THE PRESIDENTIAL SHADOW ON MIDTERM HOUSE ELECTIONS:
PRESIDENTIAL SUPPORT, PRESIDENTIAL AGENDAS, AND SEAT LOSS
Brian J. Gaines
bjgaines@uiuc.edu
and
Timothy P. Nokken
tnokken@uiuc.edu
Department of Political Science
and
Merriam Laboratory for Analytic Political Research
University of Illinois at Urbana-Champaign
361 Lincoln Hall
702 S. Wright Street
Urbana, IL 61801-3696
November 1998†
An earlier draft of this paper was delivered at the annual meetings of the Southern Political Science
Association, Atlanta, Georgia, October 28-31, 1998. Thanks to participants in the Merriam Lab seminar and to
James Cox and John Hickman for helpful comments. All of the (doubtless numerous) errors that remain can be
attributed to the authors, jointly or randomly between authors, as the attributer prefers.
†
ABSTRACT
With only two exceptions, each midterm election since 1860 has seen the president’s
party lose seats in the House of Representatives. Research on this midterm loss
phenomenon is usually conducted at the aggregate level, so that the behavior of
individual members of Congress is conspicuously absent from the factors hypothesized
to drive the election results. Building on the work of Brady et al. (1996), we examine the
midterm loss at the district level in elections from 1958 to 1994. We conjecture that
legislators sometimes face a difficult choice, between backing a comparatively extreme
president, at the risk of alienating their constituents, or else “playing to the district,” at
the risk of harming and annoying their president. An implication is that a record of
presidential support is sometimes perilous. We find that a Representative’s level of
support for the president’s agenda does, under some circumstances, have a significant,
positive effect on the probability of losing in a midterm. We are not able, however, to
identify a priori in which elections this effect is most pronounced.
1
One of the most robust empirical regularities in American elections is the
midterm loss: with only two exceptions (the old case of 1934 and the brand new case of
1998), the presidential party has lost House seats at every midterm since 1860. A number
of reasons have been proposed for this pattern. Notably, few explain midterm losses in
terms of the behavior of members of Congress (MCs). Instead, explanations for the
seemingly inevitable presidential party losses have converged on a number of factors
beyond the direct control of individual members. In part, this is a byproduct of the
favored level of analysis: the typical paper uses national elections as observations, models
aggregate seat loss, and so focuses on a set of aggregate explanatory variables such as
turnout, economic performance indicators, and so on. Member activities do not easily fit
into such a framework. In this paper, we drop down a level and seek to determine
whether the probability of reelection for US Representatives is significantly affected by
their roll-call voting behavior. Specifically, we investigate the question of whether
presidents sometimes pursue agendas that leave their partisan counterparts in the House
with a Hobson’s choice: support the president and risk alienating constituents, or put the
district ahead of the party, and risk presidential wrath.
Aggregate midterm losses of House seats (or, sometimes, vote share) are usually
modeled as a function of changes in the larger political environment. Hence favorite
predictors include: presidential popularity (Kernell, 1977; Marra and Ostrom, 1989); an
alleged tendency for public dissatisfaction with (early) presidential performance
(Erikson, 1988); prevailing economic conditions (Tufte, 1975; 1978); changes in levels and
composition of voter turnout from presidential to midterm elections (A. Campbell, 1966;
J. Campbell, 1993); voter evaluations of the president’s party (Abramowitz, Cover, and
Norpoth, 1986); and attempts by voters to “balance” policy outcomes by dividing control
of the White House and Congress (Alesina and Rosenthal, 1995). Virtually all of these
interpretations seem to imply that midterm losses are largely independent of members’
actions in office. Thus, somewhat perversely, it has become common to neglect the
electoral consequences of individual-level member roll-call voting behavior when
explaining congressional election results.
There are, of course, some analyses of how individual MCs’ voting records can
contribute to their defeat. For example, a large literature, implicitly grounded in the
delegate notion of representation, has analyzed “shirking,” by which it is usually meant
2
casting roll call votes that do not correspond well to the preferences of constituents (e.g.
Lott (1987), Dougan and Munger (1989), Kalt and Zupan (1990), Lott and Davis (1992),
Lott and Bronars (1993)). These works are mostly concerned with the consequences of
shirking, and so the sources of MC miscreance are not much explored, except insofar as it
follows a decision to retire. In this paper, by contrast, we consider a simple dilemma that
many MCs can face. Representatives from the president’s party can get caught between a
comparatively extreme president and comparatively moderate constituency opinion. Our
core hypothesis is that at least some of the time, presidential support should be perilous
(yet tempting) for MCs, so that it ought to show a significant, direct effect on the
probability of losing office. We do not attempt anything like a complete model of
presidential strategy, congressional responsiveness to presidential cues, the roll-call
generating process, agenda control, and so on. For now, we focus on only a small piece of
the theory by developing a simple model of re-election probabilities that incorporates as
an explanatory variable an index of the presidential support in roll-call voting behavior
over the immediately prior period.
Ours is not an altogether novel thesis. Brady, Cogan, Gaines, and Rivers (1996)
have shown that roll-call voting behavior did, indeed, have a significant effect on the
electoral fate of incumbent House Democrats in the 1994 elections. Higher levels of
presidential support by Democratic Representatives over 1993 and 1994--especially by
those members in whose districts Clinton ran poorly in 1992--led to a greater likelihood
of losing in 1994. Hereafter, then, we explore how general is that result. How and where
does presidential support hurt? Is there evidence for the peril of standing by a (relatively
extreme) president in other modern elections? If so, does the effect occur when expected?
That is, is there a reliable way to determine, ex ante, which presidents (if any) seem to
have placed their House colleagues in jeopardy by pressing too extreme an agenda?
The paper proceeds as follows. Section two briefly reviews prior work on the
midterm loss. Section three discusses what can happen when the preferences of the
president and his partisans in Congress diverge. We expect presidential support by MCs
to affect their re-election chances only when presidents are in some sense out-of-step,
and, in those cases, to work in a multiplicative rather than additive fashion. That is, for
members with districts having relatively left- (right-) leaning electorates, yielding to
pressure to support a president who veers left (right) is no liability. For moderates, by
3
contrast, the dilemma is real. We consider possible means of identifying the necessary
conditions for this dilemma to show. In section four, we replicate and extend a model of
individual seat loss developed by Brady et al. (1996). Section five concludes.
2. EXPLANATIONS OF MIDTERM LOSS
Modern midterm elections nearly always feature presidential-party seat loss, but
the magnitude of these losses varies considerably. Large losses have been most common
when the president’s popularity was low, as was the case with Clinton in 1994 and Nixon
in 1974. Indeed, (national) presidential popularity is a consistently significant predictor of
the size of the midterm loss (e.g. Lewis-Beck and Rice 1992: ch.4). An unpopular
president, however, is not necessarily a recipe for an electoral bloodbath, as Reagan
showed in 1982 by losing a fairly modest 26 seats despite widespread disapproval of his
job performance. In part, the difference is a simple matter of numbers: there were fewer
Republicans in non-safe seats in 1982 than there were Democrats at risk in 1994. Hence,
some variety of “exposure” variable is also a staple of the aggregate models. More
importantly, though, it is not self-evident that voters will automatically take out
displeasure with a sitting president on his partisan counterparts in House races. Some
exploration of when, how, and why such linkage occurs is in order.
Consider three major classes of explanation for midterm losses. The key
difference between “on-” and “off-” year elections could be turnout patterns, i.e.
systematic differences in the composition of the midterm and presidential-year
electorates. Presidential popularity makes only a slight contribution to such accounts,
insofar as it might be one factor causing mid-term ennui. Congressional behavior,
meanwhile, is beside the point. A very different take on the election patterns is that the
most important difference resides in the set of issues and evaluation criteria that tend to
play out in each kind of election. Specifically, there might be a natural cycle to
presidential approval that makes unwitting victims of legislators associated with the
president at midterms. The president lies at the center of these accounts, whether they are
framed in terms of a political business cycle, a tendency for modern presidential elections
to breed exaggerated expectations, or whatever. Members of Congress, by contrast, are
4
mere ciphers in these explanations. What matters about MCs is only their partisan label,
and not the degree to which they are somehow linked (or linkable) to the president.
Finally, various “balancing” models propose that midterms allow voters an
opportunity to play the Legislative branch against the Executive branch, so that the
midterm loss should be understood as originating in the fact that some portion of the
electorate has policy preferences more moderate than both the right-wing ideals of the
Republicans (president and/or House members) and the left-wing goals of the Democrats
(in one or both branches). Such models could involve more careful consideration of the
actual profiles of MCs, but, thus far, balancing theories have advanced more on the
formal and theoretical front than on the empirical side. Where authors have tested these
hypotheses at the district level, their operationalizations have been unsatisfactory (e.g.
Burden and Kimball 1998, cf. Cho and Gaines 1999).
Despite a wide array of approaches, then, research on midterm elections usually
implies that the outcomes are influenced by conditions beyond the direct control of
individual MCs.
There is, nonetheless, a surface plausibility to the conjecture that
legislators should have a direct role in this phenomenon too. We do not propose to ignore
the president, but, rather, to explore which Representatives seem most likely to be tied to
the president in voters’ minds, making them especially likely to be the victims of the
almost inevitable midterm purge.
3. PRESIDENTIAL SUPPORT SCORES AND MIDTERM ELECTION OUTCOMES
Accordingly, we wish to consider whether roll-call voting by individual
Representatives can be shown to affect their re-election prospects. Such analysis need not
be limited to midterm elections: the conjecture that some Representatives allow
themselves to be pulled away from median constituency opinion by presidential
pressure, and then suffer accordingly, is not midterm-specific. Nonetheless, we focus
exclusively on midterms here, chiefly because these elections do not allow voters any
direct say on presidential performance. Midterms thus provide a fairly clean test of
whether voters appear to punish Representatives for ideological drifting. By limiting
attention to midterms, one can duck a set of complications stemming from untangling the
various possible sources of coattail voting. The theory is also not specifically oriented to
5
the House, but for simplicity we consider only Representatives in the analysis that
follows, leaving Senators for another day. Finally, for methodological reasons to which
we shall return, we opt to study the relatively crude win-or-lose variable hereafter,
forgoing any modeling of actual vote shares.
Brady et al. (1996) show that increased support for the president significantly
influenced the likelihood of defeat for incumbent House Democrats in the 1994 midterm
elections. They contend that Clinton’s first two years of office featured a sufficiently leftist
policy agenda that, by 1994, a record of having supported Clinton had become a serious
liability for moderate Democrats. Of course, if this was true, it was true only because
Republican challengers took pains to call this association to voters’ attention. And,
presumably, there were several observable instances of overly-Clinton-friendly
Representatives losing precisely because the president had succeeded in building House
coalitions that included some (reluctant) moderates. The general version of this dynamic,
then, is that when a president is an outlier within his partyan especially liberal
Democrat or an unusually conservative Republicanand that president is aggressive in
his pursuit of congressional support, the president’s partisans in Congress end up crosspressured. If one can identify those whose districts are least favorable to the president,
these are the members for whom support should be costly. In turn, one would like to
identify which presidents have indeed shown signs of having overplayed their hands in
the years preceding the midterms.
Brady et al. rely on journalistic reporting and the reader’s tacit concurrence that
Clinton’s leftness in 1993 and 1994 was self-evident. Clearly, it is a necessary condition
for the hypothesized dynamic that the president be more extreme than his party’s House
delegation. Identifying which presidents fit this bill in a systematic manner requires some
metric for presidential behavior. It is important too that one measure not mere
presidential preferences in the abstract, but the presidential agenda to which legislators
can be plausibly linked, more or less strongly, according to their actual levels of support.
The most obvious way to estimate locations for presidents and legislators in a common
ideological space is to treat legislators’ roll call votes and presidents’ announced positions
on these roll call votes as equivalent preference-revelation mechanisms. Then, for
example, Poole and Rosenthal’s various NOMINATE® procedures for scaling observed
binary votes into voter ideal points can be applied to presidents (McCarty and Poole,
6
1995). Alternatively, presidents can be scored according to their announced positions
using interest-group indices (e.g. Zupan 1992). The ADA, for example, chooses 20 votes
in each chamber, and then scores MCs “right” or “wrong” on each vote. Their liberalism
score is simply the percentage of all votes on which legislators voted the ADA-preferred
way, so presidents can be given ADA scores on the basis of their announced preferences
on this identical set of votes.
Table 1 shows how recent presidents have scored, and how they compared to
their House delegations. Panel A., which uses W-NOMINATE scores, ranks the presidents
by their distance from their parties’ House delegations. Figures 1 and 2 illustrate, using
one case in which a president appears “extreme,” (Johnson in 1966), and one in which he
does not appears to be an outlier relative to his party (contra Brady et al., Clinton in
1994). A difficulty in detecting which presidents were genuine outliers relative to their
House delegations, however, is that our scores for legislators presumably already contain
presidential influence. Some of the reason Clinton appears much closer to House
Democrats by 1994, as compared with Johnson and the House Democrats in 1966, could
be because Clinton was more successful in pressuring Representatives to vote with him. 1
Indeed, although Johnson (as of 1966) lies left of Clinton (as of 1994) in NOMINATE space,
much of the difference in their separation-from-House-median scores is due to Clinton’s
House Democrats lying well to the left of Johnson’s. In general, then, the observed gap
between a president and his House colleagues is not precisely the measure of presidential
outlyingness we are after.
[Table 1 – NOMINATE and ADA Scores, Presidents and Their House Colleagues]
On the other hand, to the extent that a president’s ideological rating is moderated
because he was strategic with respect to what could pass Congress, we no longer expect
to see signs of the presidential-support dilemma. Hence, the most important statistic for
identifying presidents whose programs put their colleagues at peril should be the
president’s rating, rather than his separation from his House copartisans. Focusing only
on the presidents’ scores, whether using NOMINATE scores in panel A or ADA scores in
Some of the difference, of course, lies in the slow transformation of the South between the 1960s and 1990s, as
a number of conservative Democrats were replaced by Republicans.
1
7
panel B, one would reject the maintained hypothesis of Brady et al., that Clinton had been
extreme in his first two terms.
[Figure 1 – Johnson and House Democrats, 1965-66, W-NOMINATE Scores]
[Figure 2 – Clinton and House Democrats, 1993-94, W-NOMINATE Scores]
The next point about Table 1 is that there is some disagreement between the
different scoring techniques. Bush is the single most conservative president in the set by
ADA scores, but is only moderately conservative (a mirror image of fellow one-termer
Carter) in W-NOMINATE metric. Johnson is Reagan’s opposite under ADA scheme (a) and
W-NOMINATE, but scores to the right of Clinton if one takes advantage of the extra
information about presidents contained in their announced preferences over Senate votes
when calculating ADA scores. We are not the first to notice that rival methods of
computing ideological scores from roll call votes perform quite differently (see Adams
and Fastnow 1998). If we attempt to take account of all sets of scores, a general conclusion
might be that Reagan and Johnson are the most extreme in the set. That corresponds to
conventional wisdom, and the quantification, alas, has contributed little. Clinton,
notwithstanding gays-in-the-military, nationalizing health care, abandoning promised tax
cuts, and so on, does not appear particularly extreme in 1994, except under the second
method of ADA scoring, in which he gets the most liberal rating of any president in the
table, except for Kennedy.
Our main conclusion from this initial stab at analyzing presidential agendas
ideologically is pessimistic. Quantification is desirable and should be possible, but at
present we have relatively little confidence that we are able to improve on prior
subjective beliefs grounded in informal, hard-to-quantify impressions. Our hunch at the
outset was that prime examples of presidents over-reaching and placing their partisan
colleagues in the House in jeopardy are Clinton in 1994, Reagan in 1982, and Johnson in
1966. Support of Nixon in the years prior to 1974 might have been costly for Republicans,
but for different reasons: what (might have) mattered was the incumbent’s association
with a scandal-ridden figure rather than with an overly conservative agenda. We proceed
next to estimations.
8
4. A SIMPLE DISTRICT-LEVEL MODEL OF MIDTERM ELECTION OUTCOMES
In this section, we estimate probit models of the probability of victory for those
members of the president’s party who seek reelection.2 Like Brady et al., we include a
relatively small set of control variables: turnout, the president’s share of the two-party
vote in the preceding election, the share of the vote won by significant non-major-party
candidates (Perot in 1994, Anderson in 1980, Wallace in 1968) and an indicator variable
for a challenger who has previously held any elective office.
Voter turnout, of course, holds a prominent place in the literature on midterm
election outcomes. Campbell’s surge-and-decline thesis predicts that the lower levels of
turnout observed in midterms contributes to the defeat of members of the president’s
party. At least two kinds of turnout effect seem plausible. First, lower turnout might lead
to an increased probability of defeat for incumbent members of the president’s party. No
longer mobilized by the presidential election, marginal partisans might stay home. In
other words, there are no coattails to help Representatives in marginal districts keep their
offices. Second, one might expect higher turnout to assist the out party in midterms on
different grounds. If loss in a presidential election can be understood as turnout having
been above average for the winner’s party and below for the losers, regression to the
mean should assist the out party in the next election.3 Hereafter, we measure turnout as
the total number of votes cast in the House election at the midterm divided by the total
voting age population.
The president’s share of the two-party vote from the previous presidential
election is essentially a proxy for district “type.”
Specifically, districts where the
president ran strong ought generally to be more safe for that party, so that this variable
can be considered a normal vote estimate. The variable can also be construed as a
measure of the appeal of the particular president, so that it can be used to separate those
districts in which a record of support is a liability from those in which such a record
might be worn as a badge of honor. Our expectation is that the coefficient on this variable
We do not attempt to analyze retirement decisions. Nor do we examine the relatively rare cases of primaryelection defeat, although these might conceivably exhibit similar features.
2
Kernell (1977) argues that voters with negative evaluations of the president are more likely to turnout to vote,
suggesting they are more likely to oppose those MCs who are seen as supporters of the president.
3
9
should be positive and significant. Where Democratic (Republican) presidents run well,
their congressional candidates should also run well, ceteris paribus.
It is often argued that the emergence of significant third-party challenges are
indicative of voter dissatisfaction (Sundquist, 1983). Exactly what effect Ross Perot’s 1992
candidacy had on that election remains a subject of some controversy, chiefly between
those who maintain that Perot harmed Bush most and those who propose that he drew
away roughly equal numbers of Democratic and Republican votes. By some tellings, the
Perot factor played a part in the dramatic 1994 result as well. If, for example, Perot
mobilized previously inactive citizens who then turned out again in 1994, he may have
injected into the process a set of disgruntled moderate voters who turned on Clinton via
House votes in 1994. Or, again, Perot’s strength may not only have masked Republican
tendencies, but assisted Democrats in getting elected by discouraging voters who might
otherwise have cast straight Republican ballots from doing so. In that case, one could
expect a negative correlation between Perot’s showing in 1992 and the odds of Democrats
returned in 1992 winning again in the 1994 race once the distraction of a non-major-party
force was removed. Brady et al. in fact find that the “Perot factor” was not a significant
contributor to Democratic defeats.
Anderson, like Perot, aimed to capitalize on voter dissatisfaction with the two
parties. Arguably, he ran to the left of both Reagan and Carter. Unlike Perot, he did not
pose much of an electoral threat. Not even Anderson’s biggest fan (Gary Trudeau?)
predicted that the 1980 presidential race would end in the House. And, although as of
October 1980 the election was perceived to be much closer than it ultimately turned out to
be, few thought Anderson would draw votes in a manner that would systematically
advantage one party or the other. Hence, it is hard to construct a rationale for why his
candidacy should have had after-shocks in 1982. Finally, Wallace’s success was largely
confined to the South. Since most southern Representatives were Democrats, we would
not expect Wallace’s candidacy to have had a significant effect on the reelection bids of
many of Nixon’s partisans in 1970. In sum, without endorsing a particular scenario by
which the third-candidate vote matters, we will include a control variable for the Perot,
Anderson and Wallace votes in the relevant models to assess the effect their candidacies
had on midterm election outcomes. In each case, we use their share of the district-level
three-way presidential vote, and we hypothesize no significant effects.
10
Experienced challengers generally outperform their colleagues who have never
won any sort of office. A large literature has explored how best to measure candidate and
challenger quality, and most analysts still find that Jacobson’s dummy for previouslyelected works about as well as far more complicated measures. Hence, we include an
indicator coded one for those challengers who have held previous office, zero otherwise.
The coefficient on this variable should be statistically significant and negative in each of
the midterms analyzed.
The factor most often omitted from analysis of midterms is some variable
capturing member behavior in reelection bids. This analysis focuses upon a relatively
narrow aspect of member behavior, support for the president’s announced positions on
roll call votes. Members of course have at their disposal a vast array of resources to help
them stay in power. That said, midterm elections are a special case where the electoral
welfare of the president’s party in Congress is explicitly linked to the performance of the
president. A common rhetorical tactic on the midterm campaign trail is to link members
of the president’s party to the president, especially if he is unpopular. In such instances,
support for the president’s agenda could prove to be an important issue in a
congressional campaign. We expect the coefficient on Congressional Quarterly’s
presidential support scores be negatively related to a member’s probability of winning in
years in which the president was extreme and in districts in which the president is comparatively
weak. That passage in italics is important. We have already punted on quantifying
presidential extremism, and so we proceed to analyze the midterms year by year, with
only fuzzy expectations about when we expect to see signs of presidential support
hurting incumbents. On the other hand, it is important to re-emphasize that we do not
expect presidential support to be uniformly damaging, even in years in which the
extreme-president condition is met. Our hypothesis is that presidential support interacts
with district safety, so that increasing levels of support are associated with greater
likelihood of defeat in relatively moderate districts, but not in relatively extreme districts.
This makes the specification of the model tricky, since we expect roughly the following
combinations for member’s presidential support, district presidential vote, and member’s
risk of defeat: (low, low, medium); (high, low, high); (low, high, low); (high, high, low).
For simplicity, Brady et al. relied strictly on the non-linear properties of the probit
estimator to handle this property. We copy their basic specification, but also explore an
11
explicit interactive term (see Nagler 1991 on specifying interactive terms in non-linear
models).
In the models that follow, the observed dependent variable is always victory or
defeat (the latent variable is the probability of victory) for members of the president’s
party in midterm elections. We estimate probit models for re-election of presidentialparty incumbents in all midterm elections from 1958 to 1994. 4 There are various decisions
to be made in exact operationalization, for example whether to use presidential support
scores for the year of the election, the two years prior, only the first of the two years, etc.
Our main concern lies in the non-linear and multiplicative effects we expect from
presidential support. For each year we estimate two models, of the following form:
Pr(Y=0) = (0+1X1+2X2+3X3+4X4+5X5)
Pr(Y=0) = (0+1X1+2X2+3X3+4X4+6X5D1+7X5D2)
where Y is an indicator variable for re-election; X1 represents turnout in the midterm
election; X2 is an indicator for an experienced challenger; X3 is the percentage of the total
vote won by any third candidate in the prior presidential election; X4 is the share of the
two-party vote won by the president in the prior presidential election; X5 is the
incumbent’s level of presidential support in roll-call voting; D1 and D2 are dummies for
districts having values of X4 (presidential vote) below or at least above the median value
of X4 for the presidential incumbents, respectively; () represents the standardized
cumulative normal distribution function; and, observations are presidential-party
incumbents. The second model, which estimates two coefficients on X5, one for “safe
seats” (7) and one for “at-risk” seats (6), is a simple, explicit attempt to get at the
multiplicative logic already noted more directly than the first specification.
We now extend the analysis and estimate the model for each midterm election
from 1958 to 1994. We estimate separate models for each election because it is not clear
that the factors have the same influence at each point in time. (Ultimately, we might test
the poolability of the data explicitly.) Of particular interest is whether support for the
president increases the likelihood of defeat in midterm elections. The results of the
estimates of the first model are displayed in Table 2. Contrary to the turnout-based
We lose a few cases because of missing data. Presidential support, for example, is usually missing for the
speaker. Turnout is missing for some cases of uncontested races where state law does not require tabulating
votes of the winner.
4
12
explanations of midterm loss, voter turnout is, with the exception of the 1962 and 1966
elections, statistically insignificant. As expected, in districts where the president ran well,
House members generally perform better at the midterm. The president’s vote share in
the previous election is significant and positive in eight of the ten elections, statistically
insignificant only in 1962 and 1974. Facing an experience challenger significantly reduces
a member’s reelection prospects for incumbent House members from the President’s
party in half of the midterm elections we analyze (1958, 1966, 1974, 1978, and 1994)—
surprisingly few given our expectations about the importance of challenger quality. The
third party challenges of Wallace, Anderson, and Perot played no significant part in the
defeat of incumbent House members of the presidents party, which is not an unexpected
result.
[Table 2 -- Maximum Likelihood Estimates, Probability of Winning, 1958-1994]
We expect presidential support to be most salient in 1994 and in those cases
where presidents were ideologically extreme compared to their fellow partisans in the
House. Supporting the president would seem to have been most dangerous during the
Johnson (1966) and Reagan (1982 and 1986) Administrations. We find, however, that
presidential support played a significant role in midterm outcomes in only two elections,
1994 and 1970. Increased presidential support among Democrats in the 103rd House
contributed to their defeat in the 1994 midterm elections. Contrary to the expectations,
the effect in 1970 runs the other way. Support of Nixon actually helped the electoral prospects
of incumbent Republicans. That results is initially surprising, though it might be interpreted
as the flip side of our hypothesis: a sufficiently moderate president can insulate his
partisan colleagues in competitive seats.
That interpretation calls attention again to the importance of the interactive
specification. If the negative (or positive?) consequences of increased presidential support
should primarily affect those members of the president’s party from districts where the
president ran poorly, our interest lies in the interaction of a member’s presidential
support score with dummy variables indicating whether the president ran poorly in the
given district. The results for our second model are displayed in Table 3. We include the
same set of control variables as in the previous model. The effect of these variables are
13
less pronounced than in the previous model. Presidential vote share significantly
contributed to incumbent members’ victory in only two elections: 1970 and 1994.
Experienced challengers, once again, reduced the probability of reelection in half of the
midterm elections we analyze, the effect reaching statistical significance in 1958, 1966,
1974, 1978, and 1994. As in the previous model, we find no evidence that significant third
party presidential challenges contribute to midterm losses. These estimates thus provide
further disconfirming evidence for turn-out based explanations of midterm losses.
Identifying members in “at-risk” seats improves somewhat our estimation of the
effect of individual-level behavior on reelection prospects. Consistent with the
expectations that cross-pressured members in marginal seats take the greatest risk in
supporting the president’s agenda, the interactive term was statistically significant and
correctly signed in 1966 and 1994. LBJ’s policies were, by most accounts, far to the left of
the preferences of a large number of his fellow Democrats in the House, and the ones
from not-very-Democratic seats suffered when they supported him. Democrats from
marginal districts had swept into office in 1964 with the help of Johnosn’s landslide
victory, but they saw their prospects for reelection diminish with increased levels of
support for Johnson’s Great Society legislation. Members from safe seats, however,
experienced no penalty for their support of the president, consistent with our
expectations.
Similarly, in 1994, for Democrats from marginal districts, higher levels of
presidential support served to increase the probability of defeat. In 1994, in fact,
increased presidential support by Democratic House incumbents was detrimental even in
districts where the president ran well in 1992.5 Support for the Clinton agenda appears to
have been a risky undertaking in 1994.
Also of note are the statistically significant results from the 1970 and 1990
midterms where, contrary to our original expectation, increased presidential support
actually increased the likelihood of reelection for Republican incumbents. The effect is
especially strong for those members from districts where Nixon ran poorly in the 1968
elections. We also detect an electoral boost for members from relatively safe districts in
5
Note that this coefficient (Low Pres Vote*Voting Record) is significant at the 0.10 level.
14
1970 and 1990. It appears that presidential support may, in some instances, actually
benefit members of the president’s party in midterm elections.
[Table 3 -- Maximum Likelihood Estimates, Probability of Winning, 1958-1994]
Results from both sets of probit models reveal some signs that individual-level
behavior can contribute to midterm loss. The results are not, however, an unambiguous
vindication of the theory. In some elections in which we expected to observe significant
negative effects for support of ideologically extreme presidents (e.g. 1982), no such effects
are discernible. Significantly negative consequences from increased levels of support for
LBJ were observable, once one restricts attention to members from marginal seats. The
midterm elections of 1970 provide somewhat surprising results, since the electoral
fortunes of Republican House members were apparently buoyed by increased levels of
support for Nixon. Since Nixon’s ideological profile in 1969 and 1970 was plainly
moderate, this is not inconsistent with our conjecture, even though it was not an effect we
set out to find.
5.
CONCLUSION
Explanations of midterm losses in the House focus almost exclusively on the
aggregate patterns. A variety of models of total seat loss perform very well as forecasting
devices. They are, however, somewhat less helpful in understanding the micro-level of
the midterm loss. In particular, they offer no guidance as to who will lose, or why. We
have taken a different approach, by exploring a dynamic whereby some individual
Representatives place themselves at risk at midterms by following their leader. There is a
surface plausibility to the conjecture that the likelihood of defeat might, under certain
conditions, be influenced by past roll-call voting behavior. Our empirical results are
somewhat mixed: we observe the dynamic as expected in 1994, though the negative
influence of presidential support extended even into safe seats, somewhat to our surprise.
In 1966, another year in which most reasonable observers would concur that the
15
president was well left of his House colleagues, the result is a better match to our theory.
On the other hand, we detect no such effects for 1982 or 1986, against expectations.
A prudent conclusion is that we have weak confirmation of the theory, but that
further analysis is warranted. Several subsidiary analyses, for example, can bolster our
confidence that the estimation is capturing the presidential-support dilemma. In 1994,
models in which voting behavior on a few, key issues (gays-in-the-military, the budget,
health-care reform) was substituted for the overall presidential-support score performed
about equally well. The possibility remains that it is not really objective support for the
president’s program over the whole term that matters electorally, but, rather, whether the
Representative voted “with” or “against” his median constituent in a few highly salient
cases. That is a rival hypothesis crying out for more careful examination. Further, it
would improve our confidence in the theory if we detect no presidential-support effects
in open seats or seats of non-presidential incumbents.
Generally, a number of alternative specifications may provide us with a better
picture of how individual member behavior influences electoral outcomes. In particular,
modeling defeat-or-victory sets a very high standard for the level of peril in evidence
from pro-presidential voting. It would seem advisable also to model vote shares, in
search of signs that some members pay for their support, but hang on to win the elections
(narrowly) all the same. The chief barrier to that project is simply technical: a sensible
model should incorporate normal vote, incumbency effects, inter-election (uniform)
swing, and district-level behavior by some incumbents only at only some midterms, and
we have yet to devise an acceptable panel specification.
Though far from conclusive, our results are, we believe, strong enough to confirm
that the precise links between roll-call voting, presidential cues, and electoral
consequences deserve further attention. In particular, the midterm loss is well
understood as an aggregate phenomenon, but remains relatively mysterious on the
ground. That should bother not only those running scared (the Representatives), but also
those running regressions.
16
REFERENCES
Abramowitz, Alan I., Albert D. Cover, and Helmut Norpoth. 1986. “The President’s Party
in Midterm Elections: Going from Bad to Worse.” American Journal of Political
Science 30, 3 (August): 562-576.
Adams, Greg D. and Christina Fastnow. 1998. “On the Differences Between Legislative
Ideology Measures.” Paper presented at annual meetings of Midwest Political
Science Association, Chicago, IL.
Alesina, Alberto and Howard Rosenthal. 1995. Partisan Politics, Divided Government, and
the Economy. Cambridge: Cambridge University Press.
Brady, David W., John F. Cogan, Brian J. Gaines, and Douglas Rivers. 1996. “The Perils of
Presidential Support: How the Republicans Took the House in the 1994 Midterm
Elections.” Political Behavior 18, 4 (December): 345-367.
Burden, Barry C. and David C. Kimball. 1998. “A New Approach to the Study of Ticket
Splitting.” American Political Science Review 92, 3 (September): 533-544.
Cain, Bruce, John Ferejohn, and Morris Fiorina. 1987. The Personal Vote. Cambridge, MA:
Harvard University Press.
Campbell, Angus. 1960. “Surge and Decline: A Study of Electoral Change.” Public
Opinion Quarterly 24, 3 (Fall): 397-418.
Campbell, James E. 1993. The Presidential Pulse of Congressional Elections. Lexington:
University of Kentucky Press.
Cho, Wendy K. Tam and Brian J. Gaines. 1999. “Reassessing the Study of Split-Ticket
Voting” Typescript, University of Illinois.
Dougan, William R. and Michael Munger. 1989. “The Rationality of Ideology.” Journal of
Law and Economics 32, 1 (April): 119-142.
Erikson, Robert S. 1988. “The Puzzle of Midterm Loss.”
The Journal of Politics 50, 4
(November): 1011-1029.
Fenno, Richard F., Jr. 1973. Congressmen in Committees. Boston: Little, Brown.
. 1978. Home Style: House Members in their Districts. Boston: Little, Brown.
Fiorina, Morris P. 1981. Retrospective Voting in American National Elections. New Haven:
Yale University Press.
17
Hinckley, Barbara. 1967. “Interpreting House Midterm Elections: Toward a Measurement
of the In-Party’s ‘Expected’ Loss of Seats.” American Political Science Review 61, 3
(September): 694-700.
Jacobson, Gary C. 1997. The Politics of Congressional Elections, 4th ed. New York: Longman.
Jacobson, Gary C. and Samuel Kernell. 1983. Strategy and Choice in Congressional Elections,
2nd ed. New Haven: Yale University Press.
Kalt, Joseph P. and Mark A. Zupan. 1990. “The Apparent Ideological Behavior of
Legislators: Testing for Principal-Agent Slack in Political Institutions.” Journal of
Law and Economics 33, 1 : 103-131
Kernell, Samuel. 1977. “Presidential Popularity and Negative Voting: An Alternative
Explanation of the Midterm Congressional Decline of the President’s Party.”
American Political Science Review 71, 1 (March): 44-66.
Kuklinski, James H. and Darrell M. West. 1981. “Economic Expectations and Mass Voting
in United States House and Senate Elections.” American Political Science Review 75,
2 (June): 436-447.
Lewis-Beck, Michael S. and Tom W. Rice. 1992. Forecasting Elections. Washington, DC: CQ
Press.
Lott, John R., Jr. 1987. “Political Cheating.” Public Choice 52, 2: 169-186.
Lott, John R., Jr. and Stephen G. Bronars. 1993. “Time Series Evidence on Shirking in the
U.S. House of Representatives.” Public Choice 76, 1-2 (June): 125-149.
Lott, John R., Jr. and M. L. Davis. 1992. “A Critical Review and Extension of the Political
Shirking Literature.” Public Choice 74, 4 (December): 461-484.
Marra, Robin F. and Charles W. Ostrom. 1989. “Explaining Seat Change in the U.S. House
of Representatives, 1950-1986.” American Journal of Political Science 33, 3 (August):
541-569.
Mayhew, David R. 1974. Congress: The Electoral Connection. New Haven: Yale University
Press.
McCarty, Nolan M. and Keith T. Poole. 1995. “Veto Power and Legislation: An Empirical
Analysis of Executive and Legislative Bargaining from 1961 to 1986.” The Journal
of Law, Economics, and Organization 11, 2 (October): 282-312.
Nagler, Jonathan. 1991. “The Effect of Registration Laws and Education on U.S. Voter
Turnout.” American Political Science Review 85, 4 (December): 1393-1405.
18
Poole, Keith T. 1997. “Changing Minds? Not in Congress!” GSIA WP#1997-22 Graduate
School of Industrial Administration, Carnegie-Mellon University.
Poole, Keith T. and Howard Rosenthal. 1997. Congress: A Political-Economic History of Roll
Call Voting. New York: Oxford University Press.
Sundquist, James. 1983. Dynamics of the Party System: Alignment and Realignment in the
United States. Washington, DC: Brookings Institution
Tufte, Edward R. 1975. “Determinants of the Outcomes of Midterm Congressional
Elections.” American Political Science Review 69, 3 (September): 812-826.
. 1978. Political Control of the Economy. Princeton: Princeton University Press.
Zeidenstein, Harvey. 1972. “Measuring Congressional Seat Losses in Mid-Term
Elections.” Journal of Politics 34, 1 (February): 272-276.
Zupan, Mark. 1992. “Measuring the Ideological Preferences of U.S. Presidents: A
Proposed (Extremely Simple) Method.” Public Choice 73, 3 (April): 351-361.
19
Table 1. Presidents Compared To Their Parties’ House Delegations
A. W-Nominate Scores, President and Presidential Party House Median
President
Eisenhower
Kennedy
Johnson
Nixon
Nixon
Carter
Reagan
Reagan
Bush
Clinton
Clinton
Midterm
Election
Year
1958
1962
1966
1970
1974
1978
1982
1986
1990
1994
1998
President’s
Score
Presidential
Party House
Delegation
Median
0.24
- 0.42
- 0.31
0.35
0.34
- 0.24
0.33
0.41
0.23
- 0.44
- 0.55
0.51
- 0.85
- 0.72
0.26
0.55
- 0.53
0.72
0.77
0.52
- 0.43
- 0.67
PresidentHouse
Delegation
Separation
0.27
0.43
0.41
- 0.09
0.21
0.29
0.39
0.36
0.29
- 0.01
0.12
Rank
7
1
2
10
8
5
3
4
5
11
9
B. ADA Score, President and Presidential Party House Median
President
Eisenhower
Kennedy
Johnson
Nixon
Nixon
Carter
Reagan
Reagan
Bush
Clinton
Midterm
Election
Year
1958
1962
1966
1970
1974
1978
1982
1986
1990
1994
President’s
Score*
(a)
87
100
95
33
13
70
5
5
0
69
Presidential
Party House
Delegation
Median
--74
14
17
53
13
10
11
75
(b)
66
94
72
24
18
74
5
3
0
76
Presidential
Outlyingness
Rank
(a)
(b)
6
10
1
4
3
9
10
6
6
5
8
8
4
3
4
2
1
1
9
6
* Presidential “ADA scores” were computed using announced presidential positions on ADAselected roll call votes in the two years preceding the midterm. The scores are computed as
(100r/(r+w)) where r is the number of “right” votes (in ADA terms) and w is the number of
“wrong” votes, and we rounded to whole numbers. There is no expectation that presidents take
sides on all votes held in Congress, so we divide by (r+w) rather than the total number of ADApicked votes, thus not penalizing presidents for “abstention.” (By contrast, the ADA now treats
abstention by legislators as equivalent to voting the “wrong” way.) The difference between (a) and
(b) is that (a) uses only the votes chosen by the ADA in the House, while (b) scores presidents on
their House and Senate announced positions. Our scores do not match those of Zupan, both
because they span multiple years and because of apparent coding errors in his analysis.
20
Table 2. Probability of Presidential-Party Incumbent Victories At Midterms
(Maximum Likelihood Probit Coefficient Estimates)
Variable
Constant
1958
-3.10
(1.73)
1962
-0.71
(1.42)
1966
1.58
(0.60)
1970
-3.74
(1.94)
1974
2.00
(1.76)
1978
0.46
(1.37)
1982
-4.98
(2.06)
1986
-2.11
(2.73)
1990
1.62
(2.03)
1994
0.20
(1.54)
Turnout
0.44
(0.44)
-2.26
(1.29)
-1.19
(0.41)
0.36
(2.51)
-1.73
(1.39)
-2.91
(2.17)
-3.30
(2.06)
-4.45
(2.95)
-3.07
(2.12)
-0.69
(1.76)
6.43
(2.47)
5.03
(2.72)
1.91
(0.97)
4.69
(2.29)
0.06
(1.96)
4.16
(2.11)
11.65
(3.19)
15.08
(6.16)
-0.05
(3.45)
7.38
(1.80)
-0.78
(0.24)
0.08
(0.38)
-0.75
(0.21)
-0.38
(0.35)
-0.53
(0.23)
-0.73
(0.29)
-0.07
(0.35)
-0.83
(0.54)
-0.46
(0.38)
-0.77
(0.26)
-0.00
0.01
-0.01
0.04
-0.00
-0.00
0.01
-0.05
0.02
-0.03
(0.01)
(0.01)
(0.01)
(0.02)
(0.01)
(0.01)
(0.01)
(0.03)
(0.02)
(0.02)
-
-
-
2.10
(2.07)
-
-
-
3.73
(5.07)
-
-
-
-2.80
(2.69)
Log
Likelihood
-72.35
-29.30
-94.17
-34.41
-82.05
-44.65
-39.23
-15.17
-31.14
-69.69
Pseudo R2
0.14
0.17
0.12
0.15
0.05
0.16
0.27
0.32
0.09
0.25
N
165
175
Standard Errors in Parentheses
256
168
163
237
127
158
150
223
Presidential
Vote
Experienced
Challenger
Voting
Record
Wallace
Anderson
Perot
21
Table 3. Probability of Presidential-Party Incumbent Victories At Midterms
(Maximum Likelihood Probit Coefficient Estimates)
Variable
Constant
1958
-2.33
(2.49)
1962
1.86
(2.11)
1966
2.42
(0.69)
1970
-6.47
(2.58)
1974
3.28
(2.23)
1978
2.02
(1.87)
1982
-2.08
(2.85)
1986
-0.24
(3.54)
1990
5.42
(3.12)
1994
1.20
(1.89)
Turnout
0.45
(0.44)
-2.26
(1.43)
-1.20
(0.42)
0.40
(2.66)
-1.68
(1.40)
-3.57
(2.31)
-3.08
(2.04)
-4.48
(3.12)
-3.14
(2.21)
-0.48
(1.79)
Presidential
Vote
5.18
(3.83)
-1.26
(4.59)
0.28
(1.15)
9.42
(3.55)
-1.98
(2.92)
1.06
(3.21)
6.84
(4.53)
11.53
(7.26)
-6.54
(5.15)
5.76
(2.46)
Experienced
Challenger
-0.77
(0.24)
-0.01
(0.40)
-0.69
(0.22)
-0.36
(0.36)
-0.52
(0.23)
-0.78
(0.30)
-0.18
(0.36)
-0.84
(0.55)
-0.48
(0.40)
-0.77
(0.26)
Hi Pres Vt 
Votng Record
Lo Pres Vt 
Voting Record
0.00
(0.01)
-0.002
(0.01)
-
0.01
(0.01)
-
-0.001
(0.01)
-0.01
(0.007)
-
0.03
(0.02)
0.05
(0.02)
2.88
(2.07)
-
-0.00
(0.01)
-0.01
(0.01)
-
0.01
(0.01)
0.00
(0.01)
-
0.02
(0.02)
0.00
(0.01)
2.33
(5.25)
-
-0.04
(0.03)
-
0.03
(0.02)
0.01
(0.02)
-
-0.03
(0.02)
-0.03
(0.02)
-
-89.29
0.17
256
-32.68
0.20
168
-81.60
0.05
163
-43.85
0.18
237
-38.12
0.29
127
-14.35
0.24
82
-28.69
0.16
150
-69.22
0.26
223
Wallace
Anderson
Perot
Log
Likelihood
-72.26 -27.07
0.14
0.06
Pseudo R2
165
85
N
Standard Errors in Parentheses
In 1962 and 1986, there was no variation on the dependent variable in districts where the
president’s share of the two-party vote exceeded the median value: i.e. all Representatives in those
districts who sought re-election won. Hence, for those years, we report the effect of presidential
support on the probability of victory only for members from districts where the president’s share of
the two-party vote was below the median value.
22
-3.17
(2.75)
Figure 1
First-Dimension W-Nominate Scores Johnson and House Democrats, 1965-66
-1
-.725
0
First Dimension W-Nominate
Johnson’s score is represented by the vertical line.
23
1
Figure 2
First-Dimension W-Nominate Scores Clinton and House Democrats, 1993-94
Clinton’s score is represented by the vertical line.
24