WHY DO U.S. STATES ADOPT PUBLIC-PRIVATE PARTNERSHIP
ENABLING LEGISLATION?
R. Richard Geddes
Department of Policy Analysis and Management
College of Human Ecology
Cornell University
251 Martha Van Rensselaer Hall
Ithaca, NY 14853
rrg24@cornell.edu
and
Benjamin L. Wagner
Department of Policy Analysis and Management
College of Human Ecology
Cornell University
122 Martha Van Rensselaer Hall
Ithaca, NY 14853
blw38@cornell.edu
December 9, 2010
ABSTRACT
Many U.S. states are facing severe budgetary shortfalls. At the same time, there is unprecedented
demand for transportation infrastructure construction and renovation. As a result, states are
increasingly turning to private firms for assistance with their transportation infrastructure needs.
Twenty-eight states have enacted legislation that would better enable them to utilize publicprivate partnerships (PPPs) to help finance the construction of new transportation infrastructure
and the renovation of existing infrastructure. Key elements of this legislation include provisions
regarding unsolicited proposals, prior legislative approval of contracts, and the mixing of public
and private funds. Using the basic elements of PPP enabling laws, we develop an index of the
“intensity” of PPP enabling legislation. We explore reasons why states pass such laws, and why
some states pass legislation that is relatively more enabling. We consider economic, fiscal, and
political drivers of passage. We find that political factors, fiscal conditions, and the passage of
similar laws by other states are key drivers of PPP law enactment. We find that, despite the
motivations stated in many acts, variables measuring motorist demand for new capacity have
little power to explain either the passage of PPP enabling laws or their intensity.
I. Introduction Three forces in the United States are conspiring to create severe transportation
infrastructure problems: increasing traffic demand; aging, deteriorating infrastructure; and
exhausted state transportation budgets. From 1957 to 2003, total vehicle miles traveled (VMT) in
the United States increased by 347 percent while total highway mileage increased only 15
percent. 1 Unsurprisingly, traffic congestion has increased in the nation’s major urban areas.
According to the Texas Transportation Institute’s 2009 Urban Mobility Report, annual hours of
delay per peak-time traveler increased 143 percent from 1982 to 2007 in the nation’s fourteen
largest urban areas. A typical peak period commuter in Los Angeles, for example, can now
expect to experience an average of 70 hours of delay per year, or almost three full days. 2
Vehicle emissions also tend to increase significantly during congested periods, increasing
environmental harm. Combining these factors, one estimate put the annual congestion cost to the
economy at $168 billion. 3 Additionally, many U.S. industries utilize just-in-time inventory
techniques, which rely on moving goods long distances quickly.
Meanwhile, the country’s transportation infrastructure is deteriorating. Many of the roads
built as part of the Interstate Highway System have reached the end of their original design lives
and require large scale reconstruction. 4 According to the American Society of Civil Engineers
(ASCE), about one in four bridges in the United States were structurally deficient or functionally
obsolete in 2009, while about one-third of the country’s major roads were in poor or mediocre
condition. The ASCE also estimates that poor roadway conditions cost Americans about $67
1
See Table 1 in Chapter 1 of 21st Century Highways. Fischer, John W. “From Interstates to an Uncharted Future.”
TTI 2009 Urban Mobility Report
3
http://ntl.bts.gov/lib/33000/33400/33441/final_report/volume_3_html/04_public_sessions/content5546.htm?name=
062606_presentation_wells
4
Reason Foundation, Restoring Trust in the Highway Trust Fund
2
1
billion per year in additional repairs and operating costs, and that annual spending for highway
capital improvements is $116 billion less than what is needed to improve the system. 5
Additionally, many state governments are facing severe fiscal constraints. Public
resources for infrastructure construction and renovation are inadequate. This is related to reliance
on fuel (gasoline and diesel) taxes for infrastructure funding. Both inflation and the use of more
fuel efficient vehicles have caused the purchasing power of fuel tax revenues to decline.
Moreover, other national policy goals, such as tighter corporate average fuel economy (CAFE)
standards, conflict directly with a fuel-tax-based funding approach.
Government officials are consequently searching for alternative approaches to
constructing, renovating, operating, and financing major infrastructure projects. One important
approach, particularly at the state level, is to enhance the role of private designers, construction
firms, and investors through the use of public-private partnerships (PPPs). Public-private
partnerships are contractual arrangements between private partners and public sponsors that
facilitate private infrastructure investment. There are an estimated 30 major investment funds
worldwide with over $180 billion in capital, and approximately 50 domestic pension funds with
nearly $40 billion in capital, prepared to invest in infrastructure. 6 That investment has the
potential to inject substantial sums of much-needed capital into the construction, renovation, and
operation of U.S. transportation facilities.
PPP enabling laws are key prerequisites for private infrastructure investment. PPP laws
help provide a stable institutional environment that facilitates private investment. As of this
writing, twenty-eight states have enacted diverse PPP enabling laws since 1988, but there has
been little systematic study of those important acts.
5
6
http://www.infrastructurereportcard.org/sites/default/files/RC2009_full_report.pdf
“How about a Partnership Stimulus.” Wall Street Journal, November 11, 2010.
2
We here examine empirically the reasons why some states have enacted such laws, while
others have not, and why some states have passed laws that are relatively more encouraging of
private investment. We use logistic regression analysis to explore the effects of a broad set of
variables on the probability that a state will enact a PPP enabling law, and use ordinary least
squares regression to examine the determinants of PPP enabling law intensity. We divide
independent variables into five groups: (i) motorist demand, which includes vehicle-miles
traveled, population growth, and the growth in vehicle registrations, among others; (ii) fiscal
health, which includes state debt outstanding per capita and the state’s bond rating; (iii) political
variables, including a state’s political disposition and unionization rates; (iv) public finance
variables such as federal aid to highways and gas tax receipts per capita, and (v) a set of basic
controls that includes variables such as personal income. Using a variety of specifications, we
find that, contrary to expectation, demand-side variables have little power to explain either the
probability of adoption or the intensity of PPP enabling laws. We instead find that a state’s
political disposition affects both the probability of act adoption and the intensity of laws that are
adopted, in a predictable direction. We also find a large diffusion effect from other states´
passage on both probability of act adoption and on PPP law intensity. Moreover, we find that, if
a state has passed an act, public finance variables such as greater federal highway aid per capita
and higher state gas taxes, reduce the act´s intensity.
We next describe public-private partnerships in more detail. Section III discusses PPP
enabling laws and why they are important in facilitating private investment. In section IV, we
provide an overview of academic literature relevant to PPPs. Section V discusses our data and
predictions, while section VI concludes.
3
II. Public-Private Partnerships
The term “public-private partnership” has come to encompass any contractual
arrangement that provides for a greater private sector role in infrastructure projects than under a
more traditional approach. 7 Alternative PPP contracts illustrate these arrangements. Traditional
procurement approaches have in fact utilized private sector participation in a variety of ways.
Under a design- build (DB) approach, for example, a public sponsor engages (typically different)
private firms to design and construct an infrastructure project. The public sponsor remains
responsible for financing, operating, and maintaining the facility.
The PPP approach enlists the private sector in additional activities. One such arrangement
is a design-build-operate-maintain, or DBOM contract, under which the additional duties of the
private partner or partners include operating and maintaining the facility. Similar to a DB
contracts, DBOM contracts seek to take advantage of private sector incentives and specialized
expertise to design and build facilities in a way that will minimize operation and maintenance
costs.
Other PPP contracts include enhanced private sector financing. In a typical DBFOM
(design-build-finance-operate-maintain) contract, for example, the private sector agrees to design
and build a new facility using some combination of debt (leveraged against future toll revenue in
the case of toll roads) and equity, and then operates and maintains the facility for a specified
period of time in exchange for the right to collect revenues from the use of the facility over the
lease term. This type of project, in which the private sector builds a new facility, is known as a
7
According to the Federal Highway Administration:
Public-private partnerships (P3s) are contractual agreements formed between a public agency and a private
sector entity that allow for greater private sector participation in the delivery and financing of transportation
projects.7
http://www.fhwa.dot.gov/ipd/p3/defined/index.htm
4
greenfield project. A long-term lease is a contract where the private partner pays an upfront
concession fee in order to lease an existing toll road. This is known as a brownfield project. The
private partner is then responsible for its operation, maintenance, and possible expansion, and
receives the right to collect toll revenue over the length of the concession agreement. Title to the
facility remains with the public sponsor throughout.
Other contractual arrangements include build-transfer-operate (BTO) agreements, under
which the private partner actually owns the facility until its ownership rights are transferred to
the public sector following the construction period. Similarly, in a BOT (build-operate-transfer)
agreement the private partner owns the facility until its ownership right is transferred at the end
of the specified operation and maintenance period. In a build-own-operate (BOO) agreement title
to the facility remains with the private partner unless the public sector decides to purchase it.
III. The Structure and Importance of PPP Enabling Laws
PPP enabling laws are a key part of the PPP process, and are a critical prerequisite to
private investment. We here discuss several benefits of PPP laws, highlighting their importance
as a topic for study. We then discuss the key elements of PPP enabling laws, and how they form
our index of PPP law intensity.
One potential benefit of PPP laws is to provide policy stability in order to reduce the
uncertainty surrounding future investment returns. For example, in the case of a toll road, if a
state government includes in its PPP law an assurance that it will not use regulation to depress
tolls below the facility’s operating cost, it is more likely to remain committed to that policy. 8
Such assurances are likely to be valuable in attracting private investment.
8
Geddes, Road to Renewal, p. 86
5
Similarly, state PPP enabling laws can also signal the degree of a state’s commitment to
the PPP process. For example, a number of states specify either the number of projects that can
be completed under the PPP approach, the type of project delivery system to be used (such as
long term leases), the geographic location of PPP projects, or the mode of transportation eligible
for a PPP. Potential investors will be more likely to focus their resources on states that have
shown a commitment to completing projects. Investors interested in creating a network of
projects in a state are likely to be dissuaded if a state does not signal a strong commitment to
PPPs. 9
PPP enabling laws are also important for their effects on transaction costs. Transaction
costs are broad in nature and occur at all stages of the PPP process. For example, there are costs
associated with bidding and negotiating the contract, with writing the contract, and with its
monitoring and enforcement. 10 PPP laws help reduce the costs associated with private sector
contracting by outlining contract terms ex ante. If a PPP law is in place, there is likely to be only
negotiation and modification of particular pre-established provisions. Without such legislation,
parties are forced to negotiate separately over each provision, which increases costs for both the
public and private sectors.
A third benefit of PPP enabling laws stems from their encouragement of innovation
through unsolicited proposals. Proposals from the private sector can be either solicited or
unsolicited, so long as the state’s PPP statute allows for the submission of unsolicited proposals.
A solicited proposal allows the state (typically the state DOT) to ask the private sector to develop
project proposals it wants to implement. For example, a state DOT might have a broad idea for a
bridge from A to B, and ask private companies to submit more specific proposals. In contrast,
9
California PATH Report
Geddes, Road to Renewal, p. 87
10
6
unsolicited proposals are generated by the private sector, and are typically projects the public
sector has not considered. 11
Moreover, states that want to further encourage innovation and creativity on the part of
the private sector can use their statutes to exempt PPPs from traditional state procurement
processes. For example, by allowing proposals to be selected on the basis of a combination of
factors that includes price (i.e. experience, innovation, financing plan, etc.), private companies
can be confident that their creative efforts will be rewarded, and that similar “cheaper” proposals
are not guaranteed to win the contract.
These potential benefits of PPP enabling laws are important. Indeed, commentators have
suggested that the single most significant barrier to PPP use in the highway sector is the lack of
enabling legislation at the state level. 12 We next discuss how we form our PPP enabling law
intensity index, and in doing so provide more background on the content of PPP laws. The score
assignments are based on detailed reading and study of PPP laws. Appendix C provides a
detailed discussion and justification for all the elements of our index.
For the reasons discussed above, we assign a score of two to a state if it has enacted a
PPP enabling law. This also reflects the importance and difficulty of moving a PPP law through
a state´s legislature, and how much uncertainty is resolved simply by enactment. To summarize
the other key elements of our index:
11
Hedlund & Chase, Nossaman Key Elements. Utt and Ybarra note that:
In contrast, under some of the PPP programs that have recently been established in several U.S. states –
notably Virginia, Georgia, Texas, and Florida - the partnership process is designed to allow, and even to
encourage, the private sector to initiate the effort and to take responsibility for the creative work. In effect,
what these states are telling investors and road builders is to ‘bring us a deal.’11
Utt & Ybarra (2005). “Private Sector Participation in Surface Transportation in the United States.” 21st Century
Highways. The Heritage Foundation: Washington, DC.
12
See “Major Legal Issues for Highway Public Private Partnerships," beginning at page 25.
7
•
We assign a state score of one if its law includes a broad definition of what facilities are
eligible to be PPPs, which we define as including three or more transportation modes. We
assign a score of minus one if the law excludes roads and highways as eligible facilities.
•
We assign a score of one if the law allows for long term leases/concessions of existing
assets.
•
We assign a score of one if the law allows for both solicited and unsolicited proposals
•
We assign a score of one if the law explicitly exempts PPPs from the traditional
procurement process.
•
We assign a score of one if the law explicitly allows for PPP agreements to include
revenue sharing agreements, and minus one if the law explicitly prohibits revenue sharing
agreements.
•
We assign a score of one if the law allows the private partner to be compensation through
non-toll mechanisms, such as shadow tolls and availability payments. We assign a minus
one if such mechanisms are excluded.
•
We assign a score of one if the PPP law allows other levels of government (such as
municipalities or counties) to enter into PPP agreements.
•
We assign a score of one if the PPP law exempts the private partner from paying property
taxes on the land required to operate the facility.
•
We assign a score of one if the PPP law allows the contract to contain non-compete
agreements, and a minus one if the law explicitly prohibits contracts from containing
non-compete clauses.
•
We assign a score of one if the law allows a mix of both public and private funds on PPP
projects, and a score of minus one if the combination of funds is expressly prohibited.
8
•
We assign a score of one if the law contains a provision that protects the confidentiality
of proprietary information contained in the private partner´s proposal, and a minus one to
a state that requires the entire proposal be disclosed.
•
We assign a score of minus one to a state that gives an entity other than the public
sponsor (e.g. the state legislature) veto power over the PPP agreement. We assign a score
of one if the law does not grant veto power to another entity.
•
We assign a minus one if a law limits the number of PPP projects that can be developed.
We assign a plus one if the law does not place a limit on the number of projects.
Policy stability and regulatory certainty refers to the creation of a stable institutional
environment that reduces uncertainty on the part of private investors with regard to governmental
actions. Such commitments are more credible when included in legislation. As of November
2010, twenty-eight states had passed laws granting explicit authority to the state –usually through
an agent such as the state Department of Transportation – to enter into PPP agreements. Where
such authority is lacking, specific enabling legislation is required before a PPP agreement can be
entered into. This was the case in the long-term lease of the Indiana Toll Road. 13 The winning
bid for the ITR was contingent on the passage of enabling legislation, which passed in March
2006. The legislation had to survive a lawsuit that went to the Indiana Supreme Court. 14
Although the lawsuit failed and the lease was upheld, the lack of prior authorization subjected
the private sector to considerable political risk.
This was also the case in the failed attempt to lease the Pennsylvania Turnpike. In May
2008 the state of Pennsylvania announced that a partnership of Citi Infrastructure Investors and
13
14
Major Legal Issues for Highway Public Private Partnerships, p. 26
http://www.fhwa.dot.gov/ipd/case_studies/in_indianatoll.htm
9
Spanish Abertis Infraestructuras was chosen as concessionaire in a 75-year lease of the
Pennsylvania Turnpike with a winning bid of $12.8 billion. The legislature allowed the bid to
expire, however, before it passed the requisite enabling legislation. 15,16 John Durbin, former
executive director of the Pennsylvania Turnpike Commission, notes that “[t]here will not be
another consortium that will proceed in any state where they have to put their bids in first and
then gain legislative approval to lease the asset.” 17 This highlights the need for potential public
sponsors to agree on enabling legislation prior to bidding.
Importantly, some state PPP enabling laws require the final PPP agreement to be put to a
legislative vote. This increases uncertainty surrounding the completion of a PPP relative to laws
without such provisions, and can be discouraging to private investment for similar reasons. An
important difference, however, is that without a law the legislature can simply choose not to act,
which is sufficient to stop the PPP process. In the latter instance (prior legislative approval) the
agreement must be put to an explicit vote, usually within a specified time period, so there is less
uncertainty in that case.
There is, however, a third alternative that benefits the public as well as the
private sector – revenue sharing. In such an arrangement, the private sector agrees to split
revenues above a certain rate of return with the public sector. 18 Although it may seem that it
15
Tollroadsnews.com/node/3757
This problem of “wasted” proposal development costs is exacerbated in greenfield projects utilizing tolls, as the
uncertainty in projecting future toll revenues based on traffic flows leads to greater costs in developing bids.
17
“Driven by Dollars,” PEW Center Report
16
18
For example, Delaware’s PPP statute states:
(a) Excess revenues. -- As agreed upon by the parties the agreement may require that any revenues in
excess of the maximum rate of return allowed in the agreement either be applied to any indebtedness
incurred by the contracting party in connection with the project and/or be paid to one or more other
entities or funds including, but not limited to, the Revolving Loan Fund established in § 2012 of this
10
would be more enabling to allow the private sector to keep all of its profits, revenue sharing
provisions help ameliorate the public concerns cited above that the private sector will increase
toll rates with no benefit to the public. Since widespread public opposition can undermine the
PPP process before, during, and after contracts are signed, revenue sharing provisions are
typically pro-PPP.
A particularly contentious element of PPP enabling laws is the non-compete clause. A
strict non-compete clause prevents the public sector from building an unplanned facility near the
PPP facility that would cause it to lose revenue. The rationale behind non-compete clauses is
clear. It is likely to be a disincentive to investment by the private sector if a competing
government-funded facility can be built in the future. A non-compete clause allocates this type of
risk to the public sector. Alternatively, some states specify in their PPP legislation that contracts
may contain clauses requiring compensation to the private company when the public sector
builds an unplanned competing facility.
Clauses addressing commercial confidentiality are another contentious aspect of PPP
legislation. In order to ensure the legitimacy of the PPP process it is important that the public be
informed and that public comment is facilitated. 19 However, free riding may occur if proprietary
information or trade secrets are disclosed, which can be a serious impediment to private
investment. State PPP legislation attempts to balance these competing forces. For example,
Washington’s PPP legislation allows private partners to identify and justify the portions of its
title, the State's Transportation Trust Fund established under § 1404 of this title, the Department, or the
State.
1995 House Bill 177.
19
Nossaman Key Elements
11
proposal it wishes to keep confidential during the bidding process, but all information is
disclosed prior to contract signing.20
Overall, PPP enabling laws are critical components in the process of injecting private
sector capital and incentives into infrastructure provision and operation. When properly
designed, they reduce uncertainty, establish pre-set guidelines, and lower the transaction costs
associated with public-private partnerships. We next provide an overview of literature on the
issue of private infrastructure investment.
IV. Literature Review
Several groups of researchers have examined the decision making processes and analytic
tools that public agencies use when embarking on PPPs. Morallos and Amekudzi (2008) survey
the state of the practice of how agencies conduct value for money (VfM) analyses. They identify
six key VfM drivers: risk transfer, output specifications, contract length, performance
measurement and incentives, competition, and private sector management skills. Strength and
weaknesses of different calculation methods are discussed. Buxbaum and Ortiz (2009) provide a
thorough study of the decision making process involved in significant PPPs in the US, along with
a useful history of PPPs. They discuss the advantages of PPPs for financing transportation
infrastructure, with the caveat that the long-term implications are not widely understood and
superior as-yet unexplored alternatives may exist. Important changes due to PPPs cited are the
replacement of taxes with tolls, private equity versus private lending, and the private sector’s
ability to bring about cost savings. Bonnafous and Jensen (2005) provide guidance for public
agencies deciding which of several possible PPP projects to undertake. They show that correctly
ranking projects to obtain the most efficient outcome may require sophisticated mathematical
20
Washington – 2005 HB 1541
12
modeling. Such models take into account both the financial and socioeconomic aspects of the
projects. In a similar vein, Tsamboulas et al. (2000) demonstrate how a hierarchical risk analysis
can be used as a tool to help a public agency better understand the importance of different risks
to potential private investors. They also show how it could be used to structure discussions
during the negotiation of a PPP contract.
Public perception of PPPs has also been a concern, and several researchers have
addresses this issue. Ward and Sussman (2006) studied toll road PPPs in Malaysia, where a lack
of transparency and public participation in the PPP process has led to protests. They propose
policies to address these problems and ensure the long-term viability of PPPs there. Lawther
(2004) argues that attention must be paid to public outreach and marketing of new PPPs to
encourage their use. Lawther uses three urban Advanced Traveler Information Systems (ATIS)
as a case study, but the lessons can also be applied to physical infrastructure projects as well.
Buxbaum and Ortiz (2008) also provide strategies for addressing public concerns about PPPs.
PPPs have been used in contexts other than roadways, in particular in rail and aviation,
and lessons can be learned from these projects as well. Risk allocation in urban rail PPPs was
studied by Phang (2007). Across urban rail PPPs in Latin America, Asia, and Europe, common
tradeoffs that had to be addressed when formulating PPP contracts included technical knowledge
versus PPP management knowledge in the government agency, the extent to which
complementary services should be bundled into a single contract, and concession length. In
particular, longer concession lengths might enhance the ability of the government agency to
develop a long term relationship with a vendor whereas shorter concession lengths allow more
opportunities for competitive bidding. However, frequent bidding also may entail higher
transaction costs simply because renegotiation occurs more often. Else and James (1995)
13
perform a mathematical analysis of PPPs involving railways and show that in certain market
structures quality of service is likely to fall. This highlights the importance of explicitly
incorporating service standards in the PPP contract. Majumdar and Ochieng (2004) investigate
the effects of PPPs on funding, new technology, project management, pricing, and customer
service in the context of aviation navigation infrastructure. The discussion of these facets of
PPPs is also relevant to surface transportation PPPs.
The optimal length of PPP concessions has been an active area of research. Albalate and
Bel (2009) use a simulation study to compare flexible concession lengths with fixed-length
concessions. Using data from two tollways in Spain, they show that a flexible concession length
would have resulted in a shorter contract length (because of unexpected growth in demand),
hence benefiting the users of the tollway. Vassallo (2006) discusses an approach to variablelength concessions taken in Chile, in which contractors bid on the Least Present Value of the
Revenues (LPVR). The evolution of the LPVR approach in Chile is traced and it is compared
with other common tactics to mitigate demand risk. Bel and Foote (2009) compare recent PPP
tollway projects in France and the US. They found that investors in the US paid on the order of
five times as much as did investors in France (relative to current cash flow). They identify
aspects of the contracts and the bidding processes that may explain this difference. First, the
concession lengths in the US were longer and the maximum allowable toll was higher.
Secondly, in the US bid price was the sole factor used in determining the winning bid, whereas
in France multiple criteria determine the winning bid. These factors impact the relative burden
placed on users of the toll facility and taxpayers.
Understanding the perspective of potential investors is also important to a successful
PPP. Brown (2007), in a summary of recent growth trends of PPPs in the US, highlights the
14
importance of tax benefits to the private partner due to depreciation of the infrastructure assets.
An interplay exists between the contract length and the ability of the private partner to maximize
their tax benefits. Debande (2002) reports on the UK’s experience with transportation
infrastructure PPPs since the inception of the country’s Private Finance Initiative (PFI) in 1992.
A useful typology of relevant risks by project phase is provided, as is a discussion of several case
studies. Vassallo and Sanchez-Solino (2007) describe the recent use in Spain of subordinated
public participation loans (SPPL) as an instrument to facilitate the financing of toll facility PPPs.
SPPLs are essentially loans originated by the public sector whose interest rate depends on the
traffic level on the facility. Such loans can be used to encourage private participation through a
more equitable sharing of risk. Although the authors find that SPPLs have been used
successfully in Spain they also propose possible improvements.
V. Data and Predictions
We address three key questions related to PPP enabling laws: (1) what factors are
important in determining whether or not a state will pass a PPP enabling law; (2) what
determines how enabling a state’s PPP law is; and (3) given that a state has passed a PPP
enabling law, what factors are important in determining how enabling it is. We address the first
question using a binomial logistic (logit) regression where the dependent variable is set to one if
a state has a PPP enabling law in place in a particular year, zero otherwise. We address the
second and third questions using ordinary least squares regression analysis to estimate the impact
of a variety of independent variables on an index of the strength or intensity of a PPP enabling
law. We next discuss our dependent variables and estimation approach.
15
We utilized the Federal Highway Administration (FHWA) website and several other
sources to determine which states have PPP enabling laws in place. 21 FHWA information was
then using other sources. 22 Our study time frame begins in 1988 with the passage of Virginia’s
Highway Corporation Act, which is the first modern PPP law, and ends in 2008, which is the last
year for which we have complete data. Although 28 states have PPP enabling laws as of this
writing, two of those states (Massachusetts and Illinois) passed laws in 2009. As a result, only 26
states are indicated as having passed PPP laws in our data.
We measure PPP enabling law intensity using an index of discreet values between zero
and fifteen. The index includes fourteen contractual provisions, discussed above, which we used
to determine a score for each state based on which provisions a given law contained. Legal
details were gathered using LexisNexis. This approach allows us to measure the intensity of PPP
laws across time. If a certain state updated its law, our index captures the resulting change in
intensity. Our data are thus at the state-by-year level from 1988 to 2008. We group independent
variables into the five categories discussed below. Table 1 provides a summary statistics for all
variables.
Demand Variables
These variables seek to measure travel demand. If the public sector seeks to increase
private participation in response to increased travel demand, then these variables will positively
affect both the probability of passing a PPP law and the intensity of PPP laws. Previous PPP
researchers cite rapid population growth, increased VMT, and worsening congestion as reasons
why states use the PPP approach. 23 This prediction has not been formally tested however.
21
Cite here PPP legislation “surveys”
LexisNexis was used to verify all FHWA information.
23
Fishman, p.3; Brown 2007, p. 320; Zhang 2007, p.96; Farber, p. 27; Public Sector Decision Making, p. 5
22
16
Moreover, legislators themselves tend to cite such demand characteristics as reasons for passing
PPP legislation. 24
There is a perception that demand characteristics are important drivers of PPP activity
and the passage of PPP legislation. We predict that transport demand will increase both the
probability of act passage as well as act intensity.
Fiscal Health Variables
Our fiscal health variables include state debt outstanding per capita, growth in state debt
per capita, and a state’s general obligation bond ratings. If a state utilizes the PPP approach in
response to poor fiscal conditions, then greater per capita debt will increase the probability of a
PPP law. Similarly, a reduction in the state´s bond rating will increase both the probability of law
enactment and its intensity. 25 That is, the worse a state’s bond rating, the more expensive it will
24
Reducing congestion is also cited. This excerpt from Delaware’s HB177, passed in
1995, is instructive:
(d) In addition to alleviating the strain on the public treasury and allowing the State to use its limited
resources for other needed projects, public-private initiative projects also do all of the following:
(3) More quickly reduce congestion in existing transportation corridors and provide the public with
alternate route and mode selections;
while this excerpt is taken from Indiana’s HB1008, passed in 2006:
There is a public need for timely development and operation of transportation facilities in Indiana that
addresses the needs identified by the department, through the department’s transportation plan and
otherwise, by accelerating project delivery, improving safety, reducing congestion, increasing mobility,
improving connectivity, increasing capacity, enhancing economic efficiency, promoting economic
development, or any combination of those methods.
Similarly, North Carolina’s HB644, passed in 2001, states that:
The General Assembly finds that the existing state road system is becoming increasingly congested and
overburdened with traffic in many areas of the state; that the sharp surge of vehicle miles traveled is overwhelming
the state's ability to build and pay for adequate road improvements; and that an adequate answer to this challenge
will require the state to be innovative and utilize several new approaches to transportation improvements in North
Carolina.
25
A higher bond rating receives a higher numerical value in our code.
17
be to use traditional municipal bond financing, and the more likely a state will be to use the PPP
approach. Alternatively, if wealthier states have higher bond ratings because general obligation
bonds are backed by greater potential tax revenue, then wealthier states will be more likely to use
the PPP approach. 26 One reason to believe that a state will use the PPP approach in response to a
poor bond rating is evidenced by Chicago, whose debt was upgraded when it used proceeds from
the lease of the Chicago Skyway to pay down existing debt. 27
Political Variables
Political forces are important factors in the passage of any legislation. We examine three
variables that provide political context: the percentage of democrats in the state´s house of
representatives in a given year (STATEDEM), 28 the percentage of a state’s population voting
Democrat in the most recent presidential election (DEMPRES), and the percentage of the
working population belonging to a union (UNIONM). Although we have no strong priors about
the impact of these variables, conventional wisdom suggests effects. If Republicans are more
likely to favor private participation, then STATEDEM will have a negative impact on both the
likelihood of passing PPP legislation and on its intensity. If unions (especially public sector
unions) oppose PPPs in favor of a traditional approach that is more likely to involve heavy use of
union labor, then UNIONM will have a negative impact. 29 In addition, if privately operated
26
As we explain below, it is not clear ex ante whether wealthier states will be more or less likely to use the PPP
approach.
27
Brown (2007).
28
Nebraska is not included in these regressions as it has a bipartisan unicameral legislature.
29
Poole (1993) addresses this latter point, noting that:
Two different groups of unionized workers may have problems with a private tollway program: state highway
department engineers and private sector construction trade unions…State-employed engineers view the design work
done by the consortia as work that would otherwise be done in-house…The same approach could be used to frame
the issue with construction trade unions.29
18
roadways are more likely to employ electronic tolling, then toll collectors unions are likely to
oppose PPP legislation as well.
Public Finance Variables
We include three variables measuring resources available for highways through
traditional finance. Since the literature often refers to PPPs as “innovative finance,” it is plausible
that a lack of “traditional” finance will make states more likely to pass PPP legislation. 30 The
first variable is a measure of federal highway aid per capita (FEDAIDPC). This is money from
the Highway Trust Fund (funded by federal fuel taxes) that is disbursed to the states according to
federal formulas. Some states are “donors” in that they contribute more in gas taxes than they
receive back from the federal government, and some are “donees” for the opposite reason. We
expect states receiving relatively more back from the federal government to be less likely to pass
enabling legislation, and for their legislation to be less enabling, on average. Our second variable
is gas tax receipts per capita (GASTAXPC), which is a function of a state’s gas tax rate and its
population, among other things. Since gas taxes are the traditional means through which states
have funded highway infrastructure, we predict a negative impact of this variable as well. The
third variable is the ratio of a state’s highway expenditures to its total expenditures
(PCTHYWS). If states spending relatively more on highways are less likely to use PPPs, then we
will observe a negative effect of this variable as well.
30
This is evident if one looks at the PPP laws themselves. For example, California’s landmark AB680, passed in
1989, contains this statement:
(b) Public sources of revenues to provide an efficient transportation system have not kept pace with California's
growing transportation needs, and alternative funding sources should be developed to augment or supplement
available public sources of revenue.
19
Basic Controls
As basic controls we include per capita income (PINC), per capita income growth
(PINCGR), and a variable that measures how many states have passed a law in a given year
(LAWTREND). It is difficult to predict the effect income will have on the likelihood of passing
a PPP law and on the intensity of that law. One hypothesis is that states with higher incomes pay
more in taxes and have higher revenues, which suggests a negative effect. Alternatively, private
investors might favor wealthier states over poorer states. Private investors may then work toward
passage of PPP laws, and stronger laws, suggesting a positive effect. We also include the number
of states that have already passed a PPP law in a particular year (LAWTREND). This variable
measures a possible diffusion effect across states from law passage. If states are learning from
one another, and feel more comfortable passing PPP laws if other states have passed them, then
this variable will positively affect PPP law passage.
VI. Empirical Approach and Estimation Results
Table 3A provides a list of the twenty-six states that passed PPP laws as of December
2008, the year in which the law was first passed, and the index score as of 2008. Table 3B
reports summary statistics for the year of first passage and the intensity index. The mean year
of first passage is 1997.92, with a median of 1997. The mean value of the intensity index is
7.12, with a median of 6.50. There is substantial variation in index values. The maximum
observed value of the index is thirteen. Index scores are consistent with conventional wisdom
about which states have broad legislation and which have narrow. For example, it is widely
20
believed that Texas, Virginia, Georgia, and Florida are examples of states with broad PPP
enabling legislation, and these states receive index scores well above the mean. 31
Figures 1 through 4 display maps indicating the states that had PPP legislation as of 1992,
1997, 2002, and 2008. Lighter shading indicates states that most recently passed laws. As these
maps indicate, there are important regional effects. States in the South and West are much more
active than those in the Northeast and Midwest. This suggests a split between the older,
industrial economies of the Northeast and Midwest and the newer, high-growth economies of the
South and West. 32
Figure 5 shows the trend in PPP law intensity over time. The lower line displays the sum
of all intensity scores per all fifty states. 33 This measure rises over time. The upper line displays
the intensity index divided by the number of states having PPP laws in that year, and thus shows
average PPP law intensity. This line indicates that average PPP law intensity is also rising over
time. This can happen because one of two things is happening. Either states are replacing
existing PPP laws with more intense laws, or new states are passing more intense laws on
average, or both. There is evidence that states are learning from one another, for instance by
31
As Leonard Gilroy of the Reason Foundation notes, “States like Texas, Virginia, Georgia, and Florida are
generally regarded as offering the best models [of PPP legislation], as evidenced by the fact that they are reaping the
most private sector interest and investment.” Additionally, Iseki et al. (2009) write that “variation in legislation
reflects each state’s general philosophical orientation towards PPPs,” and go on to list states that have an aggressive
orientation (Indiana, Texas, and Virginia), a positive, but cautious orientation (Arkansas and Minnesota), and a wary
orientation (Alabama, Missouri, and Tennessee). (See California PATH report). If we relate those categories to our
index as aggressive (11 – 15), positive, but cautious (6 – 10), and wary (0 – 5), then our index values match up well
with the “philosophical orientations” discussed there. A striking difference appears to be that Iseki et al. (2009) have
Arkansas listed as having a PPP law, while we do not. We believe this is a misprint, and should represent Alaska, as
the postal abbreviation AK (representing Alaska) is listed in their tables, which is the abbreviation for Alaska.
Furthermore, the FHWA website has Alaska listed as having a PPP law, and not Arkansas. Arkansas does, however,
have a 1947 statute allowing county courts to grant private franchises for toll bridges, turnpikes, and causeways. We
do not consider this to be an example of modern PPP legislation.
32
33
Fishman (2009).
The numerator is the sum of the index for all states in that year.
21
starting out with a “pilot” or “demonstration” program that limits the number of projects and
then removing the demonstration status, or learning from each other’s experiences with PPPs.
Table 2 reports differences in means between states with PPP laws and states without
PPP laws for our independent variables. Almost all differences in means are in the expected
direction. For example, states with PPP laws have (on average) higher population growth, higher
travel time indices, fewer Democrats in the state house, lower percentages of union membership,
less federal aid, less money from gas tax receipts, and higher per capita income. We next explore
the robustness of these relationships within a regression framework.
We first estimate the effects of our independent variables on the probability that a state
has passed a PPP law in a given year. We use the following empirical specification, where for
any state i in year t:
(1)
ŷ i t = α + X it β + vi + ε it
yit = 1 if
= 0 if
where y^
it
i = 1, …, 50; t = 1988, 1989 . . . . 2008
y^ it > 0
y^ it ≤ 0
equals the unobserved legal response variable for state i in year t, yit is the observed
state law variable which equals 1 if the state has a PPP law in year t (and equals 0 if not), Xit is a
row vector of exogenous variables including a constant, β is a column vector of unknown
coefficients, vi is a state or regional-specific fixed-effect, εit is a state-specific error term, and n is
the number of states (50) in the sample. We use a logit model to estimate (1). Using all years and
states between 1988 and 2008 generates a sample that varies in size from 546 to 1050, depending
on the sample of states and the variables used in the specification.
Table 4 presents the results from our logistic regressions. Several variables are robust to
alternative specifications and to the inclusion of time trends and regional indicators. Among
22
basic controls, these include income per capita, which increases the probability that a state will
adopt a PPP enabling law, when both time trends and regional dummy variables are included.
Thus, ceteris paribus, wealthier but slower growing states are more likely to enact PPP laws. The
variable measuring how many other states have at that point passed a PPP law (LAWTREND),
displays a positive coefficient, which is consistent with a strong diffusion effect of passage.
Among demand variables, the travel time index, growth in vehicle registrations, and
population growth are positive in a number of specifications, but only growth in vehicle
registrations is robust to the inclusion of both a linear time trend and regional dummy variables.
Regarding fiscal health, the growth in per capita state government debt increases the probability
that a state enacts a PPP law, while an improved state bond rating reduces it, in a non-linear
fashion. These effects are consistent with predictions. Among political variables, the fraction of
Democrats in the state house reduces significantly the probability of enactment, or conversely,
the fraction of Republicans increases it. This finding is robust to the inclusion of time trends and
regional fixed effects. There is no evidence that any of our public finance variables impact the
probability of PPP act passage.
Table 5 reports ordinary least squares estimates of act intensity using all fifty states. 34
Column 3 includes time trends (both linear and quadratic) and regional fixed effects, column 4
includes time trends and state fixed effects, and column 5 contains both state and year fixed
effects. The effect of the trend toward PPP law passage (LAWTREND) remains positive and
significant. Of the demand variables, only the intensity of road use (USE) has the predicted
positive impact on law intensity. Political variables are however important in determining law
intensity, with both the fraction of Democrats in the state house and the percentage Democratic
34
As noted before, Nebraska drops out when political variables are included. We use a similar empirical
specification to equation (1).
23
vote in the most recent presidential election reducing PPP enabling law intensity. Therefore,
political preferences are strong predictors of both the probability of passing a law as well as its
intensity.
We next focus only on those states that have passed PPP enabling laws. We hope to
sharpen our analysis by excluding states that have never passed a PPP enabling law, since there
may be systematic differences in states that have passed versus those that have not. Due to the
reduced sample size, we could not include state and year fixed effects, so the specifications are
similar to the logit models in that we control for regional fixed effects. We report estimation
results in Table 6.
Demand variables again do not positively affect PPP enabling law intensity. Instead, both
population growth and intensity of use negatively affect the law index. In column 4, where we
include all variables, time trends, and regional fixed effects, the impact of both the STATEDEM
variable and the LAWTREND variable are consistent with predictions about law intensity. These
two variables consistently predict both outcomes. In addition, two of our public finance variables
-- gas taxes per capita and federal highway aid per capita -- have the predicted effect in this
specification. Of PPP law states, those that receive more fuel tax money back from the federal
government (i.e. “donee” states) and states that receive more from their own gas taxes, tend to
pass less legislation that is less enabling. This suggests that fiscal constraints lead to more intense
laws. Finally, the per capita income variable confirms the earlier finding that wealthier states are
more encouraging of private investment.
VII. Summary and Conclusion
In this paper, we have outlined why PPPs are important for the development of
transportation infrastructure, and why PPP enabling laws are a crucial element in introducing
24
more private investment. We develop two models: a logit model that uses a variety of factors to
determine why states pass legislation, and an OLS model using those factors to predict how
welcoming a state will make its legislation to private investment. Our results indicate that the
passage of PPP enabling legislation is not driven by demand-side factors such as population
growth, VMT growth, roadway use, or congestion, although many PPP laws cite those as
important reasons for passing legislation. A state’s fiscal health and its political disposition are
important factors in the passage of PPP legislation. Ceteris paribus, the intensity of legislation is
affected by the passage of legislation by other states, suggesting that there is a substantial legal
diffusion effect. It also appears that PPP law intensity is affected by resources available from
traditional sources of finance, such as federal aid and gas tax receipts. Our estimates suggest that
the two most important factors in the passage of PPP legislation are political climate and learning
by doing.
25
Appendix A: Figures 1 through 4 -- Adoption of PPP Enabling Laws as of 1992, 1997, 2002,
2008
26
27
28
29
Appendix B: Summary Statistics and Estimates:
Table 1 – Descriptive and Summary Statistics, 1988 - 2008
Variable and Definition
Demand Variables
POPGR: annual percentage
growth in population
REGGR: annual percentage
growth in motor vehicle
registrations
VMTGR: annual percentage
growth in vehicle miles traveled
VMTPC: vehicle miles traveled
per capita
USE: ratio of vehicle miles
traveled to lane mileage
TTI: travel time index
Fiscal Health Variables
DEBTPC: state debt
outstanding per capita
DEBTPCGR: annual
percentage growth in state debt
outstanding per capita
BONDS: state general
obligation bond ratings
Political Variables
STATEDEM: percentage of
Democrats in the state house of
representatives
DEMPRES: percentage voting
Democrat in most recent
presidential election
UNIONM: percentage of the
working population that is a
member of a union
Public Finance Variables
FEDAIDPC: federal aid for
highways per capita
GASTAXPC: state level gas
tax receipts per capita
PCTHWYS: percentage of
state total expenditures that are
highway expenditures
Basic Controls
PINC: personal income per
Min
Max
Mean
Standard
Deviation
No.
Observations
-5.6
7.82
1.06
1.02
1050
-53.74
28.28
1.57
4.52
1050
-14.14
41.2
2.16
2.99
1050
5,779.61
18,458.92
9,916.48
1,781.65
1050
32,998.29
1,093,667.0
336,450.9
217,254.80
1050
1.01
1.51
1.15
0.11
1050
166.13
16,501.35
2,352.50
1,735.77
1050
-30.70
85.08
2.58
9.31
1050
13
21
19.20
1.35
948
13
95
54.03
16.26
1029
25
62
44.48
7.55
1050
2.3
30.5
12.98
5.98
1050
0.22
542.78
113.03
76.15
1050
29.78
216.62
121.07
30.48
1050
2.69
17.91
8.30
2.68
1050
11,561.00
56,248.00
26,160.35
7,653.78
1050
-9.58
33.19
4.50
2.36
1050
capita
PINCGR: annual percentage
growth in personal income
30
Table 2 – Difference in Means, 1988 - 2008
Variable
Demand Variables
Population Growth
Veh. Regis. Growth
VMT Growth
VMT per capita
Intensity of Road Use
TTI
Fiscal Health Variables
State Debt per capita
Growth in State Debt per
capita
State Bond Rating
Political Variables
Percent Dems in House
Perc. Dem Vote Pres.
Perc. Workers Union
Public Finance Variables
Fed. Aid to Highways per
cap.
State Gas Tax per cap.
Percent State Expend. on
Highways
Basic Controls
Personal Inc. per capita
Growth in Personal Inc.
per capita
Mean (Act =1)
(S.E.)
Mean (Act = 0)
(S.E.)
Difference
[t-stat]
1.5006
(0.0546)
1.9937
(0.312)
1.8288
(0.1452)
10,160.21
(73.2083)
418,852.50
(11,503.14)
1.2295
(0.0061)
0.8878
(0.0362)
1.4101
(0.1511)
2.2804
(0.1145)
9,823.033
(70.4273)
304,858.20
(7,867.639)
1.1214
(0.0034)
0.6128
[9.07]**
0.5836
[1.88]*
-0.4516
[2.196]**
337.1739
[2.75]**
113,994.30
[7.83]**
0.1081
[16.04]**
1,880.4120
(67.2806)
3.5223
(0.5677)
19.5620
(0.0917)
2,533.4910
(68.3635)
2.2155
(0.3321)
19.0534
(0.0479)
-653.079
[5.53]**
1.3068
[2.04]**
0.5086
[5.34]**
49.7595
(0.6993)
45.2852
(0.375)
10.8430
(0.3266)
55.7181
(0.6405)
44.1647
(0.2876)
13.7975
(0.2152)
-5.9587
[5.36]**
1.1205
[2.16]**
-2.9545
[7.35]**
88.4987
(2.7979)
112.4106
(1.393)
7.3047
(0.1137)
122.4286
(3.0007)
124.3944
(1.1647)
8.6864
(0.1023)
-33.93
[6.59]**
-11.9839
[5.79]**
-1.3817
[7.69]**
29,766.84
(374.6668)
4.2116
(0.1579)
24,777.63
(277.7034)
4.6088
(0.0801)
4,989.207
[9.88]**
-0.3971
[2.45]**
Notes: All variables except State Bond Rating and Percent Dems in House have 759 observations for states with
PPP laws and 291 observations for states without PPP laws; the State Bond Rating variable has 674 and 274
observations, respectively; Percent Dems in House has 738 and 291 observations, respectively
** significant at the 5 percent level / * significant at the 10 percent level
31
Table 3A
Dates of First Passage of PPP Enabling Laws and Final Index Scores
State
AK
AL
AZ
AR
CA
CO
CT
DE
FL
GA
HI
ID
IL*
IN
IA
KS
KY
LA
ME
MD
MA*
MI
MN
MS
MO
First Passed
2006
1996
1991
--1989
1995
--1995
1991
1998
------2006
------1997
--1997
----1993
2007
2006
State
Score
3
6
3
--6
12
--10
10
11
------10
------11
--6
----4
8
6
MT
NE
NV
NH
NJA
NM
NY
NC
ND
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA
WA
WV
WI
WY
First Passed
----2003
--1997
----2000
------1995
----1994
--2007
1991
2006
--1988
1993
2008
1997
---
Score
----5
--0
----7
------11
----4
--2
11
10
--13
5
7
4
---
______________________________________________________________________________
Notes: Current index scores are through 2008.
* Massachusetts and Illinois both passed laws in 2009
A
New Jersey passed a law in 1997 that expired in 2003
32
Table 3B -- Summary Statistics for Year of Passage and Intensity Index
Year
passed
Intensity
Index
Mean
Median
Std. Dev.
Min
Max
Obs.
1997.92
1997
6.25
1988
2006
26
7.12
6.50
3.50
0
13
26
Table 4 – Logit Estimates of Probability of PPP Law Adoption: Full Sample
__________________________________________________________________
Variables
(1)
(2)
(3)
(4)
(5)
-0.0001
(-1.52)
-0.00004
(-0.68)
-0.00003
(-0.43)
-0.00003
(-0.36)
0.0003
(2.31)**
0.022
(0.40)
0.023
(0.41)
0.025
(0.56)
0.03
(0.71)
-0.064
(-1.90)*
0.194
(2.66)**
0.178
(2.66)**
0.129
(1.81)*
0.12
(1.63)
0.173
(2.17)**
0.818
(2.07)**
0.021
(1.16)
-0.058
(-1.80)*
0.0003
(1.65)*
2.81 x 10-6
(1.37)
9.22
(2.84)**
0.642
(1.84)*
0.018
(0.77)
-0.057
(-1.54)
0.0001
(0.79)
2.76 x 10-6
(1.36)
7.125
(2.12)**
0.552
(1.83)*
0.027
(1.30)
-0.061
(-1.48)
0.00004
(0.17)
3.02 x 10-6
(1.50)
8.442
(2.55)**
0.532
(1.79)*
0.028
(1.28)
-0.066
(-1.32)
0.00008
(0.22)
3.05 x 10-6
(1.27)
8.148
(2.41)**
-0.098
(-0.38)
0.044
(2.61)**
-0.046
(-0.97)
-0.0002
(-0.95)
-1.32 x 10-6
(-0.65)
5.19
(1.14)
Fiscal Health
State Debt per capita
---
-0.0004
(-1.09)
-0.0004
(-0.99)
-0.0003
(-1.03)
-0.0003
(-0.89)
Growth in State Debt
per capita
---
State Bond Rating
---
0.007
(0.71)
-6.615
(-3.11)**
0.004
(0.41)
-5.852
(-2.79)**
0.005
(0.55)
-5.57
(-2.51)**
0.02
(1.96)**
-6.347
(-2.66)**
Basic Controls
Personal Inc. per capita
Growth in Personal
Inc. per capita
# Stated Already
Adopted
Demand
Population Growth
Veh. Regis. Growth
VMT Growth
VMT per capita
Intensity of Road Use
TTI
33
State Bond Rating2
---
0.181
(3.12)**
0.157
(2.70)**
0.15
(2.41)**
0.17
(2.54)**
Percent Dems in House
---
---
Perc. Dem Vote Pres.
---
---
Perc. Workers Union
---
---
-0.043
(-1.91)*
0.034
(0.58)
-0.109
(-1.50)
-0.046
(-1.86)*
0.028
(0.56)
-0.113
(-1.64)
-0.094
(-3.86)**
0.029
(0.55)
0.006
(0.06)
Fed. Aid to Highways
per cap.
---
---
---
State Gas Tax per cap.
---
---
---
-0.003
(-0.21)
0.006
(0.37)
-0.005
(-0.85)
-0.001
(-0.07)
Percent State Expend.
on Highways
---
---
---
-0.1
(-0.52)
-0.248
(-1.15)
No
No
78.68
1050
No
No
169.97
948
No
No
206.08
945
No
No
220.8
945
Yes
Yes
316.2
945
Political
Public Finance
Time Trend
Region Dummies
Chi-squared
Observations
______________________________________________________________________________
Notes: Dependent variable = 1 if a state had a PPP law; = 0 if not. t-statistics are in parentheses.
** Statistically significant at the 5 percent level
* Statistically significant at the 10 percent level
34
Table 5 – OLS Estimates of the Intensity of PPP Enabling Laws:
All States
__________________________________________________________________
Variables
Basic Controls
Personal Inc. per
capita
Growth in Personal
Inc. per capita
# Stated Already
Adopted
Demand
Population Growth
Veh. Regis. Growth
VMT Growth
VMT per capita
Intensity of Road
Use
TTI
Fiscal Health
State Debt per capita
Growth in State
Debt per capita
State Bond Rating
State Bond Rating2
Political
Percent Dems in
House
(1)
(2)
(3)
(4)
(5)
2.75 x 10-6
(0.04)
0.00004
(0.46)
0.0002
(1.53)
-0.0001
(-1.10)
-0.0001
(-1.26)
0.056
(0.90)
0.041
(0.74)
-0.02
(-0.37)
0.046
(1.26)
0.058
(1.13)
0.117
(1.93)*
0.064
(1.041)
0.084
(1.68)*
0.163
(3.23)**
0.221
(2.19)**
0.572
(1.81)*
-0.001
(-0.02)
-0.056
(-2.16)**
0.00009
(0.58)
0.38
(1.54)
0.003
(0.11)
-0.054
(-1.85)*
-0.0001
(-0.58)
-0.016
(-0.07)
0.004
(0.17)
-0.038
(-1.47)
-0.0002
(-1.47)
0.091
(0.68)
0.008
(0.66)
0.005
(0.20)
-0.001
(-3.44)**
0.03
(0.20)
0.011
(0.97)
0.015
(0.62)
-0.001
(-3.35)**
8.27 x 10-7
(0.40)
5.515
(1.27)
1.06 x 10-6
(0.49)
6.357
(1.47)
-1.53 x 10-6
(-0.86)
3.382
(0.92)
0.00002
(2.78)**
3.61
(0.50)
0.00002
(2.72)**
3.847
(0.54)
-0.0002
(-0.83)
-0.00009
(-0.43)
-0.00003
(-0.21)
-0.00003
(-0.10)
-2.61 x 10-6
(-0.01)
0.011
(1.01)
-4.986
(-2.04)**
0.14
(2.06)**
0.005
(0.47)
-3.342
(-1.48)
0.093
(1.46)
0.017
(1.72)*
-2.388
(-1.26)
0.067
(1.25)
0.009
(1.13)
-1.525
(-0.88)
0.046
(0.95)
0.01
(1.21)
-1.402
(-0.85)
0.043
(0.93)
---
-0.024
(-1.26)
-0.064
(-4.07)**
-0.063
(-3.59)**
-0.069
(-3.74)**
35
Perc. Dem Vote
Pres.
---
Perc. Workers Union
---
Public Finance
Fed. Aid to
Highways per cap.
-0.006
(-0.15)
-0.146
(-2.37)**
0.047
(1.287)
-0.075
(-1.21)
-0.048
(-1.80)*
-0.014
(-0.14)
-0.064
(-1.71)*
-0.016
(-0.16)
---
-0.002
(-0.45)
-0.003
(-0.76)
0.005
(1.39)
0.005
(1.16)
State Gas Tax per
cap.
---
-0.005
(-0.62)
-0.001
(-0.20)
-0.01
(-1.45)
-0.01
(-1.39)
Percent State
Expend. on
Highways
---
0.03
(0.24)
-0.139
(-1.16)
-0.103
(-1.24)
-0.093
(-1.11)
No
No
No
No
No
No
No
No
Yes
Yes
No
No
Yes
No
Yes
No
No
No
Yes
Yes
0.28
948
0.34
945
0.45
945
0.78
945
0.78
945
Time Trends
Region Dummies
State Fixed Effects
Year Fixed Effects
R-Squared
Observations
______________________________________________________________________________
Notes: Dependent variable is a continuous variable that runs from 0 through 15 based on how
enabling the PPP statute is, with 15 being the most enabling. t-statistics are in parentheses. The
full sample consists of all 50 states.
** Statistically significant at the 5 percent level
* Statistically significant at the 10 percent level
36
Table 6 – OLS Estimates of the Intensity of PPP Enabling Laws:
States with PPP Laws Only
__________________________________________________________________
Variables
(1)
(2)
(3)
(4)
(5)
0.0002
(1.30)
0.0002
(1.16)
0.0003
(2.55)**
0.0003
(2.563)**
0.0005
(3.11)**
0.134
(3.07)**
0.108
(2.00)**
0.047
(1.00)
0.037
0.76
-0.027
-0.535
0.108
(1.15)
0.117
(1.16)
-0.114
(-1.09)
(-0.07)
(-0.73)
(0.18)
(2.50)**
0.273
(0.75)
-0.002
(-0.07)
-0.063
(-1.35)
0.0003
(1.14)
0.206
(0.49)
-0.009
(-0.24)
-0.075
(-1.60)
0.0002
(0.73)
-0.151
(-0.51)
0.007
(0.26)
-0.076
(-1.46)
2.87 x 10-6
(0.01)
-0.209
(-0.74)
0.009
(0.34)
-0.067
(-1.22)
-9.79 x 10-6
(-0.04)
-0.572
(-2.51)**
0.002
(0.11)
-0.038
(-0.73)
0.0001
(-0.43)
-1.08 x 10-6
(-0.35)
5.34
(0.85)
-1.11 x 10-6
(-0.36)
3.989
(0.64)
-3.28 x 10-6
(-1.34)
3.859
(0.70)
-3.84 x 10-6
(-1.61)
4.727
(0.82)
-6.38 x 10-6
(-2.81)**
3.36
(0.66)
---
-0.00009
(-0.41)
-0.00006
(-0.31)
0.0002
(0.98)
0.0001
(0.46)
Growth in State
Debt per capita
---
State Bond Rating
---
State Bond Rating2
---
0.014
(0.99)
-2.186
(-0.53)
0.062
(0.55)
0.003
(0.19)
1.048
(0.32)
-0.033
(-0.37)
-0.001
(-0.04)
1.475
(0.42)
-0.044
(-0.46)
0.008
(0.62)
1.691
(0.76)
-0.05
(-0.83)
Political
Percent Dems in
House
---
---
-0.063
(-2.89)**
-0.056
(-2.50)**
-0.104
(-5.89)**
Basic Controls
Personal Inc. per
capita
Growth in Personal
Inc. per capita
# Stated Already
Adopted
Demand
Population Growth
Veh. Regis. Growth
VMT Growth
VMT per capita
Intensity of Road
Use
TTI
Fiscal Health
State Debt per
capita
37
Perc. Dem Vote
Pres.
---
---
0.047
(0.82)
0.02
(0.35)
-0.058
(-1.21)
Perc. Workers
Union
---
---
-0.275
(-3.64)**
-0.26
(-3.48)**
-0.007
(-0.09)
Public Finance
Fed. Aid to
Highways per cap.
---
---
---
-0.01
(-1.33)
-0.02
(-3.54)**
State Gas Tax per
cap.
---
---
---
0.0001
(0.01)
-0.014
(-1.75)*
Percent State
Expend. on
Highways
---
---
---
0.112
(0.56)
-0.042
(-0.26)
No
No
0.39
546
No
No
0.39
507
No
No
0.50
507
No
No
0.51
507
Yes
Yes
0.62
507
Time Trends
Region Dummies
R-Squared
Observations
__________________________________________________________________
Notes: Dependent variable is a continuous variable that runs from 0 through 15 based on how
enabling the PPP statute is, with 15 being the most enabling. t-statistics are in parentheses. The
reduced sample contains 26 states that have ever passed a PPP law. All states that have never
passed a PPP law are dropped from the sample.
** Statistically significant at the 5 percent level
* Statistically significant at the 10 percent level
38
Appendix C: Index Composition
In this Appendix, we describe how we obtain our index of PPP law intensity. We provide a brief
justification for each element of the index.
PPPLAW: We give a state a score of +2 if they have a PPP law (to be defined in the paper),
regardless of whether or not they have more than one statute governing PPPs. A state without a
PPP law receives a score of zero.
Possible scores: 0, +2
Justification: A PPP law that is in place before the procurement process takes place (i.e. request
for proposals, bidding, contract negotiation, etc.) eliminates the risk that the project will be
thwarted because authorizing legislation does not pass the legislature in time. A private
consortium is likely to invest more time and resources developing proposals in states that do not
carry this risk. PPP laws also clarify certain issues about the procurement and contracting
process (see provisions below), and signal to the private sector that a state is “open” for
investment.
ELIG: We give a score of +1 if a state has a broad definition of eligible facilities. An example of
a state with this provision is Delaware:
(g) "Transportation System" means any capital-related improvement and addition to the State's
transportation infrastructure, including but not limited to highways, roads, bridges, vehicles and equipment,
ports and marine-related facilities, park and ride lots, rail and other transit systems, facilities, stations and
equipment, rest areas, tunnels, airports, transportation management systems,
control/communications/information systems and other transportation-related investments, or any
combination thereof.
If a state has three or more modes of transportation eligible as PPPs, it receives +1. For example,
highways, airports, and rail would qualify. If a state allows PPPs for less than three modes of
transportation, it receives a score of zero, and if a state explicitly excludes highways/roads from
its definition of eligible facility it receives -1.
Possible scores: -1, 0, +1
Justification: The broader the definition of a transportation facility, the greater the number of
investment and business opportunities for the private sector. For example, rail improvements and
airports provide different investment opportunities from toll bridges and toll roads. Allowing a
broad range of eligible facilities in the PPP legislation prevents states from having to pass new
legislation should they or the private sector wish to pursue a PPP for a different type of
transportation facility.
BROWN: We give a score of +1 if the law specifically allows for long term leases/concessions
of existing transportation assets. The state will receive a score of zero if it authorizes long term
leases/concessions for new facilities only, or if there is no express provision regarding long term
39
leases/concessions. Service contracts for operation and maintenance do not count as
lease/concession agreements.
Possible scores: 0, +1
Justification: Similar to enabling PPPs to be used on a broad range of eligible transportation
facilities, allowing PPPs to be used for both new and existing facilities greatly expands the
investment opportunities available to the private sector.
UNSOLIC: A state receives +1 on this measure if it allows for both solicited and unsolicited
proposals. If a state allows for only solicited or only unsolicited proposals it receives a score of
zero.
Possible scores: 0, +1
Justification: Allowing both solicited and unsolicited proposals allows for the maximum amount
of ways the private sector can get proposals to the public sponsor. They can respond to requests
for proposals, initiate proposals on their own, and respond to unsolicited proposals generated by
other private entities. Unsolicited proposals also allow the private sector to be creative and
submit ideas the public sector otherwise would not have thought of. (Insert some good quotes
from 21st Century Highways article).
EXEMPTPRO: A state receives +1 if there is an explicit exemption for PPPs from the normal
procurement rules of the state. An example is Georgia:
(a) If the department follows the evaluation criteria set forth in Code Section 32-2-79 and if an unsolicited
proposal contains all the information required by that Code section and the proposal is accepted by the
department as demonstrated by the execution of a commitment agreement, upon completion of the public
comment period, the department shall have the authority to contract with the proposer for a public-private
initiative based upon the proposal without subjecting such contract to public bid as required by Code
Section 32-2-64, 32-10-68, or 50-5-72 (emphasis added). Such contracts shall be in compliance with all
other applicable federal and state laws and each specific contract shall be specifically approved by
affirmative vote of the State Transportation Board.
A state receives a score of zero if PPP contracts are explicitly subject to procurement rules, or if
there is no express provision regarding procurement exemptions.
Possible scores: 0, +1
Justification: Exempting PPP projects from normal procurement rules allows states to maximize
flexibility in the bidding and procurement process. For example, states that have the ability to
select projects based on factors other than price create incentives for the private sector to
compete on quality, and give assurance that innovative and creative efforts will be rewarded.
Allowing exemption from the normal procurement rules of the state also allows the PPP process
to sidestep cumbersome bureaucratic regulations and red tape. Lastly, procurement exemptions
help to ensure that the procurement process that is used will withstand legal challenges
(Nossaman key elements reference).
40
REVENUE: We give a score of +1 if a state explicitly allows for or requires PPP agreements to
contain revenue sharing provisions. An example is Delaware:
(e) Excess revenues. -- As agreed upon by the parties the agreement may require that any revenues in
excess of the maximum rate of return allowed in the agreement either be applied to any indebtedness
incurred by the contracting party in connection with the project and/or be paid to one or more other entities
or funds including, but not limited to, the Revolving Loan Fund established in § 2012 of this title, the
State's Transportation Trust Fund established under § 1404 of this title, the Department, or the State.
We give a score of minus one if revenue sharing provisions are expressly forbidden, and a score
of 0 if there is no explicit provision regarding revenue sharing.
Possible scores: -1, 0, +1
Justification: Revenue sharing provisions allow profits above the negotiated rate of return to be
split between the public and private sector. While it may seem that it would be more enabling to
allow the private sector to keep all of its profits, revenue sharing provisions help ameliorate
public concerns that, years down the road when the debt is paid off, the private sector will
increase toll rates with no benefit to the public. Since widespread public opposition can
undermine the PPP process before, during, and after contracts are signed, revenue sharing
provisions are inherently pro-PPP.
AVAIL: We give a score of +1 if the statute allows for the state to make payments to the private
sector in lieu of direct user fees. Examples include such mechanisms as availability payments,
shadow tolls, etc. An example is Arizona:
2. ALLOW FOR PAYMENTS TO BE MADE BY THIS STATE TO THE PRIVATE PARTNER,
INCLUDING AVAILABILITY PAYMENTS OR PERFORMANCE BASED PAYMENTS.
Explicit prohibitions of these types of payments result in a score of minus one, and a statute with
no express provision receives a score of zero.
Possible scores: -1, 0, +1
Justification: Availability payments and shadow tolls create additional flexibility in the types of
projects that can be developed. For example, the private sector can pursue a PPP project in an
area resistant to tolling using an availability payment or shadow toll approach. In addition,
projects that may not be financially viable for the private sector based on user fees alone can be
completed using an availability payment or shadow toll approach. One drawback of this
approach is that it does not necessarily create a new source of funding. That is, fiscally
constrained governments cannot “free up” funds using this method.
OTHERS: A state that allows lower levels of government (i.e. municipalities, counties, etc.) to
enter into PPP agreements with the private sector receives a score of +1, so long as there is a
state level entity that can enter into PPP agreements as well. For example, Louisiana’s first PPP
law allows municipalities to form “tollway authorities” that have statutory authority to enter into
PPPs. However, at the time of this law there was no state level entity (i.e. Louisiana Department
of Transportation and Development) that had this authority as well. In 2001, the legislature
41
passed a new bill that created the Louisiana Transportation Authority within the DOTD, and
gave it the ability to enter into PPP contracts. It was only after this law was passed that both
municipalities and the state sponsor could enter into PPP agreements, so only after 2001 does
Louisiana receive a +1.
Possible scores: 0, +1
Justification: Allowing smaller entities with road building authority the ability to enter into PPP
agreements creates more investment opportunities for the private sector. Local public agencies
may initiate projects that would not otherwise have been undertaken by a state level agency as
local governments, municipalities, and other local authorities vested with road building authority
are more responsive to local needs. Although these projects will usually be on a smaller scale,
more investment opportunities create a more welcoming environment for private sector
involvement.
PROPTAX: We give a state +1 if it exempts the private partner from paying property taxes on
the land on which it operates the facility, or from paying income taxes on the revenue it receives
from use of the facility. An example is Arizona:
NOTWITHSTANDING ANY OTHER LAW, AGREEMENTS UNDER THIS CHAPTER THAT ARE
PROPERLY DEVELOPED, OPERATED OR HELD BY A PRIVATE PARTNER UNDER A
CONCESSION AGREEMENT PURSUANT TO THIS CHAPTER ARE EXEMPT FROM ALL STATE
AND LOCAL AD VALOREM AND PROPERTY TAXES THAT OTHERWISE MIGHT BE
APPLICABLE.
If there’s no express provision the state receives a zero.
Possible scores: 0, +1
Justification: Exemptions from property taxes allow the private sponsor to achieve a greater
return on its investment, as well as lower the rates it charges for tolls.
NONCOMP: We give a state +1 if it allows for PPP contracts to contain non-compete
provisions. These could be explicit non-compete agreements or provisions that require the public
sponsor to reimburse the private entity for lost revenue due to a competing (usually unplanned)
facility. If a statute explicitly forbids a PPP agreement from containing a non-compete provision
or requires the state to maintain a free, competing route for each PPP project that state receives a
score of minus one. For example, North Carolina’s law states that:
The Department shall maintain an existing, alternate, comparable nontoll route corresponding to each
Turnpike Project constructed pursuant to this Article.
If there is no express provision it receives a 0.
Possible scores: -1, 0, +1
Justification: It is highly unlikely that any private sector entity would invest significant resources
and effort in a multi-decade transportation project if the public sector was allowed to build a
42
competing free facility (Leonard Gilroy testimony reference). This is a risk that is better
managed by the public sponsor, as they know more about their future transportation plans than
the private entity. Thus, any blanket provisions that restrict the use of non-compete and
competing facilities agreements are inherently discouraging to private sector investment.
FUNDMIX: We give a state +1 if it allows both the public and private sector to contribute to the
financing of a PPP project. For example, the Delaware statute contains this provision:
(1) The Department is authorized, notwithstanding any other provision of this Code, to (i) use any federal,
state or other funds, including without limitation funds obtained from or through the Delaware
Transportation Authority, any loans from the Public-Private Initiatives Program Revolving Loan Fund
established in § 2912 of this title and federal transportation funds, to finance, secure, guarantee, service
project debt or repay project costs; and (ii) do such things as necessary and desirable to maximize the
funding and financing of such projects, provided that private capital participation in the total capital cost for
each project shall be negotiated with the other terms of the agreement.
A state receives a score of minus one if either the public or private sector must put up 100
percent of the financing, and if there is no express provision the state receives a zero.
Possible scores: -1, 0, +1
Justification: One can imagine a great number of projects that would not be profitable if the
private sector was required to put up all of the initial financing, but that would become profitable
if their share of the financing was reduced by an infusion of state, local, or federal funds
(Leonard Gilroy testimony reference). Many projects are so large that they simply cannot be
financed entirely by private money (Nossaman key elements reference). Allowing both public
and private funds to be combined on a PPP project is an element that is attractive to the private
sector.
CONFIDENT: A state receives a score of +1 if the PPP statute contains a provision that protects
the confidentiality of proprietary information contained in a private entity’s proposal. Many
states allow the private entity to identify which parts of the proposal it considers trade secrets,
and then discloses the rest to the public. For example, the Washington statute contains this
provision:
A proposer shall identify those portions of a proposal that the proposer considers to be confidential,
proprietary information, or trade secrets and provide any justification as to why these materials, upon
request, should not be disclosed by the authority. Patent information will be covered until the patent
expires. Other information such as originality of design or records of negotiation may only be protected
under this section until an agreement is reached. Disclosure must occur before final agreement and
execution of the contract. Projects under federal jurisdiction or using federal funds must conform to federal
regulations under the Freedom of Information Act.
A state that subjects an entire proposal to disclosure receives -1, and a state with no express
provision receives a score of 0. (Note: I don’t know if any states do this, but a state that keeps an
entire proposal confidential should not get a +1, as this creates a lack of transparency and public
distrust in the process, which the private sector would not favor).
Possible scores: -1, 0, +1
43
Justification: Subjecting the entirety of private sector proposals to public disclosure would create
a free riding problem. That is, no firm would be the first to initiate a proposal if the other firms
could simply copy it and add a few elements of their own. However, keeping the entire proposal
secret creates a lack of transparency that could undermine public support for the process. As a
result, the states that are the most enabling to private investment are those that allow certain
proprietary aspects of proposals to remain confidential.
PRIORLEG: We give a score of minus one to any state that gives an entity other than the public
sponsor (such as the state legislature) the ability to reject a proposal. For example, Minnesota
gives veto rights to any governing body through which the proposed project passes:
THE GOVERNING BODY OF A COUNTY OR MUNICIPALITY THROUGH WHICH A FACILITY
PASSES MAY VETO THE PROJECT WITHIN 30 DAYS OF APPROVAL BY THE COMMISSIONER.
A state that does not give an entity other than the public sponsor rejection rights receives a +1.
We do not count approval by the governor as prior legislative approval.
Possible scores: -1, +1
Justification: Requiring legislative approval of individual PPP projects undermines one of the
primary purposes of having a PPP law, which is the reduction of political risk. Such
requirements are discouraging to private investment because they subject the private entity to the
risk that their proposal will be rejected by the legislature after they have spent significant time
and money in the proposal development and bidding processes.
PILOTONLY: A state receives a score of minus one if it puts a limit on the number of PPP
projects than can be developed or limits the PPP approach to specifically identified projects. A
state that does not put a limit on the number of projects receives a +1.
Possible scores: -1, +1
Justification: While the pilot approach may be a good way for states to experiment with PPPs
and learn from their experiences, it is generally regarded as discouraging to the private sector.
Limiting PPPs to demonstration projects is a signal that the state has not fully committed to its
PPP program, and leaves doubt as to whether the state is committed to following through with
such projects (Fishman, Major Legal Issues for Highway PPPs reference).
44