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Policy Brief February 2013

www.wiscape.wisc.edu/publications/

Performance-Based Funding in Wisconsin By Bo McCready

Key Points 1. Performance-based funding (PBF) in higher education is an increasingly popular practice in the United States, although evidence on its success is mixed. 2. It is impossible to say which kinds of institutions would benefit and which would suffer under PBF. The ultimate effects of performance-based funding depend on how funding models are constructed and how postsecondary outcomes are prioritized. 3. Collaboration between policy makers and postsecondary leaders is likely to increase the success of PBF in Wisconsin, but developing a model that satisfies all stakeholders will be extremely difficult.

About the Author Bo McCready is a WISCAPE Affiliate and a former WISCAPE Project Assistant. He holds a master’s degree in public affairs and is a doctoral candidate in Educational Leadership & Policy Analysis at the University of Wisconsin– Madison. He currently works as a Data Researcher for the Madison Metropolitan School District.

Introduction Traditionally, public colleges and universities in the United States receive state public funding based on institutional needs and inputs, such as the number of students served. Performancebased funding (PBF), however, represents a shift from inputdriven to output-driven funding, tying state appropriations to institutional performance on measures such as retention, graduation rates, and degrees conferred. As of 2007, 26 states had implemented some form of PBF in postsecondary education, with more taking steps toward PBF since then (Harnisch, 2011). Wisconsin is among the states that have yet to implement PBF in postsecondary education in any form, although it [PBF] represents a shift is clear that PBF is on the political agenda and likely from input-driven to to appear in some form in the near future.

output-driven funding,

In general, PBF has tying state appropriations influenced only a small share of state to institutional appropriations for postsecondary education performance... (Midwestern Higher Education Compact, 2009), but PBF is now on the political agenda in many states, driven by state political actors including elected and appointed officials, legislators, business leaders, and governing boards. For example, Missouri Governor Jay Nixon argued for PBF in August 2011, and the Texas Coordinating Board of Higher Education is developing plans for PBF as well (Wieder, 2011). Indiana, which has used performance-based funding since 2008, plans to increase the share of university performance-based allocations over the next two years as part of a plan to increase degree


Policy Brief attainment (Smith 2012). In 2009, Ohio shifted postsecondary education funding to three PBF models with all allocations based on performance (Ohio Board of Regents, 2009a; 2009b; Ohio Board of Regents; Ohio Board of Regents, 2011). Illinois will phase in PBF in 2013 and a PBF plan also is on the table in Nevada (Blankenberger, 2011; Lake, 2012). Tennessee, the earliest adopter of performance-based funding, continues to increase the share of funding provided based on PBF. Given significant interest in PBF nationwide and the recent contentious debates around postsecondary education funding in Wisconsin, PBF is a pressing issue for the University of Wisconsin System and the Wisconsin Technical College System. To estimate how PBF might play out in Wisconsin, I developed five hypothetical PBF models and used input data from the 13 four-year universities of the UW System. Because of the complexity of the two-year college systems in Wisconsin, my models focus only on public four-year universities. One model allocates only a small share (5%) of funds via PBF and the other four allocate all funds via PBF. I then discuss the implications of these PBF models for public four-year postsecondary education institutions in Wisconsin and close with recommendations should PBF be implemented in the future.

The Origins and Evolution of Performance-Based Funding Jordan and Hackbart (1999) argue that the Hoover Commission of 1949, which focused on efficiency and improved service in government, laid the groundwork for performance-based funding initiatives; however, despite the inherent political appeal to many policymakers of providing funding based on performance to promote efficient spending, this practice did not gain much traction in government until the 1980s. Melkers and Willoughby (1998) found that, as of 1998, 47 of 50 states had some sort of performancebased funding for state government agencies—31 through legislation and 16 through other means. Of these 47 states, only one (Hawaii) had formal legislation before 1979. Wisconsin first considered performance funding allocations in government in 1993. The first statewide performancebased funding system in American postsecondary education began in Tennessee in 1979. Between 1997 and 2007, 26 states adopted PBF, but only 14 of these states still maintain PBF systems. Dougherty and Natow (2009) argue that PBF in postsecondary education usually is driven by state officials, legislators, governors, and business leaders focused on a market-oriented approach to institutional efficiency. They also argue that the practice has been both popular and unstable and that the demises of PBF in Illinois, Washington, and Florida

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Performance-Based Funding in Wisconsin

The Rationale for PerformanceBased Funding

exhibit important commonalities: sharp decreases in postsecondary education funding, a lack of postsecondary education institutional support for PBF, weak support from the business community, and the establishment of PBF through a budget proviso instead of a statute.

Performance-based funding is an appealing option as state funding for postsecondary education decreases and institutions face greater accountability pressures. Fingerhut, Kazis, and Altstadt argue that “performance-based funding holds out the promise of strong and clear incentives for change—without mandating specific changes that institutions should make to achieve desired outcomes” (Fingerhut, Kazis, and Altstadt, 2012). This is part of the appeal of PBF models: institutions know what outcomes matter but have the flexibility to develop their own context-specific plans to address adopted outcome metrics. Finding agreement between practitioners, administrators, and policymakers on which outcomes should matter, though, remains a central challenge.

Dougherty, Natow, and Vega (2012) revisited the end of PBF in Washington and Florida along with a new case in Missouri and reached similar conclusions. In addition, they argued that a change in administration or state political leadership can increase the likelihood of PBF cessation and that Tennessee’s PBF system remains successful in part because of institutional buy-in, ...there is limited which stems from the considerable input evidence that [PBF] they had in the PBF has been particularly design process.

successful or

Dougherty and Reddy (2011) unsuccessful. distinguish between two dominant forms of performance-based funding: 1.0 and 2.0. PBF 1.0 serves as a bonus added on top of regular state funding while PBF 2.0 is embedded within regular state funding formulas. States using PBF 2.0 include Ohio, which began in 2009, and Tennessee, which began in 2010 (Dougherty and Reddy, 2011).

Though PBF is an attractive option, there is limited evidence that it has been particularly successful or unsuccessful. Dougherty and Reddy (2011) argue that “claims that performance funding does indeed increase ultimate outcomes… are not validated by solid data.” In addition, they state that PBF 2.0 programs in particular have been understudied because much of the research focuses on programs following the PBF 1.0 approach. Their closing argument,

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Policy Brief though, is not that the absence of evidence should lead states to abandon PBF, but that policymakers should understand new forms of PBF and obstacles to its success that, once removed, could increase its effectiveness.

■■ Incentivizes institutions to align their actions and strategies with state goals and priorities. On the other hand, PBF has many potential disadvantages. PBF: ■■ Could discourage innovative practices, as institutions might be afraid to try something new when uncertain of what the effects will be,

Advantages and Disadvantages of PBF Evidence on the effects of PBF is limited. However, from a survey of the literature on PBF, a number of theoretical advantages emerge. PBF:

■■ Encourages institutions to change admissions and retention practices, as incentives to retain and graduate students could lead to decreased standards or unwillingness to admit certain types of students,

■■ Provides an opportunity to subject postsecondary educational institutions to meaningful accountability criteria,

■■ Increases financial uncertainty, because tying a substantial portion of funding to outcomes that are difficult to predict leads to greater difficulty in budgeting,

■■ Encourages greater transparency of institutional outcomes and brings these outcomes to the forefront of state and institutional budgetary debates,

■■ Is often unappealing to postsecondary institutions,

■■ Increases public trust in postsecondary education, as institutions will have to demonstrate results to justify the levels of taxpayer money they receive,

■■ Creates challenges because of the dificulty of collecting good data, and ■■ Simplifies diverse institutional missions into a series of prescribed models.

■■ Is popular among many policymakers, ■■ Motivates institutions to focus on outcomes rather than exclusively on inputs, and

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Performance-Based Funding in Wisconsin

The Current State of Postsecondary Education Funding in Wisconsin

inflation, salary increases, and program enhancement or quality improvement. This approach is common across state postsecondary education systems (Parmley et al., 2009). State GPR allocations fund many UW System functions, including operational expenses, student aid, extension outreach, and energy costs (University of Wisconsin System, 2010).

Wisconsin employs an incremental budgeting process, which means that each agency receiving state funding uses their existing budget level as the basis for the next budgetary request (Grosz, 2010). Elements of zero-base (or starting from scratch each year) and performance-based budgeting can be found in Wisconsin’s state agency budgets, but incremental budgeting remains the best descriptor of the overall process because most funds are distributed in this manner. The budget process is biennial, although most appropriations are annual and effective for only one fiscal year (Lang and Swain, 2011).

Methodology Given that currently available PBF formulas all include either missionfocused components or data that is not universally collected by UW System schools, applying Wisconsin-based data to an existing PBF formula is challenging. Therefore, to estimate how PBF might look in Wisconsin, I created several hypothetical formulas that reflect the PBF 2.0 approach of embedding PBF in regular funding formulas: one that allocates a small share of institutional funding based on PBF and another that allocates all state funding based on performance indicators. PBF 1.0 is, of course, a possibility in Wisconsin, but my aim is to illustrate how PBF could affect base levels of funding, not how “bonus� money could be distributed. Therefore, I use the PBF 2.0 approach instead of the PBF 1.0 approach.

State appropriations from general purpose revenue (GPR) constitute about 20% of the UW System budget. State GPR allocations for higher education grew at an annualized rate of 1.3% from 2000-2011, much lower than the annualized growth in tuition revenues (7.8%) and federal grants and contracts (11.2%) (Pope, 2011). Individual campuses do not submit their own budgets to the governor. Instead, the UW System submits an overall budgetary request, and UW System Administration determines allocations for each university once the overall allocation amount is identified (Pope, 2011). Important factors for changes in funding from year to year include shifting enrollment,

Performance-based funding is relevant to both four-year and twoyear public institutions; in fact, an

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Policy Brief April 2012 report from the 21stCentury Commission on the Future of Community Colleges calls for these institutions to move “from funding tied to enrollment to funding tied to enrollment, institutional performance, and student success” (21st-Century Commission on the Future of Community Colleges, 2012). But four- and two-year institutions have different missions and goals that call for differentiated PBF models. In this brief, I focus only on four-year models. Using IPEDS and UW System data, I created performance scores for each institution, with adjustments made to reflect available data and variables weighted to align with the unique missions of UW System schools. For example, I weighted research spending more heavily for researchdriven institutions and bachelor’s degree attainment more heavily for institutions with a greater focus on undergraduate instruction. I used the following variables for these models:

■■ Master’s degrees awarded ■■ Doctoral degrees awarded »» Graduate degree premium for underrepresented students ■■ Degrees per 100 FTE (weighted for underrepresented students) ■■ Six-year graduation rate ■■ Research spending Although I calculated performance scores and shares of funding for each institution, the purpose of this work was not to call out individual institutions based on their suitability for PBF or their relative performance within the System. Instead, my goal was to use these data to illuminate the kinds of issues that might emerge in a Wisconsin PBF system. Therefore, I refer to institutions in general terms and focus on broad implications instead of specific institutional impacts.  Set-aside Model

■■ Total credit attainment

For the first model, I assumed that 5% of state appropriations for the UW System will be set aside for performance-based allocations, which is equivalent to $40,994,064 for the 2011-12 year. I then allocate shares of this roughly $41 million set-aside based on the weighted performance scores calculated for each institution.

■■ Bachelor’s degrees awarded »» Bachelor’s degree premium for underrepresented students (defined for this hypothetical exercise as African American and Latino students. Each degree awarded to members of these groups counts double in these models.)

In percentage terms, no institution would see a significant change in

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Performance-Based Funding in Wisconsin

their state appropriations with a 5% set...varying weights aside model. No institution determine whether would receive increase [institutions] would gain an of more than 3.15%, and or lose funding. no institution would receive a decrease of more than 0.82%. Eight of 13 institutions would face GPR changes of less than 1%. In dollar terms, only three institutions’ appropriations would change by more than $500,000.

known PBF system in the United States. Weighting in other models reflects different emphases. Models 1, 2, and 4 have different weighting for each university based on institutional missions, while model 3 does not. Weighting in each model can be described as follows: ■■ Model 1: Baseline weights ■■ Model 2: Increased weight for graduation rate, decreased weight for graduate degrees ■■ Model 3: All institutions face the same weights with no adjustments for institutional mission ■■ Model 4: Increased weight for research expenditures, decreased weight for degrees per FTE

Comprehensive Reform Models For the rest of the models, I reallocate 100% of state appropriations for postsecondary education based on relative performance scores, again assigning hypothetical weights which vary between the models. For the 201112 year, 100% of state appropriations is equal to $819,881,287. To allocate funds, I calculate a total performance score for the UW System and distribute funds to each institution relative to their share of the overall performance score.

Under these models and the current funding model actually used in Wisconsin, the relative positions of institutions in their ranking of money received are remarkably consistent. However, examining the change in appropriations in terms of percentage changes and raw dollars leads to more dramatic results. Under these hypothetical models, institutions could gain as much as 63% of additional funding or lose as much as 42%. Only three of 13 institutions either gain or lose in all five models; for the other 10 institutions, varying weights determine whether they would gain or lose funding.

For each model, I weight variables differently to illustrate how shifting priorities can radically transform final results. Weighting in the first model is inspired by the weighting system used in Tennessee, the most widely

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Policy Brief Percent Change in Public Funding According to Performance-Based Models 5% Model

Comprehensive Model 1

Comprehensive Model 2

Comprehensive Model 3

Comprehensive Model 4

Comprehensive A

3.15%

63.01%

61.38%

59.28%

30.63%

Comprehensive B

2.19%

43.74%

46.80%

41.87%

18.24%

Comprehensive C

0.75%

14.97%

21.82%

17.50%

-3.75%

Comprehensive D

1.19%

23.75%

30.38%

26.41%

-4.30%

Comprehensive E

-0.11%

-2.14%

6.72%

8.45%

-42.36%

Comprehensive F

0.92%

18.38%

26.67%

22.38%

-2.34%

Comprehensive G

0.84%

16.79%

20.17%

17.51%

-9.24%

Comprehensive H

0.39%

7.78%

10.24%

6.31%

-11.88%

Comprehensive I

1.82%

36.44%

44.15%

41.02%

1.56%

Comprehensive J

0.36%

7.18%

10.38%

19.84%

-37.79%

Comprehensive K

1.88%

37.61%

48.99%

48.45%

-0.85%

Research A

-0.82%

-16.42%

-18.30%

-20.19%

5.52%

Research B

-0.10%

-1.99%

-8.67%

3.80%

-8.00%

Implications

funding despite succeeding across the board. But aside from UW–Madison, which paces the system in every variable I included, no institution uniformly outperforms the rest across the vector of outcomes included in the PBF model.

Based on this analysis, it is clear that immediate implementation of a comprehensive PBF system with no stop-loss component to limit maximum potential year-to-year changes in funding could result in significant changes for some UW System institutions. Although the variables driving gains and losses in appropriations vary slightly among institutions, it is clear that each institution that would face funding declines under this PBF model trails their peer institutions on at least one meaningful variable; no institution could expect to see decreased relative

The key point of this work is that the manner in which a PBF model is constructed determines which institutions do or not benefit. This point seems rather obvious, but it bears repeating. The five models mentioned in this brief are all driven by the same data and only differ in how they weight that data, but the resulting

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Performance-Based Funding in Wisconsin

funding for individual institutions varies by many millions of dollars. Therefore, it is impossible to say what the results of PBF in Wisconsin would be; everything depends on and follows from the model (including outcome variables and weights) and priorities.

which postsecondary outcomes should be prioritized that will truly impact the future of institutions under PBF models.

Each institution in the UW System has a distinct mission, history, and culture, so it is likely that each institution will advocate for an approach to PBF that protects its own interests, such as including variables or weights that reflect what they do best. Assuming that only a finite pool of money is available for funding Wisconsin’s public postsecondary institutions, any PBF model will have relative winners and losers. As a result, balancing the competing interests of diverse institutions would be a tremendous challenge for any group tasked with designing a PBF system.

It is clear from recent media coverage and legislative and gubernatorial attention that there is a renewed interest in PBF throughout American postsecondary education. Given recent interest in Wisconsin, the state’s policymakers and postsecondary education stakeholders must recognize that there is no one-size-fits-all approach to PBF. The models presented in this paper are just five of a nearly infinite number of possible approaches. They are intended not to demonstrate what would happen under PBF but to illustrate some possible outcomes and identify issues for further consideration. Based on my literature and data analysis, I offer several recommendations to help inform conversations about PBF in Wisconsin.

Conclusion and Recommendations

Although these models are hypothetical, they are research-based and use real performance data. I have shown that minor changes in variable weighting in models containing the same seven aggregate variables can have profound impacts on which institutions thrive and which do not. The decision to include or exclude variables could have even more profound effects. But what these effects are depends only partially on how institutions perform; instead, it is the decisions of policymakers as to

Confront the Challenge of Madison’s Unique Status Currently, UW–Madison receives approximately half of all state GPR appropriations given to the UW System. UW–Madison enrolls more students with higher entrance requirements, confers more degrees, and awards more credits than any other UW System institution. Research

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Policy Brief spending at UW–Madison is many times greater than the rest of the system combined. UW–Madison even leads the system in rate-based measures like graduation. Simply put, it is challenging to develop a PBF system that accounts for the preeminence of UW–Madison on a variety of variables while recognizing the vital role of other institutions. Allowing institutions to weight the variables that will determine their funding levels helps ensure that other institutions are not evaluated on the same standards as UW–Madison. But adding weights alone will not accomplish the delicate balancing act between rewarding UW–Madison for its unique contributions and treating the institution as part of a cohesive system. Instead, institutions and policymakers must engage in difficult conversations about how institutions with differentiated missions fit together in a centralized system, and whether PBF could be more effective if different institution types used different models entirely.

PBF models, some institutions lose money because of poor performance on certain variables. However, these institutions’ performance numbers might look relatively worse because they serve higher-risk populations. Encouraging access, retention, and completion for underrepresented students may be a goal for which a PBF 1.0 model is more appropriate than a PBF 2.0 model, as institutions could receive bonus funding for improving access. Similarly, institutions subject to PBF may hesitate to engage in new and unproven policies and practices because of uncertainty about how these ...the manner in practices will affect which a PBF model is PBF measures. On the one hand, constructed determines institutions might wait until there is which institutions do or a research basis for the decisions do not benefit. they make, which could be a positive development. On the other hand, this hesitation could discourage innovation and pioneering practices. Because PBF is ostensibly a way to encourage productivity, it is ironic that PBF systems could suppress creative solutions to productivity problems.

Don’t Punish Institutions For Taking Risks Given disparities in postsecondary attainment among students, any PBF model that discourages institutions from better serving underrepresented students is problematic. Wisconsin must identify targeted populations and ensure that PBF models reward institutions for progress made in serving these populations. In these

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Performance-Based Funding in Wisconsin

...minor changes in variable weighting‌ can have profound impacts on which institutions thrive and which do not.

Consider Whether Small PBF Allocations Can Change Institutional Behavior The 5% set-aside for PBF presented in this paper resulted in only modest changes to each institution’s allocations. Thus, it is worth considering whether designating only a small portion of state appropriations for PBF is enough to affect meaningful institutional change. Under the 5% set-aside model, the institution with biggest absolute change in funding saw a change of about $1.2 million. For every institution in the UW System, this amount of money is relatively small, especially as the percentage of institutional budgets coming from state appropriations continues to decline. Collaborate with UW System and its Institutions

A common cause for failure of PBF is a lack of institutional buy-in. Therefore, it is critical that if PBF discussions move forward, UW System and institutional officials participate in every stage of the PBF design process. In an era of declining state funding, PBF could be another way to reduce funds allocated to postsecondary institutions. The best way to avoid persistent dissatisfaction and delay in implementation from postsecondary educational institutions is to engage these institutions in a meaningful and authentic way rather than as a token part of the planning process. The UW System is diverse and complex and developing a model without direct institutional input to account for this complexity will only heighten the difficulties of this funding approach. However, gaining institutional buy-in will be more difficult than simply including institutions in ongoing discussions. As mentioned earlier, assuming the pool of money available for institutions remains relatively consistent, a PBF will have some institutions who gain and some who do not. Naturally, it is unlikely that any institution will support a model that results in a decline in state funding without additional benefits to offset that loss. If PBF funding comes in the form of bonus money on top of base allocations that are similar to previous allocations, then institutions have less reason to oppose the practice as they stand to lose nothing and potentially gain something. But in a system where some institutions will lose while others gain, achieving a consensus of institutional support will be extremely challenging.

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Policy Brief References 21st-Century Commission on the Future of Community Colleges. 2012. Reclaiming the american dream: Community colleges and the nation’s future. Washington, D.C.: American Association of Community Colleges. Blankenberger, Bob. Performance-based funding and higher education institutions in the state of illinois [PowerPoint slides]. 2011 [cited April 20 2012] Available from http://www.ibhe.state.il.us/PerformanceFunding/Materials/ PBFIAIRPresentation.pdf. Dougherty, K. J., and V. Reddy. 2011. The impacts of state performance funding systems on higher education institutions: Research literature review and policy recommendations. New York: Community College Research Center, 37. Dougherty, Kevin J., and Rebecca S. Natow. 2012. Popular but unstable: Explaining why state performance funding systems in the united states often do not persist. Teachers College Record 114: 1-41. ———. 2009. The demise of higher education performance funding systems in three states. New York: Community College Research Center, 41. Fingerhut, Eric, Richard Kazis, and David Altstadt. 2012. Tying funding to community college outcomes: Models, tools, and recommendations for states. Boston, MA: Jobs for the Future, . Grosz, Scott. 2010. State budget process. Madison, WI: Wisconsin Legislative Council. Harnisch, Thomas L. 2011. Performance-based funding: A re-emerging strategy in public higher education financing. Washington, D.C.: American Association of State Colleges and Universities, . Jordan, Meagan M., and Merl M. P. Hackbart. 1999. Performance budgeting and performance funding in the states: A status assessment. Public Budgeting & Finance 19 (1): 68-88. Lake, Richard. 2012. Legislators question higher education funding formula. Las Vegas Review-Journal, April 25, 2012. Lang, Bob, and Sandy Swain. 2011. State budget process. Madison, WI: Wisconsin Legislative Fiscal Bureau, 75. Melkers, Julia, and Katherine Willoughby. 1998. The state of the states: Performance based budgeting requirements in 47 out of 50. Public Administration Review 58 (1): 66-73. Midwestern Higher Education Compact. 2009. Completion-based funding for higher education. Minneapolis, MN: Midwestern Higher Education Compact, . Ohio Board of Regents. State share of instruction: Draft formula allocation. 2011 [cited April 20 21012]. Available from http://www.ohiohighered.org/sites/

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default/files/uploads/financial/ssi/FY12_13_SSI_Actual_FY11_Oct_31.pdf. ———. State share of instruction handbook: Community and technical colleges. 2009a [cited April 20 2012]. ———. State share of instruction handbook: University main campuses. 2009b [cited April 20 2012]. Available from http://regents.ohio.gov/financial/selected_ budget_detail/operating_budget_1011/handbook-university-main.pdf. ———. Performance-based funding for higher education. [cited April 20 2012]. Available from http://www.thekc.org/sites/default/files/FundingFormula%20 _092710.pdf. Parmley, Kelli, Allison Bell, Hans L’Orange, and Paul Lingenfelter. 2009. State budgeting for higher education in the united states. Boulder, CO: State Higher Education Executive Officers, . Pope, Emily. 2011. University of wisconsin system overview. Madison, WI: Wisconsin Legislative Fiscal Bureau, 35. Smith, Mitch. 2012. Doubling down on degrees. Inside Higher Ed, March 12, 2012. University of Wisconsin System. 2011-2012 appropriation structure. 2010 [cited April 19 2012]. Available from http://www.wisconsin.edu/budplan/techinst Section%203-Approp%20Structure_FY12.pdf. Wieder, Ben. 2011. States ask colleges to perform for money. Stateline, September 8, 2011.

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University of Wisconsin–Madison L139 Education Building 1000 Bascom Mall Madison, WI 53706-1326 Telephone: 608-265-6342 Fax: 608-262-4881 Email: wiscape-info@education.wisc.edu Website: www.wiscape.wisc.edu The Wisconsin Center for the Advancement of Postsecondary Education (WISCAPE) aims to inform and improve postsecondary education policy, research, and practice through the creation and exchange of knowledge. The production and dissemination of publications are a major part of this effort. Written by education scholars and practitioners, WISCAPE Policy Briefs are succinct analyses that provide policymakers, practitioners, and others with knowledge and recommendations based on the latest research and best practices in the field. Authors are solely responsible for publication content. The views, opinions, and perspectives expressed in WISCAPE publications are not necessarily those of the center’s staff, scholars, or affiliates, or of representatives of the University of Wisconsin–Madison. Credits Editing: WISCAPE Staff Layout: Rachel Nathanson External Reviewers: Nate Johnson and Todd Berry Send questions about WISCAPE publications to: Noel Radomski, Director, 608-265-6342, ntradoms@education.wisc.edu Recommended citation for this publication: McCready, Bo. (2013). Performance-Based Funding (WISCAPE Policy Brief). Madison, WI: University of Wisconsin– Madison, Wisconsin Center for the Advancement of Postsecondary Education (WISCAPE). Copyright © 2013 The Board of Regents of the University of Wisconsin System

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