For More Information

ECS Postsecondary and Workforce Development Institute:

Dr. Matt Gianneschi: mgianneschi@ecs.org

Education Commission of the States700 Broadway, Suite 810Denver, Colorado 80203

(303) 299-3624www.ecs.orgecs@ecs.org