SOLUTION: Ashford University Formal Political Sets beyond Organization Discussion Paper

The Journal of Higher Education, Volume 85, Number 6, November/December
2014, pp. 826-857 (Article)
DOI: 10.1353/jhe.2014.0031
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Nicholas W. Hillman
David A. Tandberg
Jacob P. K. Gross
Performance Funding in Higher
Education: Do Financial Incentives
Impact College Completions?
In 2000, the Pennsylvania State System of Higher Education introduced a performancebased funding model aimed at increasing degree productivity among the state’s public
colleges. This study examines how the new policy affected undergraduate degree completions. Using a difference-in-differences estimation strategy, results suggest the policy has
not systematically increased degree completions within the state. With limited evidence of
the policy’s effect, we conclude that this was an ineffective funding model in terms of its
ability to increase college completions. Although we find modest impacts when compared
against colleges in neighboring states, these impacts disappear when matched against
similar colleges from other states.
Keywords: accountability, policy, finance
States have traditionally based higher education appropriations on the
number of students enrolled in college. Under this input-oriented funding model, colleges can be rewarded for enrolling more students regardless of whether these students eventually earn degrees. Considering that
only half of all undergraduates attending public four-year colleges earn
their degrees within six years, strategies to improve college completion
has become a salient public policy concern in recent years (National
Student Clearinghouse, 2012). For example, several states now have
“college completion agendas” designed to increase educational attain-
Nicholas W. Hillman is Assistant Professor of Educational Leadership and Policy Analysis at University of Wisconsin-Madison; David A. Tandberg is
Assistant Professor of Educational Leadership and Policy Studies at Florida State University. Jacob P. K. Gross is Assistant Professor of Leadership, Foundations and Human
Resource Education at the University of Louisville.
The Journal of Higher Education, Vol. 85, No. 6 (November/December)
Copyright © 2014 by The Ohio State University
Performance Funding   827
ment in order to meet workforce development needs (Zumeta, Breneman, Callan, & Finney, 2012). Similarly, the federal government’s
American Graduation Initiative called for millions of additional college
graduates by 2020 in order for the U.S. to regain its position as a global
leader in educational attainment levels (Brandon, 2009). This context
has renewed states’ interest in increasing college completions as many
have recently turned to performance-based funding as a solution for
achieving this policy goal.
Performance-based funding changes the traditional way states subsidize public higher education. Under this funding model, public colleges receive state appropriations according to how well they are meeting broader educational goals such as college completions and degree
production. The underlying theory of action draws from the “new accountability” movement, where pay-for-performance is expected to increase educational outputs (Burke, 2002; Heinrich, 2002). Accordingly,
by rewarding colleges for the number of degrees produced rather than
by the number of students enrolled, this funding model should provide
an incentive for colleges to graduate more students. This funding reform
is not new to higher education; Tennessee adopted the nation’s first of
such programs in 1979 and in the mid-1990s several other states followed suit by developing their own versions of performance funding.
Currently, 11 states operate performance-based funding (PBF) programs
where they allocate a portion of state appropriations to public four-year
colleges and universities according to the number of baccalaureate degrees awarded each year. Some states build PBF into the base appropriations budget, while others set aside appropriations in a separate fund
to serve as a financial bonus beyond the base budget appropriations. In
each case, more degree completions are associated with higher levels
of public funding, which may be an incentive for colleges to graduate
more students.
These “new accountability” policy efforts scrutinize the outcomes
of public higher education and prioritize efforts to increase the performance of colleges and universities (McLendon, Hearn, & Deaton,
2006). Although the number of students enrolling in college has steadily
risen over the past two decades, college completion rates have remained
relatively flat (DeAngelo, Franke, Hurtado, Pryor, & Tran, 2012; U.S.
Department of Education, 2012). Proponents of PBF argue that traditional state funding models are inefficient and unresponsive to students
and taxpayers needs because they do not provide strong enough incentives for colleges to improve these outcomes (Jones, 2012). While PBF
proponents may have a compelling theoretical argument, past research
on the topic has found only weak relationships between PBF and im-
828   The Journal of Higher Education
proved institutional performance (Dougherty & Reddy, 2011; Sanford
& Hunter, 2011; Shin, 2010; Volkwein & Tandberg, 2008). As a result,
PBF has its fair share of critics who argue that the model is a management fad that offers campuses perverse incentives to reduce academic
quality in lieu of increasing the quantity of degrees awarded (Rhoades,
2012; Schmidtlein, 1999). Nevertheless, PBF is a popular policy instrument for many states, and it is gaining renewed attention in light of national college completion goals and the backing of such groups as Complete College America, the Bill and Melinda Gates Foundation, National
Governor’s Association, and the Lumina Foundation for Higher Education (Crawford, 2011; Hall & Thomas, 2012).
Despite the renewed popularity of PBF for higher education, little is
known about the extent to which these policies actually impact college
completions. Part of this research gap is due to implementation challenges at the state level, where several states adopted but later discontinued PBF models. For example, South Carolina first began its performance funding model in 1996, but by 2004 the state had discontinued
the program. An even less stable example is Colorado where performance funding was introduced in 1994, but discontinued in 1997 only to
be readopted it again in 2000. Seven other states share similar fates with
South Carolina and Colorado, beginning but later endingperformance
funding policies. This instability makes it difficult to assess program
impacts, so researchers suggest studying states that have sustained performance funding for several years without discontinuity in their operations (Doyle & Noland, 2006). Another reason to study the experiences
of individual states is because national analyses might overlook unique
differences occurring within individual performance funding state. Recent national studies find performance funding states do not outperform
other states in terms of degree completions (Tandberg & Hillman, 2013;
Tandberg, Hillman, & Barakat, 2013).
The current case study of Pennsylvania complements this body of research. Of the 11 states that currently operate PBF, Pennsylvania stands
out as having one of the most stable and longest-operating programs,
making it a unique case to study since it provides ample years to examine the pre/post impacts of this natural experiment. As two leaders
within the PASSHE system (one former and the other current) argued:
“Because it is one of the oldest continuous models in the United States,
it has longitudinal outcomes data and hence constitutes a useful proof
of concept” (Cavanaugh & Garland, 2012, p. 35). Given the research
gap on the impacts of performance funding, this study asks to what extent has performance-based funding impacted degree completions in
Performance Funding   829
Policy Context
States have long been interested in identifying strategies for improving accountability and productivity among public colleges and universities (Zumeta & Kinne, 2011). The pursuit of greater accountability
can be elusive when policymakers and campus leaders disagree on the
terms, strategies, and conditions for measuring success. Nevertheless,
states experiment by adopting new policy solutions in their pursuit towards changing the way colleges and universities respond to public
priorities. During the 1990s, the United States witnessed a shift in the
way states approached their governmental oversight and accountability responsibilities. States moved away from an approach that focused
on regulatory compliance and rudimentary reporting of inputs to one
that focused on measuring performance and accounting for outcomes
(Burke, 2002; McLendon, 2003; Volkwein & Tandberg, 2008). This new
approach has commonly been referred to as the reinventing government
movement (Fryar, 2011; Osborne & Gaebler, 1992; Rabovsky, 2012).
This approach to governmental oversight also included new approaches
to state governance and finance of higher education, which higher education scholars have termed as the “new accountability” movement in
public higher education (McLendon, Hearn, & Deaton, 2006; Toutkoushian & Danielson, 2002).
Consistent with the new accountability movement, an approach that
gradually grew in popularity was the development of state higher education performance funding programs. While Tennessee had a performance funding program in place since 1979, these programs did not
take hold nationally until the 1990s. McLendon et al (2006), note that
in 1985 only two states had such a policy, but by 2001 nearly half of all
states adopted (though did not necessarily maintain) performance funding systems. The United States witnessed a decline in the number of
these programs in the early 2000s, but a new wave of states have recently begun adopting PBF programs. Since 2007, eight states have adopted or significantly revised their performance funding programs and
several other states are actively working towards the development of
their own programs (Dougherty & Reddy, 2011; Rabovsky, 2012). Each
state implements their program differently, although one commonality
across them all is the priority of aligning institutional behaviors toward
state priorities. States do this by linking a portion of state funding “directly and tightly to the performance of public campuses on individual
indicators” (Burke & Minassians, 2001, p. 4). The amount of PBF an
institution receives is determined via the institution’s performance and
the specified weights for various performance factor values.
830   The Journal of Higher Education
currently operating performance funding (11)
discontinued performance funding
never adopted performance funding
Authors (under review)
F igure 1. Performance-based funding models for public four-year colleges and
universities. Source: Tandberg & Hillman (2014).
States adopt PBF programs for various reasons and scholars have
long been interested in understanding these policy antecedents. For example, states may adopt PBF for symbolic purposes to initiate a compliance or oversight mechanism without the intention of actually improving institutional outcomes (Burke, 2005; Zumeta & Kinne, 2011).
Alternatively, policymakers are more likely to initiate PBF programs
during times of increased financial resources and abandon them during
economic downturns (Dougherty, et al., 2011; Zumeta & Kinne, 2011).
Still others have found that PBF is motivated by politics, where higher
percentages of Republican legislators in a state and the absence of a
consolidated governing board increased the probability of a state adopting such a policy (McLendon, Hearn, & Deaton, 2006). In addition to
these considerations, such factors as demand for increased efficiency,
increased capacity of states to collect detailed data from colleges and
universities, a disillusionment with previous higher education accountability mechanisms, and the level opposition leveled by colleges and
Performance Funding   831
universities can also impact the likelihood that a state will adopt a
PBF program (Alexander, 2000; Burke, 2002; Dougherty, et al., 2011;
Rhoades & Sporn, 2002; Ruppert, 1995; Zumeta, 2001).
To understand the origins and design features of the Pennsylvania
performance funding model, we offer a brief overview of the state’s
higher education policy context. The Pennsylvania State System of
Higher Education (PASSHE) was first established in 1983 to govern 13
Carnegie master’s institutions and one Carnegie doctoral/research institution in the state. In 2000, PASSHE implemented a broad-based PBF
program for each of the universities within its system. This was the system’s primary policy strategy for improving institutional outcomes and
there were no other significant state or system-level policy innovations
implemented around the time of the PASSHE PBF program. When financing colleges, state appropriations are delivered directly to the system office that, in turn, allocates to individual institutions using its own
internal processes. This governance structure provides PASSHE with
broad statutory authority over these institutions, particularly in terms
of setting institutional standards related to performance measures and
funding levels. Linking funding to performance measures was part of
the system’s broader new accountability movement, where campuses
were required to measure and report performance levels using 17 indicators, including: total number of degrees awarded, second-year persistence, graduation rates, faculty productivity (credit-hour production),
employee diversity, instructional cost, faculty with terminal degrees,
and personnel ratio (total personnel compensation as a fraction of total
expenditures). Under this model, PASSHE measured institutional outcomes according to baseline expectations, where institutions that perform better than expected received additional funding. 1
Funding for the PBF program was embedded in the system’s annual
appropriations process, where 8% of state appropriations were allocated
according to institutional performance. If an institution did not meet its
target for a specific outcome, then it received no performance-based
funding. But if an institution met or exceeded its target goals, then the
state allocated performance-based funding based on the number of institutions that fell into each outcome category. If more than one university achieved that outcome, the funds were divided across those institutions based on a formula weighted by institutional size. This meant
that the universities competed for the funds and that if more institutions
met their goals within a specific category there was less money to go
around. For example, if only one university exceeded the target goal in
a particular category, it received all the available funds for that category.
However, the institution could do even better in year two but receive
832   The Journal of Higher Education
less money if additional institutions met their targets in the second year
(Cavanaugh & Garland, 2012).
Under its accountability and performance-funding program the state
system saw improvements on a number of indicators, but the extent to
which PBF contributed to these increases is unclear. Additionally, it is
important to point out that some policymakers, and others interested in
institutional accountability, may believe student completions are not the
only (or most important) component of a PBF program and therefore
may argue that even if completions do not improve, the policy may still
be desirable because of alternative policy goals (e.g., increased oversight) (Zumeta & Kinne, 2011).
Conceptual Framework and Relevant Literature
To understand how public colleges might respond to state PBF policies, we first draw upon principal-agent literature and then we provide
an overview of the current research on the impacts of higher education
PBF on institutional performance. Based in economic theory, a principal will hire (or enter into a contract with) an agent who is expected
to work on the principal’s behalf. The agent must be willing to engage
in the contractual relationship with the principal, and both parties will
maximize their expected utility in this relationship (Stiglitz, 2008).
When one party has access to relevant information and the other does
not, information asymmetries occur that can strain this relationship.
This basic principal-agent relationship helps us understand how incentives can be developed to encourage the agent to act on behalf of the
interests of the principal. This relationship can be extended to public
policy contexts (Bergman & Lane, 1990), as we do in this study. It can
also guide us conceptually and analytically in a number of ways, discussed next.
Conceptually, the principal-agent relationship helps us consider why
colleges may—or may not—achieve PASSHE’s performance goals related to improving college completions. According to the framework,
a principal (e.g., PASSHE) enters into a contract with any number of
agents (e.g., colleges) who are responsible for working on behalf of the
principal’s agenda. In our study, the performance funding policy is the
contract between principal and agents, where PASSHE informs colleges on the system’s performance goals that, if met, will be rewarded
with money. In theory, this “pay for performance” strategy should help
PASSHE monitor colleges and universities, ensuring they do not shirk
on their performance responsibilities. In the absence of monitoring, colleges might be inclined to pursue their own self-interests of maximizing
Performance Funding   833
institutional reputation and prestige rather than achieving the system’s
performance goals (Brewer, Gates, & Goldman, 2002; Lane & Kivisto,
But in practice, there are several reasons why colleges may be unable to fulfill their performance responsibilities, even if they are not
“shirking” on these responsibilities. For example, colleges may not
have the information or financial resources necessary for implementing
best practices that could improve student success. They may be unclear
about PASSHE’s priorities if there are several competing performance
metrics that must be attended to. Similarly, external pressure to improve
campus performance can signal mistrust between principals and agents
(Weibel, Rost, & Osterloh, 2010). Campuses may be less responsive to
the state’s performance goals due to this mistrust that, in turn, can result
in unfulfilled performance goals (Fryar, 2011). As a result, some colleges may not achieve the policy goals if they do not have sufficient
capacity or if the incentives are insufficiently strong, clear, or appropriate (Dougherty, Jones, Lahr, Natow, Pheatt, & Reddy, 2013). Within this
basic principal-agent framework, we can conceptualize and anticipate
some of the challenges campuses and state policymakers face when implementing performance-based funding models, particularly with regard
to signaling effects, capacity constraints, and performance incentive designs. This framework also helps guide our analytical strategy and variable selection, where we want to identify whether the contract (i.e., the
performance funding policy) has resulted in greater institutional performance, conditional upon each campus’ enrollment profile and financial
capacity. If we find the policy has resulted in positive effects, then it
suggests the princi …
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