Building public support from the grassroots up: the impact of presidential travel on state-level approval.
Cohen, Jeffrey E. ; Powell, Richard J.
On September 11, 2001, as terrorists were attacking the World Trade
Center ant the Pentagon, President George W. Bush was visiting a Florida
school, publicizing and promoting his educational policies. Of course, a
terrorist attack of that magnitude rare, but a domestic presidential
trip is a common occurrence. As Figure 1 displays, from 1981 through
1999, presidents made an average of 59 visits to the states per year,
aver aging nearly 79 travel days per year. (1) Furthermore, the figure
shows an increase in presidential travel to the states over that period.
Presidential travel is an increasingly important aspect of the
public presidency, with the public presidency being one of the signature
developments of modern presidential leadership (Brace and Hinckley 1992;
Hart 1987; Lammers 1982). The public presidency involves, among other
things, presidential speeches to the public aimed at increasing
presidential visibility and mobilizing public support for the president
and his policies.
A considerable body of research has aided our understanding of the
many types of presidential activities that make up the public
presidency. We know, for instance, about the factors that motivate many
presidential public activities, such as press conferences and political
speeches (Hager and Sullivan 1994; Kernell 1986; Powell 1999). We also
know that major presidential speeches lift presidential job approval,
albeit briefly (Brace and Hinckley 1992, 1993; Kernell 1986; Ostrom and
Simon i985; Ragsdale 1984, 1987; Simon and Ostrom 1989). In contrast, we
know almost nothing about the impact of presidential trips around the
nation despite their frequency.
In this study, we investigate the impact of presidential travel on
state-level public approval. Not only do we steer our analysis to a
topic rarely studied, we also shift our focus from national- to
state-level effects. A shift in focus from the nation to the states is
important because presidents often target state publics in traveling
around the nation. When traveling to a state, presidents may aim to
boost their own approval, generate support for local politicians running
for (re)election (Cohen, Krassa, and Hamman 1991), build support for
their policies among members of Congress (Cohen et al. 1991; Kernell
1986; Powell and Schloyer 2003), and enhance their own reelection
prospects. The role of the Electoral College in presidential elections
and the importance of states as political units in the American federal
system also underscore the importance of looking at state-level effects
of presidential travel. This study looks specifically at the job
approval implications of presidential travel to the states.
Despite a conventional wisdom that the public activities of
presidents reap approval gains, research provides a mixed assessment of
the success of presidential efforts to influence public opinion. Some
studies, especially those focusing on major public speeches (Brace and
Hinckley 1992, 1993; Kernell 1986; Ragsdale 1984, 1987; Ostrom and Simon
1985) and campaign appearances (Cohen et al. 1991; Shaw 1999), find that
presidents can affect public opinion. Other studies, however, have
raised doubts about presidents' ability to gain the public's
attention and influence the direction of public opinion (Edwards 2003).
Given these varying assessments, domestic travel provides a useful
setting for testing these competing expectations about presidential
leadership of public opinion.
In the next section, we present a theoretical explanation of how
presidential travel affects public opinion. Then we discuss a new data
set that allows us to examine the impact of presidential travel on
state-level approval from 1981 through 1999 (Beyle, Niemi, and Sigelman
2002).2 For the first time, we are thus able to match appropriate levels
of analysis--travel to the states with state-level approval. (3) We then
present our data analysis and conclude with some thoughts on the impact
of public presidential activities on presidential approval and
suggestions for future research.
A Theory of Presidential Public Opinion Strategies
Presidents commit extensive resources to maintaining and enhancing
their level of support in the mass public. Some accounts contend the
White House assigns more staff to such publicity operations than any
other activity (Grossman and Kumar 1981; Maltese 1994; Patterson 2000).
To enhance their mass support, presidents engage in a number of public
activities, including nationally televised addresses, staged
pseudo-events, minor speeches to specialized audiences, and domestic and
international travel.
The volume of public presidential activities seems paradoxical
because research suggests the uneven effectiveness of such efforts.
Major public speeches and foreign trips, for example, result in only
small, fleeting increases in presidential job approval. Ragsdale (1987)
finds that major, nationally televised addresses produce a
three-percentage point increase in presidential approval on average.
Furthermore, these approval boosts are short-lived, evaporating within
several weeks. Upon further examination, Brace and Hinckley (1992) find
that major speeches lift presidential approval by about three points
during presidents' first terms, but have no effect during second
terms. Similarly, Ostrom and Simon (1985, 1989) find that presidential
trips abroad do little to boost approval when controlling for other
factors.
Assuming presidents are rational in their allocation of scarce
resources, why would they dedicate so much in the way of time and staff
for such a meager payoff?. Possibly, political scientists have been
looking for such effects in the wrong places. Specifically, presidents
may not view the public as an undifferentiated mass, but may be
sensitive to different subgroups. While political scientists have
typically tested for the impact of major speeches on the American public
as a whole, most presidential public appearances are targeted at
narrower, more specialized audiences (Hager and Sullivan 1994; Hart
1987; Kernell 1986; Powell 1999). To reach such audiences, presidents
frequently travel outside the immediate Washington, DC area.
So why might presidents expect to receive greater payoffs from
targeted visits to specific locales? Answering this question involves an
understanding of presidential motivations in seeking public support and
the role played by different types of media outlets in that process.
First, presidents believe public support helps their ability to govern
effectively and to get reelected. High levels of popular support may
lead others in the policymaking process, especially Congress, to be more
supportive of presidential initiatives (Cohen 1997; Edwards 1997).
Second, presidents believe that positive news coverage is necessary
to build and maintain public support (Kurtz 1998). Research suggests
that presidential approval rises when the public receives positive
information about the president, either because news is positive (Brody
1991) or elite discourse carried in the news is supportive of the
president (Zaller 1992). However, gaining positive news coverage has
become more difficult for presidents in the post-Vietnam, post-Watergate
era because the Washington press corps has become much more adversarial and negative in its coverage (Groeling and Kernell 1998; Grossman and
Kumar 1981; Patterson 1994). Although presidents have developed numerous
techniques aimed at diminishing such negativity (DiClerico 1993), the
incentives for journalists to maintain an aggressive, negative tone seem
to be stronger than presidential dissuasions (Patterson 1994).
Consequently, presidents direct many public activities to the local
stage through travel to specific locales where they expect news coverage
to be more positive (Kaniss 1991). Although presidents often bring some
members of the Washington press corps with them on such trips, the brunt of news coverage is borne by local news organizations and national wire
services. Wire service coverage can be very helpful for presidents
because it tends to emphasize straight news rather than interpretation
(Graber 1997). Even more beneficial for presidents, local press coverage
of presidential trips tends to be highly positive. Local journalists
often view such events as career-enhancing opportunities and they are
typically less competent and/or less willing to ask presidents tough
questions on controversial issues. These factors converge to produce
positive news stories about presidential trips, often emphasizing the
pomp, ceremony, and prestige of the office (Kaniss 1991).
Local news coverage of presidential trips also tends to be highly
visible. It often garners front-page and lead-story status in the local
and regional press, and may persist in the news for days. Thus, news
reporting about a local presidential trip may generate positive news
that reaches a large, local audience. Over time, presidents can travel
around much of the nation, knitting together a sizeable audience in this
fashion.
The State Presidential Job Approval Data
Public opinion data for this study come from the State Job Approval
Project, (4) which collected state-level job approval ratings for
presidents from a host of survey organizations. We utilize the
presidential polls from 1981 through 1999 (1,002 observations). (5)
However, there are several complications in using these data for our
analysis that need to be addressed.
First, the collected polls use a variety of question wordings and
response categories and come from a number of different polling
organizations using a variety of methodologies. A question arises as to
whether we can compare the level of presidential support across
questions, especially approval and favorability or likeability
questions. Appendix Table 1 lists the number of presidential polls by
response category. The JAR data set does not provide question wordings.
As the table indicates, almost all presidential poll questions appear to
be approval-type questions, based upon the response categories. Only two
categories use the term "favorable" (5, 37) for a total of two
cases. Almost all of the other response categories use either approval
terms or excellent/good variations. While we can be confident that the
approval response categories are based on approval questions, we cannot
be entirely certain that the "excellent/good" categories are
job evaluation questions. Because of this ambiguity in mind, we entered
dummy variables for each of these response categories as controls in all
of our models, a total of 21 dummies.
In some instances, only positive evaluations of the president are
available and "don't know" response rates also seem to
vary (Beyle et al. 2002). To correct for these problems, we use the
formula "(percent positive)/(percent positive + percent
negative)" to measure presidential approval (Beyle et al. 2002).
Similarly, Beyle et al.'s (2002) analysis found that as the number
of response categories increases, the likelihood of a negative rating
also increases. In sum, we need to be cognizant about the potential for
house effects. To guard against this problem, our models include dummy
variables to control for polling firm effects.
The JAR data set also contains many missing data points. Assuming
monthly readings and fifty states, 11,400 observation points are
possible, yet we have only 1,002 (8.8 percent) readings. Missing data
are more common in earlier than later years, in some states than others,
and in non-election years versus election years. This non-random pattern
may violate standard regression assumptions. We use robust standard
errors to help correct for this problem, but the missing data present a
more fundamental design issue that we address by creating a baseline
model of presidential job approval.
Ideally, we would want to test whether a presidential visit to a
state changes presidential approval. However, the many gaps in the data
make it impossible to measure approval change from one month to the next
at the state level. It is possible to work around this problem by
comparing the president's approval level in a particular state in
the days immediately following a presidential visit to those periods
when no such visit has taken place, relative to the president's
expected baseline popularity in that state. Such a cross-sectional
design requires that we control for other factors that affect
state-level presidential approval. As we demonstrate below, our normed
baseline model effectively accounts for these other sources of variation
in state-level presidential job approval.
The Appendix provides some descriptive information about the job
approval ratings employed in this analysis. Appendix Table 2 presents a
frequency count of the number of job approval ratings by year. Trips to
Maryland, Virginia, and the District of Columbia are excluded from these
totals. The number of state-level presidential poll readings varies from
5 to 164 per year, with an average of nearly 50 per year. Over time,
poll readings tend to increase in frequency. The average number of polls
per year tops 84 during the 1990s, compared to 11 per year from 1981 to
1989.
Appendix Table 3 presents the frequency of presidential polls by
state. The number of polls per state range from 1 for North Dakota to 93
for California, with an average of 19.6 per state. Although some large
states possess a higher than average number of polls, some smaller
states, notably Alabama, Arizona, Connecticut, and Kentucky, also show a
relatively high number of polls, and an occasional large state, such as
Massachusetts, has relatively few presidential polls. The number of
commercial, media, and academic polling organizations within the states
determines to a large extent the number of state-level presidential
polls.
A Baseline Model of Presidential Job Approval
The above discussion suggests two sources of variation in
state-level job approval, factors associated with conducting the polls
(e.g., response categories and polling firm) and factors that emanate from the political context. To control for changes in the political
context we include a normed measure of the presidential vote. Durham et
al. (2003) demonstrate that the normed state-level presidential vote in
the last election and the Gallup monthly national presidential approval
rating effectively explain most of the variance in state-level job
approval. The normed presidential vote, which measures the difference
between a state's presidential vote and the national average,
provides us with a sense of the basis of support for the president
across the various states. The Gallup national approval rating controls
for the temporal path of presidential approval. Thus, our baseline model
controls for both spatial and temporal sources of variation in
presidential approval. Following Durham et al. (2003) we employ these
two terms, lagging the Gallup measure to insure proper causality.
To isolate the effects of presidential travel, we add several other
variables in an attempt to explain as much variance in state-level
presidential approval as possible. As the fit of the baseline model
improves so too does our confidence that we can estimate the true impact
of presidential trips on state-level approval. Thus, we add variables
representing state-level economic conditions, consumer perceptions of
the economy, and state-level partisanship and ideology, all of which
have been found in prior research to affect public attitudes toward the
president.
Although we experimented with a larger number of economic
variables, we found four to be consistently related to state-level
presidential approval--inflation-adjusted state income (lagged one
quarter), the consumer price index (lagged one month), consumer
expectations, and consumer confidence (lagged one month). The consumer
expectations and confidence data come from the University of
Michigan's Survey of Consumers. (6)
Last, we add controls for state partisanship and ideology, using
the updated Erikson, Wright, and Maclver (1993) measure. For state
partisanship, we calculate the percentage of Democratic and Republican
identifiers for subsets of years (1977-1984, 1985-1992, and 1993-2001).
The subsets are long enough to protect against short-term variation that
may result from sampling and other error, but still remain relatively
close in time to the measurement of the president's popularity. We
calculate state partisanship as (percentage of the president's
party identifiers)--(percentage of opposition party identifiers).
Similarly, we calculate state ideology with the formula for Democratic
presidents as (percentage of liberal identifiers)--(percentage of
conservative identifiers), and vice versa for Republican presidents.
Table 1 presents the results of regressing state presidential
approval on the political context variables, plus dummies for polling
firm and response category, using robust standard errors. This baseline
model explains the overwhelming proportion of the variance in
state-level presidential approval, with an R2 surpassing 76 percent.
These results indicate that state-level approval is, in fact, largely a
function of the normed presidential vote, the prior month's
national approval rating, quarterly lagged income, lagged economic
confidence, current economic expectations, lagged CPI, state
partisanship, and state ideology. Although not shown in Table 1, many of
the polling firm and response category dummies also attain statistical
significance. Given the strong [R.sup.2], the baseline control model
effectively accounts for the major sources of variation in state-level
presidential approval.
A Model of Presidential Job Approval in the States
Our primary question asks whether a presidential trip to a state
significantly influences presidential approval, controlling for that
state's expected approval of the president from the baseline model.
The strong [R.sup.2] of the baseline model presents a high hurdle for
assessing the effects of presidential trips.
We measure presidential visits with a dichotomous dummy variable (VISIT), which indicates the presence or absence of a presidential visit
to a state during a particular month. (7) We use the lagged measure of
this variable to eliminate endogeneity between presidential visits and
popularity. Also, we drop Maryland, Virginia, and the District of
Columbia from the estimation because of the large number of visits they
receive and ambiguity about whether these are truly "local"
visits. As shown in Appendix Tables 2 and 3, about 19 percent of the
data points with presidential state polls were preceded by a
presidential visit to the state in the previous month. Nine states for
which we possess presidential poll data do not show a presidential trip
to the state in the preceding month. Most of these states are ones with
small numbers of state polls. (8)
Above, we also conjectured that presidential visits to the states
are typically covered by the local media. We were able to get an
illustrative sense of local news coverage of presidential trips by using
the Lexis-Nexis news database. To do so, we used the U.S. News category,
which permits one to search the news sources for each state separately.
Unfortunately, it was not possible to collect data that were comparable
across states because of unevenness in the inclusion of news media
sources across states. For instance, some major newspapers, like the
Detroit Free Press, are not included. Thus, even large states with major
news organizations are not always included in the Lexis-Nexis database.
Second, the earlier in time, the fewer the number of news organizations
included. In the early years of the Lexis-Nexis compilation, the New
York Times dominated coverage.
With these limitations in mind, we performed an exploratory
examination of news coverage of presidential trips in 1995, a year we
chose because it was a non-election year and also recent enough to
contain relatively broad coverage in Lexis-Nexis. Then, we ran a search
for news coverage in each state the president visited during the month
of the visit. (9) Appendix Table 4 displays the results of this search
for each state the president visited. As this table indicates, many of
the presidential trips did, in fact, generate healthy doses of coverage.
For example, President Clinton's 1995 trips generated a total of 34
stories in California, 37 in Florida, 12 in Georgia, 15 in Illinois, 29
in Michigan, 28 in New York, 8 in Ohio, and 15 in Texas. While 11 of the
25 states indicate no corresponding story, we have no way to determine
whether this was due to the limitations of the Lexis-Nexis archive, as
noted above, or the failure of the news media in these states to cover
the president's trip. Nevertheless, our search suggests that
presidential trips often yield local news coverage.
As shown in Table 1, regressing VISIT on presidential approval,
with controls for the baseline variables, indicates that a presidential
visit boosts state-level support by about 1.3 percent on average, which
is statistically significant (p = .043, t = 2.03). While this effect is
modest, it may be the case that longer stays in a state will have more
impact on approval than shorter stays. To test this hypothesis, we reran the model with a variable measuring the total number of days the
president visited the state. (10) Results (not shown) indicate that the
length of stay in a state matters little, failing to reach statistical
significance. All of the impact of a trip on approval is picked up by
the dichotomous VISIT variable. (11)
Contextual Effects and Presidential Trips
The effects of presidential trips may vary with characteristics of
presidents and the state to which they travel. In this section, we test
for contextual effects of state size and the election cycle.
Large- Versus Small-State Effects of Presidential Visits
Presidents are more likely to travel to large states than small
ones (the correlation between population and days in the state is .56, p
= .000). Small population size reduces presidential incentives to visit.
This is especially the case during election periods, when Electoral
College implications become increasingly important in presidential
calculations. The relative scarcity of presidential trips to small
states, however, may raise the value of a trip by generating greater
levels of press coverage due to the novelty of a presidential visit.
Also, trips to small states may receive relatively more statewide
attention because small states are likely to have fewer large media
markets. For example, a presidential trip to Buffalo, NY may go
unreported in the New York City area, but a trip to Casper, WY would
likely generate news across the state. This may lead to greater
popularity boosts in small as opposed to large states, despite general
incentives to focus more attention on large states. We test this
hypothesis by dividing our sample into small and large states. (12)
Table 2 reports the results of our model with dummy variables added
for large and small states. Contrary to our hypothesis, visits to large
states are more likely to generate approval effects than visits to small
states. Although the regression coefficients for the two trip variables
are similar, only the large-state variable attains statistical
significance. (13) The results indicate that a trip to a large state
generates about a 1.2 percent increase in approval, about the same
magnitude of the undifferentiated trip variable from Table 1. (14)
Although we were surprised by these findings, on further
examination it seems that several factors may account for the greater
impact of presidential trips in large states than small states. Perhaps
the news media in small states do not possess the resources to cover a
presidential trip as intensely as media organizations in larger states,
which serve larger media markets. Moreover, the major news media in many
small states are often dominated by news organizations from larger
states, especially for small states located near larger ones. These
out-state news organizations may not cover presidential trips to
neighboring small states as intensely as they report presidential trips
to their home state. For example, news media based in New York or
Pennsylvania may be less likely to cover trips to New Jersey or
Delaware.
Election Cycle Effects
Election cycles, by influencing presidential travel decisions,
might also affect whether a trip boosts the president's popularity.
For instance, presidential sensitivity to public opinion may be greater
in election than non-election years. Therefore, election-year travel may
be geared more toward popularity effects, focusing on the electoral
implications of enhanced presidential popularity. Such concerns might be
muted during non-election years.
These effects may also be different in presidential and midterm election years. In midterm election years, presidents often travel in
support of their party's candidates for a variety of offices (Cohen
et al. 1991). In the absence of being directly challenged during
midterms, presidents may accent their presidential duties and wrap
themselves (and the candidates for whom they are aiding) in the aura of
the office. In contrast, presidential election years pit the president
against an adversary who may try to undermine the president's
image, forcing the president to engage in political self-defense.
Presidents may look more like candidates and less like presidents in
presidential election years. Thus, we may not find as great an impact of
trips on approval during presidential election years as in midterm
election years, even though the impact of travel on approval is likely
to be stronger in both types of election years than non-election years.
We test these hypotheses by adding to our baseline model
interaction terms between a presidential visit and the three points of
the electoral cycle: non-election years, midterm election years, and
presidential elections years. The results from this model, shown in
Table 2, confirm that trips in presidential election years do not affect
presidential approval, but neither do those in midterm election years.
On the other hand, trips in non-election years display a significant
effect, boosting approval by about 1.4 points (p = .05, two-tailed
test). (15)
Perhaps it is the case that presidents appear more presidential
when they are not campaigning. When campaigning for themselves or
others, presidents may look like politicians. While presidential
campaign appearances may help stimulate turnout among those already
likely to support the president or his allies, campaign appearances, due
to their overtly partisan nature, may not result in higher job approval
for the president. In contrast, when traveling around the nation during
non-election years, presidents may utilize the symbolic aspects of the
office to generate heightened support. As such, they look more like
presidents than candidates for office, eliciting a more positive
response from citizens.
Furthermore, in presidential election years, the opposition
party's candidate for the presidency is also highly likely to visit
the state, undermining the effects of the sitting president's visit
to a state. In other words, the campaign effort of the two competing
candidates may cancel each other's impact on state electorates. And
as Cohen et al. (1991) argue, in midterm elections, the presidential
decision calculus to visit a state may be motivated more by a desire to
help his co-partisans than to boost his own popularity. Thus, the
context of elections may mute the popularity effects of a presidential
visit.
Conclusion
Over the past hundred years or so, public activities have become a
pronounced aspect of the presidency. Even though a great deal of
research has been conducted on the public presidency, almost all of it
has focused on the impact of these presidential activities on national
opinion. Although much presidential activity targets subsets of the
nation, we have little understanding of the impact of presidential
activities on these subnational publics. In this study, we shift our
research focus to the states to address this concern.
Our study began with a seeming paradox: If presidents are rational
in their allocation of scarce resources (time, staff, etc.), why do they
commit so many resources to boosting public approval when their ability
to do so by giving speeches and appearing in public seems so modest? We
hypothesized presidents will enjoy greater returns from their public
activity by traveling outside of the Washington, DC area where the local
news reporting environment is less hostile. Using a new data set of over
1,000 poll readings at the state level across the 1980s and 1990s, we
find that presidents can achieve a modest boost in state-level approval
through strategically crafted public appearances. However, these effects
are not uniform across all types of states and contexts. In general, we
find that presidents hoping to achieve approval gains through domestic
travel are more likely to be successful by focusing their efforts on
large states in non-election years.
Because we detect only about a one- to two-point impact on approval
from a presidential trip, some may find our results exceedingly modest
and thus of little substantive interest. However, data and design
limitations almost certainly contribute to the limited nature of the
effects we detect. Although we possess 1,000 cases for analysis, they
represent a sprinkling of data points across the time period we
examined. This forced us to use a cross-sectional design, when ideally
we would prefer a dynamic design that would enable us to measure the
difference in approval before and after a presidential trip. Our
cross-sectional approach may have attenuated the effect of presidential
trips. Given these data and design restrictions, we find it remarkable
that we uncovered a statistically significant effect at all.
Furthermore, we should only have expected a marginal effect on
presidential approval. As an aggregate attribute, presidential approval
tends to move slowly, even when major shocks hit, like positive or
negative events (Brace and Hinckley 1992). Few events produce massive
surges or declines in presidential approval. That is, few events
stimulate rallies (Edwards and Swenson 1997). Given the inertia in
presidential approval, our results are more impressive than they appear
at first glance.
Finally, our measurement of presidential trips is quite blunt. When
we refine our analysis to distinguish between trips to different types
of states and at different points in the electoral cycle, we find that
trips only affect opinion in larger states and during non-election
periods. This indicates that the impact of presidential trips on public
opinion varies with key aspects of the political context. A fruitful
avenue for future research along the lines pursued here might be to
refine the measurement of presidential trips, as well as public
activities in general.
Despite these obvious limitations, we learn something new about the
relationship between the president and the public from our findings.
Presidents seem to more greatly affect public opinion when they appear
presidential, as opposed to being a candidate for office or a supporter
of their party's candidates for office. Partisan behaviors are
naturally divisive; they are likely only to mobilize those already
favorable to the president, as Cohen et al. (1991) find in their study
of presidential appearances in midterm elections. But when presidents
appear "presidential," that is, when they speak to the mass
public writ broadly and when they speak to it as the nation's
representative and leader, they are able to increase their level of
support.
Appendix
APPENDIX TABLE 1
Number of Presidential State-Level Popularity Polls by Question
Response Category
JAR Code N Response
1 451 Excellent, good/fair, poor
3 275 Approve/disapprove
5 1 Favorable/unfavorable
6 78 Excellent, good/only fair, poor
7 11 Excellent, good/not so good, poor
8 60 Excellent, good/fair, poor, very poor
10 9 Excellent, pretty good/only fair, poor
12 9 Very good, good/fair, poor, very poor
13 1 Excellent, above average/average/below average, poor
16 6 Strongly approve, approve/disapprove, strongly
disapprove
19 2 A B/C/D F rating
21 16 Excellent, pretty good/just fair, poor
22 1 Positive/negative
28 3 Excellent, pretty good/fair, poor
30 1 A 4-point scale from high {4/3} to low [2/1]
37 1 Very favorable, somewhat favorable/somewhat
unfavorable or very unfavorable
39 2 Excellent, good/below average, poor
40 1 Fairly good/fairly bad, in between
41 2 Above average/average, below average
42 3 Excellent, very good/fair, poor
43 1 Satisfied/dissatisfied
Source: Official State Job Approval Ratings data set. See text for
details.
APPENDIX TABLE 2
State Presidential Poll Readings and State Trips, by Year, 1981-1999
Presidential Trips to State
Year Number of Poll Readings No Yes % (a)
1981 5 5 0 0
1982 7 7 0 0
1983 7 7 0 0
1984 11 9 2 18.18
1985 11 11 0 0
1986 15 11 4 26.67
1987 16 15 1 6.25
1988 18 13 5 27.78
1989 12 10 2 16.67
1990 23 15 8 34.78
1991 48 41 7 14.58
1992 19 13 6 31.58
1993 102 87 15 14.71
1994 164 141 23 14.02
1995 124 109 15 12.10
1996 164 122 42 25.61
1997 49 41 8 16.33
1998 100 74 26 26
1999 48 31 17 35.42
APPENDIX TABLE 3
State-Level Presidential Polls and Trips, by State, 1981-1999
Presidential Trip
State Total No Yes % (a)
Alabama 39 38 1 2.56
Alaska 2 2 0 0
Arizona 42 41 1 2.38
Arkansas 12 11 1 8.33
California 93 41 52 55.91
Colorado 13 13 0 0
Conn. 34 30 4 11.76
Delaware 3 3 0 0
Florida 37 28 9 24.32
Georgia 24 21 3 12.50
Hawaii 5 5 0 0
Idaho 6 5 1 16.67
Illinois 34 19 15 44.12
Indiana 19 17 2 10.53
Iowa 23 22 1 4.34
Kansas 7 7 0 0
Kentucky 31 24 7 22.58
Louisiana 16 15 1 6.25
Maine 4 4 0 0
Mass. 6 4 2 33.33
Michigan 32 27 5 15.63
Minnesota 16 14 2 12.50
Mississippi 12 11 1 8.33
Missouri 5 2 3 60.00
Montana 14 13 1 7.14
Nebraska 11 11 0 0
Nevada 9 9 0 0
New Hampshire 24 22 2 8.33
New Jersey 61 53 8 13.11
New Mexico 21 20 1 4.76
New York 58 24 34 58.62
North Carolina 26 24 2 7.69
North Dakota 1 1 0 0
Ohio 32 26 6 18.75
Oklahoma 10 10 0 0
Oregon 7 7 0 0
Pennsylvania 9 7 2 22.22
Rhode Island 20 19 1 5.00
South Carolina 10 10 0 0
South Dakota 4 4 0 0
Tennessee 11 9 2 18.18
Texas 36 28 8 22.22
Utah 3 3 0 0
Vermont 7 7 0 0
Washington 15 14 1 6.67
West Virginia 5 4 1 20.00
Wisconsin 22 22 0 0
Wyoming 12 11 1 8.33
(a) Percentage of state presidential polls with a presidential visit
to the state in the previous month.
APPENDIX TABLE 4
Number of Local News Stories about Presidential Trips in the
Month of the President's Trip to a State, 1995
State Stories
Arkansas 9
California 34
Colorado 18
Connecticut 2
Florida 37
Georgia 12
Hawaii 0
Illinois 15
Iowa 0
Massachusetts 0
Michigan 29
Minnesota 2
Montana 0
New Hampshire 0
New Jersey 0
New York 28
North Carolina 0
Ohio 8
Oklahoma 0
Oregon 0
Pennsylvania 1
Tennessee 1
Texas 16
Vermont 0
Wyoming 0
Source: Lexis-Nexis. See text for details.
TABLE 1
Impact of Baseline and Presidential Visits on State-Level
Job Approval, 1981-1999 (Robust Regression)
Baseline Model
b SE t p
Visit (lag) --
Gallup (lag) .79 .04 21.76 .000
Normed vote .32 .06 5.01 .000
St. income (lag) .08 .02 3.06 .002
Expectations .13 .04 3.43 .001
Confidence (lag) .22 .04 5.23 .000
CPI (lag) -.40 .04 -11.27 .000
St. PID .21 .06 3.74 .000
St. ideology .22 .08 2.84 .005
Constant -7.68 5.83 -1.32 .188
[R.sup.2] .77
n 929
Visit Model
b SE t p
Visit (lag) 1.31 .64 2.03 .043
Gallup (lag) .79 .04 21.95 .000
Normed vote .32 .06 5.02 .000
St. income (lag) .07 .02 2.94 .003
Expectations .13 .04 3.54 .000
Confidence (lag) .22 .04 5.20 .000
CPI (lag) -.40 .04 -11.35 .000
St. PID .21 .06 3.66 .000
St. ideology .21 .08 2.74 .006
Constant -6.84 5.86 -1.17 .244
[R.sup.2] .77
n 929
Source: JAR data set. The estimation also includes controls for polling
firms and response categories.
TABLE 2
Impact of Presidential Visits by Election Cycle and State Size,
1981-1999 (Robust Regression)
Election Cycle
b SE t P
Visit-midterm 2.18 2.49 .88 .38
Visit-pres. elec. .53 1.17 .46 .65
Visit-no election 1.40 .72 1.94 .05
Visit-large state -
Visit-small state -
Gallup (lag) .79 .04 21.93 .00
Normed vote .32 .06 5.11 .00
St. income (lag) .07 .02 2.89 .004
Expectations .14 .04 3.61 .00
Confidence (lag) .21 .04 5.19 .00
CPI (lag) -.40 .04 -11.35 .00
St. PID .20 .56 3.64 .00
St. ideology .21 .77 2.73 .01
Constant -6.49 5.77 -1.13 .26
[R.sup.2] .77
n 929
State Size
b SE t p
Visit-midterm --
Visit-pres. elec. --
Visit-no election --
Visit-large state 1.19 .72 1.66 .10
Visit-small state 1.67 1.30 1.28 .20
Gallup (lag) .79 .04 21.94 .00
Normed vote .32 .06 5.00 .00
St. income (lag) .07 2.00 2.95 .003
Expectations .13 .04 3.55 .00
Confidence (lag) .22 .04 5.20 .00
CPI (lag) -.40 .04 -11.41 .00
St. PID .21 .56 3.66 .00
St. ideology .21 .77 2.75 .01
Constant -6.91 5.89 -1.17 .24
[R.sup.2] .77
n 929
Source: JAR data set. The estimation also includes controls for polling
firms and response categories.
(1.) A visit to a state occurs every time a president travels
outside of the Washington, DC area, appears in a state, and makes a
public speech. Presidents may visit several states on one excursion.
These counts exclude all public presidential appearances made within
Washington, DC, Maryland, and Virginia.
(2.) Because we use state-level approval data, our level of
analysis is the state. Thus, when we speak of domestic presidential
travel, we are speaking of presidential visits to states. Other units of
analysis are possible, such as to localities, but lacking data on
approval at the local level, we cannot pursue an analysis such as the
one offered here.
(3.) The only existing analysis of presidential domestic travel
looks at its impact on national-level presidential approval. That
research suggests that domestic travel results in lower national
presidential approval during the president's first term in office,
but has no effect during the second term (Brace and Hinckley 1992, 52).
It is not clear why presidential travel should sometimes result in lower
approval levels. Brace and Hinckley argue that presidents travel around
the nation in response to negative events, but they provide no direct
evidence in support of their hypothesis. We argue one possible cause of
Brace and Hinckley's negative finding is that they mismatch units
of measurement, state travel with national-level approval. Simon and
Ostrom (1989) look at the impact of foreign travel on presidential
approval and find no impact.
(4.) This data collection project was directed by Thad Beyle,
Richard Niemi, and Lee Sigelman, and funded by the NSF (grant
SES-9974176). We thank them for allowing us to use the data.
(5.) The data series begins with 1947, but only 34 readings exist
from 1947 to 1980.
(6.) We experimented with various lags of the named variables, plus
monthly unemployment data measured for the month of the poll reading, as
well as for each of the three months preceding each poll (a total of
four variables). Many of the economic variables are highly correlated
with each other. This may induce multicollinearity, rendering the
coefficient's significance tests unreliable. To determine whether a
variable should remain in the baseline model, we computed F-tests
comparing the [R.sup.2]'s of equations that included or excluded
the variable in question. Each of the final variables in the baseline
model added a significant increment to the explained variance based on
the F-tests.
(7.) Data on presidential trips were collected from successive
issues of the Public Papers of the Presidents of the United States series, which provides a complete record of all public presidential
statements. We include any trip on which the president delivered at
least one spoken public statement of at least 150 words. Thus, we do not
include purely private trips such as family vacations with no public
appearances.
(8.) These nine states account for 12 percent of the presidential
poll readings.
(9.) In searching the states' media sources, we used the
following criteria: "President Clinton w/s (within the same
sentence as) speech or visit or trip or appearance or reception or spoke
or attend or tour or address or campaigned."
(10.) The VISIT variable was actually calculated from the DAYS
variable. For both variables, when the president did not visit the
state, the variable is scored a "zero." The only difference in
VISIT and DAYS is that VISIT is scored a "one" no matter how
many days a president visited the state, but DAYS takes on the actual
value of the number of days that a president visited the state.
(11.) To test for the robustness of these results, we reran all
estimations using OLS, which essentially replicated the reported
results. Furthermore, we estimated fixed effects models, identifying
fixed effects for polling firm, response categories, and question
wording. Reported results remained intact, with a presidential visit to
a state boosting job approval by about 1.5 percentage points.
(12.) We use a cut point of 5 million people to classify small and
large states. This bisects the sample into subsets of 415 and 514 cases.
We tried other cut points, but the results remained essentially the
same.
(13.) The table indicates a two-tailed p value of .10, but because
we know direction, we should more properly use a one-tailed test, which
produces a p value of .05.
(14.) The small-state coefficient may be depressed because we have
not distinguished between small states that out-state media have
penetrated significantly from small states with little out-state media
presence. Our idea here is that when out-state media possess a large
presence in a small state, they are less likely to cover a presidential
trip. The lack of presidential trip coverage should result in weaker
trip effects. We used the Nielsen Media Designated Market Area (DMA) map
to determine how much of a state's media markets are controlled by
out-state news media. Of small states, we find 17 in which indigenous
media control the overwhelming percentage of the state's news media
markets. Unfortunately, in our data set, we located only 10 presidential
trips to these 17 states in months for which we also have state-specific
presidential popularity data. We created a dummy variable for these
small states with a presidential visit. When entered into various
equations with and without the other state size variables we find no
impact, but the lack of effect may be a function of the paucity of data
to test this hypothesis.
(15.) We also investigated three-way interactions among VISIT, the
election cycle, and state size by creating a dummy variable for VISIT
plus large state plus non-election year and another one for VISIT plus
small state plus non-election year. Our hypothesis is that the modest
effects noted for the election cycle and state size might grow when both
conditions are present. In neither case did these interactions prove
statistically significant. When we enter the visit-large-non-election
dummy, we generate b = .87, SE = .77, t = 1. 13, p = .26 (two-tailed).
For the visit-small-non-election dummy we produce b = 2.45, SE = 1.82, t
= 1.35, p = .18 (two-tailed). With both of these dummies entered
together, results are comparable to those reported here. It is not clear
why the three-way interaction would not reach significance when the
election cycle and state size variables do separately, other than the
three-way interaction may be segmenting the states into small subsets or
the new interactions may not be discriminating among the states as well
as the original state size and electoral cycle variables. In fact, when
large-state and non-election cycle variables are added into the
estimation together, neither reaches significance because they are
highly correlated (r = .73, p = .00), indicating high multicollinearity
between them. Presidents, it appears, are more likely to visit large
states in non-election years compared to election years. The
correlations for visits to large states in presidential and midterm
election years are .27 (p = .00) and .33 (p = .00), respectively. While
statistically significant, these correlations are of modest magnitude.
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Jeffrey E. Cohen is professor of political science at Fordham
University and the author of several books, including Presidential
Responsiveness and Public Policy-Making, as well as articles in numerous
journals, including the American Political Science Review, American
Journal of Political Science, and Journal of Politics.
Richard J. Powell is assistant professor of political science at
the University of Maine and the author of journal articles and book
chapters on the presidency, Congress, elections, and state politics, and
co-author of Changing Members The Maine Legislature in the Era of Term
Limits.