The Honeymoon Effect:
Investigating Individual Members’ Propensities to Support the President
Justin Buchler
Department of Political Science
Case Western Reserve University
Justin.buchler@case.edu
Casey B. K. Dominguez
Department of Political Science and International Relations
University of San Diego
caseydominguez@sandiego.edu
Abstract
Conventional wisdom has long held that newly elected presidents have a so-called
“honeymoon” with the Congress. Recent research has modified this conventional wisdom by
showing that only presidents who face divided government have higher win rates during the first
hundred days of their first year in office than during other periods. Existing work, though, does
not identify the mechanism that produces this effect. In this preliminary paper, we search for the
origins of the honeymoon effect by comparing Members’ of Congress presidential support scores
in a president’s first and second years in office. We find that measuring the honeymoon effect at
the level of individual Members of Congress gives a very different picture of who had a
honeymoon, and that the honeymoon seems to be driven by increased presidential support from
marginally party-loyal Members of both parties during the first year in office.
Paper prepared for delivery at the 2005 Annual Meeting of the American Political
Science Association, Washington, D.C., September 1-4, 2005.
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In this paper we search for the origins of the president’s honeymoon with Congress by
examining the behavior of individual Members of Congress. The traditional honeymoon
hypothesis is that the immediate post-inaugural period is often characterized by rhetoric of
bipartisan cooperation, a coming-together after a divisive election. During the first year a new
president has not had many opportunities to make enemies or alienate potential allies, and so he
might win the support early on of people who will oppose him later in his term. Therefore, the
honeymoon effect might be due to an initially high level of popular and professional prestige,
and because of deference from Members of Congress who will later become opponents
(Neustadt 1990; Mueller 1973). This implies that some Members of Congress, perhaps
marginally partisan Members of both parties, initially support the president out of a sense of
deference to his election, and gradually come to oppose his policies. If this explanation for the
existence of a presidential honeymoon with Congress is correct, we should be able to observe
over-time changes in degree to which individual Members of Congress support the president’s
positions on roll call votes. If presidents do have higher support scores during their first year (a
honeymoon) but are not uniformly supported more in their first year by a particular group of
Members of Congress, then any added successes in their first year must be due to their more
effective coalition-building in their first year, and not to any systematic deference by Members
of Congress.
Previous Work on The Honeymoon Effect
In their study of the press’ treatment of the president, Michael Baruch Grossman and
Martha Joynt Kumar (1981, 259-265; 275-279) found that during the inaugural year, the press
covered the president in greater volume and in a more positive light than later in the term. Their
2
analysis showed that early coverage was favorable to presidents because reporters rely heavily
on official White House briefings while they develop their own administration sources, and
because reporters and editors believe announcements of policy proposals and profiles of new
Members of the administration are inherently newsworthy. If conflicts or scandals emerge in the
first few months of a presidency, the press will cover them in ways that might be perceived as
negative toward the president, but barring major mis-steps, presidents can expect their press
coverage to be neutral or positive. This rosy relationship diminishes as reporters develop
informal sources within the administration and as political conflicts emerge over specific
proposals made and results achieved. Research by Cook and Ragsdale (2000) and by the Project
for Excellence in Journalism (2002) indicates that the press’ honeymoon with the president may
have diminished over time, but the effect noted by Grossman and Kumar is likely to persist in
some form.
Partially in response to that favorable press coverage, the president has been found to
have a honeymoon with the public during his first few months in office. Approval ratings are
stable and higher than average during their first few months. Most presidents achieve higher
approval ratings at some later point in their administration, but those ratings are based to some
degree on the president’s record of achievement, which new presidents lack. At the beginning of
an administration, when polls ask whether respondents approve of the job the president is doing,
partisans of the president respond by saying they approve of his performance, as do a sizeable
number of independents and opponents who will change their minds once he actually builds a
record on which to make judgments. Many others offer “no opinion”(Brody 1991, 28-44).
Research also shows that presidents have higher “success rates” when they take positions
on bills before the Congress during their inaugural year than they do later in their terms
(Dominguez 2005; Lockerbie, Borrelli and Hedger 1998). Recent work also suggests that
presidents who face divided government may experience a larger honeymoon effect, at least in
3
their first hundred days in office (Dominguez 2005). They do not appear to benefit from
increased legislative output in their first hundred days in office (Frendreis, Tatalovich, and
Schaff 2001). The president’s apparent legislative advantage has been documented, but not
thoroughly explained. Do the inaugural year’s increased public approval ratings drive Members
to support the president? Do Members with different partisan, ideological, district, and career
characteristics differ in their susceptibility to the honeymoon effect? These questions must be
answered in order to fully understand the honeymoon phenomenon.
Presidential scholars have devoted considerable attention to the president’s role as
legislative leader. Some argue that presidential success in Congress should be explained using
presidency-centered variables, such as whether the president is seen to be responsible for a
policy area (for example, Pritchard 1983), and whether the president prioritizes a given policy
area or bill (Covington, Wrighton and Kinney 1995).1 It is certainly the case that the honeymoon
effect could depend on presidential skill, and would be a more significant phenomenon if it
affected presidents’ ability to win enactment of proposals that are important to their programs.
The lack of readily accessible data on what bills and votes are “presidential priorities” makes this
presidency-centered approach more difficult.
Other studies have attempted to explain presidential success using more or less Congresscentered variables. Partisanship, ideology, and district influences have all been used to explain
why individual Members vote with or against the president (Fleisher and Bond 1992 and 1996,
Cohen 1982, Pritchard 1986).Both partisanship and ideological coalitions have been seen to have
effects on presidential support (Fleisher and Bond 1996).
Here, we take a Congress-centered approach, and focus our attention on individual
Members. If we try to measure the honeymoon effect by looking at a presidential “batting
average,” we are essentially basing our analysis on ecological inference. When we look at the
success or failure of a bill, that measure is an aggregation of 435 House votes and 100 Senate
Public prestige, measured as the president’s approval rating, has often been thought to influence Members of
Congress to support the president, although recent research seems to discount that notion (Collier and Sullivan
1995).
1
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votes. If several bills the President supported acquire a majority, then they will show up as
“hits” in the presidential batting average, but if the Members voting “yes” on the bills are not the
same Members, then can it truly be said that any individual Member of Congress is giving the
President a honeymoon? Furthermore, if that is the case, then is the honeymoon effect really
anything more than an unusual effect of aggregating votes to the level of the bill? Practically, a
president cares primarily about his batting average, but analytically, if we want to test the theory,
we must also look at the behavior of individual Members of Congress. Additionally, it makes
sense to focus on Member behavior because the honeymoon effect has been shown to exist
across presidencies, regardless of particular strategies or sets of bills prioritized by different
presidents.
With that in mind, we address two primary questions in this paper. First, we address the
measurement issue. Do individual Members of Congress (as opposed to Congress as a whole)
support the President’s legislative agenda more strongly shortly after the President takes office?
In doing so, we find several interesting differences between measures of a honeymoon based on
individual vote scores and measures of a honeymoon based on batting averages.
Second, after observing variation over time in Members’ propensities to support the
President, we begin to look for explanations for why some Members might give the President a
“honeymoon,” and why other Members might not. In particular, we consider the “loyalty
hypothesis.” Since the President is also his party’s figurehead, Members of the President’s party
who are loyal to the party should also be consistently loyal to the President, so they should not
become less supportive over time. Similarly, Members of the opposing party who are loyal to
their own party should consistently oppose the president, and should not be inclined to give the
President the benefit of the doubt, even shortly after the election. So if any set of Members
systematically give the President a honeymoon, it should be the marginally loyal Members of the
president’s party, and the marginally loyal Members of the opposition party.
A subsidiary to this hypothesis is that it is possible that the honeymoon effect is driven
exclusively by increased support for a new president among his partisan opponents (perhaps the
5
less party-loyal among them). Dominguez (2005) found that the honeymoon effect for presidents
from Kennedy through Clinton was most pronounced for those who faced Congresses controlled
by the opposing party. If we find that a Member’s party loyalty affects his or her propensity to
give a new president a break, and if that effect is most pronounced for partisan opponents of the
president, that would explain the origins of the divided government honeymoon finding.
Methodology
Because we are primarily concerned with the behavior of different Members of Congress,
we rely on presidential support scores, which consist of the percent of votes on which each
Member of Congress votes with the president’s stated position. We measure the degree to which
individual Members of Congress support the President in any given year with Congressional
Quarterly’s Presidential Support scores (adjusted for absences). In this initial set of analysis, we
examine patterns in support scores for Presidents starting with Carter and ending with George W.
Bush. As this project continues, we will extend our analysis to earlier Presidents. Our primary
approach is to compare Members’ support scores in the first year of a president’s term and in the
second year of a president’s term. If there is a “honeymoon effect,” then Members will tend to
vote the way the President wants more frequently during the President’s first year. Thus, we can
measure an individual Member’s “honeymoon effect” by calculating the following:
honeymoon = (support score in first year) - (support score in second year)
If a Member has a positive score on this variable, that means he or she supported the
President more often during the first year than during the second year of the President’s term.
This is what the honeymoon hypothesis would predict.
It should be noted that since we are using scores that are created for each year, we are not
testing the “100 days” hypothesis. In fact, if a president’s honeymoon is during only the first
6
100 days, our model will underestimate the honeymoon effect because our first year contains 265
days (minus the time before inauguration) outside the “honeymoon” period.
The benefit of this method is that it allows us to side-step the methodological issues of
time-series cross-sectional analysis by creating a single cross-section for each president. Ideally,
and in the model towards which we are working, we would create a single time-series crosssectional model that tracks each Member’s support score throughout their career in Congress.
Aside from the normal problems associated with TSCS analysis, in this case, we would have a
unique problem. Each time a new president takes office, we would have to either “reset” the
time series, or create a set of “president dummy variables” with which to interact any other
variable. The problem with the first approach would be that cross-sections would not be
independent of each other since there would be several cross-sections for the same Member. The
result would be a multi-level model, which is problematic even without the TSCS component.
The problem with the dummy variable approach is that since we would have to interact these
dummy variables with a variety of other variables in order to conduct our analysis, results would
not be easily interpreted, and the method is not substantively different from running separate
regressions for each presidency, so it doesn’t get us much analytically beyond the approach of
this paper. The “first difference” approach of this paper avoids the econometric pitfalls of
combining TSCS analysis with a multi-level model while giving us results that can be easily
interpreted.
Results
Our first basic question is whether or not we have variation to explain. Previous studies
have only found that a honeymoon exists in presidential success scores, or win rates, in
Congress. If Presidential Support Scores (based on individual Members’ votes) do not change
very much between the first and second year of a president’s term, then there is no honeymoon
7
for our purposes. Table 1 below provides Pearson’s correlation coefficients between support
scores in the first year of a president’s term and in the second year of a president’s term.
Table 1: Correlations between presidential support in first and second years
Carter
Reagan
Bush 41
Clinton
Bush 43
All MCs
.9187
.9006
.9412
.9487
.9752
President’s Partisans
.8605
.7257
.7422
.7521
.6867
President’s Opponents
.8657
.8685
.8689
.8563
.8418
As Table 1 indicates, there is a great deal of consistency in presidential support scores in
the first and second years of a president’s term. When we take all Members together,
correlations for each president are over .9, and go as high as .9752, which is the equivalent of an
R2 of .95. Thus, it does not appear that there is much variation to explain. When we look at
correlations separately by party, some differences emerge, although this may be due to the
smaller sample sizes. While the correlations are the same for both parties in Carter’s term, there
seems to be an interesting pattern with subsequent presidents. The correlation between first and
second year support scores for opposing party is consistently higher than the correlation between
scores for the president’s party. The correlation for Members of the opposing party is
consistently around .85, but the correlation for Members of the President’s party fluctuates
around .7. So, it would seem that there is more variation from first to second year within the
president’s party than within the opposing party. This suggests that the honeymoon might
originate within the president’s party, perhaps with the more marginally loyal Members of his
party, rather than with his partisan opponents, as would be suggested by the finding of a stronger
divided government honeymoon. Of course, this is merely suggested by the correlations above.
While there is not a great deal of variation to explain, there is some, and thus there is still
a possibility for a “honeymoon effect.” Using the method described earlier, we calculate a
“honeymoon effect” for each Member of Congress for each President. Descriptive statistics for
honeymoon effects are provided below.
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Table 2: Descriptive Statistics for Measure of “Honeymoon Effects”
(CQ Pres. Support Score in 1st year)-(CQ Pres. Support Score in 2nd year)
Carter
Reagan
Bush 41
Clinton
Bush 43
All Members
President’s Party
Opposing Party
Mean
S.D.
Mean
S.D.
Mean
S.D.
3.3796
8.3664
1.7345
8.3369
6.6020
7.4600
2.3304
8.2369
1.9033
9.2441
2.7092
7.3282
9.5866
7.5460
6.2841
8.2862
11.8483
6.0432
-3.2459
7.6264
.6353
5.8333
-8.8857
6.3208
.5394†
6.8493
2.5747
6.2603
-1.5905
6.8206
All means are significantly different from 0 at p<.05 except †
Positive coefficients signify a “honeymoon”.
Almost all of the averages are positive, and significantly different from 0, which is
consistent with the honeymoon hypothesis. In general, Members of Congress are more
supportive of the President during his first year in office than during his second year. The largest
effects are for George H.W. Bush, and it is interesting to see that most of his “honeymoon” came
from Democrats, whose support scores were nearly 12 points higher in his first year than in his
second year. Since these scores indicate the percent of the time MCs vote the president’s way,
this means Democrats voted Bush’s way 12 percentage points more of the time during his first
year than during his second year. While Republicans seemed to give him a boost as well in his
first year, that boost was only half the size of the boost for Democrats. The only comparably
sized honeymoon effect was for Carter. Republican support scores were 6.6 points higher in his
first year than in his second, so again, the honeymoon effect came from the opposing party.
Note, though, that there was more variation to explain within the president’s party, as discussed
earlier, so while this is theoretically sensible, it is somewhat surprising given the results in Table
1. However, these results indicate that there is a honeymoon effect, and support the “opposing
party” hypothesis that they honeymoon should be expected to come the party opposed to the
president rather than the President’s party.
It is important to note, though, that there are three negative numbers in Table 2. One of
them is easy to explain. Democratic support for George W. Bush went up from his first to his
second year, giving us a negative “honeymoon effect”: -1.59. While small, it is statistically
9
significant, and perhaps can be explained by 9/11. Most of Bush’s first year was pre-9/11, and it
is possible that a post-9/11 boost among Democrats had most of its effect in his second year.
Interestingly, despite 9/11, Republican support scores for Bush still went down from his first to
his second year. Perhaps Republicans gave him a honeymoon, and the decline was mitigated by
9/11. After all, a decline of 2.57 points is not a staggering loss. It is also interesting to note that
Democratic and Republican effects for George W. Bush somewhat canceled each other out, so
when we look at all Members of Congress together, there was no statistically significant
difference between support scores in his first and second years.
The other negative honeymoon effects to explain are for Clinton. While Democrats gave
Clinton a very slight (but still statistically significant) honeymoon boost, on average,
Republicans were much more supportive of his agenda in his second year. Republican support
scores were nearly 9 points higher during his second year than during his first. This is the
opposite of a honeymoon effect, and perhaps more indicative of a learning curve. Clinton’s first
year was marred by controversy over nominations and gays in the military, and he lost an
important vote on his economic stimulus package. Again, though, it is interesting to note that the
bigger effect came from the opposing party, even though the difference between the first and
second years was the opposite of a honeymoon. For all the presidents except George W. Bush,
whose first year included a major crisis, larger effects seen to come consistently from the party
opposing the president.
While consistent with the overall honeymoon hypothesis, and the partisan hypothesis,
these results are significantly different from the findings in Dominguez (2005), which measured
the honeymoon effect by looking at presidential success rates during the first hundred days of
each year. For example, the results of that paper indicated that Carter experienced the opposite
of a honeymoon-- his success rate in the first 100 days of his first year was 79.2%, but his
success rate in the first 100 days of his second year was 86.9%. In terms of his success rate,
Carter did not seem to have much of a honeymoon. In contrast, when we look at individual
Member support scores, Carter seemed to enjoy a significant honeymoon in his first year. Two
10
possible explanations present themselves. First, such a difference in findings might result from
the time periods examined. We compare presidential support scores for Carter’s entire first year
to scores for his entire second year, as opposed to comparing the first 100 days of his first year to
the first 100 days of his second year. However, if that difference were responsible for the
contrasting findings, that would mean that the actual honeymoon is in the second 265 days of the
president’s first year. In other words, perhaps the higher support scores in Carter’s first year
came in the second 265 days of the year, meaning that his success rate didn’t pick up until after
the first 100 days. While mathematically possible, this explanation does not seem theoretically
plausible. The more likely explanation is that while Carter’s support scores were higher in his
first year than in his second, those additional votes were not on the margins-- in other words, he
got more support, but on bills for which those extra votes did not make the difference between
bill passage and failure. Thus, we see that a measure of the honeymoon effect based on success
rates may obscure actual changes in Members’ voting patterns.
On the other side of the issue, by Dominguez’s (2005) measure of success rates, Reagan
experienced a fairly large honeymoon. During the first 100 days of his first year, he had a 100%
success rate, but only a 55.6% success rate in the first 100 days of his second year, while
presidential support scores were only about 2 points higher in his first year than in his second
year. However, this difference should not be the focus of too much attention since Reagan’s
success rate in the House in his first 100 days was based on only two votes.
A more important difference is in the analysis of Clinton. By Dominguez’s (2005)
measure, Clinton experienced a significant honeymoon effect when looking at his success rate.
During the first 100 days of his first year, his success rate was 95%, but only 85.7% in his second
year. However, by the measure of individual presidential support scores, he showed the opposite
of a honeymoon effect. Individual presidential support scores for Clinton, especially among
Republicans, were higher during his second year than during his first year. How can we
reconcile the appearance of a honeymoon with respect to success rates with the observation that
individual support scores for Clinton were lower during his first year than during his second
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year? First, it may be significant that success rate was only calculated for the first hundred days
of each year. It is possible that Clinton did very well during his first 100 days, and very badly
during the rest of his first year, and better the following year.
Another explantion for this difference may be that Clinton’s successes in his first year
may have come not from individual Members being more likely to support him, but from
efficiently cobbling together ad hoc coalitions during his first year that are different for different
bills. In other words, the votes against him in his first year were not on the margins. This
explanation seems at odds with the general belief that Clinton became more politically adept
after his first year in office. Of course, the “learning curve” prediction is the polar opposite of
the honeymoon prediction, but it seems that both have some support in the data. However he
accomplished this, it is quite surprising to see that Clinton managed to achieve more successes in
his first year in office even though presidential support scores were lower during his first year.
We can be fairly confident that there is a honeymoon effect, but based on the differences
between what we see looking at success rates and what we see looking at individual Member
support scores, the honeymoon effect is clearly more complicated than it might appear on the
surface, and these differences further demonstrate the importance of thinking through the
mechanics of how the honeymoon effect works, and on what level of analysis it works.
Why a honeymoon?
Now that we know there are effects to explain, the question is, what explains them? Why
do some Members give presidents a honeymoon and others not? Our primary hypothesis is the
loyalty hypothesis. As we argued earlier, we should expect Members of Congress who are less
loyal to their party, whichever party that is, to be more likely to give the president a honeymoon
effect. We test this hypothesis by regressing our honeymoon variable (first year support score
minus second year support score) on CQ Party Unity scores (absence-adjusted).2 A positive
2
We use the average of party unity scores in the first and second year of each President’s term.
12
coefficient would indicate that more loyal Members give the president a honeymoon, while a
negative coefficient would indicate that less loyal Members give the president a honeymoon.
We also include a control variable-- district presidential vote.3 We explored the hypothesis that
Members from districts in which the President polled well might be more likely to give the
President a honeymoon, but found little empirical support, and include it merely as a control
variable.
For each President, and for each party, we regress our honeymoon effect on party loyalty
and district presidential vote. We use OLS4 with robust Huber/White standard errors to correct
for heteroskedasticity.5 Since we are modeling a “first difference,” we are running a model
similar to a fixed effects regression that controls for ideology and constituent characteristics
since those factors should be invariant. Results are reported below.
Table 3: Determinants of the “honeymoon effect”: Carter
District Presidential Vote
SE
Party Loyalty
SE
Constant
SE
N
R2
F
President’s Party
.01
.04
-.18***
.02
13.98
2.72
286
.18
27.48
Opposing Party
.14
.09
.18***
.04
-13.91
5.87
146
.14
10.98
* p<.05, ** p<.01, *** p<.001, one-tailed probabilities
3 “District presidential vote” is calculated as the percentage of the two-party vote the president received in a given
congressional district. Data on district presidential votes were generously provided by Gary Jacobson.
4 Technically, the dependent variable in these regressions is bounded, which might suggest that the appropriate
method is tobit analysis, but observations are never 0 and only rarely 100, so there are virtually no censored
observations.
5 Errors in these models must be heteroskedastic if for no other reason than the ceiling effect. For example,
Members who are very loyal to the president in his second year cannot possibly have large honeymoon effects
because there is a limit on how much higher their scores can go, even if we don’t observe much censoring, so they
can’t have very large positive residuals. The reverse is true for Members who are very loyal to the opposing party.
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Table 4: Determinants of the “honeymoon effect”: Reagan
District Presidential Vote
SE
Party Loyalty
SE
Constant
SE
N
R2
F
President’s Party
-.17**
.07
-.31***
.04
36.05
4.93
191
.31
31.68
Opposing Party
-.04
.03
-.09**
.03
11.44
3.36
238
.04
4.08
* p<.05, ** p<.01, *** p<.001, one-tailed probabilities
Table 5: Determinants of the “honeymoon effect”: Bush 41
District Presidential Vote
SE
Party Loyalty
SE
Constant
SE
N
R2
F
President’s Party
-.23**
.08
-.16***
.03
32.62
4.33
176
.20
29.79
Opposing Party
-.06
.03
-.09**
.04
22.57
4.69
257
.02
2.78
* p<.05, ** p<.01, *** p<.001, one-tailed probabilities
Table 6: Determinants of the “honeymoon effect”: Clinton
District Presidential Vote
SE
Party Loyalty
SE
Constant
SE
N
R2
F
President’s Party
.06
.04
.08
.05
-9.66
3.42
255
.05
7.17
Opposing Party
-.15**
.06
-.11*
.05
7.71
6.28
175
.04
3.79
* p<.05, ** p<.01, *** p<.001, one-tailed probabilities
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Table 7: Determinants of the “honeymoon effect”: Bush 43
District Presidential Vote
SE
Party Loyalty
SE
Constant
SE
N
R2
F
President’s Party
-.01
.05
.58***
.11
-50.95
9.50
221
.27
16.68
Opposing Party
-.01
.04
-.09
.07
7.00
7.15
210
.02
1.17
* p<.05, ** p<.01, *** p<.001, one-tailed probabilities
Here, we find some support for the loyalty hypothesis. In most of the models, the party
loyalty coefficient is negative, and highly statistically significant, meaning Members who are
less loyal to the party (either party) are the ones who tend to give the President extra support
during his first year in office. There are two exceptions to this pattern: Jimmy Carter and George
W. Bush. For Carter, Republican loyalists were the ones who gave him a boost in his first year,
and for George W. Bush, Republican loyalists were the ones who gave him a boost in his first
year. Perhaps in both cases the honeymoon from very loyal Members rather than marginally
loyal Members was a response to the circumstances of the president’s election, Carter promising
change and challenging the Democratic establishment, and Bush having just survived the
Supreme-Court-decided election of 2000. Of course, this is merely speculation.
However, when interpreting the results for the loyalty hypothesis, we must remember that
party loyalty has been increasing since the 1990s, so the somewhat odd findings for George W.
Bush might be related to the fact that party loyaty is high, and has less variance than in the past.
A coefficient of .58 seems large (larger than the coefficient for any other model)-- after all, this
means that every additional point on the Party Unity score is associated with a .58 point first year
bump in Presidential Support scores. However, Republican party unity scores in the 2000’s are
very high, and have little variance. In the 2001-2002 period, Republican party unity scores had
an average of 93.45 with a standard deviation of 5.64. For the sake of comparison, Republican
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party unity scores in the first two years of his father’s term had an average of 76.71 and a
standard deviation of 16.28. It is difficult to separate the unusual .58 coefficient from the
unusually high and consistent levels of party loyalty.
The results for district presidential vote were inconclusive at best. When statistically
significant, the coefficients were negative, indicating that Members from districts where the
President received a high proportion of the vote gave him less of a honeymoon. However, the
results were not consistent throughout the data, and the variable was included primarily as a
control variable.
Additional hypotheses to consider
We only briefly explored the relationship between a president’s level of support within
the district and whether or not that district’s Representative gives the President a honeymoon.
Perhaps a more appropriate test of this hypothesis would be to look at the relationship between
how well the President polled relative to how well the Representative polled. If, for example, the
President out-performed the Representative, perhaps the Representative might take that as an
electoral mandate for the President. However, testing this hypothesis is more complicated than it
sounds because most Members of Congress face very weak challengers. Thus, it is possible, and
quite common, for a Representative to be in a somewhat marginal district and win by a larger
margin than the President, not because the Representative is more popular, but because he faced
no serious opposition. We are currently exploring modeling approaches to this issue.
Another hypothesis to consider is that the first-term Members of Congress, or at least less
senior Members, might be more likely to give the president a honeymoon (Lockerbie, Borrelli
and Hedger 1998). New Members, whether or not they perceive that they “owe” their election to
the president’s popularity in their district, may be more predisposed to look to the president for
cues, having not yet established their own information sources. This effect might diminish in the
second year as they gain experience in Congress, and so might account for the honeymoon
effect. If this were the case, we would expect that presidents who came into office with more
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newly elected Members of their party in Congress might experience more significant honeymoon
effects. We briefly explored this hypothesis, and found mixed results. After all, first-term
Members of Congress also tend to have higher party unity scores, and Members with higher
party unity scores gave presidents less of a honeymoon. Also, the relatively small numbers of
first term Members of Congress means they can only account for a small part of the honeymoon
effect. However, we are exploring this hypothesis for future analysis.
Conclusions
Although work is ongoing, we have reported some interesting findings here. We showed
for the first time that there is a honeymoon in presidential support scores. The honeymoon
seems to both consist of presidents winning more often, and of winning more votes from more
individual Members. On average, MCs, especially the president’s partisan opponents, are more
supportive of the president during his first than during his second year.
We also noticed different patterns based on success scores and on support scores. Some
presidents appear to experience a honeymoon by one measure and not by the other. Success
scores, the presidential “batting average,” may be the outcomes that are most widely observed,
and may be more important to presidents themselves and the way they are judged by the public
and the press. But support scores are more informative about the nature and origins of the
honeymoon effect, and whether it is really a systematic phenomenon, or perhaps more dependent
on skill, strategy, and changes over time in a president’s behavior. It is important to continue to
investigate the sources of the honeymoon, both by looking at patterns in individual Members’
support for the president, and by asking whether there is anything systematically different about
the bills on which presidents win in the first year and in other years.
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Finally, we find, in general, that the less partisan Members of each political party are
more likely to give the president a honeymoon, that is, to support him more often during his first
year than during his second year. This seems an intuitively plausible finding. If further analysis
confirms that those are the Members who give the president a honeymoon, further interesting
questions still arise. Are these Members also more ideologically centrist? Do they come from
districts where the president did especially well, or perhaps better than they did? Does the
increased partisanship of Congress as a whole make the honeymoon less visible for later
presidencies?
This paper is preliminary. In future drafts we will hopefully find a way to model changes
in individual Members’ presidential support scores over time, and investigate additional
hypotheses about the sources of the president’s honeymoon with Congress. We will also extend
our dataset through the 1960s and 1970s and ask whether there may have been changes over time
in presidents’ propensities to benefit from a honeymoon effect, especially any changes that may
be due to increased partisanship in Congress.
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