The Potential Effects of Clean Elections Laws on Legislative Behavior:
A Sketch of a Research Design
Thad Kousser
UC San Diego
If clean elections laws can fundamentally alter political systems, then evidence of the
changes that they bring must be present in the behavior of legislators. When electoral
competitiveness rises, this should spur an increase in the responsiveness of elected officials
to the demands of their constituents, observable in their voting patterns. In order for the
direction of policy to shift, legislators must introduce different types of bills or decide on
them differently. If public finance laws affect the role or potency of political parties, this too
will alter the behavior of legislators.
Yet even though changes in legislative behavior should be among the key effects of
the clean elections laws now being implemented in several US states and cities, little research
has been done so far in this area.1 Most likely, this is because the reforms are so recent that
only now have legislatures established a record of operation in sessions held after elections in
which clean money grants played a widespread role. Both the Maine and the Arizona
programs did not go into effect until 2000. Another complicating factor is that the impact
of campaign finance laws on legislative voting is notoriously difficult to isolate. The link
between contributions and roll call votes presents a well-known chicken and egg problem.
Campaign finance researchers are interested in isolating the “treatment” of money, in
measuring how a grant or contribution causes a member to vote differently than she would
have if she had not received it. Yet we cannot simply compare the behavior of those who
get the money with those who do not, because the process of getting it is nonrandom.
Indeed, there is little research on the legislative effects of any form of campaign finance activity or regulation
in the states, according to Ramsden’s (2002) review of the literature.
1
This “endogeneity” is well known in the literature on the influence of interest group
contributions, though the challenge to inference that it presents is not always taken seriously.
Donors contribute to legislators who are sympathetic to their cause. We observe that
legislators receive the money, and then see them voting in line with the interests of the
donor. The question is whether they voted with the donor because they got the money, or
whether they got the money because their past behavior and statements indicated that they
would vote with the donor. Ansolabehere, de Figueiredo, and Snyder (2003) review the
Congressional literature on this question, showing that many that claimed to find effects of
contributions had not investigated this ambiguity. Using statistical techniques tailored to
resolving this dilemma, they find that evidence that contribution influence roll call voting
disappears when the endogeneity is taken seriously.
Scholars who wish to study the legislative impact of clean money laws face a
challenge that presents a variant on the traditional problem. Instead of asking whether or
not legislators who get money from a particular interest group vote to further the group’s
narrow objectives, we need to investigate whether or not those who accept clean money
grants behave according to the broader demands of their constituents. But note that who
gets the money, who falls into our treatment group, is still not chosen randomly. In 2002 in
Maine, for instance, 41% of legislators took the grants and 59% did not (General
Accountability Office, 2003). There could be systematic differences between these
legislators. Those who did not take the grants may be those who expected to raise much
more money from campaign contributors, possibly because they already had positions on
policies that they knew would be attractive to a large group of donors such as labor unions,
business organizations, environmentalists, or a resource extraction industry. If they
eventually voted with one of these groups, it may be because they took the contributions
rather than the public grant. But it is also plausible that their intention to vote in that
manner gave them the opportunity to turn down the grant in favor of larger campaign
contributions. This means that attempting to gauge the impact of clean elections laws by
making the most obvious behavioral comparison – contrasting legislators who took public
money with those who accepted private contributions – will be problematic. This inferential
obstacle may not loom as large as it does in similar studies of interest group influence, for
reasons that I will discuss below, but it is still present. To draw careful conclusions about
the effects of clean elections laws on state legislatures, we will need to follow the lessons and
techniques of the wider literature on campaign finance.
I will begin this essay by exploring some of these techniques in a section that looks at
participation in a clean elections program as an independent variable. I will also address two
additional complexities that come to mind when thinking about the causal impact of these
public grants. The first is that they may exert their effects through two pathways; by
changing the behavior of legislators already in office and by attracting new types of public
servants. In order to determine how clean election laws change politics rather than merely if
they do, it is important to set up a research design which will differentiate between these two
potential effects. The second complexity created by the political realities of implementing
public finance laws is that independent expenditures may allow interest groups or parties to
exert just as much influence on legislators who accept clean elections grants as have on other
members. Recognizing and testing for this influence is necessary in order to create a clean
test of clean election reforms.
The second half of the essay focuses on the effects of these laws, proposing a
number of dependent variables. It begins with some of the more obvious measures, such as
party support in roll call voting patterns and adherence to the agendas of well-funded
interest groups. I also discuss ways of gauging less direct effects, which may or may not be
worth gathering data to explore. These including committee voting behavior, changes in
committee assignment patterns, competition for leadership slots, patterns in bill authorship,
levels of access granted to interest groups, and legislative oversight of the executive branch.
I conclude by suggesting one additional path for future research on the legislative impact of
clean election laws.
I. Clean Elections Laws as a Causal Variable
They key causal inference that we are trying to draw is to whether or not the act of
accepting clean election funding causes legislators to behave differently than they would
have if they relied on private contributions. The most obvious empirical comparison,
between the behavior of accepters and non-accepters, may not allow us to make this
comparison. As research on the influence of interest groups on Congress has noted, money
may cause votes, or expected votes may direct the flow of money (Herndon 1982, Grier and
Munger 1986). In my view, we have three options for dealing with this obstacle.
The first is to think hard about what makes accepting clean elections grants different
from receiving interest group contributions and to question whether or not the acceptance
of these grants is actually endogenous to systematic differences between legislators. We may
conclude that it is not, or that we can measure all of these differences. After all, since
qualifying candidates from across the ideological spectrum can take clean money, the link
plaguing traditional studies – between the specific policy positions of lobbyists and the
legislators to whom they donate – is severed. There are legislators from all points of the
spectrum both accepting and rejecting the grants. Controlling for district preferences and
other member characteristics, there may not be any significant differences between accepters
and rejecters. If this is the case, we can compare their behaviors, ceteris paribus, and draw a
straightforward inference about the impact of grants. Arizona’s multimember lower house
districts can make such a comparison especially clear, when paired legislators who represent
the same constituents make different decisions about accepting clean elections funds.
Yet if some unmeasured characteristic such as “potential to raise large sums in
private contributions” distinguishes accepters from rejecters, ignoring this endogeneity will
bias our estimates of the effect of clean money. If we agree that this is a problem, a second
approach that we can take is to conduct a time series analysis that tracks individual legislators
before and after the implementation of clean elections laws. This will hold constant their
potential to raise private money, as well as their district preferences and other characteristics.
If nothing else changes from before to after the implementation of the laws, this will be our
strongest research design. Unfortunately, time brings other changes to legislatures. From
one session to another, the legislative agenda can shift, along with levels of party
competition, policy demands, and the legislative-executive dynamic. These problems will be
present everywhere, but our cases pose particular challenges to conducting clean time series
analyses. In the same year that Arizona’s clean elections law first went into effect (2000), the
state’s term limit law was also implemented, and a new redistricting commission was created
(Mayer, Werner, and Williams, 2004). In both Arizona and Maine, 2002 brought new
legislative districts. With the exception of the post-2000 session in Maine and the session
that is currently being held, all is else is clearly not held constant in a time series analysis of
individual legislators.
A third option for addressing endogeneity in the link between money and votes is to
follow Chappell (1981) and Ansolabehere, de Figueiredo, and Snyder (2003) by taking an
instrumental variables approach. This technique identifies a set of instruments which can
predict (in our application) whether or not a legislator will choose to accept clean money
grants, but which should have no independent effect on that legislator’s voting behavior.
These instruments are then used to predict the legislator’s financing choice, and the
predictions are used in a two-stage model to explain a legislator’s voting behavior.
Ansolabehere, de Figueiredo, and Snyder (2003) use the political competition that a member
faces2 and her power3 within the legislature as instruments for the amount candidates receive
in business and labor contributions. They then estimate a two-stage least squares model that
ultimately explains variation in the ratings that legislators receive from the US Chamber of
Commerce. We could follow a similar strategy. The level of competition that a legislator
faces and her power within the body should affect her decision about whether or not to take
the grants. Then we could use these predicted probabilities to explain variation in ideal point
estimates, interest group ratings, and other roll call measures.
Regardless of which of the three strategies we pursue, we will explore whether or not
accepting clean money grants changes the behavior of legislators. But we should also pay
particular attention to another causal pathway through which clean money laws might work.
They may bring a new type of legislator to state capitols, either by making running for office
more attractive to those who had been discouraged by the cost of campaigning, or by giving
poorly-funded candidates the opportunity to get out their message and win. To test for
these effects, we will likely need to compare new legislators elected after the implementation
of clean elections laws (and participating in them) with those who represented the same
districts in the prior era. This will face the aforementioned obstacles to time series analysis
They measure competition by the total campaign spending of the legislator’s opponent, her general election
vote share minus 50%, and whether or not she faced a general election opponent.
3 They measure power by recording whether or not a legislator was a party leader, a committee chair, or a
member of a fiscal committee.
2
in these states, but, since it examines one of the key claims made by clean elections
advocates, seems to be worth pursuing.
A final consideration for treating participation in a clean elections program as a
causal factor is how to treat candidates whose campaigns are supported by large independent
expenditures. In Maine, the prominent role that these interest group-led shadow campaigns
have had in competitive districts has been well documented. According to La Raja (2004),
44% of House contests and 60% of Senate races featured independent expenditures in
Maine. Even if a candidate forgoes private financing in exchange for a clean elections grant,
she may still be influenced by an interest group that makes a considerable independent
expenditure on her behalf. We should put such candidates in a category that is separate
from the category for those who take clean money grants and receive no outside support. A
reasonable dividing line defining a “significant” independent expenditure could be when it
totals 25% of the value of the clean money grant. Legislators who accepted public grants
but were supported by this much money from an interest group may be just as likely as
privately-funded candidates to behave as if they are under the group’s influence.
II. Where to Look for Legislative Effects
The literature on campaign contributions and Congressional behavior suggests many
places to look for the influence of interest groups, though it generally finds little clear
evidence that they hold sway. This section proposes a series of hypotheses that we could
test in states with clean elections programs. Most are applications of Congressional studies
to the states, though a few present new tests that are specific to state legislative dynamics or
to the predictions of clean elections advocates.
• Legislators who accept clean elections grants will be less likely to vote as if they are influenced by
particular interest groups, compared with legislators who take contributions from these groups. Testing this
hypothesis could proceed in the manner that is common in many Congressional studies:
Regress legislators’ support scores from an interest group that is active in the state upon
their party membership, their district’s partisanship, and their fundraising activity. This
model could be a simple linear regression, a two-stage model, or a panel analysis with
legislator fixed effects, depending on our approach to concerns about endogeneity. If we
found that legislators who accepted contributions from a group scored significantly higher
than those who did not, holding other factors constant, we would conclude that clean
elections grants served as a bulwark against moneyed influence. Since the category of
legislators who did not receive money from the group would include both clean money
grantees and privately-financed members who did not attract funds for that specific group,
we would need to repeat this exercise using scores and contributions from interest groups
with varying ideological positions. Once an initial dataset is constructed, though, this will be
trivial. Gathering scores from interest groups in prior sessions is possible, but will take some
effort. In the past, I have had trouble getting groups in Maine to dig these up, even when I
visited them in Augusta, but I located a legislative almanac which printed a variety of scores
as of 1997 (Maine People’s Resource Center, 1997). If it has been published consistently
since then, this data collection will be trivial.
• Legislators who take donations for a particular interest group will be more likely to cast committee
votes against bills which that interest group opposes, compared to legislators who accept clean elections grants.
While the political science literature has found little evidence that interest groups can turn
contributions into support for their bills on the floor, my intuition from my days as a
legislative staffer is that money often translated into opposition in committee. The power to
kill bills is vital, but evidence of the carnage never shows up in interest group scores based
on floor votes. Yet it can be observed if committee votes are public and if a high
contributing interest group either registers its opposition to bills with committee staff or
publishes a member newsletter advertising its attempts to stop legislation. If so, we could
create our own measure of interest group support scores in various committees, and estimate
the impact of campaign finance activity on these scores in a way that parallels our analysis of
interest group support on the floor.
• Legislators who accept clean elections grants will be less likely to follow the party line on roll call
votes, compared with legislators who receive substantial support from parties or party leaders. Clean money
programs may free members from the influence of their party as well as from interest
groups. In order to investigate this, we would need access to a dataset with the full set of
contested roll call votes for a session. Using this dataset, we would conduct a number of
tests for party effects. First, we could create party support scores for each legislator in the
way that Congressional Quarterly compiles them for members of Congress, and analyze them in
much the same way that we analyze interest group support scores. Second, we could
estimate each legislator’s ideal point using some form of the Nominate procedure (Poole,
2005) and see whether those who accept clean money grants are more likely to stray from
their party’s median, controlling for their district’s partisanship. Third, we could identify
votes that brought “party rolls” – roll calls in which a majority of one party’s caucus was on
the losing side of a vote (Cox and McCubbins, 2005) – and ask if clean money grantees were
more likely to bolt from the party and allow it to be rolled. Much of the roll call data
necessary to conduct these analyses has already been collected. Gerald Wright’s project at
Indiana University has already released roll calls from all states in the 1999-2000 session, and
will soon release the 2003-4 session. Nolan McCarty’s project at Princeton is gathering roll
calls from all states for the 2001-2 and 2002-3 sessions.
• Legislators who accept clean elections grants will be more likely to vote in line with their
constituents than other legislators. This hypothesis lies at the heart of the claim the clean elections
will make legislatures more representative of voter preferences, but will be difficult to test.
One way would be to look at the match between a legislator’s district partisanship and her
ideal point estimate. The problem is that because these two measures are not on the same
scale, it is impossible to know what translation of partisanship into ideal point denotes a
perfect level of representation. An option we have in direct democracy states that report
initiative results by legislative district is to attempt to create a common ideal point estimate
by looking at how a district votes on issues that also came up on the floor of legislatures. I
have advised undergraduate projects that do this in a simple way for California, and I believe
that Lillard Richardson and Anthony Knownes have made a more sophisticated attempt in
Arizona. With ideal point estimates for both legislators and districts, we would see whether
clean money grantees were more faithful representatives. (Of course, it is entirely possible
that the opposite might be the case, because listening to and being influenced by
contributors could be an efficient way of learning about what your district wants and needs.)
• Lobbyists will have greater access to legislators who take private contributions than they will to
legislators who accept clean elections grants. Although scholars have found little evidence that
contributions buy influence, some have found that money leads to greater access. Langbein
(1986) shows that members of Congress spend more time with lobbyists who contributed to
their campaigns. To test for this sort of effect, we would have to get legislators to
participate in a survey about how they spent their time and whose policy advice they took. I
see many challenges in administering this sort of survey. Response rates for state legislator
surveys are not very high, and would likely be lower for such a delicate matter. I would also
worry about priming effects that push clean money grant recipients to declare their
independence from lobbyists if they know this is a survey about clean elections. But if we
did conduct it, this sort of survey would be useful for figuring out where clean money
legislators turn for advice. Arizona and Maine are term limits states, and it is almost certain
that all clean elections states will be term limits states since both reforms are usually made
through the initiative process. Where do term limits rookies who have no institutional
memory turn for information if clean money grants severs their ties with lobbyists? If they
become more reliant on the executive branch for information, this could be an undesirable
side effect of clean money laws.
• The subject matter addressed in bills authored by legislators who accept clean elections grants will
be significantly different than the issues taken on by other legislators. It is possible that public financing
changes the legislature’s agenda. Using online bill databases, we could code the subject
matter of bills authored by different types of legislators to see whether they are more or less
likely to address the fields in which major interest groups are active.
• Legislators who accept clean elections grants will be less likely than other legislators to be elected to
key floor leadership posts in the majority and minority parties. According to Bowser et al. (2003),
leadership battles in post-term limits legislatures are fought primarily with money. Since
those who accept clean elections grants do not have any money to spread around to
members of their caucus, they may effectively remove themselves from consideration for
leadership slots. If this is the case, we should rarely if ever see them capture top slots.
• Party leaders will be less likely to assign legislators who accept clean elections grants to powerful
committee slots. Here is another way in which legislative leaders may be adapting to clean
elections laws and dampening their effects. Since members who accept the grants have little
to give the caucus, they may have little chance of obtaining seats on key committees. By
gathering the same legislative rosters that we would need to get to examine leadership
patterns, we could look at committee assignments.
• Legislators who accept clean elections grants will be less likely to engage in oversight of executive
agencies. This could be a negative effect of clean money laws. If legislators who accept grants
are less responsive to interest groups, they may be less energetic in pursuing the legitimate
complaints that these groups have about policy implementation (or the lack thereof).
Oversight is difficult to quantify, but we may be able to find records of legislator-initiated
audits and legislative requests for information (both of which are available in California).
III. Further Avenues of Research
A final thought I have is that the Maine and Arizona clean elections laws appear to
be quite similar. It may be that every clean election law follows the same mold, but it is also
possible that there is significant variation in the provisions (the size of grants relative to the
size of the electorate, the number of signatures required to qualify for grants, provisions to
counter large opposition spending or independent expenditures). If so, much of this
variation may come in city clean elections ordinances. It may be worth discussing how the
measures that we devise for studying legislative behavior and other aspects of state politics
can be applied to local government. This could give us the ability to discover not only
whether or not clean elections laws have their intended effect but also which types of public
financing work best.
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