Retrospective Economic Voting and the Intertemporal ...gkrause/Intertemporal Attribution...into an...

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.

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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

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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.

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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.

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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

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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.

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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.

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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

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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.

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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).

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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.

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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.

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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.



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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.


By definition, this measure is always equal to 1 for incumbent governors.


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.

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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.

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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.

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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


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.


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

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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).

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Figure 2: The Impact of Intertemporal Attribution Discounting on Retrospective Economic Voting Behavior

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Election Delay (Months)

Panel 2A: Conditional Marginal Effects: Tenure Model

ConditionalMarginal Effects

95% C.I.: Upper

95% C.I.: Lower

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Panel 2B: Conditional Marginal Effects: Recent Term Model


95% C.I.: Upper

95% C.I.: Lower

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Panel 2C: Conditional Marginal Effects: Recent Year


95% C.I.: Upper

95% C.I.: Lower

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Figure 3: The Consequences of Intertemporal Attribution Discounting on Expected Electoral Vote Share

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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)

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Panel 3B: Expected Electoral Vote Share for Incumbent & Non-Incumbent Governors:

Recent Term Model


Net ∆ UE Rate: 50th Pctile (.10)


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Panel 3C: Expected Electoral Vote Share for Incumbent & Non-Incumbent Governors:

Recent Year Model




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