interrelationship between presidential approval, presidential votes and macroeconomic performance,...

Journal of Macroeconomics 25 (2003) 411–424

www.elsevier.com/locate/econbase

Interrelationship between presidentialapproval, presidential votes and

macroeconomic performance, 1948–2000

Gerald Fox *, Earl N. Phillips

School of Business, High Point University, University Station, 911 Montlieu Avenue, High Point,

NC 27262-3598, USA

Received 16 December 2000; accepted 10 June 2002

Abstract

Analyses of presidential votes generally differ from that of presidential popularity concern-

ing the key economic variables that influence citizen opinions. Vote research usually empha-

sizes real economic growth, while popularity research typically focuses on unemployment.

Actually, both determinants significantly affect both variables of citizen sentiment. Citizen eco-

nomic preferences, however, appear more unemployment averse during democratic presiden-

cies than republican presidencies.

� 2003 Elsevier Inc. All rights reserved.

JEL classification: D72

Keywords: Presidential popularity; Presidential elections; Political business cycle; Partisan cycle; Voters

1. Introduction

Macroeconomic performance affects voter attitudes, as measured both by popu-

larity polls and presidential votes. Presidential approval, moreover, influences pres-

idential votes (Erikson and Wlezien, 1996; Carlsen, 1998). When citizens approve of

the job done by the incumbent, they are likely to vote for the incumbent or the pres-

idential candidate from the incumbent�s political party.From 1948 to 2000, corresponding to fourteen presidential elections since WWII,

the correlation between incumbent votes and presidential popularity just prior to the

* Corresponding author. Tel.: +1-336-841-4559/883-8735; fax: +1-336-841-4599.

E-mail address: [email protected] (G. Fox).

0164-0704/$ - see front matter � 2003 Elsevier Inc. All rights reserved.

doi:10.1016/S0164-0704(03)00046-6

mail to: [email protected]

V = 32.1 + 0.351A (4.52)

R2 = 0.63

30

35

40

45

50

55

60

65

70

30 40 50 60 70 80 90

Presidential Approval in October Just Prior to Election (A)

Vot

es f

or t

he

Incu

mbe

nt (

V)

Fig. 1. Relation between presidential approval and presedential votes.

412 G. Fox, E.N. Phillips / Journal of Macroeconomics 25 (2003) 411–424

election (during October) is 0.79. The impact of popularity upon incumbent votes,

furthermore, is directly significant at 99% confidence according to simple regression

analysis (t-statistic ¼ 4.53; see Fig. 1).

Despite this interrelationship, an inconsistent set of assumptions generally ap-

pears in the research. Vote analyses usually emphasize real economic growth (or real

income growth) as the key economic variable that affects voter opinions (e.g., Fair,

1996; Suzuki and Chappell, 1996; Fackler and Lin, 1995). Popularity analyses, onthe other hand, tend to focus upon unemployment (or the unemployment gap or

the GDP gap) as the key economic variable that influences citizen attitudes (e.g.,

Fox, 1997; Smyth et al., 1991; Garman and Richards, 1989).

The reasons for this difference are both theoretical and empirical. Popularity

research is often based on the political business cycle (PBC) theory, and therefore

typically emphasizes the short run inflation–unemployment trade-off. Empirical re-

search involving presidential votes, on the other hand, has generally evolved inde-

pendently of the PBC literature and has not centered upon the short-runmacroeconomic trade-off.

Vote research, however, is impacted by the difficult problem of scarce observa-

tions since presidential elections take place only once every four years. Vote regres-

sions are consequently constrained in the number of independent variables that may

be specified. As a result, research experimentation involving additional economic de-

terminants such as unemployment may have been somewhat inhibited in vote ana-

lysis.

Regardless of the causes, vote regressions have generally not specified unemploy-ment as an independent variable, 1 while popularity regressions have infrequently

1 Swank (1995) uses unemployment as a determinant in his analysis and finds the effect significant for

the issue model, but not for the score model. Swank, however, does not include real economic growth as a

determinant in his analysis.

G. Fox, E.N. Phillips / Journal of Macroeconomics 25 (2003) 411–424 413

used real economic growth as an independent variable. 2 Because of the close asso-

ciation between votes and polls, however, both economic determinants should be

tested for possible simultaneous influence upon both measures of citizen sentiment.

Real economic growth and unemployment are interrelated, but the two variables

are weakly correlated (r ¼ 0:012). Real economic growth is more related to the changein unemployment (r ¼ �0:613), while the unemployment rate is more related to thereal GDP gap (r ¼ 0:875). The unemployment rate and real GDP growth thus denotesomewhat different aspects of the economy. The unemployment rate and the real GDP

gap provide a measure of the economic level. Economic growth and the change in un-

employment, alternatively, provide a measure for the change in economic level.

The purpose of this paper is to estimate the influence of both unemployment and

real GDP growth upon both votes and popularity. The multiple regression results

show that the two economic variables significantly influence both measurements ofvoter sentiment. A quantifiable interrelationship occurs between presidential votes,

popularity polls, and the underlying macroeconomic determinants. Unemployment,

however, appears to influence voter attitudes more during democratic administra-

tions than republican administrations. This result relates to the partisan-cleavage

theory that democrats are relatively unemployment averse.

2. Disparities between presidential popularity and presidential votes

Five factors cause the popularity and vote equations to differ from each other.

These consist of (i) non-economic determinants, (ii) preferences regarding current ver-

sus future outcomes, (iii) instances when an incumbent does not run for re-election,

(iv) differing opinion-formation processes, and (v) the issue of available data.

Several non-economic pressures affect voter perceptions. One determinant that is

relevant for both polls and votes is the political party effect. Any bias that citizens

may exhibit toward or against a particular political party should appear analogouslyin both the vote and popularity regressions.

Several other non-economic determinants that influence citizen sentiment, how-

ever, are distinct for popularity behavior versus vote behavior. In particular, presi-

dential approval is affected by five non-economic factors, consisting of (i) the

honeymoon effect, (ii) the wartime effects, (iii) presidential scandals, (iv) the presiden-

tial personality effect, and (v) the partial adjustment effect. Votes for the incumbent,

alternatively, are influenced by two non-economic variables, which include the (a) in-

cumbency and (b) party-duration effects (refer to Sections 3 and 4 for a discussion ofthe non-economic determinants that impact polls and votes).

Votes and polls may also diverge from each other due to citizen preferences

regarding present outcomes versus future expected events. Presidential approval is

affected by current economic outcomes, while votes are influenced by expected eco-

nomic performance. Citizens vote for the presidential candidate who they believe is

2 Popularity analyses by Hibbs (1987) and Haynes (1995) are exceptions. Both popularity models

specify real economic growth, unemployment and inflation as explanatory variables.


best able to solve future problems. Economic expectations in vote analyses, however,

are closely tied to current economic outcomes (e.g., Fair, 1978; Suzuki and Chappell,

1996; Fackler and Lin, 1995). The economic determinants that influence votes, as a

practical matter, are consequently similar to those that impact popularity.

Additionally, polls and votes may deviate from each other when an incumbentdoes not run for re-election due to either term limits or retirements. Since the presi-

dential candidate is a different individual from the incumbent in these circumstances,

the two politicians probably display some differing political characteristics. Voter

opinions of the two persons are therefore likely to differ somewhat, but probably

not dramatically. The two politicians, being from the same incumbent political party,

likely favor a number of similar policies.

Popularity, moreover, is a function of the gap between the median voter�s dis-utility and an underlying shadow disutility level (Hibbs, 1987). Vote behavior, incontrast, consists of a process wherein citizens select the candidate closest to their

own individual preferences (Fair, 1978). Differing mechanisms generate the two dif-

ferent variables of voter sentiment.

An important empirical consideration involves the available data. Presidential ap-

proval observations occur in the hundreds, and are tabulated monthly, while presi-

dential elections took place only 14 times during the period 1948–2000. Presidential

vote regressions, hence, must restrict the number of independent variables due to low

observations and low degrees of freedom. Popularity regressions, though, may in-clude numerous explanatory variables because of abundant observations.

Due to these various dissimilarities, the vote and popularity regressions exhibit

some differing characteristics in the explanatory variables, particularly regarding

the non-economic effects. The macroeconomic determinants for the two measures

of citizen opinion, however, are potentially alike. The sizes of the economic coeffi-

cients in the two behavioral equations, nevertheless, could be moderately different.

3. Presidential popularity

Presidential approval is influenced by a combination of economic and non-

economic explanatory variables. The two usual economic determinants, which are

often emphasized, consist of the unemployment rate (or the unemployment gap or

the GDP gap) and the inflation rate. Real GDP growth, however, is also added as

an explanatory variable in this analysis because presidential vote research consis-

tently finds this determinant to be significant (e.g., Carlsen, 1998; Fair, 1996; Suzukiand Chappell, 1996). Popularity is inversely related to squared inflation, p2, and thesquared deviation between unemployment and its target, ðu� u�Þ2, and directly re-lated to real GDP growth, g. 3

3 The evidence is vague regarding the precise specification for the unemployment effect. The influence of

unemployment upon voter disutility may be related to the unemployment gap rather than the unemploy-

ment rate (see Fox, 1997).


Several non-economic determinants, which have been found to be significant

in previous popularity research, are likewise included. These factors consist of the

presidential personality effect, the honeymoon effect, two wartime effects, two pres-

idential scandals and the partial adjustment effect (for similar specifications of these

non-economic determinants see Fox (1997), Smyth et al. (1991) and Garman andRichards (1989)).

The personality effect refers to the appeal of the president�s character upon citizenattitudes. Separate intercepts for each administration in the popularity equation cap-

ture this effect. The honeymoon effect indicates the popularity boost a president en-

joys during the first year in office. This popularity spike is short lived and gradually

dissipates to zero after the regime�s first year. The two wartime effects include theVietnam Conflict and the Gulf War. The Vietnam Conflict adversely impacts presi-

dential approval during the Johnson administration (1964–1968), due to the longlength of the war and the high American casualties. The impact of the Gulf War

upon popularity during the Bush term, conversely, is positive, since the victory arose

quickly and with low US casualties.

The two scandal effects consist of the Watergate and Iran-Contra episodes. The

impact of these adverse political incidents upon popularity during the Nixon and

Reagan regimes is negative. The partial adjustment effect refers to the gradual shift

in citizen opinions that occurs due to changes in the determinants; this effect is esti-

mated by including the lagged dependent variable in the popularity equation.

4 Pr

preside

Gallup

handli5 In

across

consta

A ¼ a1i � a2ðu� u�Þ2 � a3p2 þ a4g þ a5H � a6K � a7WG

� a8IRþ a9GW þ a10A�1

¼ C1 � a2u2 þ /1u� a3p2 þ a4g þ a5H � a6K � a7WG

� a8IRþ a9GW þ a10A�1 ð1Þ

where C1 ¼ ða1i � a2u�2Þ, A¼ percentage of citizens who approve of the president�sperformance, based on Gallup Poll monthly data, 4 a1i ¼ intercept term that varies

across eight administrations for the period 1948–2000 (Truman, Eisenhower, Ken-

nedy-Johnson, Nixon-Ford, Carter, Reagan, Bush Sr., Clinton), 5 u¼monthly(seasonally adjusted) unemployment rate measured as a percentage, u� ¼ unem-ployment target (u� ¼ /1=2a2 or /1 ¼ 2a2u�). If u� is less than the natural unem-ployment rate, then inflation bias is imbedded in voter preferences. See Fox (1997),

Alesina and Sachs (1988) and Kydland and Prescott (1977) for a discussion,p¼monthly (seasonally adjusted) CPI inflation rate expressed as an annual per-

centage over the previous 12 months, g¼monthly real GDP growth rate expressed

esidential popularity is based upon the number of survey respondents who approve of the

nt�s job plus half of those who express no-opinion, divided by the sum of all respondents. The

Poll survey question states, ‘‘Do you approve or disapprove of the way [president�s name] isng his job as president?’’

addition to a distinct intercept term for each presidency, the other coefficients may also fluctuate

administrations (see Fox, 1997; Smyth et al., 1991). For simplicity, all other coefficients are held

nt across administrations in this model.


as an annual percentage, 6 H ¼ honeymoon-effect variable, which equals 12 for thefirst month in office, 11 for the second month, etc., down to one for the 12th month,

and then zero thereafter, K ¼ variable that denotes the number of American warcasualties per month due to the Vietnam Conflict during the years 1964–1968, cor-

responding to the Johnson presidency, W ¼ dummy variable that equals one for theperiod 1973:4–1974:7, corresponding to the Watergate Scandal during the Nixon

presidency, and zero elsewhere, IR¼ dummy variable that equals one for the period1986:12–1988:12, corresponding to the Iran-Contra scandal during the Reagan

presidency, and zero elsewhere, GW ¼ dummy variable that equals one for 1991:1–3,corresponding to the Gulf-War period during the Bush presidency, and zero else-

where, A�1¼ presidential popularity lagged one month.

4. Presidential votes

A mix of economic and non-economic determinants affects presidential votes.

Real GDP growth (or real income growth) and inflation are normally used as the

key economic determinants. Unemployment, however, is also specified as an explan-

atory variable in this analysis because presidential popularity research consistently

finds this determinant to be significant.

The economic determinants in the vote function (2) are therefore identical to theeconomic variables in the popularity equation (1). Votes are inversely related to in-

flation and unemployment, and directly related to real GDP growth. The main dis-

similarity between the two regressions is that the economic explanatory variables in

the vote equation consist of annual observations, whereas the economic variables in

the popularity equation consist of monthly observations. 7

The non-economic determinants in the vote equation include the usual personal-

incumbency and the party-duration effects (for similar specifications of non-

economic effects see Fair, 1996; Fackler and Lin, 1995; Haynes and Stone, 1994).The incumbency effect reflects the advantage an incumbent enjoys when running

for re-election. The duration or popularity decay effect measures the erosion in in-

cumbent votes that typically occurs when an incumbent political party holds the

White House for several consecutive terms. Voters often seek a change in the pres-

idency, the longer a single political party controls the executive branch.

6 R

preside

interpo7 So

observ

voters

strong

V ¼ b1 � b2ðU � U �Þ2 � b3P2 þ b4Gþ b5ðDPERÞ � b6ðDURÞ

¼ C2 � b2U2 þ /2U � b3P

2 þ b4Gþ b5ðDPERÞ � b6ðDURÞð2Þ

eal GDP growth observations from the NIPA accounts take place on a quarterly basis. Since this

ntial popularity analysis pertains to monthly observations, the real GDP growth variable is

lated to also occur monthly.

me presidential vote research specifies economic variables that consist of the most recent quarterly

ations prior to elections rather than annual observations. This is based on the assumption that

heavily discount the past. In my analysis, however, yearly data are used because the determinants

ly correlate with the dependent variable.


where C2 ¼ ðb1 � b2U�2Þ, V ¼ percentage of the two-party vote in support of the

incumbent political party for president, 8 U ¼ annual (seasonally adjusted) unem-ployment rate expressed as a percentage, U � ¼ unemployment target (U � ¼ /2=2b2or /2 ¼ 2b2U

�). If U � is less than the natural unemployment rate, then inflation bias

is imbedded in voter preferences, P ¼ annual (seasonally adjusted) CPI inflation rateexpressed as a percentage, G¼ annual real GDP growth rate expressed as a per-

centage, DPER¼ dummy variable that equals one if the incumbent is running for re-election, and zero otherwise, 9 DUR¼ duration variable that indicates the length interms that an incumbent political party controls the White House. DUR equals 1 ifthe incumbent party has been in power for 1 term, 2 if the incumbent party has been

in power for 2 consecutive terms, 3 for 3 consecutive terms, etc.

5. Basic empirical results

The popularity (1) and vote (2) equations are estimated by OLS multiple-

regression analysis using post-WWII observations from 1948 to 2000. 10 Four sets

of regression findings are displayed in Table 1. Each set consists of a popularity re-

gression and a vote regression that contain analogous economic determinants. SET

I, for example, includes popularity regression (1A) and vote regression (2A). Bothequations contain the determinants p2, g, u and u2, which are election year variablesin the vote regression (P 2, G, U and U 2) and monthly variables in the popularity re-

gression (p2, g, u and u2).To test for robustness, the real GDP gap (gdpgap) and the squared real GDP gap

(gdpgap2) are substituted for unemployment (u) and squared unemployment (u2) inregression sets II and IV. 11 The variables u and gdpgap are directly related, and both

provide a measure for the economic level. Additionally, the change in the unemploy-

ment rate, Du, is substituted for real GDP growth, g, in regression sets III and IV. 12

The variables g and Du are inversely related, and both give a measure for the changein the economic level.

All eight popularity and vote regressions display the predicted signs for the coef-

ficients of g, Du, u, u2, gdpgap and gdpgap2, and in most instances those coefficientsare significant. Both the economic level and the change in the level influence both

presidential approval and votes. The estimated unemployment target, u�, varies

8 Due to the unusually large number of third party (Ross Perot) votes in 1992, V equals votes for the

incumbent plus half the Perot votes divided by the sum of votes for the Bush, Clinton and Perot.9 Following the approach by Fair (1978), DPER ¼ 0 (rather than 1) for 1976, since Ford was appointed

president in 1974 following Nixon�s resignation.10 Due to sporadic presidential approval observations during the 1940s, continuous monthly time series

data do not occur until 1951.11 The real GDP gap equals 100 times the difference between potential and actual real GDP divided by

potential real GDP (gdpgap ¼ 100� ðpgdp � gdpÞ=pgdp). This determinant is an annual variable for thevote analysis, and a monthly variable for the popularity analysis.

12 The change in the unemployment rate, Du, equals the difference during a three month period in thepopularity analysis, and the difference during a one year period in the vote analysis.

Table 1

Basic popularity and vote behavior, 1948–2000

Regressions SET I SET II SET III SET IV

Popularity (1A) Vote (2A) Popularity (1B) Vote (2B) Popularity (1C) Vote (2C) Popularity (1D) Vote (2D)

Truman 11.33�� (3.98) 12.66�� (6.06) 11.74�� (4.12) 13.13�� (6.61)

Eisenhower 22.09�� (6.85) 22.13�� (11.18) 21.6�� (6.69) 22.45�� (11.62)

Kenn–Johnson 21.95�� (6.6) 22.14�� (10.57) 21.75�� (6.5) 22.58�� (11.23)

Nixon-Ford 19.43�� (6.16) 19.11�� (10.32) 19.19�� (6.07) 19.52�� (11.04)

Carter 17.89�� (5.29) 16.62�� (8.23) 17.65�� (5.18) 17.03�� (8.85)

Reagan 22.82�� (6.89) 20.84�� (10.76) 22.14�� (6.67) 21.16�� (11.29)

Bush Sr. 20.72�� (6.13) 20.18�� (10.3) 20.02�� (5.92) 20.47�� (10.69)

Clinton 17.93�� (5.84) 18.2�� (11) 17.42�� (5.67) 18.49�� (11.54)

Constant 48.01�� (73) 48.71�� (152) 49.31�� (56.8) 48.83�� (52.4)

u2 )0.196�� ()2.79) )0.315�� ()4.2) )0.208�� ()2.97) )0.391�� ()3.56)u 1.14� (1.3) 1.36�� (2.03) 1.42� (1.63) 2.97�� (3.72)

u� 2.91 2.16 3.41 3.8

g 0.176�� (2.67) 1.71�� (5.12) 0.066 (0.996) 1.2�� (10.26)

gdpgap )0.447�� ()4.03) )1.46�� ()7.97) )0.447�� ()3.99) )1.44�� ()2.8)gdpgap2 )0.098�� ()4.05) )0.451�� ()5.5) )0.097�� ()3.96) )0.342� ()1.51)Du )1.25�� ()1.8) )3.49�� ()2.93) )0.552 ()0.77) )3.34�� ()2.74)p2 )0.015� ()1.7) )0.001 ()0.07) )0.012 ()1.4) )0.011 ()1.26) )0.02�� ()2.31) )0.033()1.26) )0.013� ()1.58) )0.006 ()0.25)

A�1 0.67�� (25.2) 0.685�� (26.4) 0.671�� (25.1) 0.684�� (26.46)

Honeymoon 0.595�� (7.46) 0.578�� (7.25) 0.592�� (7.38) 0.576�� (7.22)

Vietnam War )0.008�� ()6) )0.007�� ()5.3) )0.007�� ()5.87) )0.007�� ()5.37)Watergate )8�� ()5.69) )7.92�� ()5.5) )8.39�� ()5.93) )8.14�� ()5.72)Iran-Contra )5.28�� ()4.1) )3.84�� ()3.25) )5.19�� ()4.06) )3.87�� ()3.29)Gulf War 13.98�� (5.15) 14.28�� (5.23) 13.72�� (5.04) 14.23�� (5.21)

Incumbency 5.21�� (5.44) 4.81�� (9.08) 5.03�� (3.61) 6.75�� (5.19)

Duration )2.37�� ()6.4) )1.72�� ()7.6) )2.18�� ()3.92) )0.821� ()1.48)

Observations 529 14 529 14 529 14 529 14

SE of Est. 4.49 1.57 4.51 0.981 4.5 2.29 4.51 2.73

R2 0.874 0.965 0.873 0.986 0.873 0.925 0.873 0.893

Adjusted R2 0.870 0.935 0.869 0.974 0.869 0.861 0.869 0.802

Durbin-H 0.0436 )0.1577 0.2625 )0.0572Durbin-W 1.997 3.018 2.011 2.499 1.982 1.792 2.004 2.303

Economic

determinants

p2, g, u, u2 p2, g, gdpgap, gdpgap2 p2, Du, u, u2 p2, Du, gdpgap, gdpgap2

Based on one-tailed t-tests, � denotes significance at 0.1, ��denotes significance at 0.05 and �� denotes significance at 0.01.

418

G.Fox,E

.N.P

hillip

s/Journ

alofM

acro

econom

ics25

(2003)

411–424


between 2.16 and 3.8 across the eight regressions. Since this range lies below the nat-

ural unemployment rate (perhaps equal to about 5.5), the occurrence of some infla-

tion bias among voter preferences is possible.

The inflation effect upon voter sentiment, however, is frequently insignificant in

the vote and popularity regressions. The inflation coefficient is also smaller thanthe other economic coefficients. Much of the inflation effect upon voter sentiment

may be absorbed into the real GDP growth effect, since these two variables are in-

versely related (real GDP growth equals nominal GDP growth minus inflation,

r ¼ �0:343). Citizens appear more concerned about real economic variables ratherthan aggregate price changes. 13

The non-economic coefficients in the vote and popularity regressions exhibit the

expected signs and are significant, as has been found in prior research. The diagnos-

tic statistics indicate that the regressions correlate favorably with the data. Also, se-rial correlation of residuals is mostly insignificant, except for vote regressions 2A, 2Band 2D, where the Durbin–Watson statistics is high.

6. Partisan influence upon voter macroeconomic preferences

The partisan-cleavage theory asserts that democratic administrations are rela-

tively unemployment averse, and perhaps relatively growth oriented as well, sincethe change in unemployment and real GDP growth are inversely related. Republican

administrations, conversely, tend to be relatively inflation averse according to the

partisan model.

An extension of this partisan-cleavage theory is that voters may assess presidencies

by how well administrations attain their partisan goals. Citizens may weigh inflation

relatively high when judging republican presidents, and weigh unemployment and

possibly real economic growth relatively high when evaluating democratic presidents.

Fox (1997) finds some empirical evidence for this effect in analysis of presidentialpopularity and aggregate inflation aversion for the period 1961–1992. Specifically,

the unemployment gap significantly influences citizen attitudes during republican

and democratic regimes. Inflation, however, significantly influences citizen attitudes

only during republican administrations, and not during democratic presidencies. In

this earlier research, however, real economic growth, which is inversely related to in-

flation, is not specified as an explanatory variable.

This hypothesis of partisan differences in the economic coefficients is similarly

tested in the vote and popularity regression results shown in Table 2, correspondingto the longer time frame 1948–2000. The same four sets of vote and popularity equa-

tions from Table 1 are re-estimated after making two modifications: the separate in-

tercepts for each administration in the popularity equation are omitted, and two

dummy variables, D and R, are added to the vote and popularity regressions.

13 The standardized coefficient for p2 is also smaller than the standardized coefficients for u, u2, g,gdpgap and gdpgap2.

Table 2

Partisan influence upon popularity and vote behavior, 1948–2000

Regressions SET I0 SET II0 SET III0 SET IV0

Popularity (1A0) Vote (2A0) Popularity (1B0) Vote (2B0) Popularity (1C0) Vote (2C0) Popularity (1D0) Vote (2D0)

D p2 )0.021�� (�2.39) )0.028�� ()3.6) )0.026�� ()3.06) )0.033�� ()4.24)R p2 )0.019� ()1.55) )0.013 ()1.13) )0.018� ()1.54) )0.012 ()1.05)D u2 )0.831�� ()3) )0.609� ()1.82) )0.851�� ()3.08) )0.391 ()0.274)D u 8.64�� (2.95) 7.58�� (2.28) 8.85�� (3.02) 3.42 (0.249)

u�ðDÞ 5.2 6.22 5.2 4.37

R u2 )0.102� ()1.32) )0.157 (0.728) )0.114� ()1.5) )1.24� ()1.59)R u 0.515 (0.491) )2.06 (0.747) 0.736 (0.717) 13.19 (1.38)

u�ðRÞ 2.52 0 3.23 5.32

D gdpgap2 )0.125�� ()2.19) )0.194� ()1.72) )0.133�� ()2.32) )0.505� ()1.9)D gdpgap )0.291� ()1.32) )0.022 ()0.04) )0.41�� ()1.93) )2.11� ()1.98)R gdpgap2 )0.047� ()1.52) )0.523�� ()4.56) )0.047� ()1.51) )0.788�� ()2.4)R gdpgap )0.45�� ()2.73) )1.56�� (8.92) )0.396�� ()2.42) )0.886�� ()2.14)D g 0.185�� (1.68) 2.78�� (7.69) 0.179� (1.53) 2.6�� (6.56)

R g 0.125� (1.54) 2.73�� (11.2) 0.017 (0.216) 0.961�� (6.02)

D Du 0.937 (0.642) )7.82 ()1.33) 1.09 (0.738) )4.4� ()1.6)R Du )1.74�� ()2.19) )3.76�� ()2.23) )0.943 ()1.16) )0.899 ()0.89)

Constant 16.18�� (4.32) 40.15�� (5.1) 15.68�� (9.06) 47.8�� (46.52) 15.51�� (4.16) 80.16�� (2.84) 15.19�� (9.56) 42.9�� (24.46)

D )23.71�� ()2.9) )21.66�� ()2.44) )1.4� ()1.56) )4.8� ()1.96) )22.77�� ()2.79) )35.3 ()0.884) )0.435 ()0.7) 10.04�� (3.42)

A�1 0.755�� (31.9) 0.762�� (32.68) 0.758�� (32.53) 0.769�� (34.05)

Honeymoon 0.555�� (5.29) 0.477�� (4.89) 0.562�� (5.38) 0.498�� (5.12)

Vietnam War )0.002� ()1.52) )0.002�� ()1.82) )0.002� ()1.5) )0.002�� ()2.07)Watergate )7.01�� ()4.56) )7.72�� ()4.64) )7.23�� ()4.68) )7.45�� ()4.58)Iran-Contra )2.54�� ()2.4) )2.63�� ()2.49) )2.7�� ()2.54) )2.63�� ()2.48)Gulf War 12.04�� (4.38) 12.38�� (4.49) 11.87�� (4.34) 12.35�� (4.48)

Incumbency 3.98�� (8.5) 4.32�� (9.57) 5.64�� (3.26) 5.76�� (4.76)

Duration )0.483 ()1.31) )1.37�� ()5.74) )1.82 ()1.42) )2.25�� ()4.14)

Observations 529 14 529 14 529 14 529 14

SE of Estimate 4.65 0.637 4.66 0.539 4.65 2.52 4.67 1.61

R2 0.865 0.997 0.864 0.998 0.865 0.948 0.864 0.979

Adjusted R2 0.861 0.989 0.860 0.992 0.861 0.832 0.860 0.931

Durbin-H )0.7814 )0.8584 )0.6266 )0.8075Durbin-W 2.057 2.368 2.063 1.939 2.046 1.732 2.06 1.194

Economics

determinants:

p2, g, u, u2 p2, g, gdpgap, gdpgap2 p2, Du, u, u2 p2, Du, gdpgap, gdpgap2

Based on one-tailed t-tests, �denotes significance at 0.1, ��denotes significance at 0.05 and ��denotes significance at 0.01.

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D ¼ 1 if the incumbent is a democrat, and D ¼ 0 if the incumbent is a republi-

can. 14 The dummy variable R indicates the reverse (R ¼ 1� D). In the popularityregressions, the dummy variable D is substituted for the separate presidential inter-

cepts, so as to estimate overall partisan differences in the intercept (rather than pres-

idential variations). Additionally, the two dummy variables D and R are multipliedby each of the economic variables in the vote and popularity regressions, so as to

estimate separate economic coefficients during democratic and republican presiden-

cies.

The inflation variable, however, is excluded from the vote analysis. Preliminary

findings show the inflation effect to be small and insignificant (see Table 1). More-

over, the problem of low degrees of freedom due to scarce observations limits the

number of determinants that may be modeled in the vote equation. Separate partisan

inflation coefficients in the popularity regressions, however, are estimated; high de-grees of freedom due to numerous observations easily permit this specification in

the popularity equation.

The coefficient for the binary variable D, which identifies the difference in the in-tercept between the two political parties, is negative in 7 of the 8 popularity and vote

regressions, and this coefficient is significantly negative in 5 of those regressions. The

political party effect, hence, appears similar for both vote and popular behavior. The

GDP growth coefficient is greater (sometimes marginally) during democratic presi-

dencies in all four of the associated popularity and vote regressions ð1A0; 2A0;1B0; 2B0Þ. Vote regression (2B0), furthermore, indicates this effect to be significantly

different between the two political parties at the 0.01 level according to a two-tailed

t-test.The u and u2 coefficients and their significance levels are greater during democratic

presidencies in 3 of the 4 corresponding popularity and vote regressions (1A0, 2A0 and

1C0; vote regression 2C0 is the exception). Popularity regressions (1A0) and (1C0),

moreover, indicate these effects to be significantly different between the two political

parties at the 0.01 level according to a two-tailed t-test. Also, the estimated unem-ployment target for democratic presidencies, u�ðDÞ, varies from 4.37 to 6.22, while

the estimated unemployment target for republican presidencies, u�ðRÞ, ranges from0 to 5.32. 15

In all four popularity regressions, the u, u2, gdpgap2 and g coefficients are largerduring democratic presidencies, while the gdpgap and Du coefficients yield mixed par-tisan results. 16 Vote regression (2A0) similarly shows that the u, u2 and g coefficients

14 Separate intercepts for individual administrations cannot be simultaneously specified along with the

dummy variable D in the popularity regressions because of perfect collinearity among the explanatory

variables.15 The unemployment target during republican incumbencies, u�ðRÞ, is assumed to be zero in vote

regression (2A0) since the estimated coefficients for R u and R u2 are both negative. A non-zero

unemployment target occurs only if the coefficient for R u2 is negative and the coefficient for R u ispositive.

16 Partisan influence upon the Du coefficient does not appear in the popularity regressions; the D Ducoefficient exhibits the wrong sign in regressions (1C0) and (1D0). The variable g is consistently superior toDu as a measure for the change in economic performance.

Table 3

Relative inflation aversion

Ratio of coefficientsa (1A0) (1B0) (1C0) (1D0)

D p2=D u2 )0.021/)0.831¼ 0.025 )0.026/)0.851¼ 0.03R p2=R u2 )0.019/)0.102¼ 0.186 )0.018/)0.114¼ 0.158

D p2=D u )0.021/8.64¼)0.002 )0.026/8.85¼)0.003R p2=R u )0.021/0.515¼)0.041 )0.018/0.736¼)0.024

D p2=D g )0.021/0.185¼)0.114 )0.028/0.179¼)0.156R p2=R g )0.021/0.125¼)0.168 )0.013/0.017¼)0.765

D p2=D gdpgap2 )0.028/)0.125¼ 0.224 )0.033/)0.133¼ 0.248R p2=R gdpgap2 )0.013/)0.047¼ 0.277 )0.012/)0.047¼ 0.255

D p2=D gdpgapb )0.028/)0.291¼ 0.096 )0.033/)0.41¼ 0.08R p2=R gdpgap )0.013/)0.45¼ 0.029 )0.012/)0.396¼ 0.03

D p2=D Duc )0.026/0.937¼)0.028 )0.033/1.09¼)0.03R p2=R Du )0.018/)1.74¼ 0.01 )0.012/)0.943¼ 0.013aVoters are relatively inflation averse during republican presidencies if the republican coefficient ratio in absolute terms is greater than the ratio for

democratic presidencies.bVoters do not exhibit relative inflation aversion with respect to gdpgap during republican presidencies; the democratic gdpgap ratio is greater than the

republican ratio.c The D Du coefficients in popularity regressions (1C0) and (1D0) exhibit the theoretically incorrect signs.

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are larger during democratic presidencies, while the other three vote regressions,

which use gdpgap2, gdpgap and Du, produce inconsistent partisan results. Overall,however, the vote findings are slippery to interpret because of very limited observa-

tions and low degrees of freedom. Popularity analysis, which relies on numerous ob-

servations, probably produces more reliable results, and is less susceptible to theproblem of data mining.

Both the republican and democratic inflation coefficients, in the popularity regres-

sions of Table 2, are small compared to the coefficients for the other economic deter-

minants, which is analogous to the findings in Table 1. The inflation coefficients and

their significance levels, nevertheless, are greater during democratic administra-

tions. 17 This possibility of a higher inflation coefficient for democrats is comparable

to Winder�s analysis of presidential approval across demographic groups (1992).Democrats may be more concerned about all economic variables, including infla-

tion. The economy tends to have a greater marginal impact upon democrats, since

they tend to belong to the middle and lower economic classes. Republicans, alterna-

tively, tend to be more secure in the their total economic utility since they often be-

long to the wealthier class.

Based on the results in Table 2, the partisan hypothesis that the inflation coeffi-

cient is greater in absolute terms during republican presidencies is consequently re-

jected. Voter attitudes during republican administrations, however, are relatively

inflation averse with respect to four of the six other economic variables. The p2 co-efficient divided by the coefficients for g, u, u2 and gdpgap2 yield higher ratios duringrepublican presidencies (see Table 3); while the coefficient ratios for Du and gdpgap

do not display this partisan outcome.

Overall, citizens seem to place greater absolute emphasis upon unemployment––

and perhaps upon economic growth and inflation––when forming opinions of dem-

ocratic administrations. Voters, conversely, appear relatively inflation averse in

relation to economic growth and unemployment during republican presidencies.

The effects of the GDP gap and the change in unemployment upon voter sentiment,on the other hand, do not show consistent partisan influence.

All of the non-economic coefficients in Table 2 display the predicted signs and are

generally significant for both the vote and popularity regressions, as was found in

Table 1. The diagnostics indicate that the model strongly correlates with the obser-

vations, and that serial correlation of residuals is insignificant.

7. Summary

Presidential popularity and presidential votes measure citizen perceptions of pres-

idential effectiveness. Conventional analyses emphasize unemployment as the key

17 A one-tailed t-test in popularity regression (1D0) shows that the inflation coefficient is significantlydifferent between the two political parties at the 0.01 level. The other popularity regressions ð1A0; 1B0; 1C0Þindicate insignificant differences in the inflation coefficient between the two political parties.


economic determinant that affects popularity, and real economic growth as the key

economic variable that affects votes. If citizen preferences are consistent, however,

then both determinants should influence both popularity and votes. Multiple regres-

sion analysis of post-WWII data confirms this hypothesis. The results are also robust

when substituting the explanatory variables Du, gdpgap and gdpgap2 into the model.The popularity and vote equations are comparable to each other.

Voter attitudes, however, appear more sensitive to unemployment during demo-

cratic administrations. This effect is based on the partisan theory that the democratic

party is more unemployment averse than the republican party. Citizens seem to form

judgments of presidents by observing how well administrations achieve their partisan

economic objectives.

Acknowledgements

I wish to thank the two anonymous referees for their helpful comments. Any er-

rors are my responsibility.

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