Retrospective Economic Voting and the Intertemporal Dynamics of Electoral Accountability in the American States
George A. Krause† University of Pittsburgh
and
Benjamin F. Melusky‡
University of Pittsburgh
Draft as of Monday, August 27, 2012
* An earlier version of this paper was presented at the 2012 annual meetings of the Midwest Political Science Association. Chicago, IL. April. We thank Dave Peterson for helpful comments on a preliminary draft of this essay.
† Professor, Department of Political Science, University of Pittsburgh, 4442 Wesley W. Posvar Hall. Pittsburgh, PA 15260. [email protected] (e-mail address). Corresponding Author.
‡ Ph.D. student, Department of Political Science, University of Pittsburgh, 4600 Wesley W. Posvar Hall. Pittsburgh, PA 15260. [email protected] (e-mail address).
Keywords: Dynamic Electoral Accountability, Intertemporal Attribution Discounting, Retrospective Economic Voting, Elections in the American States
Abstract A theory of intertemporal attribution is advanced to explain how voters discount
sanctions and rewards for politicians’ past performance in office when the latter runs for elective
office as a non-incumbent candidate. Analysis of aggregate electoral data on incumbent and
non−incumbent (i.e., outgoing and former) governors in the American states generally offers
strong support for the testable implications of this theory. For both recent term and tenure
evaluative time frames, voters possess the strongest economic attributions for incumbent
(current) governors, while dynamically discounting the economic stewardship of outgoing or
former governors. Intertemporal attribution discounting is increasing in the width of the
evaluative time used by voters to assess economic stewardship. These findings underscore the
dynamic slippage present in electoral accountability by demonstrating how time elapsed from
prior service in elective office not only makes it increasingly difficult for voters to effectively
reward competent politicians, but to also sanction incompetent counterparts.
1
INTRODUCTION
Holding politicians electorally accountable for their performance in office is a central
tenet in representative democracies (Key 1966). Voters’ capacity to hold politicians accountable
for their performance in office is directly linked to not only their attributions regarding
policymaking competence via macroeconomic conditions (e.g., Ansoloabehere, Meredith, and
Snowberg 2011; Gomez and Wilson 2003; Healey and Lenz 2012; Powell and Whitten 1993;
Markus 1988; Lewis-Beck and Stegmaier 2007), but also linking this competence to a particular
politician (or party) in a consistent manner. With few exceptions (e.g., Schwabe 2011), canonical
theories of retrospective economic voting pertain to a canonical two-period logic, whereby
re−election to the same office in period t is based on economic performance in period t −1
(Barro 1973; Downs 1957; Ferejohn 1986; Fiorina 1981). Retrospective economic voting theory
is both intuitively appealing and empirically persuasive. This is because citizens can easily make
such attributions without worrying about the passage of time adversely affecting their ability to
hold elected officials accountable for past performance in office (cf. Healy and Lenz 2012).
In many instances, however, politicians will seek subsequent elective office after taking a
hiatus. Therefore, the need to understand the extent to which voters can make the link between
policymaking competence and politicians for a sustained period of time is of critical importance
for analyzing the efficacy of electoral accountability in a democracy. This research puzzle asks –
To what extent is the electorate capable of holding individual politicians accountable for
economic stewardship in prior elective office? A theory of intertemporal attribution discounting
(IAD) is advanced to address this question. IAD theory posits that voters’ capacity to hold
politicians accountable for past economic conditions declines the longer time that elapses
between past performance in office and the seeking of elective office. Put another way, voters
discount politicians’ past performance when they make determinations of electoral support, and
2
this performance is discounted at differential rates. Hence, voters’ (principals) ability to
discriminate between “good” versus “bad” politician (agent) types becomes blurred over time,
and the extent and speed of this blurring is increasing in the evaluative time frame used by voters
when making retrospective economic attributions. IAD theory yields the following testable
implications to the study of retrospective economic voting behavior: (1) attributions are strongest
for incumbent office-holders; (2) attributions are decreasing in the time elapsed between an
individual politician’s prior elective service and them seeking current elective office; (3)
attributions involving incumbent office-holders become more less robust as evaluative time
frame increases; and (4) the intertemporal discounting rate is increasing in the width of the
evaluative time frame used by voters to make attributions.
Evidence from aggregate electoral data for incumbent (current) governors, as well as
non-incumbent (outgoing or former) governors in the American states generally provides strong
empirical support for these four main testable predictions derived from IAD theory. Specifically,
voters discount a former governor’s past economic stewardship through time when determining
whether to grant electoral support in subsequent election contests. Only recent term evaluative
time frames used by voters reveal that non−incumbent governors’ incur short-run responsibility
for their past economic stewardship. As a politician’s hiatus from elective office increases, any
benefits (costs) that they may have accrued due to excellent (poor) economic stewardship fade
away when voters employ either a tenure or recent term evaluative time frame. Although voters’
immediate retrospective economic attributions are much clearer, they also discount at a higher
rate when the reference point for assessing economic stewardship is based on the politician’s
tenure in office vis-à-vis being restricted to their final term in office.
3
Three substantively interesting findings are obtained that transpire outside the scope of
IAD theory’s testable implications. First, recent (election) year length evaluative time frames
produce weak retrospective economic attributions in a current election year for incumbent
governors. This evidence of a null effect under a short evaluative time frame runs contrary not
only to IAD theory, but also to the ‘end-heuristic’ logic advanced by Healy and Lenz (2012).
Second, although decreasing the evaluative time frame results in a lower discount rate for
intertemporal retrospective economic attributions consistent with IAD theory, surprisingly these
attributions become stronger with the passage of time when voters only utilize information on
economic stewardship in the most recent year of the governor’s service in office. That is, voters
compound economic stewardship by governors in their final year in office when determining
electoral support for these same elected officials seeking major statewide office at a later date.
Though less cognitively demanding shorter evaluative time frames can mitigate (and possibly
reverse) decaying retrospective economic attributions, it comes at the heavy expense of a
significant reduction in making accurate electoral judgments. Finally, evidence of intertemporal
regressive bias is obtained for both the tenure and recent term evaluative time frames. Voters
discount past economic stewardship by non-incumbent governors in their current electoral
behavior such that poor (excellent) performance yields an increase (decrease) in electoral vote
share when the time elapsed between exiting and seeking elective office is sufficiently large.
The paper proceeds as follows. Next, the basic logic of intertemporal attribution
discounting (IAD) theory is discussed in relation to retrospective economic voting. The third
section covers the data, research design, and variable issues. The fourth section presents and
interprets the empirical findings. The paper concludes with a discussion of this study’s broader
implications for understanding electoral accountability in democratic governments.
4
Intertemporal Attribution Discounting and Retrospective Economic Voting
Intertemporal electoral accountability is analyzed through the lens of retrospective
economic voting. Retrospective economic voting behavior is ubiquitous – the extant literature is
replete with rich theorizing, coupled with robust empirical evidence of retrospective economic
voting. The decision-calculus used by voters for assessing a politician’s policymaking reputation
is thus firmly established. Retrospective economic voting theory places low information and
cognitive processing demands on voters seeking to hold elected officials accountable for their
policymaking performance. Analyzing intertemporal electoral accountability rooted in economic
stewardship thus constitutes an evaluative criterion where one expects voters will exhibit
comparatively robust, persistent attributions when evaluating politicians in election contests.
Therefore, any observed attribution discounting, as well as potential behavioral anomalies
inherent to intertemporal electoral accountability, should be of a conservative nature.
IAD theory is premised on the notion that voters generally rely less on information that is
temporally more distant to them than compared to information that is more temporally proximate
to them. This logic is undergirds the cognitive aspects of understanding performance appraisals.
Because subjects will employ the most readily accessible information for purposes of making
performance appraisals at some later date (Woehr and Feldman 1993), it is reasonable to infer
that voters’ capacity for holding elected officials accountable for the economy will atrophy with
the passage of time as their ability to accurately make performance attributions declines. This
logic is consistent with theories of cognition which posit that information decay mechanisms
occur in long-term memory, thus constraining what suitable information can be retrieved from
short-term memory through time (Taber and Young 2011: 101-102). Information stored in long-
term memory is thus incompletely retrieved by short-term memory before it is processed further
5
into an attribution (Ericsson and Simon 1981: 18-19). Hence, it becomes difficult for individuals
to make attributions based on more distantly observed events. This is because the cognitive
capacity for making attributions is diminishing with respect to more distant events or longer time
horizons due to increasing slippage between long-term and short-term memories as time elapses.
This logic is directly applicable to retrospective economic voting behavior in an
intertemporal context. Voters’ recall of past economic conditions becomes hazier the more
distant they are observed in the past. As the temporal gap between retrospective economic
evaluations and electoral choice increases, this link should become increasingly frayed. Further,
as the evaluative time frame employed to make these economic evaluations becomes wider, this
information becomes discounted at a greater rate compared to those acquired via narrower
evaluative time frames. This ‘what have you done lately for me?’ phenomenon is the byproduct
of individuals more heavily discounting events that are less proximate in time, whether it
involves evaluating past (retrospective) information or making a future (prospective) attribution.
In turn, this IAD theoretical logic generates four hypotheses. The first pair of hypotheses
pertains to absolute assessments of intertemporal electoral accountability that are independent of
the evaluative time frame used in formulating the retrospective economic evaluation.
H1 (Immediate Accountability Hypothesis): The positive linkage between economic stewardship
and level of current electoral support should be its strongest in the absence of a hiatus between
service in office and seeking election.
H2 (Diminishing Accountability Hypothesis): The positive linkage between economic
stewardship and level of current electoral support is decreasing in the time elapsed between
service in office and seeking future elective office.
6
The first hypothesis (H1) means that retrospective economic voting should be most robust when
observed economic performance is evaluated immediately after it transpires. That is,
retrospective economic voting should be strongest in the canonical two-period model, whereby
incumbents are judged on their economic performance while in office. The second hypothesis
(H2) predicts that retrospective economic voting behavior will weaken through time as more
distant economic performance is temporally discounted in future electoral choices.
This pair of hypotheses fails to distinguish between varying evaluative time frames by
which economic stewardship is assessed. This is a critical consideration since the choice of
evaluative time frame has tangible implications for understanding the efficacy of electoral
accountability (Healy and Lenz 2012). Voters’ reliance on retrospective information to determine
current electoral choices may vary based on whether they are making global assessments based
on the politician’s entire tenure in office, restricted to their most recent term in office, or
truncated to only considering their most recent (election) year. If voters discount more
temporally distant events, then they should form relatively crisper connections between past
performance in office and future attributions reflected in current voting behavior as the
evaluative time frame becomes narrower. Relatedly, because individuals exhibit attribution
discounting when linking increasingly more distant past events to current ones, a widening
evaluative time frame employed by voters that accounts for evaluations of a more distant
temporal nature will possess a higher rate of intertemporal discounting of future events than
compared to a narrower evaluative time frame. In the realm of retrospective economic voting,
this translates into a politician’s electoral support rooted in economic stewardship will be
diminishing at a faster rate as voters’ evaluative time frame widens.
7
This theoretical logic yields a pair of hypotheses that are comparative analogs to the ones
proposed in H1 and H2 that do not make distinctions based on the evaluative time frame being
employed for retrospective economic voting decisions.
H3 (Evaluative Time Frame −Immediate Accountability Hypothesis): In the absence of a
hiatus between serving in office and seeking elective office, the positive linkage between
economic stewardship and level of current electoral support should be greater for those
retrospections anchored to most recent performance than those anchored in the distant past.
H4 (Evaluative Time Frame −Diminishing Accountability Hypothesis): As the time elapsed
between service in office and seeking election grows, the positive linkage between economic
stewardship and level of current electoral support should be decreasing more rapidly for those
retrospections anchored to distant past performance than those anchored to the recent past.
IAD theory posits that voters’ attributions of more distant events increasingly limit their
capacity to hold elected officials accountable in subsequent election cycles for past economic
stewardship. Therefore, voters’ collective attributions based on past economic stewardship are
most potent when they can be applied in the immediate or near future according to H1 & H2.
Furthermore, these collective attributions are also both more potent in the short-term (H3) while
also being more durable over the long-term (H4) when the evaluative time frame used to
construct these economic retrospections narrows.
Research Design, Data, and Model Specification
IAD theory’s testable predictions are analyzed using data on gubernatorial and U.S.
Senate election results from 1970 to 2010. The unit of analysis is the individual elected official.
This database is comprised of incumbent gubernatorial general elections, as well as subsequent
8
gubernatorial and U.S. Senate election contests for both outgoing and former (non−incumbent)
governors during this time period. These data comprise 309 total election event observations
consisting of 198 cases where incumbent governors seek re−election cases, 27 cases involving
outgoing governors immediately seeking a U.S. Senate seat, and 84 former governor cases
seeking either a U.S. Senate seat or the governorship at some later date in the future. This
research design analyzes a common political jurisdiction (state-level) across different electoral
contexts by focusing on the elected official at the state level most likely to be held accountable
for past economic conditions accordance with retrospective voting theory – governors.
The dependent variable is the percentage of the total vote received by the former
governor in the current election of interest (Electoral Vote Share).1 This dependent variable
captures aggregate electoral vote choice for the election contest held t + i periods into the future,
where i ≥ 0. The grand mean of this variable is 56.9, with a standard deviation of 14.54, a
minimum of 0 and maximum of 100 for the overall sample.2 The dependent variable’s summary
statistics broken down by its three components are as follows: Incumbent Governors (t = 0: n =
198): mean = 57.71, SD= 9.28, min = 25.8, max = 79.2; Outgoing Governors (t =1: n = 27):
1 These data are from Scammon, McGillivray, and Cook’s America Votes series, various years.
2 The descriptive statistics for the non−incumbent governor observations based on election type
are as follows: Outgoing Governors−General Election (t =1: n= 13): mean = 51.22, SD = 8.85,
min = 39.3, max = 76.1; Outgoing Governors−Primary Election (t =1: n = 14): mean = 79.35,
SD = 18.77, min = 45.5, max = 100; Former Governors−General Election (t >1: n= 39): mean =
46.44, SD = 13.84, min = 0, max = 71.2; and Former Governors−Primary Election (t >1: n = 45):
mean = 57.04, SD = 23.09, min = 19.2, max = 100.
9
mean = 65.81, SD= 20.43, min = 39.2, max = 100; and Former Governors (t >1: n = 84): mean =
52.11, SD= 19.97, min = 0, max = 100.
Governors are rewarded for presiding over times of prosperity and punished for bad times
in the American states (e.g., Dometrius 1999; Hansen 1999; Wolfers 2007). We utilize a state’s
unemployment rate as the evaluative basis to retrospective economic voting behavior at the state-
level. This aggregate economic indicator is chosen for this analysis since it is generally shown to
possess stronger predictive content for gubernatorial elections and subnational elections than
compared to income-based measures.3 Economic stewardship by governors is retrospectively
assessed by the electorate in three distinct evaluative time frames as a means of testing both H3
and H4. The narrow evaluative time frame, ∆ State Quarterly UE Rate: Recent Year, is
measured as the net change in the state unemployment rate from the first quarter of most recent
year of the governor’s most recent term in office through the last quarter of their most recent
term in office (mean = 0.11, SD = 0.91 , min = −2.5, and max = + 4.20). The moderate
evaluative time frame, ∆ State Quarterly UE Rate: Recent Term, is simply the net change in the
state unemployment rate from the first quarter of the governor’s most recent term in office
through the last quarter of this term (mean = −0.28, SD = 2.64 , min = −8.1, and max = + 6.90).
The wide evaluative time frame is operationalized as the net change in the state unemployment
rate from the first quarter of the governor’s first term in office through the last quarter of the
governor’s final term in office: ∆ State Quarterly UE Rate: Tenure (mean = −0.06, SD = 2.72 ,
3 In either absolute or relative terms, this literature generally finds a much weaker relationship
between income-based measures and aggregate vote functions for governors and other
subnational elections vis-à-vis unemployment type measures (e.g., Besley and Case 1995; Chubb
1988; Hansen 1999; Kiewiet and Udell 1998; Peltzman 1987; Wolfers 2007).
10
min = −7.8, and max = + 6.90).4 These state unemployment rate variables represent different
evaluative time frames used by voters when evaluating governors’ past economic stewardship.
The intertemporal element by which we attempt to evaluate the attribution discounting by
the aggregate electorate is captured by the linear variable Election Delay. This covariate is
measured as the number of months that has elapsed between the day the former governor left
office and the day of the given election contest of interest (Non−Incumbent Governor Cases
only: mean = 53.29, SD = 60.11, min = 1, max = 335).5 The distribution of this variable is
represented by the histogram in Figure 1. This graph exhibits strong right-skewness – most
4 These seasonally-adjusted data are from the Federal Reserve Bank of St. Louis,
www.research.stlouisfed.org/fred2/categories/27281, as provided by the U.S. Department of
Labor: Bureau of Labor and Statistics. Because of missing data, the effective sample size of the
‘tenure’ observations used in the upcoming regression analysis consists of 296 cases. The
discrepancy of 13 cases are almost evenly divided between primary (n = 4) and general election
(n = 5) contests, as well as among incumbent governor (n = 4), outgoing governor (n = 2), and
former governor (n = 7 – albeit two of these observations constitute the most extreme election
date duration values by well over 100 months). The source of this missing data is due to
preceding election results from the early portion of the sample period (dating in the 1970s).
5 A full month is greater than 15 days. Data for this variable were taken from the biographical
information of the former governors as provided by the National Governors Association,
www.nga.org. This variable exhibits both positive skewness and leptokurtosis, with the center of its
distribution being skewed towards t = 0 (median = 41). The application of nonparametric median
regression is employed later in this study to address this problem, as well as other problems relating to
distributional assumptions being violated by the nature of this data design.
11
election events occur closer in time to their tenure in office. Roughly 96 percent of the
observations for the entire effective sample occur at t ≤ 96 (eight years) into the future. This
numerical value diminishes only to 89 percent over this same intertemporal range when one
considers only the outgoing and former governor subset of observations. Nearly 43.24% of these
observations occur within two years of leaving office, with the remaining generally being
increasingly more sparsely distributed through time. The pair of cases in the tail of the
distribution represent Jerry Brown (D-CA) efforts at being re-elected Governor of California in
2010 after a 28 year hiatus since leaving this elective office in January 1983.
[INSERT FIGURE 1 ABOUT HERE]
The intertemporal nature by which voters (in aggregate) retrospectively discount past
economic stewardship of these former governors are captured by the respective interaction terms
in each model specification: ∆ State Quarterly UE Rate: Recent Year × Election Delay, ∆ State
Quarterly UE Rate: Recent Term × Election Delay, and ∆ State Quarterly UE Rate: Tenure ×
Election Delay. These coefficients should possess negative signs since IAD theory predicts that
voters intertemporally discount past economic stewardship in their electoral choices. Negative
coefficient values of a greater magnitude imply a higher discount rate that is indicative of greater
attribution decay involving retrospective economic voting behavior. The full set of hypothesized
predictions derived from IAD theory is listed as follows:
H1: β Δ State Quarterly UE Rate: Recent Year > 0, β Δ State Quarterly UE Rate: Recent Term > 0,
β Δ State Quarterly UE Rate: Tenure > 0.
H2: β Δ State Quarterly UE Rate: Recent Year × Election Delay < 0,
β Δ State Quarterly UE Rate: Recent Term × Election Delay < 0, β Δ State Quarterly UE Rate: Tenure × Election Delay < 0.
H3: β Δ State Quarterly UE Rate: Recent Year > β Δ State Quarterly UE Rate: Recent Term > β Δ State Quarterly UE Rate: Tenure.
12
H4: β Δ State Quarterly UE Rate: Tenure × Election Delay < β Δ State Quarterly UE Rate: Recent Term × Election Delay <
β Δ State Quarterly UE Rate: Recent Year × Election Delay .
Apart from the main theoretical covariates of interest, several variables are incorporated in the
model specifications to control for confounding factors that may affect statewide electoral
outcomes.6 Because a candidate’s electoral fortunes may exhibit persistence, we include a
measure that captures the governor’s vote share in their preceding general election contest for
governor (Previous Gubernatorial General Election Results: mean = 56.52, SD = 7.67, min =
36.2, max = 82.4). This coefficient should possess a positive sign.7 A binary indicator is included
to account for the fact that non-incumbent governors – those that seek a U.S. Senate seat either
immediately or at some future date, or the governorship at some later date – will receive less
electoral support than their incumbent counterparts (Non−Incumbent Governor: mean = 0.36, SD
= 0.48, min = 0, max = 1). Substantive differences exist in both the electorate and the size of the
vote share candidates garner between primary election and general elections (e.g., Brady, Han,
and Pope 2007; Hanks and Grofman 1998). One expects that non-incumbent governors will fare
better in primary election contests than general election contests due to advantages resulting
from their name recognition, as well as resource and organizational advantages over their rivals.
Therefore, a binary variable, General Election Contest, is included that indicates for whether the
current electoral contest is a general election contest (= 1), or a primary election contest (= 0).8
6 While this analysis would prefer to control for the level of gubernatorial approval, taken from
the U.S. Officials' Job Approval Ratings (JARs) database, there is a high degree of missingness
in the dataset, with some years or months having no approval data.
7 These data are from Scammon, McGillivray, and Cook’s America Votes series, various years.
8 These data are from Scammon, McGillivray, and Cook’s America Votes series, various years.
13
This variable only takes on ‘1’ values for incumbent governors. For non−incumbent governors,
this variable has a mean = 0.47, SD = 0.50, min = 0, and max =1.
The effect of the incumbency advantage is well established in the voting behavior
literature (e.g., Ansolabehere and Snyder 2002). Incumbent, outgoing, and former governors
seeking elective office can directly benefit this incumbency advantage. Non−incumbent
governors can benefit from the coattails effect of the incumbent seat holder when running in the
current race if that incumbent is of the same political party as the former governor given the
persistence in voting behavior. The variable Incumbent Party is coded 1 if the former governor
is running in an election contest where their political party currently holds the seat (governor or
senate seat in question), 0 if the former governor is running in an election contest for a seat
currently held by the opposition party (Incumbent PartyNon−Incumbent Governors: mean = 0.20, SD =
0.40, min = 0, max = 1).9 Further, when either an outgoing or former governor is running against
an incumbent candidate for a given elective office, the former are at an electoral disadvantage,
and thus should have a lower level of electoral support under these circumstances (Incumbency
DeficitNon−Incumbent Governors: mean = 0.43, SD = 0.50, min = 0, max = 1).10
Finally, current economic conditions, changes in state ideology, and other electoral
considerations may affect electoral support for both incumbent and non−incumbent governors.
9 These data are from Scammon, McGillivray, and Cook’s America Votes series, various years.
By definition, this measure is always equal to 1 for incumbent governors.
10 These data are from Scammon, McGillivray, and Cook’s America Votes series, various years.
By definition, this measure will always be equal to zero for incumbent governor cases. The
electoral effects of non−incumbent governors running in open seat contests are captured by
default in the baseline intercept term.
14
The state of the economy at the time of the election can influence aggregate voting behavior.
The State UE Rate (Election Quarter) variable is simply the state unemployment rate in the
election quarter. This covariate should be inversely related to the level of electoral support. This
measure reveals that the state unemployment rate is slightly lower for non−incumbent governors
that run as either opposition party or open seat candidates compared to when they represent the
incumbent party currently holding this statewide elective office (UE Rate (Election Quarter)
Non−Incumbent Governor & Incumbent Party: mean = 7.13, SD = 3.39, min = 3.34, max = 15.2; UE Rate
(Election Quarter)Non−Incumbent Governor & Opposition Party or Open Seat: mean = 6.10, SD = 3.10, min = 2.3,
max = 12.4).11 By construction, the incumbent governor observations will be accounted for by
the current state unemployment rate measure that is adjusted for partisan incumbency. The
baseline current state unemployment measure thus captures the effect of the current state
unemployment rate on non−incumbent governors vote share as either opposition party or open
seat candidates. In addition, we control for the absolute change in a given state’s voting age
population (Absolute Δ in VAP [Voting Age Population] Since Governor Left Office). This
variable accounts for the changing nature of the electoral landscape during non−incumbent
governors hiatus from major statewide elective office (Non−Incumbent Governor Cases only:
mean = 5.78, SD = 11.03, min = 0, max = 70.55).12 A non-incumbent governor previously
11 These data are from the Federal Reserve Bank of St. Louis,
www.research.stlouisfed.org/fred2/categories/27281, provided by the U.S. Department of Labor:
Bureau of Labor and Statistics. Quarterly averaged data, seasonally adjusted.
12 These data are from Census Bureau’s yearly population estimates
http://www.census.gov/popest/data/historical/index.html. By construction, this measure will
always be equal to zero for incumbent governor cases.
15
exiting office due to a lost re−election bid (20 cases) or being impeached (two cases) should
experience less support in subsequent election contests (Negative Exit Reason).13 Finally, the
changing ideological policy predispositions of a given state’s electorate can either benefit or hurt
a non−incumbent governor seeking subsequent elective office. This is captured by the state
citizen ideology measure developed by Berry et al., (1998), and adjusted for the party of the
non− incumbent governor (Δ State Citizen Ideology [Party−Adjusted]: mean = −7.71, SD =
11.22 , min = −39.78, max = 20.44).14 Changes in this measure compatible with the candidate’s
party should have the effect of enhancing their vote share since they will benefit from ideological
swings in the electorate.
EMPIRICAL FINDINGS
Three sets of regression results appear for each type of evaluative time frame appear in
Table 1. OLS and Beta parametric estimation methods are employed for analyzing electoral
vote share data in two-party systems. While these parametric estimators produce substantively
similar results for the core theoretical hypotheses, these models’ residuals suffer from excessive
kurtosis and skewness. Because the former governor observations are distributed through a
lengthy period of time, it is important to employ an estimation strategy that is not sensitive to
distributional assumptions induced by extreme values or outliers related to these observations.
To remedy this problem, nonparametric median regression models are estimated, and thus serve
13 These data are from various web searches (these can be obtained from the authors). By
construction, this measure will always be equal to zero for incumbent governor cases.
14 State citizen ideology measures originally developed by Berry, et al. (1998) come from
http://www.bama.ua.edu/~rcfording/stateideology.html. By construction, this measure will
always be equal to zero for incumbent governor cases.
16
as the sole basis for subsequent empirical inquiry. Each model specification also accounts for
covariates that may serve as confounding factors that predict variations involving current
electoral support for both incumbent and non−incumbent governors based on past and current
indicators. Based on the significant Machado–Santos Silva (2000) heteroskedasticity test, the
reported standard errors are corrected using the robust estimates of the variance-covariance
matrix developed by Angrist, Chernozhukov, and Fernandez-Val (2006).15
Based on the nonparametric regression estimates, previous election results exert marginal
persistence effects for predicting current election results only in the Recent Term model.
Consistent with expectations, general election contests produce an average of roughly 18 percent
lower expected vote shares compared to primary election contests across these three models. On
average, non-incumbent governors receive 10.34, 12.14, and 6.31 percent lower expected vote
shares than compared to incumbent governor counterparts in the Recent Year, Recent Term, and
Tenure models, respectively. This variable gap between incumbent and non−incumbent
governors suggest that the benefits of incumbency advantage are more acutely realized when
voters employ either a narrow or moderate evaluative time frame to assess incumbent
performance in office. Whether outgoing or former governors are representing the incumbent
party or is running against an incumbent for either a Senate seat or governorship has no bearing
on current electoral vote share. For the Recent Term and Tenure models, the unemployment rate
at the time of the current election is not significantly different from zero, irrespective of whether
they represent the incumbent party (UE Rate (Election Quarter) × Incumbent Party) or not (UE
Rate (Election Quarter)). This finding stands in stark contrast from the significant effects
15 The conventional standard errors estimated by the least absolute deviation (LAD) estimator are
less conservative (smaller) in magnitude than the robust standard errors reported here.
17
obtained for these covariates in the Recent Year model. Neither partisan−favored changes in state
citizen ideology, nor absolute changes in the voting age population affect current electoral vote
share. Although non−incumbent governors seeking office incur a drop in electoral support for
leaving office due to either impeachment or losing a re−election bid, it is not statistically
discernible from zero in the median regression models that are robust to violations of
distributional assumptions underlying the data generating processes.
[INSERT TABLE 1 ABOUT HERE]
IAD theory’s testable predictions center on the impact of the net change in the quarterly
average unemployment rate during the governor’s most recent year in office (Recent Year
model), most recent term in office (Recent Term model), and during their tenure in office
(Tenure model), and its discounting through time as captured by its corresponding multiplicative
term: ∆ State Quarterly UE Rate × Election Delay.16 Recall that the Immediate Accountability
Hypothesis (H1) predicts that voters’ current electoral support for incumbent governors seeking
re−election to this office will be most strongly tethered to their economic stewardship (β Δ State
Quarterly UE Rate > 0). There is support for this hypothesis in both the Recent Term and Tenure
models. Moreover, support for the Evaluative Time Frame−Immediate Accountability
Hypothesis (H3) is obtained for both moderate and wide evaluative time frames. Specifically,
16 In preliminary analysis, an attempt was made to analyze nonlinear models that allow for
hyperbolic-behavioral1
1 Election Delay
and exponential-rational (e−Election Delay) intertemporal
discounting behavior. Unfortunately, these models provided a rather poor fit to these
relationships – a fact corroborated via multivariate Lowess plots which indicated that attribution
decay approximately follows a constant rate (linear) discounting process.
18
retrospective economic assessments made during an incumbent governor’s most recent term in
office will produce a greater than proportional impact on their electoral support (β Δ State Quarterly UE
Rate: Recent Term = 1.190, p < 0.01), while these attributions are much weaker when made during the
governor’s entire tenure in office (β Δ State Quarterly UE Rate: Tenure = 0.641, p > 0.10: one-tailed test).17
Evidence in favor of the Diminishing Accountability Hypothesis (H2) is obtained in both the
Recent Term and Tenure models. In these particular instances, retrospective economic voting
behavior will be discounted as time elapses between the outgoing or former governor’s service in
office and their next electoral bid (β Δ State Quarterly UE Rate × Election Delay < 0, p ≤ 0.072 one-tailed test).
These regression coefficient estimates are the correct hypothesized sign (negative) and
statistically significant at p = 0.032 and p = 0.072 based on a one-tailed directional hypothesis
test. When the governor seeks re−election to this elective office (Election Delay = 0), each one
percent net improvement in the state’s unemployment rate during their final term in office
translates into almost a 1.19% increase in expected current vote share. For example, an
interquartile range increase in this economic stewardship variable restricted to this particular
subset of cases from π0.25 [−1.6] to π0.75 [+1.5] yields a 3.69% immediate improvement in the
incumbent governor’s expected current vote share. This discounting of retrospective economic
voting behavior increases as time elapses between the outgoing or former governor’s service in
office and their next electoral bid consistent with H2 (β Δ State Quarterly UE Rate: Tenure × Election Delay < 0).
The coefficient on the multiplicative term involving net change in state unemployment rate and
election date delay reveals a higher rate of discounting for this interaction coefficient in the
17 An interquartile range increase in this economic stewardship variable restricted to this
particular subset of cases from π0.25 [−1.5] to π0.75 [+1.8] yields a 2.12% immediate improvement
in the incumbent governor’s expected current vote share.
19
Recent Term model compared to the corresponding estimates in the Tenure model consistent
with H4: Evaluative Time Frame−Diminishing Accountability Hypothesis (β Δ State Quarterly UE Rate:
Recent Term × Election Delay < β Δ State Quarterly UE Rate: Tenure × Election Delay). Inferential support for H4,
however, is elusive since the expected electoral vote share difference between these discount
parameters is only 0.30, and also fails to attain statistical significance at conventional levels.
Interestingly enough, the evidence from the Recent Year model reveals that a narrow
evaluative time frame for making retrospective economic attributions comports with neither H1
nor H3. This model uncovers a weak negative retrospective economic attribution that is not
discernible from zero. One possible explanation for these contrary results may be attributed to
confounding priming effects sent by campaigns and the media that do not allow for voters to
make effective retrospective economic attributions in real time based on a short evaluative time
frame. If this is the case, then voters should not be able to improve upon these ‘null attributions’
in subsequent election contests contrary to H2. Alternatively, this null result may reflect
cognitive information processing delays which are eventually overcome at some later period.
The electorate may be incapable of processing this economic information in an efficient manner
in a condensed period of time, but can process it with delay so that they make effective
attributions at some later date for a future election contest. While this latter alternative
explanation of this null result for H1 and H3 is inconsistent with H2 since retrospective
economic attributions may take time to formulate, it is not inconsistent with H4. The positive
and statistically significant interaction coefficient for UE Rate: Recent Year × Election Delay suggests as
much since retrospective economic attributions do not decay in absolute terms with the passage
of time as posited by H2. Instead, this particular retrospective economic attribution becomes
20
compounded through time, and hence, is dynamically more robust than either evaluations based
over the course of the most recent term or entire tenure in office consistent with H4.
The corresponding intertemporal dynamics of electoral accountability for economic
stewardship are displayed in Figure 2. These graphs reveal the marginal conditional impact of
past economic stewardship on current electoral support, conditional on time elapsing between
these two events under tenure, recent term, and recent year evaluative time frames. The dynamic
conditional marginal effects generated from the Tenure model are displayed in Panel 2A.
Although the potency of retrospective economic voting declines through time consistent with
intertemporal attribution discounting theory, it remains statistically indiscernible from zero
across all future periods. This dynamic attribution process reaches the zero impact threshold
(based on point estimates) in approximately 3.5 years (42 months ≈ π0.54).18 In the Recent Term
model displayed in Panel 2B, the effect of past economic stewardship is positive, yet ceases to
be statistically discernible from zero after approximately 2.3 years (or 28 months ≈ π0.43) at the
95% confidence level, and 3.25 years (or 39 months ≈ π0.48) at the 90% confidence level. The
threshold in which past economic stewardship appears to have zero impact on current electoral
support for former governors is 8 years (= 96 months ≈ π0.90), and beyond this point actually
results in an inverse relationship based on the point estimates. This should be interpreted with
caution, however, given that it is estimated rather imprecisely based on the large confidence
limits for more distant future attributions.19 Panel 2C reveals that most recent year retrospective
18 These percentile rank interpretations are defined in terms of non-incumbent (outgoing and
former) governor observations (n = 111).
19 It should be noted that while this zero threshold is reached more quickly when retrospective
economic voting is based on net changes in state unemployment rate during the tenure of a
21
economic attributions are negative, albeit statistically insignificant, for incumbent governors.
The threshold where past economic stewardship appears to have zero impact on electoral support
for former governors is one year into the future (= 12 months ≈ π0.28). The conditional marginal
effect of this dynamic attribution compounds through time at a rate of 1.31 per month, with
statistical significance being attained at the 95% confidence level 80 months (≈ π0.73) beyond the
former governor’s time in office had ended. After more than 200 months has elapsed since the
former governor left office, each one percent reduction in the unemployment rate during this
most recent year in office produces a 13.15 surge in vote share, albeit these larger impacts are
based on a smaller density of observations. The intertemporal compounding of retrospective
economic attributions is suggestive of a strong anchoring bias effect in subsequent election
contests. This finding, however, should not be interpreted as providing evidence of effective
dynamic electoral accountability. Retrospective assessments based a governor’s most recent
(election) year in office constitute a rather small fraction of their service, and thus constitutes a
strongly biased representation of economic stewardship under their watch.20
[INSERT FIGURE 2 ABOUT HERE]
Figure 3 examines three distinct economic stewardship scenarios to assess how
variations in past economic stewardship affects both incumbent and non−incumbent governors
former governor, this is due to the fact that the immediate attribution for incumbent governors is
almost half of that compared to evaluations limited to the most recent term in office.
20 This assertion is empirically substantiated since the net change in the state unemployment rate
over the course of a governor’s tenure and most recent term is correlated at 0.844, while these
measures are correlated with the net change in the state unemployment rate during the governor’s
most recent (final) year in office at −0.424 and −0.572, respectively.
22
subsequent electoral fortunes in major statewide election contests. This is implemented by
generating the expected value of the dependent variable (Electoral Vote Share), and
manipulating Δ State Quarterly UE Rate: Recent Term, Election Delay, and the interaction
between these covariates, while holding all other covariates at their mean values. Panel 3A and
Panel 3B uncover several interesting patterns regarding the impact of intertemporal attribution
discounting behavior that occurs when retrospective economic evaluations are made during the
governor’s tenure in office (Tenure model) vis-à-vis their most recent term in office (Recent
Term). First, Panel 3A reveals that the electoral vote share between incumbent governors
seeking re-election and outgoing governors seeking immediate election to the U.S. Senate falls
of from anywhere between six to 6.5 percent when evaluating the governor’s overall economic
stewardship. This drop constitutes roughly half the magnitude of the drop in economic
attributions made by voters when using a moderate evaluative frame of the governor’s last term
in office displayed in Panel 3B. This difference suggests that the candidate’s most recent
economic record is less fungible for seeking a different elective office than when their overall
economic performance is assessed. Second, once the focus is limited to outgoing governors
beyond t > 1, it is apparent that intertemporal attribution discounting is greater for assessments
made based on their overall tenure in office compared to their most recent term in office. A
former governor’s expected electoral vote share declines by an additional one percent, 1.34
percent, and 1.50 percent for each additional 20 months pertaining to the poor, average, and
excellent economic stewardship scenarios, respectively.
Closer inspection of Panel 3B indicates that poor past economic stewardship (π0.05 = −
5.20) results in an average electoral support baseline of 56.20 percent for incumbent governors
seeking re-election at time t = 0, and declines sharply to 44.06 percent for outgoing current
23
governors immediately seeking U.S. Senate seats (t = 1), and subsequently decreases by 0.03
percent for each subsequent 20 months beyond when their economic stewardship took place
Total attribution discounting for both outgoing and former governors is only a meager 0.31%
after 213 months has elapsed between economic stewardship and aggregate vote choice.
Average caliber past economic stewardship (π0.50 = + 0.30) yields an average electoral support
baseline of 62.50% for incumbent governors seeking re-election at time t = 0 and, once again,
drops sharply by 12.21 percent down to 50.30 percent for outgoing governors immediately
seeking U.S. Senate seats at t = 1. Each subsequent 20 month span causes a declining vote share
of 1.30%, with a total attribution discounting effect of 14 percent after 213 months has elapsed
between economic stewardship and aggregate vote choice. Finally, excellent past economic
stewardship (π0.95 = + 4.0) produces the highest baseline for expected electoral vote share for
incumbent governors seeking re−election (67.14 percent). While the drop in electoral support
for outgoing governors immediately seeking a U.S. Senate seat at t =1 is substantively identical
to those from the other economic stewardship scenarios, it also produces the largest decline in
retrospective economic attributions. Specifically, each additional 20 months leads to a 2.28
percent drop in the expected electoral vote share of former governors, with a total intertemporal
attribution decline of 24.10 percent after 213 months has elapsed between economic stewardship
and aggregate vote choice.
[INSERT FIGURE 3 ABOUT HERE]
Panel 3C displays that poor economic stewardship in a governor’s most recent year in
office (π0.05 = − 1.0) drops their expected vote share by slightly more than ten percent for
outgoing governors seeking U.S. Senate seats, before further declining by a rate of 2.72% for
every 20 months into the future until it reaches its nadir at 22.75% -- 213 months since the
24
former governor left office. Conversely, excellent economic stewardship in a governor’s most
recent year in office (π0.95 = + 1.9) increases former governor’s expected vote share by 0.98% for
every 20 months into the future until it reaches its apex at 60.90% -- 213 months since the former
governor left office. This evidence shows that this intertemporal attribution compounding effect
is asymmetric insofar that poor economic stewardship is discounted 2.77 more times than it is
compounded for excellent economic stewardship.
Comparison of these three evaluative time frame scenarios displayed in Panels 3A−3C
exhibit two opposing types of cognitive biases in decision-making that are not explicitly
predicted by IAD theory. Both the wide (tenure) and moderate (recent term) evaluative time
frames reflect intertemporal regressive bias that is not predicted by the theory. The electorate
administers a one-time immediate electoral sanction for governors possessing poor economic
records in both Panels 3A and 3B, yet increasingly fails to apportion credit for governors
possessing strong records of economic performance. This asymmetric pattern of dynamic
retrospective economic voting behavior implies that voters quickly forgive and absolve
incompetent politicians for their excellent economic stewardship, but that they more quickly
forget the excellent economic stewardship of competent politicians. Finally, asymmetric
regressive bias is more pronounced under a wide evaluative time frame. This growing bias in
electoral support for each of these economic stewardship scenarios not only occurs earlier, but is
also much more pronounced than when the overall economic record is used to form attributions.
Panel 3C shows that retrospective economic voting exhibits intertemporal anchoring biases
when a narrow evaluative time frame is employed. In other words, the weight attached to a
governor’s economic stewardship during a former governor’s last year in office increases as time
elapses between their exit from office and their re-entry into the electoral arena.
25
DISCUSSION
Electoral accountability is a fundamental criterion by which all representative
democracies are evaluated. If citizens cannot reward competent politicians and sanction
incompetent ones, then it calls into question the viability of democratic institutions to serve the
interests of the broader polity. At its core, electoral accountability most often translates into
understanding the voters’ ability to effectively reward and sanction politicians for their
policymaking performance at the polls. Retrospective economic voting is the most common, and
perhaps the most effective, channel by which voters make assessments regarding the
performance of their elected representatives (e.g., Barro 1973; Downs 1957; Ferejohn 1986;
Fiorina 1981). Current theories and empirical evidence of retrospective voting are generally
rooted in a two-period view of the world in which the incumbent party is evaluated for a given
political office at time t based on their stewardship of the economy at time t-1 (but see Schwabe
2011). The extant research does not explicitly consider the intertemporal dynamics of
retrospective economic voting behavior. Extant research that focuses on party responsibility
undervalues the importance of the actual stewards (persons) that actually appear on the ballot
seeking elective office, and their corresponding individual reputation for policymaking
competence. That is, whether voters deem a politician as being a ‘good type’ or ‘bad type’ in
principal-agent terms, depends upon a given individual’s record in elective office.
To address both issues, a theory of intertemporal attribution discounting (IAD) has been
advanced to facilitate our understanding as to how voters (in aggregate) retrospectively discount
past economic stewardship of elected officials seeking other elective offices or the same office at
some point in the future. This puzzle deals with the tangible reality that elected officials often
have more than one act to their political careers. Attention is restricted to aggregate electoral
voting outcomes for incumbent governors seeking re-election and non-incumbent (i.e., outgoing
26
or former) governors running in either gubernatorial or U.S. Senate election contests. Further,
attention is restricted to a common political jurisdiction (i.e., major statewide elective office) to
ensure comparability in analyzing electoral accountability. The statistical evidence offers strong
support for several of the predictions generated by IAD theory. For instance, voters discount a
former politician’s past economic stewardship through time when determining whether to offer
electoral support to these particular individuals in subsequent election contests when evaluating
them on their tenure or most recent term in elective office. Voters’ attributions of economic
stewardship are not only weaker when evaluated over the politician’s tenure in office, but also
discount at a faster rate than compared to when the voters’ reference point for assessing
economic stewardship is anchored to the more recent past (i.e., last term in office). In the
exceptional case of most recent (final) year retrospective economic attributions, voters exhibit an
intertemporal anchoring bias, whereby they compound their assessments of the governor’s
performance in office when evaluating these individuals for elective office at a later date.
Although dynamic electoral accountability appears to be more effective in this latter instance, it
is a mirage since it is premised on a highly biased evaluation of governors’ economic
stewardship in office because it only comprises a single year that represents anywhere from
12.5% to 25% of their time in this elective office for almost 90% of the effective sample cases.
These findings have critical implications for understanding electoral accountability in a
dynamic setting. Because voters increasingly discount past economic performance associated
with particular politicians through time with respect aggregate electoral choice, politicians
bearing a strong record of economic stewardship, based on a sufficiently informative record in
office, should seek higher office not long after stepping out of their previous office. Conversely,
politicians with a poor record of economic stewardship under such circumstances can benefit
27
from a prolonged hiatus seeking elective office in order to ensure that ‘old wounds’ can heal with
the passage of time. That is, more distant retrospective economic voting assessments are
discounted at a greater rate than less distant ones. This claim is the mirror image of voters
possessing information and cognitive limitations, and thus employ simplifying heuristics in order
to effectively hold elected officials accountable (Lupia 1994), including the weighting of only
the most recent past information in electoral choice (Healy and Lenz 2012).
On a normative level, this study suggests that electoral rules such as term−limits, that
often produce former governors seeking statewide office at some point in the future, may
actually make it more difficult for voters to collectively weed out competent politicians from
incompetent ones. Both the logic and evidence presented here thus complements scholarship
which claim that reducing institutional restrictions associated with elective office actually
increases the quality of electoral accountability in a democracy (Besley and Case 1995; Besley
2006). Moreover, the application of overly-simplified heuristics, such as an end-heuristic
identified by Healy and Lenz (2012), will only exacerbate the difficulty that voters confront
when discriminating between competent and incompetent politicians in dynamic settings. From
the politician’s perspective, differential strategies should be pursued by competent and
incompetent agents. When politicians are competent types (i.e., excellent economic stewards),
they should seek elective office either concurrently or in the not too distant future by running on
their positive economic record based on the most recent term of service. Conversely,
incompetent politicians (i.e., poor economic stewards) should defer to seek elective office for a
lengthy period of time into the future until voters’ collective attributions begin to reflect
intertemporal regressive bias, and when they do re−enter the electoral arena they should
emphasize their overall economic record from their tenure in office. Because voters’ ability to
28
distinguish between competent and incompetent politicians based on prior service becomes
increasingly blurred through time, politicians’ individual-level reputations can be thought of as a
rapidly depreciating asset that loses value when a politician takes a hiatus from elective office.
Future research should pursue developing unified theories of attribution that integrate insights
from the IAD theory, with insights generated spatial theories of heterogeneous attributions
rooted in political sophistication (Gomez and Wilson 2001, 2003), partisan identification
(Rudolph 2003), or geographical considerations (Ansolabehere, Meredith, and Snowberg 2011).
Acquiring a better understanding of the context in which the reputational durability of politicians
systematically varies can serve to improve electoral accountability in dynamic settings.
29
REFERENCES
Angrist, Joshua D., Victor Chernozhukov, and Ivan Fernández-Val. 2006. “Quantile Regression
Under Misspecification, with an Application to the U.S. Wage Structure.” Econometrica
74(March): 539-563.
Ansolabehere, Stephen and James M. Snyder Jr. 2002. “The Incumbency Advantage in U.S.
Elections: An Analysis of State and Federal Offices, 1942–2000.” Election Law Journal:
Rules, Politics, and Policy 1(June): 315-338.
Ansolabehere, Stephen, Marc Meredith, and Erik Snowberg. 2011. “Mecro−Economic Voting:
Local Information and the Micro−Perceptions of the Macro−Economy.” Harvard
University. Typescript.
Barro, Robert J. 1973. “The Control of Politicians: An Economic Model.” Public Choice
14(Spring): 19-42.
Berry, William D., Evan J. Ringquist, Richard C. Fording, and Russell L. Hanson. 1998. “Measuring Citizen and Government Ideology in the American States, 1960-93.” American Journal of Political Science 42(January): 327-348.
Besley, Timothy and Anne Case. 1995. “Does Electoral Accountability Affect Economic Policy
Choices? Evidence from Gubernatorial Term Limits.” The Quarterly Journal of
Economics 110(August): 769-798.
Besley, Timothy. 2006. Principled Agents: The Political Economy of Good Government.
New York: Oxford University Press.
Bloom, Howard S. and Douglas H. Price. 1975. “Voter Response to Short-Run Economic
Conditions: The Asymmetric Effect of Prosperity and Recession.” American Political
Science Review 69 (March): 124-154.
Brady, David W., Hahrie Han, and Jeremy C. Pope. 2007. “Primary Elections and Candidate
30
Ideology: Out of Step with the Primary Electorate?” Legislative Studies Quarterly
32(February): 79-105.
Chubb, John E. 1988. “Institutions, The Economy, and The Dynamics of State Elections.” The
American Political Science Review 82(March): 133-154.
Cohen, Jeffrey E. and James D. King. 2004. “Relative Unemployment and Gubernatorial
Popularity.” The Journal of Politics 66(November): 1267-1282.
Dometrius, Nelson. 1999. “Governors: Their Heritage and Future.” In American State and Local
Politics: Directions for the 21st Century, edited by Ronald Weber and Paul Brace. New
York: Chatham House Publishers, Seven Bridges Press.
Downs, Anthony. 1957. An Economic Theory of Democracy. New York: Harper Row.
Ericsson, K. Anders, and Herbert A. Simon. 1981. “Sources of Evidence on Cognition: A
Historical Overview.” In Thomas V. Merluzzi, Carol R. Glass, Myles Genest, eds.
Cognitive Assessment. New York: Guilford Press. Chapter 2 (pp. 16-51).
Ferejohn, John. 1986. “Incumbent Performance and Electoral Control.” Public Choice 50 (March): 5-25.
Fiorina, Morris P. 1981. Retrospective Voting in American National Elections. New Haven: Yale
University Press.
Gomez, Brad T. and J. Matthew Wilson. 2001. “Political Sophistication and Economic Voting in
the Electorate in the American Electorate: A Theory of Heterogeneous Attribution.”
American Journal of Political Science 45(October): 899-914.
Gomez, Brad T. and J. Matthew Wilson. 2003. “Causal Attribution and Economic Voting in
American Congressional Elections.” Political Research Quarterly 56(September): 271-
282.
Hanks, Christopher and Bernard Grofman. 1998. “Turnout in Gubernatorial and Senatorial
31
Primary and General Elections in the South, 1922-90: A Rational Choice Model of the
Effects of Short-Run and Long-Run Electoral Competition on Relative Turnout.” Public
Choice 94(3/4): 407-421.
Hansen, Susan B. 1999. “’Life Is Not Fair’: Governor’s Job Performance Ratings and State
Economies.” Political Research Quarterly 52(March): 167-188.
Healy, Andrew, and Gabriel S. Lenz. 2012. “Substituting the End for the Whole: Why Voters
Respond Primarily to the Election−Year Economy.” University of California-Berkeley.
Typescript.
Key, V. O. 1966. The Responsible Electorate: Rationality in Presidential Voting 1936-1960.
Cambridge, MA: Harvard University Press.
Kiewiet, D. Roderick, and Michael Udell. 1998. “Twenty-Five Years after Kramer: An
Assessment of Economic Retrospective Voting Based Upon Improved Estimates of
Income and Employment.” Economics and Politics 19(November): 219-248.
Kramer, Gerald H. 1971. “Short Term Fluctuations in U.S. Voting Behavior, 1896–1964.”
American Political Science Review 65(March): 131-43.
Lewis-Beck, Michael and Mary Stegmaier. 2007. “Economic Models of Voting.” In The Oxford
Handbook of Political Methodology, eds., Russell Dalton and Hans-Dieter Klingemann.
Lupia, Arthur. 1994. “Encyclopedias versus Shortcuts: Information and Voting in California
Insurance Reform Elections.” American Political Science Review 88(March): 63-76.
Machados, J.A.F., and J.M.C. Santos Silva. 2000. “Glejser’s Test Revisited.” Journal of
Econometrics 97(March): 189-202
Markus, Gregory B. 1988. “The Impact of Personal and National Economic Conditions on the
Presidential Vote: A Pooled Cross-Sectional Analysis.” American Journal of Political
Science 32(February): 137-154.
32
Niemi, Richard G., Harold W. Stanley, and Ronald J. Vogel. 1995. “State Economies and States
Taxes: Do Voters Hold Governors Accountable?” American Journal of Political Science
39(November): 936-957.
Partin, Randall W. 1995. “Economics Conditions And Gubernatorial Elections: Is the State
Executive Held Accountable?” American Politics Quarterly 23(January): 81-95.
Peltzman, Sam. 1987. “Economic Conditions and Gubernatorial Elections.” American Economic
Review 77(May): 293-297.
Powell, G. Bingham Jr. and Guy D. Whitten. 1993. “A Cross-National Analysis of Economic
Voting: Taking Account of the Political Context.” American Journal of Political Science
37(May): 391-414.
Rudolph, Thomas J. 2003. “Who's Responsible for the Economy? The Formation and
Consequences of Responsibility Attributions.” American Journal of Political Science
47(October): 698-713.
Schwabe, Rainer. 2011. “Reputation and Accountability in Repeated Elections.” Typescript.
Bank de Mexico.
Taber, Charles S., and Everett Young. 2011. “Information Processing, Public Opinion, and
Accountability.” In Accountability Through Public Opinion: From Inertia to Action.
Sina Odugbemi and Taeku Lee, editors. Washington, D.C.: The World Bank
Woehr, David J., and Jack. Feldman. 1993. “Processing Objective and Question Order Effects on
the Causal Relation Between Memory and Judgment in Performance Appraisal: The Tip
of the Iceberg.” Journal of Applied Psychology 78(2): 232-241.
Wolfers, Justin. 2007. “Are Voters Rational? Evidence from Gubernatorial Elections.” National
Bureau of Economic Research. Typescript.
33
Figure 1: Distribution of Major Statewide Elections For the Intertemporal Range: Sample of Current, Outgoing, and Former Governors
0.0
1.0
2.0
3.0
4D
ensi
ty
0 100 200 300 400
Election Delay (in Months)
34
TABLE 1: Regression Analysis Predicting Election Vote Share for Incumbent, Outgoing, and Former Governors in the American States Tenure Net Δ in UE Rate Recent Term Net Δ in UE Rate Recent Year Net Δ in UE Rate
OLS Beta Median OLS Beta Median OLS Beta Median Economic Stewardship & Attribution Discounting
∆ State Quarterly UE Rate × Election Delay
0.004 [0.007]
0.0001 [0.0003]
−0.015+ [0.010]
−0.004 [0.005]
−0.0002 [0.0002]
−0.012* [0.006]
0.011 [0.019]
0.0008 [0.0008]
0.065** [0.028]
∆ State Quarterly UE Rate 0.309
[0.393] 0.002
[0.0162] 0.641
[0.573] 1.085***
[0.388] 0.032**
[0.016] 1.190***
[0.435] −0.278
[0.927] −0.004
[0.038] −0.823
[1.016] Election Delay
(months) −0.258***
[0.061] −0.010***
[0.002] 0.130+ [0.096]
−0.099*** [0.031]
−0.005*** [0.001]
−0.065+ [0.042]
−0.097*** [0.031]
−0.005*** [0.001]
−0.075* [0.040]
Ancillary Controls Previous Gubernatorial
General Election Results 0.196* [0.100]
0.008* [0.004]
−0.023 [0.126]
0.212** [0.101]
0.008** [0.004]
0.165+ [0.125]
0.180* [0.101]
0.007* [0.004]
0.080 [0.113]
Non-Incumbent Governor −10.137***
[3.854] −0.351** [0.163]
−6.306 [6.348]
−15.299*** [3.776]
−0.538*** [0.159]
−12.138* [6.417]
−15.347*** [3.828]
−0.533*** [0.161]
−10.347+ [6.708]
General Election Contest
−17.363*** [2.494]
−0.722*** [0.109]
−19.363*** [5.582]
−17.004*** [2.431]
−0.696*** [0.105]
−18.164*** [5.810]
−16.744*** [2.459]
−0.685*** [0.105]
−17.841*** [3.914]
Incumbent Party −10.021+ [6.285]
−0.495* [0.270]
−14.484+
[9.751] −11.186* [5.899]
−0.553** [0.250]
−9.834 [9.289]
−11.235* [6.065]
−0.543** [0.256]
−16.986** [8.125]
Incumbency Deficit 1.647
[2.749] −0.165+ [0.119]
−3.831 [6.701]
−0.095 [2.612]
−0.209* [0.112]
−0.675 [5.039]
−0.476 [2.636]
−0.216* [0.112]
−0.998 [4.688]
State UE Rate (Election Quarter)
−0.726 [0.869]
−0.034 [0.037]
−0.747 [1.297]
0.361 [0.745]
0.0001 [0.032]
−0.228 [1.016]
−0.284 [0.732]
−0.018 [0.031]
−1.949** [0.796]
State UE Rate (EQ) × Incumbent Party
0.218 [0.945]
0.004 [0.040]
0.806 [1.279]
−0.259 [0.831]
−0.006 [0.035]
0.405 [1.087]
−0.289 [0.851]
−0.008 [0.036]
1.592* [0.852]
Absolute ∆ in VAP Since Governor Left Office
1.646*** [0.600]
0.047* [0.026]
0.223 [1.164]
0.364** [0.157]
0.016** [0.007]
0.248 [0.283]
0.378** [0.158]
0.016** [0.007]
0.236 [0.217]
Negative Exit Reason −16.691***
[3.955] −0.823***
[0.163] −15.833 [12.417]
−18.733*** [3.734]
−0.884*** [0.155]
−11.264 [14.587]
−18.659*** [3.774]
−0.889*** [0.155]
−11.051 [9.194]
∆ State Citizen Ideology (Party−Adjusted)
0.030 [0.139]
−0.002 [0.006]
0.058 [0.321]
0.007 [0.131]
−0.003 [0.005]
0.202 [0.260]
−0.011 [0.133]
−0.003 [0.005]
−0.012 [0.259]
Constant 77.251***
[8.499] 1.257***
[0.362] 91.755***
[15.754] 73.812***
[8.374] 1.133***
[0.352] 75.318***
[17.150] 79.129***
[8.312] 1.272***
[0.349] 89.732***
[11.778] Number of Observations 296 290 296 309 303 309 309 303 309
R2 0.305 ------------- 0.248 0.279 --------- 0.251 0.260 ------------- 0.208 Adjusted R2/Pseudo R2 0.273 ------------ ----------- 0.247 ----------- ----------- 0.227 ------------- --------
Root MSE 12.418 -------------- -------------- 12.617 ---------- ------------- 12.78 ------------- ------------- εSkewness 0.0004 0.002 ------------ 0.004 0.005 ------------- 0.001 0.001 -------------
εKurtosis 0.001 0.001 ------------- 0.002 0.002 ------------- 0.0003 0.0005 ------------- Machado-Santos Silva Heteroskedasticity Test
____________ ___________ 26.456***
[0.000] __________ ____________
33.419*** [0.000]
____________ ____________ 43.739***
[0.000] Notes: Dependent variable is defined as the Former Governor’s Vote Share in the given election.. Standard errors are inside parentheses (Median regression SEs are heteroskedastic-consistent and robust to misspecification of the variance-covariance matrix). *** p ≤ 0.01; ** p ≤ 0.05; * p ≤ 0.10; +significant at the 0.10 level (one-tailed test).
35
Figure 2: The Impact of Intertemporal Attribution Discounting on Retrospective Economic Voting Behavior
‐8
‐7
‐6
‐5
‐4
‐3
‐2
‐1
0
1
2
3
0 1 20 40 60 80 100120140160180200213
Cond
ition
al M
argina
l Effects of
Past Econo
mic Stewardship on
Expe
cted
Electoral Vote Share
Election Delay (Months)
Panel 2A: Conditional Marginal Effects: Tenure Model
ConditionalMarginal Effects
95% C.I.: Upper
95% C.I.: Lower
‐5
‐4
‐3
‐2
‐1
0
1
2
3
0 1 20 40 60 80 100120140160180200213
Cond
ition
al M
argina
l Effects of
Past Econo
mic Stewardship on
Expe
cted
Electoral Vote Share
Election Delay (Months)
Panel 2B: Conditional Marginal Effects: Recent Term Model
ConditionalMarginal Effects
95% C.I.: Upper
95% C.I.: Lower
‐5
0
5
10
15
20
25
0 1
20
40
60
80
100
120
140
160
180
200
213
Cond
ition
al M
argina
l Effects of
Past Econo
mic Stewardship on
Expe
cted
Electoral Vote Share
Election Delay (Months)
Panel 2C: Conditional Marginal Effects: Recent Year
ConditionalMarginal Effects
95% C.I.: Upper
95% C.I.: Lower
36
Figure 3: The Consequences of Intertemporal Attribution Discounting on Expected Electoral Vote Share
10
20
30
40
50
60
70
0 1 20 40 60 80 100120140160180200213
Expe
cted
Electoral V
ote Share
Election Delay (Months)
Panel 3A: Expected Electoral Vote Share for Incumbent & Non-Incumbent Governors:
Tenure Model
Net ∆ UE Rate: 5th Pctile (‐5.2)
Net ∆ UE Rate: 50th Pctile (.30)
Net ∆ UE Rate: 95th Pctile (4.0)
10
20
30
40
50
60
70
0 1 20 40 60 80 100120140160180200213
Expe
cted
Electoral V
ote Share
Election Delay (Months)
Panel 3B: Expected Electoral Vote Share for Incumbent & Non-Incumbent Governors:
Recent Term Model
Net ∆ UE Rate: 5th Pctile (‐5.2)
Net ∆ UE Rate: 50th Pctile (.10)
Net ∆ UE Rate: 95th Pctile (4.0)
10
20
30
40
50
60
70
0 1 20 40 60 80 100120140160180200213
Expe
cted
Electoral Vote Share
Election Delay (Months)
Panel 3C: Expected Electoral Vote Share for Incumbent & Non-Incumbent Governors:
Recent Year Model
Net ∆ UE Rate: 5th Pctile (‐1.0)
Net ∆ UE Rate: 50th Pctile (‐0.1)
Net ∆ UE Rate: 95th Pctile (1.9)