The Gubernatorial Coattail Hypothesis Considered: Determining the Effects of the Gubernatorial Race on the Senatorial Contest

THE GUBERNATORIAL COATTAIL HYPOTHESIS CONSIDERED:

DETERMINING THE EFFECTS OF THE GUBERNATORIAL RACE ON

THE SENATORIAL CONTEST

Peter F. Bums University of Maryland

Do gubernatorial races influence Senate outcomes when the two candihtes run on the same ticket? The gubernatorial coattail hypothesis posits that gubernatorial elections have a major influence on senatorial elections because of the governor’s ( I ) visibilig, (2) accountabilig, and (3) role as state parg leader. The hypothesis also claims that the voters use the gubernatorial race as the barometer for the rest of the ticket. Analyses of fwe diverse states indicate that a uniform gubernatorial coattail effect is not present. Each state varies in its electoral c&namics indicating that political orientation, party organizational and institutional differences among the states are important determinants of gubernatorial and senatorial votes.

American federalism is a “system of government in which power is divided by a constitution between a central government and regional governments” (Lowi and Ginsberg 1996, A41). Do American voters view their central and regional governments as distinct and divided when they vote for federal and state candidates in the same election? More specifically, what factors do voters consider when they vote for governor and U.S. senator in the same election? Are these two races disjointed or linked? If they are related, which office influences the other?

PREVIOUS LITERATURE Three factors tend to make gubernatorial elections and the governor

more prominent in the voters’ minds than senatorial elections and the senator. First, the governor’s race is more visible than the senatorial race. More media attention and a greater focus on issues are afforded to gubernatorial races than senatorial ones (Kahn 1995). The findings that guber-

Southeastern Political Review Volume 27 No. 1 March 1999

I52 Southeastern Political Review Vol. 27 No. I

natorial races are more distinct (Tompkins 1988) and more competitive (Gross and Breaux 1991) than senatorial races support the claim that gubernatorial elections and the candidates that run for that office are more prominent than their senatorial counterparts. Furthermore, the attention paid to the Senate race is not consistent. The popularity of the Senate race depends upon senatorial candidate characteristics (Abramowitz and Segal I992), the intensity of Senate elections, the resultant information these elections provide and the national backdrop (Westlye 1991). In net, these combined attributes of both the gubernatorial and senatorial races suggest that the governor is more prominent in the eyes of the voters than is the senator.

Second, several works find that voters hold the governor and not the senator accountable for the condition of the state, in general, and the economy, in particular (Shaffer and Chressanthis 1991; Howell and Van- derleeuw 1990; Leyden and Borrelli 1995; Partin 1995; Atkeson and Partin 1995; Svoboda 1995). Not all research, however, claims that the governor is held accountable for the state’s economic performance (Chubb 1988; Simon 1989; Kenney 1983). These latter works, however, do not suggest that the senator is held accountable for the state or national economy.

In a variation of the accountability theme, Stein (1 990) argues for a federalist interpretation of voting. Voters evaluate candidates based upon the duties that they expect a particular officeholder to perform. These expectations are rooted in the constitutional responsibilities of the office. The president and senators are therefore held accountable for the national economy because of their constitutional and fiscal responsibilities, whereas the governor is not held responsible for the state’s economy because voters realize that the “actions of subnational governments are simply constrained by macroeconomic conditions generally defined by national and interna- tional economic policies” (Stein 1990, 30). While research is undecided on the question of accountability, a body of literature exists which supports the notion of gubernatorial accountability.

The third attribute that has been afforded to the governor, yet not the senator, is that of party leader. While governors may not cherish the role of party leader, it is written in their Handbook that they are expected to be the state party leader (Muchmore and Beyle 1983). Very few scholars, if any, acknowledge that the state party leader is the U.S. senator. Overall, these three traits-recognition, accountability, and party leadership-place the governor in a more visible and prominent position among voters. Does this position affect how voters decide their choice for governor and senator when the two candidates run in the same election?

The Gubernatorial Coattail HvDothesiS 153

HYPOTHESES This paper operates under two levels of hypotheses. The first level

hypothesizes that the gubernatorial race has a major influence on the Senate election. The second level of hypotheses explains how gubernatorial coattails work. A description of the first level of hypotheses, which provides the theoretical foundation for the gubernatorial coattail effect, will be followed by a discussion of the second level of hypotheses, which explains how voters emphasize certain socioeconomic and political factors in voting for governor when the governor and the senator run on the same ticket.

The first level of hypotheses posits that people receive their voting cues from the candidate who has the most impact upon their lives. It has been hypothesized that in presidential election years, voters base their decisions for the other races, in large part, upon their opinion of the presidential candidate (Campbell and Summers 1990). The same phenomenon holds true in gubernatorial elections. In gubernatorial election years, voters base their decisions for the other races, in large part, upon their opinion of the gubernatorial candidate. This trend can be referred to as gubernatorial coattails.

The three aforementioned factors which make the governor more prominent than the senator combine to explain why the gubernatorial candidate carries the senatorial candidate. First, gubernatorial candidates are more recognizable and visible than senatorial candidates. There are 100 senators and 435 congresspersons but only 50 governors. Furthermore, governors live and work in the state during their tenure whereas senators spend only part of their time at home and actually work in Washington, DC. The governor’s visibility and proximity to the voters are reflected in the voters’ emphasis on the gubernatorial race.

Second, the actions of the governor impact the voters more quantita- tively and directly than the actions of the U.S. senator. This accountability makes the governor the focal point of the ticket. For example, many voters can blame the governor if state taxes increase. Voters could vent their frustrations for a federal tax increase on the president or their U.S. senators or representative. Governors have much less electoral camouflage than federal officeholders. The literature that contends that the governor is not held accountable does not take into account that gubernatorial institutional power has significantly increased over the years, particularly in regard to budget making capacities, duration of term, appointment authority, item vetoes, reorganization authority, salary, and improved staffing (Beyle 1995; Walker 1995; Sabato 1983).

Third, as the titular head of the state party, the gubernatorial candidate serves as the voters’ primary party cue. Voters, who will often use party as

154 Southeastern Political Review VoL 27 No. I

a voting cue, focus upon the gubernatorial race because the governor is perceived as the head of the party. They will consequently take any stereotype that applies to the governor’s party and exaggerate it when determining the governor. Conversely, senators will not be regarded as the party leader and their election results will follow the results of the gubernatorial election.

The preceding hypotheses suggest that voters (a) have a stereotypical view of the political parties (Rahn 1993) and (b) take this stereotype and emphasize it while voting for governor. The political variables, which are described below, will not be as emphasized for the senator as they are for the governor because the senator is not the head of the party. Overall, it is hypothesized that voters first seriously consider socioeconomic and political variables in determining the governor and then use this opinion of the governor to decide upon the senator.

The following hypotheses, which constitute the second level of hypotheses, will be built into a model to test if and by how much voters emphasize the gubernatorial race over the senatorial race. If the coefficients are higher for the governor than the senator, then the gubernatorial coattail hypothesis can be asserted because this would provide evidence that the senatorial results follow the gubernatorial results. These hypotheses also attempt to explore whether proximity to the voters, accountability, and party leadership can be attributed to the governor.

First, as family median income increases, the percentage of voters for the Democratic gubernatorial candidate will decrease. This hypothesis plays upon the theme that the Republicans favor the wealthy. Next, on the one hand, as the unemployment rate increases, the percentage of vote for the Democrat will increase because Democrats are seen as being supportive of social programs that seek to combat poverty. On the other hand, Republicans are viewed as anti-big government and are more likely to cut big social programs. The exception to this hypothesis is that incumbent Democratic governors would be penalized for high unemployment because they are held accountable for the state’s economy.

In addition, because minorities are traditionally seen as being in favor of the Democratic party, it logically proceeds that as the percentage of minorities in a county rises, the percentage of the vote for the Democratic candidate will also rise. Urban areas are also more likely to vote Demo- cratic. As the population density of a county increases, the percentage of vote for the Democratic candidate will also increase.

Furthermore, research indicates that the middle class is often determined by level of education. People with a college education are members of the middle to upper, middle class and upper class while those with a high school

The Gubernatorial Coattail Hvpothesis 155

education are mostly members of the lower middle to middle class and the lower class (Ehrenreich 1989; Centers 1961). As the percentage of people with a bachelor’s degree increases in a county, the more likely that county is to vote Republican. As the percentage ofhigh school graduates increases, the percentage of vote for the Democratic candidate will increase. These hypotheses play upon the theme that the Republicans, in general, are more highly educated than the Democrats.

Party plays a role in and of itself. A voter’s socioeconomic status helps determine the voter’s party and party often helps the electorate determine the candidate of its choosing. Even if the voters are unaware of the unemployment, poverty, and crime rates, they can still use party as a voting guide. When the voters go into the booth and do not recognize candidate X by name, they can use party to familiarize themselves with the candidate. As the number of Democrats, as a percent of major voters, increases, the percentage of votes for the Democratic gubernatorial candidate will also increase.*

Party organization is also critical to a candidate. If the party is unified, the candidate’s percentage will increase. The more divided a party is, the lower that party’s candidate’s percentage will be. The higher the divisiveness for the Republican party, the higher the percentage for the Democrats.

Does the coattail effect apply for all races? Do gubernatorial coattails exist if the gubernatorial race is being contested by two unknowns while one Senate candidate is extremely well-known? The proximity, accountability, and party label of the governor will impact the Senate candidate regardless of who the incumbent is or who is better known.

Incumbency does influence elections, however. On the one hand, gubernatorial incumbency will raise the percentages of the gubernatorial and senatorial candidate of that party. On the other hand, senatorial incumbency will have a positive influence on the senatorial race but will not transcend that race as is hypothesized in the gubernatorial model. The five states that are examined4alifornia, Kansas, Pennsylvania, New York, and Florida-have gubernatorial elections that occur during mid- term presidential elections. Presidential incumbency in these states will have minor effects on both the gubernatorial and senatorial races in the negative direction. For example, ifthe incumbent president is a Republican, the percentage for the Democratic candidate will increase because these gubernatorial and senatorial elections occur in the mid-term, which is traditionally harmful to candidates of the president’s party.

How do all these factors relate to how people vote for governor and senator and more important for this research question, how does the gubernatorial vote influence the senatorial vote? Voters use all of these

156 Southeastern Political Review Vol. 27 No. I

variables to decide upon the governor because of the governor’s proximity to the voters, accountability, and party leadership role. The gubernatorial candidate influences the rest of the ticket because voters first focus on this race for these reasons and then use this race as the voting cue. In comparison to the governor, the senatorial candidate’s relative unimportance leads the voter to place less weight on the aforementioned variables when determining the senator. This is not to say that these variables are irrelevant in determining a U.S. senator. Rather, the impact of the variables is more influential on the gubernatorial race. The variable that is most important and influential on the senatorial race is the gubernatorial percentage. The emphasis on the gubernatorial race means that the senatorial race will follow it in result, but not in magnitude.

DATA AND MODEL Each model is specified to test the impact ofpolitical and socioeconomic

variables on the vote for the Democratic gubernatorial and senatorial candidate^.^ Pooled, cross-sectional, county-level data from the last four elections in which the governor and the U.S. senator ran together in California, Florida, Kansas, New York, and Pennsylvania were used. County-level data are utilized in order to detect a potential coattail effect for two reasons. First, in contrast to city-level data, county-level data control for the effects of one city dominating the results. While New York City, for example, may dominate the city findings, its dominance is controlled by the many other counties in New York State, provided county- level data are used. In this regard, county-level data provide a more complete and accurate picture of coattails than city-level cases because they are less prone to be dominated by one entity.

Second, in contrast to state-level data, county level data are large enough to capture the context and nuances of the two races. If only state-level data are used, the researcher would know who won and lost the races, but would not know if the individual areas of the state actually experienced a coattail effect. “County-level figures [also] capture the relative concentration of particular constituencies within states” (Gimpel 1996, 37). Blue-collar, white collar, racial, and ethnic constituencies, which tend to be concentrated in certain counties, are better captured by county-level data than they are by any other level of aggregation.

Finally, county-level data are also used because political campaigns are often organized around counties. Politicians conceptualize races in terms of winning counties. “When interviewed, elites do not make statements like ‘I have lost Ann Smith’s vote in three out of the last four elections.’ Instead, they say something like ‘Multnomah County has always been a

The Gubernatorial Coattail Hvuothesis 157

difficult county for Republicans to win’ ...” (Gimpel 1996,36). The use of county-level data and the fact that many socioeconomic and political variables are controlled for allow for a more contextual and deeper probing analysis of coattails than state-level data.

Granted, a gubernatorial candidate can get more votes than the senatorial candidate in a majority of the counties but still receive fewer votes overall. However, the same phenomenon can take place using city-wide data. That is, one or two cities can dominate the election results. County-wide data are less prone to one or two cities dominating the results because of their larger size.

A state-wide analysis using all 50 states is not used for three reasons. First, some states, such as New Jersey and Virginia, do not run their gubernatorial and senatorial candidates in the same election. Second, other states have gubernatorial and senatorial elections that coincide with presidential elections, which have a great potential to influence both races and nullify any gubernatorial or senatorial coattails. Third, state-level data do not take into consideration the influence that various sections of a state have on elections results. An analysis at the county-level accounts for diversity within a state. Many areas and sections constitute a state. For instance, a popular explanation of New York State politics is that upstate votes against downstate, specifically New York City, and vice-versa. County-level data capture this diversity better than state-level data.

The five states that are tested provide a geographical cross-section of the United States. The west (California), the midwest (Kansas), the mid- Atlantic (Pennsylvania), the northeast (New York), and the south (Florida) were all covered. This geographical cross-section is used because the study seeks to determine the effect of the gubernatorial race on the senatorial race.4 Each of these examined states is large, has a diverse cross-section of inhabitants and major cities, and, for the most part, is representative of its geographical region.

The gubernatorial and senatorial election results in these five states beg the question about which office is driving the other. Overall, in the twenty elections that are examined, ten have the same party winning both elections (two in California, two in Florida, two in Kansas, one in New York, and three in Pennsylvania) and ten have different parties winning the gubernatorial and senatorial contests (Table 1). In the ten races in which the same party won, which office had more influence on the other? In the ten elections in which different parties won each race, upon which office does the electorate tend to place the most emphasis? Do voters place a greater emphasis on the socioeconomic and political variables in voting for gover-

158 Southeastern Political Review VoL 27 No. 1

Table 1 Gubernatorial and Senatorial Election Results in California,

Florida, Kansas, New York, and Pennsylvania

Governor Senator California

1974 Edmund G. Brown, Jr. (D) 51.5% *Alan Cranston (D) 62.6% Houston 1. Floumey (R) 48.5% H. L. (Bill) Richardson (R) 37.4%

1982 Tom Bradley (D) 49.4% Edmund G. Brown, Jr. (D) 46.6%

1986 *Tom Bradley (D) 38.2% *Alan Cranston (D) 50.7% George Deukmejian (R) 50.6% Pete Wilson (R) 53.5%

George Deukmejian (R) 61.8% Ed Zshau (R) 49.3% 1994 Kathleen Brown (D) 42.4% *Diane Feinstein (D) 5 1 .ooh

*Pete Wilson (R) 57.6% Michael Huffington (R) 49.0%

1974 *Reubin Askew (D) 6 I .2% Richard Stone (D) 5 I .5% Florida

Jeny Thomas (R) 38.8% Jack Eckerd (R) 48.5% 1982 *Robert Graham (D) 64.7% *Lawton Chiles (D) 61.7%

L.A. Bafalis (R) 35.3% Van B. Poole (R) 38.3% 1986 Steve Pajcic (D) 45.4% *Robert Graham (D) 54.7%

Bob Martinez (R) 54.6Yo Paula Hawkins (R) 45.3% 1994 *Lawton Chiles (D) 50.8% Hugh Rodham (D) 29.5%

Jeb Bush (R) 49.2% *Connie Mack (R) 70.5%

1974 Vern Miller (D) 49.8% William R. Roy (D) 49.1 Yo Robert F. Bennett (R) 50.2% *Bob Dole (R) 50.9%

Kansas

1978 John Carlin (D) 51.1% William R. Roy (D) 44.1% *Robert F. Bennett (R) 48.9% Nancy Landon Kassebaum (R) 55.9%

1986 Tom Docking (D) 48.1% Guy MacDonald (D) 30.00/0 Mike Hayden (R) 5 1.9% *Bob Dole (R) 70.0%

1990 Joan Finney (D) 53.3% Dick Williams (D) 26.4% Mike Hayden (R) 46.7% *Nancy Landon Kassebaum (R) 73.6%

New York 1974 Hugh Carey (D) 57.3% Ramsey Clark (D) 45.8%

Malcolm Wilson (R) 42.3% *Jacob Javits (R) 54.2% 1982 Mario Cuomo (D) 5 1.7% *Daniel Patrick Moynihan (D) 65.6%

Lew Lehrman (R) 48.3% Florence M. Sullivan (R) 34.4% 1986 *Mario Cuomo (D) 67.1% Mark Green (D) 42.0%

Andrew P. O'Rourke (R) 32.9% *Alfonse D'Amato (R) 58.0% 1994 *Mario Cuomo (D) 48.2% *Daniel Patrick Moynihan (D) 57.1%

George Pataki (R) 51.8% Bernadette Castro (R) 42.9% Pennsylvania

1974 *Milton Shapp (D) 54.3% Peter Flaherty (D) 53.6% Andrew L. Lewis, Jr. (R) 45.7% *Richard S. Schweiker (R) 46.4%

1982 Allen E. Ertel (D) 48.6% Cyril H. Wecht (D) 39.8% *Richard L. Thornburgh (R) 5 1.4% 'John Heinz (R) 60.2%

1986 Bob Casey (D) 5 1.2% Bob Edgar (D) 43.0% William W. Scranton (R) 48.8% *Arlen Specter (R) 57.0%

1994 Mark Singel (D) 46.8% Harris Wofford (D) 48.7% Tom Ridge (R) 53.2% Rick Santorum (R) 51.3%

Note: Major vote results only. *=incumbent Source: Scammon and McGillivray, 1995.

The Gubernatorial Coattail Hypothesis I59

nor than senator? Voters can concentrate on one race over another even if they split their tickets.

The important variables to analyze in order to determine the effect that the governor has on the Senate race are the socioeconomic and political ones, which are described below. Certain races that are examined have nuances that the models cannot take into account. For instance, Florida had a popular governor win the Senate race in 1986 while former Senator Lawton Chiles won the governor’s race in 1994. Likewise, Senator Pete Wilson won the governor’s race in California in 1994 while Governor Jerry Brown lost the 1982 Senate race. These types of circumstances illustrate that statistical models can only explain so much about politics. The impact that these personalities and their campaign organizations have on elections are to a large extent unmeasurable. In this case, the best that can be done is to run the models using key socioeconomic and political variables and interpret the results accordingly. The hypothesis guiding this paper suggests that the office and not the candidates who run for it focus the voters’ attention and influence the election results. Consequently, the gubernatorial winner should drive the senatorial winner regardless of the personalities of and the previous offices held by the senatorial candidates.

Before the statistical models are analyzed, it is important to lay out some of the intricacies of the state-wide results in each of these states for each election. In California, the Democratic senatorial candidates out-polled the Democratic gubernatorial candidates in 1974, 1986, and 1994 (Table 1). The senatorial candidate also received a slightly higher percentage of the major vote in 1982. In Florida the Democratic gubernatorial candidate received a higher percentage of the vote than the Democratic senatorial candidate in three of the four elections. The Democratic gubernatorial candidates in Kansas gained a higher percentage of the vote than the Democratic senatorial candidates in all four elections. In 1974, however, the Democratic gubernatorial and senatorial candidates received almost the same percentage of the major vote. New York has mixed results. The Democratic senatorial candidate received at least eight percentage points more than the Democratic gubernatorial candidate in 1982 and 1994 while the Democratic gubernatorial candidate significantly out-polled the Demo- cratic senatorial candidates in 1974 and 1986. Finally, in Pennsylvania, the Democratic gubernatorial candidates received a higher percentage of the vote than the Senate candidates in 1982 and 1986 while the Democratic senatorial candidate gained a slightly higher percentage in 1994. In 1974, the percentage of major vote was nearly identical for the Democratic gubernatorial and senatorial candidates.

160 Southeastern Political Review Vol. 27 No. I

These state-level statistics would lead us to infer that gubernatorial coattails are present in Florida and Kansas, senatorial coattails exist in California, while there are no clear-cut coattails in New York or Pennsyl- vania. This state-wide look at the election results, however, does not provide insight into how the voters reached their decisions. More specifically, the state-level results cannot tell us if one offke is carrying the other. As stated earlier, a county-wide analysis allows one to break down the election results and get a clearer picture of what is transpiring at a smaller level of aggregation.

Two models are tested. One model will use percent of major vote for the Democratic gubernatorial candidate as the dependent variable while the other model will utilize percent of major vote for the Democratic senatorial candidate as the dependent ~ar iable .~ When each dependent variable is not being tested, it will be used as an independent variable. The reciprocal effects will be tested even though one way directional hypotheses are posited because it is unclear which race influences the other or if the two races are connected at all. This test will consequently allow one to see if one race influences the other.

The indicators for the constructs are operationalized as follows: Incum- bency is a dummy variable used to test the impact of incumbency on each dependent variable. The model tests only Democratic candidates because the purpose of the analysis is to test whether and by what degree the gubernatorial candidate influences the senatorial candidate. Party influence is tested using two variables. The number of Democrats as a percent of each county’s major voters is one variable. A party divisiveness index used by Mayhew (1986) is the other party variable.6 A separate party divisiveness number was calculated for each gubernatorial and senatorial race. Presidential party influence is operationalized using a dummy variable. Economy is operationalized by using unemployment rate, which is the civilian unemployed as a percent of total labor force, and median family income. Education is quantified by the percent of those in the county with a high school diploma and the percent of those in the county with a college degree or higher. Percent minority living in a county and population density are the other socioeconomic variables.

Each model will be weighted by population in order to adjust for population differences across counties. The method of weighted least squares is used because it is “the most straightforward method of correcting heteroscedastici ty...” (Gujarati 1995, 38 1). Testing and correcting for heteroscedasticity is important when pooled, cross-sectional data are used, as is the case with this study.

The Gubernatorial Coattail Hvvothesis I61

RESULTS

Gubernatorial Coattail States California 1974,1982,1986,1884 California closely resembles the hypothetical existence of gubernatorial

coattails (Table 2). The variables explain more of the variation in the percent of vote for the Democratic gubernatorial vote (R2=.82) than the percent of Democratic senatorial vote (R2=.50) and the effect of the percentage of the Democratic gubernatorial vote on the percentage of the Democratic senatorial vote is significantly greater than the effect of the percentage of the senatorial vote on the percentage of the gubernatorial vote. A gubernatorial coattail can be asserted because the coefficients for the same variable are greater in the gubernatorial model. This indicates that the California voters place more emphasis on the gubernatorial race. The senatorial percentage actually follows the gubernatorial percentage. The existence of coattails can also be supported by the findings that California voters focus upon more issues when deciding the governor and the gubernatorial vote affects the senatorial vote more than all other variables except one.

Pennsylvania 1974,1982,1986,1994 The Pennsylvania models also indicate that the gubernatorial race

influences the Senate race (Table 2). The variables have greater explana- tory power for the gubernatorial percentage (R2=.79) than the senatorial percentage (R2=.73). Furthermore, the effect of the percent of vote for the Democratic gubernatorial candidate is greater on the percent of vote for the Democratic senatorial candidate than vice versa. The strong effect of the Democratic gubernatorial percentage on the Democratic senatorial percentage supports the hypothesis that the governor’s proximity to and impact on the voter influences the rest of the ticket, specifically the Senate candidate.

These results also suggest that Pennsylvania voters do not use a federalist interpretation in voting for governor and senator. Overall, the socioeconomic indicators do not impact the senatorial vote more than the gubernatorial vote. As a matter of fact, more social and economic indicators statistically impact the percent of vote for the Democratic gubernatorial candidate than the Democratic senatorial candidate. The impact of socioeconomic variables on the gubernatorial race indicates that the voters hold the governor and not the senator accountable for these factors.

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Table 2

The Effects of Socioeconomic and Political Variables on Gubernatorial and Senatorial Candidates in California,

Pennsylvania, Kansas, New York, and Florida

Gubernatorial Model Senatorial Model Variable Coefficient (t-score) Coefficient (1-score)

California 1974,1982,1986,1994 constant

Median Family Income

Percent Minority

Population Density

Percent of People in County with Bachelor's Degree

Percent of Registered Democrats

Democratic Divisiveness

Percent of Vote for Democratic


Republican Divisiveness

Election Year

Senatorial Candidate

Gubernatorial Candidate

Pennsylvania 1974,1982,1986,1994 Constant


Percent Minority

Population Density



Percent of Vote for Democratic Senatorial Candidate


738.22 6.00** 0.00 2.05*

-0.001 -0.97' 0.00 4.75* 0.03 2.54, 0.75

16.30** Y

0.07 2.60. NIA

16.09 9.07**

-0.38 -6.06**

N =232 F =93.60** R2=0.83

aR2=0.82

30.14 11.63** -0.00 -3.05* 0.06 2.87* 0.00 5.40**

-0.15 -1.35 0.3 1 7.36** 0.22 3.5 I * N/A

176.38 0.49 0.00 0.95

-0.00 -0.20 0.00 0.20 0.02 0.52 0.06 3.50*

-5 1.24 -6.67** NIA

0.48 2.60*

-0.24 -0.02 -0.08 -0.46

N =232 F =21.21** R2=0.53

aR2=0.50

65.25 I .01 Y

-0.07 3.02' 0.00 -0.3 I 0.20

-2.06. 0.32 6.36** NIA

0.33 Gubernatorial Candidate 4.11'

The Gubernatorial Coattail HvDothesh 163

Gubernatorial Model Senatorial Model

N =268 N =268 F =102.42** F =71.45** RZ=0.80 R2=0.74

aR2=0.79 aR2=0.73

Variable Coefficient (t-score) Coefficient (t-score)

Kansas 1974,1982,1986,1994 Constant


Percent Minority

Population Density

Unemployment Rate






Republican Divisiveness



New York 1974,1982,1986,1994 Constant


Percent Minority

Population Density

Unemployment Rate



Percent of Vote for Democratic Senatorial Candidate

Percent of Vote for Democratic Gubernatorial Candidate

24.76 10.7 1 ** 0.00 7.80**

-0.09 -4.01* -0.00 -0.39 0.02 0.11

Y

0.46 12.97**

Y

0.15 3.73* NIA

Y

N 4 2 0 F =95.64** R2=0.65

aRZ=0.64

-2052.96 -4.82** -0.00 -4.27 -0.02 -0.56 0.00 9.55**

Y

0.07 1.79 0.27 7.67" 0.00 0.06 NIA

42.68 19.50** -0.00

-1 6.29- 0.17 6.58' 0.01 5.20**

-0.42 -2.25* 0.12 2.41. 0.20 4.68**

-31.04 -1 4.68* *

NIA

0.20 3.89*

-2.10 -2.03*

N 4 2 0 F =174.47** R2=0.81 aR2=O.81

2042.39 4.85** 0.00 5.32**

-0.10 -3.45 0.00 6.98** 4.03

12.95** 0.14 3.55. 0.15 4.04* NIA

0.00 0.06

I64 Southeastern Political Review VoL 27 No. I

Gubernatorial Model Senatorial Model Variable Coefficient (t-score) Coefficient (t-score)

Election Year 1.06 -1.03 4.91** -4.78**

Presidential Party Influence

Florida 1974,1982,1986,1994 Constant

Population Density

Unemployment Rate






Election Year



Democratic Senatorial Incumbency

-10.90 -4.65**

N =248 F =6027** R2=0.72

aR2=0.71

-955.55 -4.00* 0.00 2.13* 0.03 0.15 0.16 I .92 0.08 2.26*

-10.07 -2.16' 0.58

I1.50** NIA

0.50 4.15** Y

N =268 F =103.30** R2=0.79

aR2=0.79

7.19 3.02*

N =248 F =56.41** R2=0.71

aR2=0.70

-26.51 -5.80** 0.00 3.96' 1.68 6.42** 0.67 6.19** 0.29 6.13** Y

NIA

0.29 4.42** Y

16.85 11.99**

N =268 F =122.23** R2=0.80

aR2=0.80

*p<.oooo *p<.05 WLS ESTIMATION-weighted for population Y variables with low tolerances and high variance inflation factor were excluded. N/A Not Applicable Only the statistically significant variables were included in table with the exception of the New Yo& model

Mixed Coattail States Kansas 1974,1978,1986,1990 A clear conclusion about the presence of coattails, be they senatorial or

gubernatorial, in Kansas cannot be drawn from the data. Overall, more of the variation is explained for the Democratic senatorial candidate (R2=.8 1 ) than the Democratic gubernatorial candidate (R2=.64) (Table 2). All of the

The Gubernatorial Coattail HvDoChesk I65

variables that are used in the senatorial model are statistically significant whereas this is not the case for the gubernatorial model. This finding contradicts the hypothesis that the voters weigh all or most of the variables in order to select the governor but not the senator.

The socioeconomic variables are more influential on and predictable for Kansas’ Democratic senatorial percentage than its Democratic gubernatorial percentage. The socioeconomic variables are statistically significant for and impact the senatorial vote in the hypothesized direction whereas they do not act in this fashion for the gubernatorial vote. The socioeconomic variables indicate that the Senate race adheres to national stereotypes whereas the gubernatorial race does not. This supports Cigler and Loomis’ (1992) assertion that Kansas is predictable in national politics, consistently voting Republican, yet it has a mixed bag approach to state races, rotating between voting Republican and Democratic.

The Kansas results also support the federalist interpretation of voting (Stein 1990). The effects of family median income, percent minority, and unemployment rate are greater on the Democratic senatorial percentage than the Democratic gubernatorial percentage. Kansans hold their national office-holder (senator) more accountable for the economy, specifically unemployment rate, than their state-wide office-holder.

The political variables impact the gubernatorial race more than the senatorial race. First, the number of registered Democrats in a city affects the gubernatorial race more than the Senate race. Second, the gubernatorial race has more of an impact on the Senate race than vice versa.

New York 1974,1982,1986,1994 The variables in each New York model explain relatively the same

amount of variation in the Democratic gubernatorial percentage (R2=.7 1) as the Democratic senatorial percentage (R2=.70) (Table 2). Furthermore, the effects of the Democratic gubernatorial and senatorial percentages on each other are not statistically significant. According to these measures, a gubernatorial coattail effect does not exist in New York because the variables do not explain more of the gubernatorial percentage and the gubernatorial percentage does not have a significant pulling effect on the senatorial percentage.

One of the three variables that is statistically significant for both percentages suggests, however, that the gubernatorial race influences the senatorial race. Party registration impacts the gubernatorial candidate more than the senatorial candidate. This finding, coupled with the fact that only one socioeconomic variable is significant for the Democratic gubernatorial percentage (population density) while five are significant for the Demo-

I66 Southeastern Political Review Vot! 27 No. I

cratic senatorial percentage (median family income, percent minority, population density, unemployment rate, and percent of people in county with a bachelor’s degree) suggests, as the Kansas findings do, that party drives the gubernatorial percentage whereas a combination of socioeconomic and political factors influence the senatorial percentage. These statistics once again show national accountability for unemployment rate and income while party impacts the state election.

Presidential influence is strong in New York. The president has a negative effect on the gubernatorial candidate. In each ofthe four examined races, the winning gubernatorial candidate came from the party that was opposite of that of the president.’ New York voters play divided government with their national and state executives. In three of the four Senate races, however, the winning senatorial candidate came from the president’s party.* In terms of party, New Yorkers vote in unison in the federal races.

These findings lend support to a couple of earlier assertions. First, the New York Senate and gubernatorial races are distinct. The voters use different thought processes to make their electoral decisions. In one election the president is a negative influence. In the other election he is a positive factor. Second, Stonecash (1989) claims that New York voters rely on partisan cues when the choices for governor become ideologically distinct. These findings take this conclusion one step hrther noting that partisan cues are relied upon to determine the governor when the choice between the governor and the president becomes more distinct. The ideological contrast can be particularly seen in the Cuomo (liberal) versus Reagan (conservative) comparison (1982, 1986), in addition to Carey (liberal) versus Nixon (conservative) (1 974), and Pataki (conservative) versus Clinton (liberal) (1994). Overall, a presidential party coattail effect exists for the Senate race while a divided government trend is present for the gubernatorial race.

Senatorial Coattail State Florida 1974,1982,1986,1994 A senatorial coattail effect is clearly present in Florida. The percent of

vote for the Democratic senatorial candidate has a stronger effect on the percent of vote for the Democratic gubernatorial candidate than vice versa and has the second largest impact on percent of vote for the Democratic gubernatorial candidate (Table 2). The variables in the senatorial race are not only weighed more by the voters but they also have a significant pulling effect on the gubernatorial race. Also, more variables are significant for the Senate model than the gubernatorial model. This trend is exactly opposite of that predicted by the gubernatorial coattail hypothesis. The political and socioeconomic variables are significant for both races in

The Gubernatorial Coattail Hypothesis 167

Florida yet they have a greater impact on the Senate race. A senatorial coattail effect exists in Florida because all of the variables for the gubernatorial race follow the variables for the senatorial race.

CONCLUSION Gubernatorial coattails do not exist across the five examined states. The

findings tell an interesting story about politics nonetheless. Politics are dynamic. To suggest that voters rely exclusively upon an office in order to make entire electoral decisions is an inaccurate and much too simplistic depiction of democratic politics. The results do indicate, however, that certain principles guide the voter. These principles vary according to the voter’s political orientation and that state’s party organization.

First, the political orientation of voters influences how they vote. The California voter is primarily issue oriented. The prominence of issues in the California races, as is captured by the impact of the various socioeconomic variables on the vote, is largely a result of the influence that referenda and initiative have on the functioning of government. Referenda and initiative also focus the voter on state, as opposed to national, events and politics. Consequently, the governor is given more attention than the senator. Also, events in California, unlike happenings in most other states, influence the rest of the nation. This impact also focuses the voters’ attention locally instead of nationally. The voters’ familiarity with initiative and referenda causes them to treat political candidates in an issue-oriented manner.

Political orientation also affects voting in Florida. The migratory nature of the Florida voters helps explain why the senatorial race influences the gubernatorial race. “By 1990, less than half of the state’s population was born [in Florida]” (Gimpel 1995,20). As the transplanted northeasterners migrate to their retirement homes in Dade County or the migrating mid- Westerners relocate to the west coast, for example, they are much more familiar with national politics and much less familiar and concerned with what is transpiring in Florida. Therefore, the Florida voters, particularly the migrants, use the national race as the cue for the state race because they understand and relate to the former and not the latter.

Differences in party organization also influence each race differently. The relationship between party and the vote for governor indicates that the governor is the party leader in California, Pennsylvania, Kansas, and New York. The emphasis on federal elections combined with the prominence of incumbent Republican Senators Bob Dole (1974 and 1986) and Nancy Landon Kassebaum (1990) suggest that the senator should be the party leader in Kansas. This finding is not supported by the statistics, however.

168 Southeastern Political Review VoL 27 No. I

The stronger impact of the political variables on the gubernatorial percentage supports the hypothesis that the governor is the party leader. One possible explanation for this is that the strength of these two senators wards off all challengers. The Democrats, consequently, regard their gubernatorial candidates as their party leader because they realize that this candidate has a chance to win whereas the Democratic senatorial candidate does not. Party organization is an important factor in determining the governor but its impact is much less significant in deciding the senator. The federal race in this context depends more upon the socioeconomic state of the nation and the state and is less prone to be controlled by party competition.

In New York, like Kansas, politics have a greater impact on the Demo- cratic gubernatorial candidate. The influence of Mario Cuomo explains why the Democratic Party has such an impact on the gubernatorial races. Cuomo ran in three of the four examined cases. In the last two races, his impact was significantly felt by his party. In 1986 Cuomo was seen as the triumphant leader of his party. He was the Democrat in New York and even the country. His speeches at the Democratic National Conventions served to catapult him to the top of the Democratic Party. Therefore, in 1986 Cuomo carried the Democratic Party. In 1994, however, the party had a major effect on the governor because it was trying to save Cuomo from defeat. In the former election, Cuomo was connected to the party because he was its leader; in the latter election Cuomo needed the party in order to gain votes. Cuomo was the leader of New York’s Democratic Party regardless of why he and the party bonded. The statistics in turn represent this connection.

SUMMARY The importance of the governor’s race upon the senatorial election

varies across the five examined states. The governor, indeed, is not neces- sarily closer to the voter than is the senator. The influence of one race on the other is dependent upon the political orientation of the voters, institutional nuances of each state, and party organizational structure. Account- ability is geared more toward the senator than the governor but the results are by no means universal. Likewise, the governor appears to be the leader of the state political party. While recent research (Soss and Canon 1995; Leyden and Borrelli 1995; Partin 1995; Atkeson and Partin 1995) has addressed the topic of the interdependence of the gubernatorial and senatorial races, more should be done. This study is an attempt to open the door to a greater understanding of how the two races interact but attention in the future should be paid to the impact that a) variance in gubernatorial power, b) the competitiveness of the party system, and c) institutional structures

The Gubernatorial Coattail Hypothesis I69

have on each race. The influence of one race on the other should also be studied with an eye on the importance that regional differences can have on elections. Furthermore, the governor may have a coattail effect on the lower-level state-wide candidates (attorney general, secretary of state, comptroller). This fertile area of state politics research should also be addressed

NOTES ‘Presidential elections have also been seen as determinants of the

gubernatorial race (Piereson 1977). Therefore, this study will test non- presidential election years.

2Major voters are registered Democrats or Republicans.

3The full model includes family median income, population density, percent minority, percent in county with a high school diploma, percent in county with a college degree, unemployment rate, Democratic gubernatorial or senatorial percentage (depending on X variable), gubernatorial and senatorial incumbency, party fragmentation, election year, percent of major voters who registered as Democrats, presidential party. (The socioeconomic variables consist of only the italicized variables while the political variables consist of only the bold variables.) Not all the models include all the variables because certain variables are multicollinear and were consequently excluded. Multicollinearity was determined by high Variance Inflation Factors usually 23.

4The model wishes to test only the elections in which the governor and the senator run together. The model is not designed to test what happens when the president, governor and the senator run together.

5Percent of major vote is the number of votes for the Democratic candidate divided by the number of votes for the Democratic candidate plus the number of votes for the Republican candidate times 100.

6According to Mayhew, “fragmentation of vote (FRAG), or 1-CPi2, where pi is the proportion of the primary vote won by the it,, candidate” (1986, 335).

’1974, Governor Carey (D) and President Nixon (R); 1982 and 1986, Governor Cuomo (D) and President Reagan (R); 1994, Governor Pataki (R) and President Clinton (D).

I70 Southeastern Political Review VOI! 27 No. I

*1974, Senator Javits (R) and President Nixon (R); 1986, Senator D’Amato (R) and President Reagan (R); 1994, Senator Moynihan (D) and President Clinton (D).

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Documents

The Gubernatorial Coattail Hypothesis Considered: Determining the Effects of the Gubernatorial Race on the Senatorial Contest