Advantages and Disadvantages of Cognitive Heuristics in Political Decision Making
Author(s): Richard R. Lau and David P. Redlawsk
Source: American Journal of Political Science, Vol. 45, No. 4 (Oct., 2001), pp. 951-971
Published by: Midwest Political Science Association
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Advantages and Disadvantages of Cognitiv
Heuristics in Political Decision Making
Richard R. Lau Rutgers University
David P. Redlawsk University of Iowa
This article challenges the often untested
assumption that cognitive
"heuristics" improve the decisionmaking
abilities of everyday voters.
The potential benefits and costs of
five common political heuristics are
discussed. A new dynamic processtracing
methodology is employed to
directly observe the use of these five
heuristics by voters in a mock presidential
election campaign. We find
that cognitive heuristics are at times
employed by almost all voters and
that they are particularly likely to be
used when the choice situation facing
voters is complex. A hypothesized
interaction between political sophistication
and heuristic use on the quality
of decision making is obtained across
several different experiments, however.
As predicted, heuristic use
generally increases the probability of
a correct vote by political experts but
decreases the probability of a correct
vote by novices. A situation in which
experts can be led astray by heuristic
use is also illustrated. Discussion
focuses on the implications of these
findings for strategies to increase
input from under-represented groups
into the political process.
T he "cognitive revolution" may not have revolutionized research in
political science to the extent it has in psychology, but it did provide
a pat answer to one of the most troubling and persistent questions
in the field: how a public that is notoriously uninterested and largely "innocent"
of political matters can provide any control over public policy. The
widespread ignorance of the general public about all but the most highly
salient political events and actors is one of the best documented facts in all
of the social sciences (e.g., Converse 1975; Delli Carpini and Keeter 1996;
Kinder and Sears 1985). While almost everyone in the United States knows
who the President is, barely half of the public can name even the most
prominent members of the cabinet, and only a third can name their two
senators or their representative in Congress.' Bare majorities know the simplest
facts about how government works, and fewer still hold "real" attitudes
toward even the most important political issues of the day (Converse
1964).
Yet this widespread ignorance flies in the face of what is required of
citizens by classic democratic theory, which assumes that an informed and
attentive public is necessary for democracy to work effectively. The problem
is that democracy seems to be working pretty well, despite the "hands
off" approach of most of its citizens. Lau and Redlawsk (1997) estimate
that in recent U.S. presidential elections, about 75 percent of the voting
public (which admittedly is barely half of the eligible electorate) voted
"correctly," by which they mean "in accordance with what their fully informed
preferences would be." And if we look not at individual opinions
but at "aggregate" public opinion, that opinion appears far more stable
Richard R. Lau is Professor of Political Science, Rutgers University, 89 George St., New
Brunswick, NJ 08903 (ricklau@rci.rutgers.edu). David P. Redlawsk is Assistant Professor
of Political Science, University of Iowa, Iowa City, IA 52246 (david-redlawsk@
uiowa.edu).
An earlier version of this article won the Alfred F. Freedman Award for the best paper
presented at the 21st annual meeting of the International Society of Political Psychology,
Crowne Plaza Hotel, Montreal, Canada, July 12-15,1998. This manuscript was completed
while the first author was a fellow at the Center for the Study of Democratic Politics
at Princeton University.
'This evidence is reviewed in Chapter 2 of Delli Carpini and Keeter (1996). Moreover,
they note that because surveys' samples are not completely representative, and those
who are not represented tend to have the least knowledge, these numbers undoubtedly
overestimate the true figures.
American Journal of Political Science, Vol. 45, No. 4, October 2001, Pp. 951-971
?2001 by the Midwest Political Science Association
951
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952 RICHARD R. LAU AND DAVID P. REDLAWSK
and reasonable than the "minimalist" view of public
opinion would suggest (Page and Shapiro 1989).
These seemingly contradictory findings are typically
reconciled in one of two ways. Aggregate opinion can be
much more stable and apparently "rational" than individual
opinions, as long as error in individual opinions
is assumed to be random (see Miller 1986; Wittman
1989). Even large proportions of random error "cancel
out" in the aggregate, resulting in fairly efficient "collective
choices." The benefits of aggregate decision making
disappear once nonrandom error is introduced, however
(Althaus 1998). Well-known biases in both what
gets reported in the press (e.g., Gans 1979; Patterson
1980) and how people selectively perceive political information
(Graber 1984; Kinder and Sears 1985) means
that a great deal of the error in individual opinions must
be nonrandom.
The second, and in our opinion, more compelling
way that widespread political ignorance can be reconciled
with the view that democracies work reasonably
well is by referring to the psychological literature on
"cognitive heuristics" (e.g., Kahneman, Slovic, and
Tversky 1982; Nisbett and Ross 1980). This literature is
predicated on the view of humans as "limited information
processors" or "cognitive misers" (Fiske and Taylor
1991; Lau and Sears 1986; Simon 1957, 1985) who have
become quite adept at applying a variety of information
"shortcuts" to make reasonable decisions with minimal
cognitive effort in all aspects of their lives. Indeed, one of
the reasons this line of argument is so compelling is that
it explains the low levels of political information to begin
with: it is not just in politics that people are faced with
making decisions with far less than full information, and
it is only reasonable to assume that people will apply to
politics the same information shortcuts they have
learned to use throughout life (see also Downs 1957).
This line of argument presumes two essential points.
The first is that just about everyone can (and does) employ
cognitive shortcuts in thinking about politics-that
is, heuristic use is not limited to political experts, say, or
any other nonrepresentative sample of the public-just
as everyone must at times rely upon cognitive heuristics
to comprehend nonpolitical aspects of their lives. The
second point is that heuristic use at least partially compensates
for a lack of knowledge about and attention to
politics, so that citizens who are largely unaware of
events in Washington nonetheless can make reasonably
accurate political judgments. This view is so pervasive
now in political science that we could probably refer to it
as the new conventional wisdom.
As Bartels (1996) warns, however, it is far easier to assume
that information shortcuts allow uninformed voters
to act as if they were fully informed, than to demonstrate
that in fact they do (see also Kuklinski and Quirk 2000, for
a recent critique of this literature). Indeed, it is far easier
to assume that voters use cognitive heuristics in the first
place than to carefully define and actually demonstrate
their use. In some real sense, "low information rationality"
(Popkin 1991) has become a catch-all term, a verbal solution
to tricky analytic problems that is consistent with certain
stylized facts about the electorate, a verbal solution
which allows researchers to move on to other problems
they find more tractable (see also Sniderman 1993).
Bartels' (1996) recent demonstration of very real and politically
consequential effects of information per se on the
political preferences of otherwise similar individuals illustrates
the dangers of merely assuming that cognitive
shortcuts somehow overcome most of the problems of
cognitive limitations and political ignorance. Bartels'
findings should also remind us of a possible liability of
cognitive heuristics, one emphasized much more by psychologists
than by political scientists: heuristics can sometimes
introduce serious bias, along with cognitive efficiency,
into decision making.
Believing that information matters is not inconsistent
with believing that cognitive heuristics also matter,
however. While we should not simply assume that cognitive
heuristics are used (or are used effectively) by everyone,
they may nonetheless be an important part of the
decision-making processes of most voters. Heuristics
may even improve the decision-making capabilities of
some voters in some situations but hinder the capabilities
of others. The trick is not assuming or guessing, but
providing hard evidence. The proof, as they say, is in the
pudding.
The remainder of this article is divided in four sections.
The first will carefully define five cognitive heuristics
that are widely used by voters during an election. By
"heuristics," we mean problem-solving strategies (often
employed automatically or unconsciously) which serve
to "keep the information processing demands of the task
within bounds" (Abelson and Levi 1985, 255). The reader
should not expect any surprising "discoveries" here, for
none of these heuristics will be new to students of voting
behavior. Rather, discussion will focus on the extent to
which various familiar influences on the vote decision act
as heuristics, as cognitive shortcuts, the ways they provide
cognitive "savings," and how their use might result
in biased decision making.
Then we will present a relatively new research technique,
a "dynamic process-tracing methodology," that is
ideally suited for studying information processing and
decision making during an election. Next, a series of experiments
that we have conducted using this technique
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HEURISTICS AND POLITICAL DECISION MAKING 953
will be briefly described. Data from several of these experiments
will then be used to address two major empirical
questions: (1) What are the individual and contextual
determinants of heuristic use? and (2) Does the use of
heuristics affect (without prejudging whether it improves
or hinders) the quality of political decision making? Our
own expectations are expressed in the guise of formal hypotheses.
The final section of the article will summarize
what we have learned, try to place it in the context of related
work within political science and psychology, and
set out a research agenda for the future.
Five Common Cognitive Heuristics
Employed by Voters
Political scientists have considered a number of different
heuristics that citizens can employ to help make sense of
politics (Brady and Sniderman 1985; Hamill, Lodge, and
Blake 1985; Iyengar 1990; Jervis 1986; Lodge and Hamill
1986; Lupia 1994; Ottati 1990; Ottati, Fishbein, and
Middlestadt 1988; Scholz 1998; Sniderman, Brody, and
Tetlock 1991; Sniderman et al. 1986). We have grouped
these into five major categories. The first and perhaps
most important political heuristic is relying on a
candidate's party affiliation (Lodge and Hamill 1986;
Rahn 1993); a closely related heuristic is relying on a
candidate's ideology for cognitive savings (Conover and
Feldman 1986, 1989; Hamill, Lodge, and Blake 1985;
Sniderman et al. 1986). Party and ideological stereotypes
or schemata are among the richest and most widely
shared in American politics. If the salient characteristics
of a particular politician are consistent with or representative
of the prototypic Republican, say, then voters may
readily infer that she is for a strong defense, low taxes,
against government intervention in the economy, against
abortion, and so on; and will probably have a readilyavailable
affective response (what Fiske 1986, calls a
schema-based affective response) to the party label. Relying
on stereotypes or schemata provide an obvious cognitive
saving, to the extent that particular attributes (e.g.,
issue stands) are assumed "by default" rather than
learned individually in each specific instance. They can
also lead to obvious biases or errors, most dramatically
when a particular candidate is mistakenly categorized as
liberal when he is really moderate, say, but more subtly
(and probably more frequently) when a general categorization
is more or less correct but the presumed default
values are not true in all instances (e.g., a pro-choice Republican
like former Governor Whitman of New Jersey).
Although these two heuristics are quite similar, party
cues are somewhat simpler to grasp, and noticeably more
prevalent on the American political scene. For theoretical
reasons it will be convenient to treat them as distinct.2
Endorsements are another type of political information
that has obvious heuristic value. In contrast to carefully
considering each candidate's stands on all policies
that affect women in a particular election, say, a voter
could instead simply learn a relevant interest group's endorsement
(like NOW) as a summary of all of the difficult
candidate- and issue-specific information processing.
In essence, voters who rely on endorsements defer
the tough cognitive effort to trusted others. All that is
necessary is to learn the candidate endorsed by a group,
and one's own attitude toward the endorsing group, and
an obvious and cognitively-efficient inference can be
made (see Brady and Sniderman 1985; Sniderman,
Brody, and Tetlock 1991). The more candidates in an
election, and the larger the number of issues that should
be considered, the greater the cognitive savings. Potential
biases or errors in influence are introduced when the reason
for the endorsement is different from what the voter
expects, or when the actual candidate endorsed is unclear.
Although we have no examples of them in our experiments,
exactly the same cognitively efficiency is
gained when voters rely on the endorsements or recommendations
of respected individuals like former party
leaders, prominent politicians or political commentators,
or the editorial boards of trusted newspapers (see Carmines
and Kuklinski 1990; Mondak 1993; Sniderman et
al. 1986; Sniderman, Brody, and Tetlock 1991).3
Although it is typical to derogate political polls as
merely "horse race" information, poll results provide another
very important type of cognitive savings. Here the
heuristic cues are coming from the electorate as a whole
2We may be bucking the current tide in political science by employing
the "schema" term. We agree with critics who claim the
term has been used far too energetically and uncritically by political
scientists, and that the older terms of "attitudes" or "stereotypes"
could be substituted into much of the published work on
political schemata with little loss of meaning (Kuklinski, Luskin,
and Bolland 1991). If there are any areas in which this criticism
does not hold true, however, it is in treating party and ideology as
cognitive schemata. Researchers in these domains have carefully
documented the memory, processing, and heuristic value of these
two concepts (Conover and Feldman 1984,1986,1989; Hamill and
Lodge 1986; Hamill, Lodge, and Blake 1985; Lau 1986,1989; Lodge
and Hamill 1986), and we feel on safe ground by utilizing the
"schema" concept here.
3The term "endorsement" implies more formality than need be the
case. A voter might easily infer that a particular candidate supports
and is supported by a particular individual or social group by observing
the individual with the candidate, or seeing many group
members wildly cheering the candidate at a rally. The possibilities
of mistaken inferences are greater with such "informal" endorsements,
of course.
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954 RICHARD R. LAU AND DAVID P. REDLAWSK
rather than a particular subsample of the electorate, and
as such provide less specific information. But the information
that is provided can produce tremendous reductions
in cognitive efforts. Polls provide "viability" information,
and particularly early in the primary season
when there are typically many candidates competing for
a nomination, polls can help the voter eliminate several
alternatives from consideration. Reducing the choice set
from four candidates to two, say, immediately provides a
50 percent reduction in the amount of information that
must be processed. Seeing a candidate leading in the polls
provides a type of "consensus information" that could
motivate a voter who had previously rejected or ignored
a candidate to more closely consider that candidate
(McKelvey and Ordeshook 1985; Mutz 1992). Errors can
occur, however, if one candidate is ahead in the polls, and
a brief consideration of this candidate proves him to be
"satisfactory" (Simon 1957). In such cases voters might
be willing to support this candidate and refrain from further
political information processing, thus never actually
locating the "best" candidate for them.
The final political heuristic to be considered here is
possibly the most important (or at least most frequently
employed): candidate appearance. This heuristic is so important
because it is not restricted to the political realm
but is used in all aspects of our social lives. Visual images
are so pervasive in the social world that researchers rarely
consider their heuristic value. A single picture or image
of a candidate provides a tremendous amount of information
about that candidate, including gender, race, and
age, and often general "likableness," which immediately
brings many social stereotypes into play (Riggle et al.
1992).4 Visual images can also trigger emotions, which
can have great impact on candidate evaluation (Marcus
1988; Marcus and MacKuen 1993). People who know absolutely
nothing about politics nonetheless know a great
deal about other people and make social judgments of all
types using these social stereotypes with great cognitive
efficiency (Rosenberg, Kahn, and Tran 1991 ). Moreover,
most people have schemas or stereotypes for political
leaders (Miller, Wattenberg, and Malanchuk 1986), just
as they do for the political parties, and thus Kahneman
and Tversky's (1972) representativeness heuristic can
easily come into play. Of course one can legitimately
question the appropriateness or reliability of making
vote decisions on the basis of such "person" judgments,
and when certain images become disproportionately
4The psychology literature often treats these individual characteristics
as distinct heuristics or stereotypes influencing person judgments.
Because in practice these are all based on a person's appearance,
however, we will combine them into a single heuristic.
available (e.g., Bush getting sick in Japan, Dukakis riding
around in a tank), even otherwise reliable person judgments
could be mistaken.
Hypotheses
The growing conventional wisdom within political science
suggests that cognitive heuristics are used more or
less effectively by virtually everyone to help them "tame
the tide" (Graber 1984) of political information. Three
primary hypotheses test this conventional wisdom and
shape the analyses to follow. To begin with, and consistent
with the conventional view, we expect most voters to
employ at least some of the political heuristics identified
above in trying to make sense of a political campaign and
decide how to vote. Cognitive heuristics are made necessary
by severe limitations in human information processing.
This "prediction" seems so noncontroversial that we
will not unduly glorify it by calling it a hypothesis. We
will, however, be presenting a new method for determining
or "observing" heuristic use, and we will examine our
new measure in light of this baseline prediction.
Just because everyone uses some cognitive heuristics
does not mean that everyone uses all of them, or uses all
of them equally effectively. We will examine a variety of
individual difference factors as predictors of heuristic
use, the most theoretically interesting of which is political
sophistication or expertise. Sniderman, Brody, and
Tetlock (1991, 24-25; see also Brady and Sniderman
1985) clearly predict an interaction between political sophistication
and the use of a "likability" heuristic (similar
to our endorsement heuristic), on the one hand, and
the use of abstract ideology (part of our political schemata
heuristic), on the other. According to Sniderman,
Brody, and Tetlock, use of these particular heuristics is
limited to the more sophisticated portion of the public.
Other common heuristics (viability and certainly candidate
appearance) are less likely to be related to political
sophistication, however, given the pervasiveness of
"horserace" information during major elections and the
importance of various person perception mechanisms
in all aspects of our lives. Thus our first hypothesis states
that virtually all voters employ some common political
heuristics during political campaigns. Consequently, individual
difference factors should not be strongly related
to their use, with the exception of political sophistication.
Sophistication should be related to the use of certain
cognitive heuristics in political decision making,
particularly the Ideological Schema heuristic and the
Endorsement heuristic.
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HEURISTICS AND POLITICAL DECISION MAKING 955
Situational or contextual factors should also influence
heuristic use. Because heuristics provide cognitive
efficiency, they should be relied upon more heavily in
more cognitively complex situations and/or for decisions
that involve more difficult choices. Bodenhausen and
Wyer (1985), for example, find that stereotypes (similar
to our two political schema heuristics) are more likely to
be employed in complex judgment tasks (see also
Bodenhausen and Lichtenstein 1987), and Abelson and
Levi provide numerous examples of "informational biases
that serve a simplifying function ... [being] amplified
under overload conditions" (1985, 287). When a choice is
relatively easy, on the other hand, there is less need to use
cognitive shortcuts. Hence our second hypothesis suggests
the more complex the information environment,
and the more difficult the choice, the more voters should
rely on political heuristics, all else equal.
Most importantly, we hypothesize that the use of
cognitive heuristics generally will be associated with
higher quality decisions. Our reasoning is simple: if heuristics
did not "work," at least most of the time, they
would not be developed and utilized. Somewhat paradoxically,
however, we expect heuristic use to be most efficacious
for political experts. This is paradoxical because
if heuristics serve to compensate of a lack of knowledge,
they should be less necessary for the politically sophisticated.
But as Sniderman, Brody, and Tetlock put it, the
"comparative advantage [of experts] is not that they have
a stupendous amount of knowledge, but that they know
how to get the most out of the knowledge they do possess"
(1991, 24). In other words, not only will experts be
more likely to employ certain cognitive heuristics, but
they should also be more likely to employ them appropriately.
Thus our third hypothesis suggests that the use of
cognitive heuristics will interact with political sophistication
to predict higher quality decisions. In general, the
decision making of relative experts will benefit most
from political heuristic use.
Method
We have developed a new technique for studying political
information processing, which we call a dynamic processing
tracing methodology (see Lau 1995; Lau and
Redlawsk 1997, in press; Redlawsk 2001 a). Our technique
is a revision of the classic "information board" developed
by behavioral decision theorists for studying decision
making (see Caroll and Johnson 1990, for an overview).
The standard information board presents decision makers
with an m by ni matrix, where the columns of the matrix
are headed by the different alternatives (e.g., candidates)
and the rows of the matrix are labeled with different
attributes (e.g., issue stands, past experience, and so
forth). None of the specific information is actually visible,
however, and decision makers must actively choose
what information they want to learn by clicking a box on
a computer screen. The researcher can record and analyze
what information was accessed, the order in which it
was accessed, how long it was studied, and so on. The basic
premise of process tracing studies is that it is best to
study decision making while the decision is being made. A
growing literature in psychology, marketing, and the interdisciplinary
field of behavioral decision theory employs
information boards as a basic research tool.5
While the standard decision board is a reasonable
model for studying certain types of decision making, it is
a poor analog to the vote decision for a number of important
reasons. With a decision board the decision
maker can access any information any time he or she
wants, while campaigns have a dynamic quality about
them such that information easily available today might
be harder to find tomorrow and almost completely gone
by the following day. All information on a standard information
board is equally easy to access, while in a political
campaign certain types of information (e.g.,
hoopla and horse race) are much easier to find than others
(e.g., detailed issue stands). Decision makers must actively
choose to learn everything they find out about the
alternatives with a standard information board, but
much information during political campaigns (e.g., political
commercials) comes to us without any active effort
by the decision maker to learn that information. And
most importantly, decision making with an information
board is far too "manageable," too controllable, too easy;
while during a typical high level political campaign (e.g.,
presidential elections and many statewide races in the
U.S.), voters are overwhelmed by far more information
than they can possibly process. In many ways the static
information board represents an "ideal world" for decision
making that can be contrasted to voting in an actual
political campaign.
Our dynamic process-tracing methodology retains
the most essential features of the standard information
board while making it a better analog of an actual political
campaign. Our guiding principle was to devise a technique
that would mimic crucial aspects of an actual election
campaign while still providing a detailed record of
5For summaries of this literature, see Abelson and Levi 1985;
Dawes 1988; Ford et al. 1989; Jacoby et al. 1987; Payne, Bettman,
and Johnson 1992, 1993. For applications of information boards to
political decision making by other researcher teams, see Herstein
1981; Mintz et al. 1997; and Riggle and Johnson 1996.
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956 RICHARD R. LAU AND DAVID P. REDLAWSK
the search process employed by voters. If a standard information
board is artificial because it is static and therefore
too "manageable," we overwhelm subjects with
information. If the standard information board is unrealistic
by making all information available whenever a
subject wants it, we mimic the ongoing flow of information
during a campaign, where information available today
might be much harder to find tomorrow. If the standard
information board is artificial because all different
types of information are equally available, we model in a
realistic way the relative ease or difficulty of finding different
types of information during a campaign. And if a
standard information board only allows for information
that is actively accessed by the decision makers, we provide
our decision makers with a good deal of relevant information
"free of charge," without any active decision
on their part to learn that information.
We accomplished these goals by designing a radically
revised information board in which the information
about the candidates scrolls down a computer screen
rather than being in a fixed location. There are only a
limited number of attribute labels (six) visible on the
computer screen-and thus available for access-at any
given time. Most of these labels include a candidate's
name and the particular information about that candidate
that would be revealed if this label were "accessed"
(e.g., "Martin's political experience;" "Walker's stand on
defense spending"). The rate of scrolling is such that
most people can read approximately two labels before
the positions change. Subjects can "access" (i.e., read) the
information behind the label by clicking a mouse. Thus
this methodology combines the printed nature of information
presentation in newspapers with the relatively
uncontrollable order of information availability of electronic
media. The scrolling continues while subjects process
the detailed information they have accessed, so that
typically there is a completely new screen when subjects
return to the scrolling-thus mimicking the dynamic,
ongoing nature to the political campaign.
The scrolling format of the information presentation
achieves two of our goals, by making only a small subset
of the information available at any one time, and by
making the entire decision-making task much less "manageable."
We also wanted to make some types of information
"harder" to get than others and accomplished this by
varying the probabilities that specific types of information
would appear on the screen.6 Finally, at periodic intervals
the computer screen is taken over by a twenty-second
political advertisement for one of the candidates in
the campaign. Voters can carefully watch these commercials
or avert their eyes while they are on the screen, but
they cannot gather any other information relevant to the
campaign while the commercial is on.7
Subjects
We have run four experiments with the dynamic processtracing
methodology described above, one of which also
included a standard static information board. Three of
the experiments used paid volunteers (most subjects
were donating their $20 payment to a voluntary organization
to which they belonged) and one used unpaid volunteers.
All subjects had to be eligible voters (American
citizens above the age of 18), with the only other restriction
that no one currently attending college could participate
in the experiment.
The 657 subjects who participated in the four experiments
are not meant to be a representative sample,
but they do comprise a broad pool of adult citizens. They
ranged in age from 18 to 84 with a mean of 45. Fifty-four
percent were female, and 16 percent were nonwhite; 28
percent had at most a high school degree, while 47 percent
of the subjects were college graduates. Fifty-nine
percent of the sample were currently employed, 5 percent
unemployed, 23 percent retired, and 13 percent homemakers.
In terms of religious preference, 35 percent were
Catholics, 17 percent Jewish, 25 percent Protestants, and
11 percent professed some "other" religious preference.
When it came to politics, 38 percent of the sample identified
with the Democratic Party, and 27 percent identified
with the Republican Party.
Procedure
The basic experimental paradigm has subjects "experience"
and "vote in" a primary election involving multiple
candidates in each party, and a subsequent general election
involving one candidate from each party. We created
7Our typical experiment included ten twenty-second commercials
during a twenty-two- minute primary campaign, and six twentysecond
commercials during a twelve-minute general election campaign.
Thus information from political commercials monopolized
17-22 percent of the total time during a campaign, with the remainder
available for voters to access the information they wanted
to learn (within the constraints of what was available, of course).
6To make these probabilities realistic, we first conducted an elaborate
study of the prevalence of different types of information in
newspapers during the 1988 presidential campaign (Lau 1992) and
modeled the probabilities after the actual prevalence of those types
of information during the 1988 campaign.
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HEURISTICS AND POLITICAL DECISION MAKING 957
a scenario for a mock presidential election involving 2-4
Democratic and 2-4 Republican candidates. Subjects
"registered" to vote in either the Democratic or Republican
primary, learned as much about any of the candidates
as they wanted (or could, given the time and information
available) during the primary campaign, "voted"
for one of the candidates from their party, evaluated all
candidates in the primary on a 100-point feeling thermometer,
answered a few questions about the difficulty
of the decision they had just made, learned which two
candidates will be running in the fall campaign, gathered
as much additional information about these two candidates
as they wanted (or could) during the "general election"
campaign, voted for one of them, evaluated the remaining
candidates again on feeling thermometers,
attributed a few issue stands to them, and answered the
questions about the difficulty of the general election
choice. Subjects also received an unexpected memory
task where they were asked to recall as much as they
could remember about the two candidates running in the
general election campaign.
Before the campaigns began, subjects completed a
fairly standard political attitudes questionnaire designed
to measure their political preferences (crucial for determining
which candidates they "should" support) and
their general level of political sophistication. Figure 1 of
Lau and Redlawsk (1997, 588) summarizes the typical
experimental procedure, which on average lasted about
one hour and forty-five minutes.
The candidates were all designed to be very realistic
(e.g., they were dispersed along the ideological spectrum
appropriate for their party, they were politically experienced,
they were all at least 45 years old, etc.), although
we were careful not to make any of the candidates appear
too much like some actual individual. Creating mock
candidates provides crucial control over differences between
subjects in prior knowledge of actual politicians.
No one had any knowledge of any candidate before the
mock campaign began, other than what might be inferred
from, say, party affiliation.
Results
Direct Measures of Heuristic Use
Few studies of cognitive heuristics, whether in the political
or any other realm, have direct measures of the use of
the hypothesized heuristic. More typically, the availability
of some cue is manipulated in a simple experiment,
and heuristic use is inferred if hypothesized differences
in some dependent variable occur (e.g., Carmines and
Kuklinski 1990; Iyengar 1990; Mondak 1993; Quattrone
and Tversky 1988). Alternatively, a significant regression
weight in some model of impression formation or attitude
change will be taken as evidence of heuristic processing
(e.g., Brady and Sniderman 1985; Conover and
Feldman 1986, 1989; Iyengar 1990; Lau 1986, 1989;
Sniderman, Brody, and Tetlock 1991).
With process-tracing methodologies, however, hypothesized
information-processing strategies can be directly
observed and measured. We contend that if a decision
maker is employing a particular heuristic, then in
general information relevant to that heuristic should be
sought out early and often. For example, if endorsements
are to be of maximum use to a decision maker, they
ought to be accessed as soon as they become available,
and many of them ought to be examined. Particular
types of information were determined a priori to be indicative
of the use of a given heuristic, and we measured
how early information within each category was accessed,
the proportion of all available items within that
category that were accessed, and the proportion of all accessed
items that fell into that particular category, separately
for information processing during the primary and
general election campaigns.8 We then formed summary
scales of the use of the different types of political heuristics
in the primary and general election campaigns by
standardizing and then averaging together the three measures,
after the priority measures were reversed so that
early access of items within a category was scored high.
We will have more to say about equating information
search with heuristic use below.
8 Candidates"'Party Affiliation,' "Basic Social/Political Philosophy,"
and their "Basic Economic Philosophy" were deemed relevant to
using a political schema heuristic; their pictures (e.g., "Picture of
Gerry Singer") were relevant to the candidate appearance heuristic.
The endorsements of any of fourteen interest groups were relevant
to the endorsement heuristic; finally, any poll result was relevant
to the viability heuristic. "Nonheuristic" information was
thus everything else available about the candidates, including specific
issue stands, background information, and personality descriptions.
What characterized this nonheuristic information was
that it was candidate-specific and less prone to generalization than
ideological or partisan labels.
Because the proportion of available items falling into the different
categories differed widely, and because the order in which
they appeared on the screen varied randomly, we could not simply
consider how early during a campaign a particular item was accessed.
Instead, the measure of early access was computed by noting
whether the first available item within a category was accessed,
the second accessed, and so on. This variable would be undefined
if no items within a category were accessed during a campaign. To
overcome this problem, in such instances we assigned a priority
score of one more than the highest nonmissing priority score observed
across subjects-in essence, assuming the subject would
have accessed the next available item within that category if the
campaign had lasted a little longer.
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958 RICHARD R. LAU AND DAVID P. REDLAWSK
TABLE I Measures of Political Heuristic Use
Mean % of All % Unique Information
% Using Accessed Info. from Category
Heuristic Coming from Ever Examined Scale
at All Category Mean Std.Dev. Reliability
Partisan Schema 98% 9.2% 83% 22% .63
Ideology Schema 93% 4.6% 63% 31% .77
Endorsement Heuristic 97% 10.4% 42% 23% .82
Viability Heuristic (Polls) 98% 12.1% 37% 22% .86
Candidate Appearance Heuristic 95% 6.7% 69% 29% .73
Note: The first column reports the percent of all subjects accessing an item from the appropriate category (at least twice, to control for accidental
accessing and "sampling"). The second column reports the percent of all accessed items that fell into a particular category, irrespective of how often
any particular bit of information is accessed. The third column reports the mean percent of all relevant unique items within a category that were accessed
at least once, while the fourth column reports the standard deviation of this measure. This last measure does not "double count" items that were
accessed more than once, whereas data in the second column allows for such double counting. Table entries in the last column are Cronbach's alpha
from the scales built to measure heuristic use. Data are limited to subjects in the more realistic dynamic scrolling conditions of the experiments.
N varies between 550 and 555.
The first four columns of Table 1 present various indicators
of the extent to which voters in our experiments
employed the five political heuristics discussed above.
The first column shows the percent of subjects who examined
at least two items categorized a priori as indicating
heuristic use. This is a minimal standard of "use." The
second column is perhaps the best indicator of the pervasiveness
of heuristic use during our mock election campaigns,
because it shows the average proportion of items
actually selected during the mock campaigns that were
examples of the different types of political heuristics. An
average of 43 percent of the items selected came from
one of the five categories of political heuristics. It is important
to keep these numbers in perspective, however.
One of the reasons the political heuristics we have identified
here are so useful is that information relevant to
them is so widely available-an availability modeled by
the stochastic algorithm of our computer program. If all
subjects had chosen information randomly, the data in
the second column of Table 1 would not be very different.
Nonetheless our baseline prediction is clearly supported:
virtually all voters employ cognitive heuristics at
least some of the time in making their vote decisions.
More indicative of how important the different heuristics
were to individual subjects is data in the next two
columns, which reports the mean percent and variability
of the unique information considered within each category.
On average subjects examined 42 percent of all of
the group endorsements, for example, and 37 percent of
the poll results that concerned candidates from their
party in the primary and the two candidates during the
general election. More important analytically, the variance
of all five of these measures includes the full range
of the potential scale, from not accessing any information
relevant to a heuristic, to finding and accessing all of
the relevant information. The internal consistency
(Cronbach's alpha) of the summary scales of each type of
heuristic use is reported in the last column of Table 1.
The scale reliabilities vary between .63 and .86, very respectable
numbers for relatively short scales.
Political Sophistication and Heuristic Use
It would certainly appear from the data reported in Table
1 that most voters in our experiments utilized the five political
heuristics at least some time during their decisionmaking
task. But a more complete investigation is warranted.
In particular, Hypothesis 1 suggests that more
politically sophisticated voters will be more likely to
employ an Ideological Schema and the Endorsement
Heuristic. The top panel of Table 2 shows the results of an
analysis where the summary measures of use of each political
heuristic are regressed on a comprehensive measure
of political sophistication comprised of separate
indicators of Political Knowledge, Political Behavior, Political
Interest, Political Discussion, and Media Use (see
Lau and Erber 1985); plus various demographic variables
and standard political beliefs as controls. The bottom half
of the table reports a similar analysis, keeping the different
components of sophistication distinct.
As predicted by Hypothesis 1, political experts are
more likely to use an Ideology Schema (p < .05, onetailed)
and the Endorsement Heuristic (p < .001). In the
former case it is Political Knowledge and Following PoliThis
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HEURISTICS AND POLITICAL DECISION MAKING 959
TABLE 2 Effect of Political Sophistication on Use of Political Heuristics
Candidate
Party Ideology Endorsement Viability Appearance
Schema Schema Heuristic Heuristic Heuristic
Variable B SE B B SE B B SE B B SE B B SEB
Analysis 1
Overall Measure -5.31 (3.45) 9.87@ (5.34) 24.32*** (5.59) 4.30 (5.52) -10.83* (5.40)
of Sophistication
Analysis 2
Knowledge -1.38 (3.26) 17.02*** (5.04) 14.38** (5.32) -2.97 (5.25) -6.35 (5.16)
Behavior .94 (2.25) -.06 (3.49) 2.64 (3.68) -2.56 (3.63) -5.44 (3.57)
Discussion -2.96 (2.44) -2.39 (3.77) -.48 (3.98) -4.07 (3.93) -1.52 (3.86)
Interest -3.94 (2.61) -3.40 (4.04) 949* (4.27) 2.46 (4.21) .43 (4.14)
Media Use -1.19 (3.08) 10.56** (4.76) -.61 (5.03) 12.62** (4.96) -.88 (4.87)
@p <.05 (one-tailed) *p < .05 **p < .01 ***p <.001
Note: Table entries are unstandardized regression weights (with standard errors in parentheses), from two separate sets of analyses, the first where
the summary measures of heuristic use are regressed on a comprehensive measure of political sophistication, the second where the same dependent
variables are regressed on separate indicators of the constituent parts of political sophistication. All regressions also include controls for gender, race,
age, education, family income, religiosity, and strength of partisanship and ideology. All variables have a 1-point range. Analyses are limited to the more
realistic "dynamic scrolling" presentation format. N = 482.
tics in the Media which are particularly important, while
in the latter case it is Political Knowledge and self-professed
Political Interest.9 Although we could find no prior
literature suggesting this might be the case (and thus not
formally specified in Hypothesis 1), it follows logically
that if almost everyone uses political heuristics, but certain
political heuristics are more likely to be employed by
experts, then other political heuristics may be more the
province of those low in political sophistication. Our data
suggest two decent possibilities, the Candidate Appearance
Heuristic and the Party Heuristic (although in the
latter case the results are not quite statistically significant).
All told, our data provide strong support for Hypothesis 1.
We will control for the effects of political sophistication in
the remainder of the analyses.
Situational Factors Determining
Political Heuristics Use
The second hypothesis holds that voters will be more
likely to employ cognitive heuristics in more difficult
choice situations-that is, in situations with greater cognitive
demands. The strongest test of this hypothesis
comes from an experiment that varied the basic presen-
9 There is a scattering of significant effects among the control variables
in these analyses, most strikingly a strong negative effects of
age on use of all five of the political heuristics. This effect is probably
an artifact of the timing of our experiments (older people in
the 1990s being generally less familiar with personal computers)
rather than a true difference in political heuristics use.
tation format: in one condition the experiment utilized
the classic static information board (which can be viewed
as an ideal world for decision making), while the second
condition used the much more challenging (and realistic)
dynamic scrolling procedure described above. Our
hypothesis clearly predicts greater use of cognitive heuristics
with the dynamic rather than static procedure.'0
To test this hypothesis we conducted an multivariate
analysis of variance (MANOVA) in which the Static-Dynamic
presentation format and Political Sophistication
(dichotomized at its median) were the independent variables,
and the five heuristic-use variables, summed across
the primary and general election campaigns, were the dependent
variables. The main effects of both the StaticDynamic
manipulation-multivariate F(5,158) = 127.31,
p < .001-and Political Sophistication-multivariate
F(5, 158) = 2.3 1, p < .05-were statistically significant. As
can be seen in the top half of Figure 1, all five of the political
heuristics were much more likely to be employed
when information was presented via the more realistic,
and more cognitively difficult, dynamic scrolling format,
'0After subjects voted and evaluated the candidates in each election,
they were asked how difficult the choice had been for them to
make. These question can be used as a manipulation check to determine
if subjects perceived the static presentation format to be
easier than the dynamic, scrolling format. Indeed they did: averaged
across the two campaigns and all of our experiments, the
choice was perceived as significantly more difficult in the dynamic,
scrolling condition (M = 2.9) than the static condition (M = 2.3),
t(609) = 3.78, p < .001
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960 RICHARD R. LAU AND DAVID P. REDLAWSK
FIGURE 1 Effect of Dynamic/Static Manipulation and Political
Sophistication on Heuristic Use
DynamldStatic Manipulation
80
70
60
50
40
30
20
10
0
Party Ideology Endorsement Viability Appearance
Static * Dynamic
Political Sophistication
80
70
60
50
40
30.
20
.10
0
Party Ideology Endorsement Viability Appearance
Novice U Expert
compared to the ideal world of a static information board.
All five of the univariate F tests were also highly significant.
In contrast, differences in heuristic use between
those high and low in political sophistication (displayed
in the bottom half of Figure 1) were quite modest in magnitude
and, as already seen in Table 2, mixed in direction.
Only the Viability Heuristic produced a significant univariate
F tests for sophistication." I
A second operationalization of task complexity is the
number of alternatives in the choice set. Several of our
"The general election campaign of that same experiment included,
along with the presentation format, two further manipulaexperiments
randomly manipulated the number of candidates
running in the primary of the party in which the
subject "registered" to vote. A choice is relatively simple
with only two candidates, but much more complex with
tions of the difficulty of the choice. The first manipulation involved
the ideological distinctiveness of the two competing candidates,
the second whether the candidate the voter supported in his
or her party's primary had "won" the nomination and was running
again in the general election campaign. The ideological distinctiveness
manipulation had a significant effect on heuristic use,
F(5,147) = 2.54, p < .03, albeit one which was much smaller than
the effect of the static/dynamic manipulation. The prior rejection
manipulation had no effect on heuristic use, however. The details
of these analyses are available from the authors upon request.
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HEURISTICS AND POLITICAL DECISION MAKING 961
FIaURE 2 Effect of Number of Candidates Manipulation
on Heuristic Use
70-
60-
50
40-
30-
20-
10
0Party'
Ideology Endors'ement Viability Appearance
Two Candidates Four Candidates
four candidates.'2 We again conducted a MANOVA with
use of the five political heuristics during the primary
election campaign as the dependent variables and Number
of Candidates in the subject's party and Political Sophistication
as the independent variables. The effect of
Political Sophistication is essentially the same here as in
Figure 1, albeit slightly weaker statistically. Of more immediate
interest is the Number of Candidates manipulation,
which was statistically significant, multivariate
F(5,356) = 4.71, p < .001. An examination of the group
means of the different dependent variables, however,
shown in Figure 2, reflects a fairly complicated pattern of
results. Subjects were slightly (and nonsignificantly)
more likely to employ the Ideology and Candidate Appearance
heuristics in the four candidate condition than
the two candidate condition, but significantly more likely
to employ the Endorsement and Viability heuristics in
the two candidate condition. Clearly, something more
than the need for cognitive efficiency is determining
these results. Notice that there were only trivial differences
in the use of the Party heuristic across conditions
in this campaign-but of course party is of little use in
'2The total number of candidates in the primary campaign was
held constant at six, such that if there were two candidates running
in the Democratic primary, there were four candidates running in
the Republican primary, and vice versa. The manipulation check
confirmed that subjects perceived the four-candidate primary to
pose a more difficult choice than the two-candidate primary,
t(458) = 2.53, p < .02.
distinguishing between candidates running in a primary
election, at least after candidates belonging to the different
parties are sorted out.
Together, these results are more complicated than
Hypotheses 2 predicts. While voters of all stripes employ
cognitive heuristics, they do not all equally appreciate the
difficulty of the choice situation they face and revise their
information-processing strategies to compensate for that
difficulty. It is important to note that sophistication does
not help explain any of these conflicting findings. More
generally, the data on heuristic use suggest that cognitive
heuristics may not be a panacea for the broad lack of information
and interest in politics displayed by the average
citizen they have been assumed to be. Heuristics may
not be used in a cognitively most efficient manner by everyone,
even the most politically sophisticated voters.
Is "Information Acquisition" the Same
Thing as "Heuristic Use"?
We have argued that directly observing and measuring
heuristic use is superior to indirectly inferring heuristic
processing from some simple experimental manipulation
or significant regression weight. Still one could ask
with our operationalizations of heuristic use, is gathering
relevant information the same thing as using a certain
heuristic? At one level the answer is obvious: no one can
"use" a heuristic if they do not know it is applicable, e.g.,
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962 RICHARD R. LAU AND DAVID P. REDLAWSK
TABLE 3 Further Validity Evidence for Measures of Political Heuristics
Party Ideology Endorsement
Schema Schema Heuristic
Memory for Relevant Items r = .25*** r = .02 r = .22***
Accuracy of Perception of Issue Stands NS r = .16** r = .17**
Accuracy of Inference Absent Actual Knowledge b = 11.44** b = 10.73** b = 4.62*
Substitutes for Information Search NS b = -1.32** b = -2.82***
in 4-Candidate Primary Condition
*p <.10 **p <.05 ***p< .01
Note: Data in the first two rows of the table are partial correlations between the measure of heuristic use and the relevant criteria,
controlling for Political Sophistication and Total Item Search. "Accuracy" in rows 2 and 3 is defined as agreement with experts'
ratings of the candidates' actual issue stands. Data in the third row reports the regression weight for the interaction between the
heuristic of interest and not actually accessing a candidate's issue stand, thus requiring inference. In the fourth row we report the
regression weight for the interaction between heuristic use and the 2- or 4-candidate manipulation, where the dependent variable
is the average number of issue stands accessed for in-party candidates. All regressions also controlled for Political Sophistication.
Because these various criteria were not available in every experiment, N is 285 in the first row, 110 in the second and third rows,
and 364 in the last row.
if they do not know the party affiliation of candidate(s).
But we are not employing simple dichotomous operationalizations
of heuristic use; frequency and time of information
acquisition are also part of our measures. And
even with simple information acquisition, how do we
know the information is actually being processed and
used in a heuristic manner?
The political science literature provides almost no
guidance on this issue, and the psychology literature is
little better. However, our experiments gathered a great
deal of information that can be used to "flesh out" just
what heuristic processing is (or ought to be), and to simultaneously
validate our measures of heuristic use. We
do not have the space to go into great detail here, but
Table 3 provides a sense of the type of evidence we have
gathered for three of our heuristics.13 To begin with, heuristic
use tends to be positively correlated with memory
13Although we would argue that poll results generally have a great
deal of heuristic value, particularly in campaigns with more than
two candidates, the manipulations in several of the experiments
required that it be possible for any of the candidates from the primaries
to win their party's primary and advance to the general
election campaign. To maintain plausibility across election campaigns,
it was therefore necessary for all candidates to have roughly
similar popular support during the primary campaign, as indicated
in polls. In practice, then, there was little heuristic value to
accessing poll results during our experiments, although of course
no subjects knew this going into the experiment. Hence we cannot
provide any validity evidence for the Viability Heuristic. Likewise
candidate appearance can very efficiently provide a great deal of
information to voters, although there is much less variance in the
"type" of people running for President than there is for lesser offices
(a narrowness mirrored by our experiments), reducing in
practice the heuristic value of the Appearance Heuristic for our experiments.
Other than memory, none of the criteria examined in
Table 3 were available for the Appearance Heuristic.
for relevant information. These positive correlations provide
evidence that relevant information is at least processed.
More telling for current purposes, however, would
be evidence that employing heuristics allow voters to
process information efficiently, to reduce information
processing demands in some domains. That is the key.
After asking subjects to remember as much as they
could about the two candidates in the general election
campaign in our last experiment, we asked them to place
the candidates on five different issue scales. Controlling
on general Political Sophistication, both the Ideology and
Endorsement heuristics-but not Party-are associated
with more accurate placement of the two candidates on
the issues in general. Even more telling (again controlling
on Political Sophistication), all three of these heuristics
were associated with more accurate placement of candidates
on issues in the absence of actually learning the candidates'
stand on the issues. Ideology and Endorsementsbut
again, not Party-also tend to substitute for accessing
detailed issue information in the more taxing four-candidate
primary condition, in that they were associated with
less accessing of specific issue stands per candidate. Together,
the data presented in Table 3 indicates that our
measures of political heuristics truly are associated with
heuristic processing of information. We know of no similar
evidence in the political science literature.
Effect of Political Heuristics on Correct Voting
The third hypothesis states that use of political heuristics
will be associated with higher quality decisions primarily
among political experts. Defining "higher quality" decisions
can be a very tricky matter. Fortunately, we can rely
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HEURISTICS AND POLITICAL DECISION MAKING 963
on the definitions presented earlier by Lau and Redlawsk
(1997). We developed two techniques for determining
whether subjects voted "correctly" in our experiments,
one determined by the subjects themselves after a very
thorough examination of all information available about
the competing candidates (including much information
the subjects had not actually seen when they made their
vote choice); the second technique a more normative,
objectively determined criteria. Because the subjective
measure is only available for the primary election from
two of the four experiments, but the normative measure
is available for all elections in all experiments, we rely on
the latter measure here.'4
Our normative measure of correct voting is based on
an approximation of how people could naively or intuitively
go about making the vote decision. From the questionnaire
filled out by subjects before the experiment began,
we know where subjects stand on the issues, what
groups they like, what party they identify with, and so on.
We also know, objectively, where the candidates stand on
the issues, what groups endorse which candidates, what
party a candidate belongs to, and how attractive the candidates'
appearance and personalities are.15 We determine
empirically what categories or types of information
are important in the decision calculus of each voter by
assuming that if a particular attribute (say, a candidate's
stand on crime) was only considered for a single candidate,
it was probably the product of simple curiosity, random
error, or "sampling" but then rejection of this type
of information, and therefore was not at all important in
the voter's decision calculus. If a particular attribute was
examined for two or more of the available candidates, on
the other hand, we assume this type of information was
an important part of the voter's decision calculus and is
therefore a relevant consideration about every candidate.
The favorableness of each individual attribute was
rescaled to range between -1 at its most unfavorable
(e.g., endorsement by a group the voter dislikes) to +1 at
its most favorable (e.g., complete agreement with a candidate
on an issue), and then a "normative naive" evaluation
of each candidate was computed by averaging together
the different considerations. This evaluation is
"naive" in that it is based on the voter's own political values
and preferences, and their own determination of
what specific information is important to them. But this
measure is "normative" in that it is also based on an objective,
externally-determined evaluation of the candidates,
and on the normative judgment that voters should
have considered the same (important) information
about all candidates in the choice set. A "correct" vote decision
is then defined as a vote for the candidate with the
highest "normative naive" evaluation. See the appendix
of Lau and Redlawsk (1997) for more details on the construction
of this measure.
There is one further complication. Although it is
clear how to determine the "correct" choice with such a
procedure, it is not so clear what to do about "incorrect"
choices.'6 Should they all be treated equally, or should
they somehow be scaled to reflect the egregiousness of
the error? It does not seem right to treat voting for the
worst possible candidate the same as voting for one that
is only slightly inferior to the "best" possible candidate.
We decided to employ a simple dichotomous "correct" or
"not correct" dependent variable, but to create a "difficulty
of choice set" independent variable to control for
these other considerations. This control variable was created
by computing the average difference between the
naive normative evaluation of the best candidate in the
choice set and the evaluation of each individual alternative
in the choice set. When the alternatives are all evaluated
very similarly, this average difference will be quite
small, and it should be relatively difficult to pick out the
best alternative. When the alternatives are evaluated quite
differently, on the other hand, the average difference
score will be much larger, and it should be relatively
easier to pick out the best alternative. Our measure of the
difficulty of the choice set is then the reciprocal of this
14Moreover the two measures, when they are both available, produce
very similar results; see Lau and Redlawsk ( 1997).
15 The "objective" stands of the candidates on the issues was determined
by the mean ratings of every issue stand by seven experts.
The attractiveness of the candidates' appearance and personalities
was determined objectively by the mean ratings of sixty pretest
subjects.
16One possibility is Payne, Bettman, and Johnson's (1993) "optimal
decision" measure. Their optimal choice formula equals the difference
between the evaluation of the chosen alternative minus the
evaluation of the worse alternative in the choice set, divided by the
difference between the evaluations of the best and worst alternatives,
or (Chosen - Worst)/(Best - Worst).
If the decision maker actually chooses the best alternative, this
ratio equals 1.0; if the decision maker chooses the worst alternative,
the ratio equals 0. The problem with this measure is that the
best and worst alternatives in any choice set are always equated, irrespective
of how difficult the choice was for the individual decision
maker. To illustrate this problem, if for simplicity we reduce
candidate evaluation to ideology, when a liberal is running against
a conservative it is fairly easy for most voters to determine which
candidate is better; but when two ideologically similar candidates
are opposing each other, the correct choice is much more difficult
for anyone to determine. Moreover, while a choice between a liberal
candidate and a conservative candidate is easy for liberal and
conservative voters to make, it is much more difficult from the
point of view of moderates. Furthermore, when there are only two
alternatives in the choice set, one is always the best choice and the
other is always the worst choice. Somehow both the difficulty of
the choice faced by a decision maker, and the "optimality" of the
decision given that choice set, must be taken into consideration.
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964 RICHARD R. LAU AND DAVID P. REDLAWSK
average difference score, so that the more difficult choice
sets have the highest scores on this control variable. This
variable should be negatively correlated with the probability
of a correct vote, all else equal.
We then specified logistic regression equations in
which the dichotomous correct vote dependent variable
was regressed on (1) the Difficulty of Choice Set control
variable just described; (2) experimental manipulations
of Task Complexity; (3) the comprehensive measure of
Political Sophistication described above; (4) a summary
measure of use of Political Heuristics,'7 dichotomized at
its median; and finally (5) interactions between the last
three factors. Because Hypothesis 3 argues that heuristic
use will aid decision making primarily among politically
sophisticated voters, we pay particular attention to the
interaction between political sophistication and heuristic
use on the probability of making a correct decision.
Our analysis considers the probability of a correct
vote in the primary election of the experiments which
manipulated the number of candidates in the choice set.
The results of the logistic regression are shown in Table 4.
As expected, subjects were much less likely to vote correctly
in the more difficult four candidate condition than
the two candidate condition (p < .001), and controlling
on this manipulation, somewhat less likely to vote correctly
when the choice set was more difficult (p < .07,
one-tailed). Neither political sophistication nor heuristic
use had a main effect in the analysis. But as predicted by
Hypothesis 3, there was a significant two-way interaction
between sophistication and heuristic use (p < .01). The
nature of this interaction is shown in Figure 3. Cognitive
heuristics are a great aid to the decision making of relatively
sophisticated voters, increasing the probability of
their making a correct decision by 20 percent. But this
advantage to the most sophisticated voters is almost exactly
balanced by a comparable disadvantage for relatively
unsophisticated voters, whose probability of making
a correct vote decreases by almost 21 percent when
they rely heavily upon cognitive heuristics. As Hypothesis
3 predicts, then, the decisions of more sophisticated voters
are often helped by employing cognitive heuristics,
but less sophisticated voters may actually end up making
lower quality decisions if they employ those same heuristics
(albeit, in a less efficient manner). Seen from another
perspective, political sophistication absent heuristic use
contributes little to better decision making. Only in combi"7This
summary measure combined our indicators of the Party
Schema, Ideology Schema, and Endorsement Heuristic. As discussed
in footnote 13 above, in practice there was little heuristic
value associated with learning poll results or candidates' appearance
in our experiments, and thus little reason they should be associated
with correct voting.
TABLE 4 Effect of Political Sophistication and Use
of Heuristics on Correct Voting
Variable B S.E.
Constant .40 .29# of Candidates Manipulation -2.04** .42
Difficulty of Choice -1.08 .71
Political Sophistication -.21 .31
Heuristic Use -.20 .38
Manip. x Sophist. .46 .37
Manip. x Heuristics .39 .60
Heuristics x Sophist. .92* .37
-2 * Log Likelihood 285.74
Model Chi-Square (7 df) 56.21**
Percent Correctly Classified 69.2%
N 254*p < .01 **p < .001
Note: Table entries are logistic regression coefficients.
nation with heuristic use does sophistication help improve
decision making. What political sophistication
brings a voter is knowledge of how the political world is
typically structured, and the ability to make clear inferences
from heuristic cues.18
Disadvantages of Heuristic Use
That very knowledge could work against sophisticated
voters if the world (i.e., a political campaign) is not
structured in the typical manner. One final manipulation
varied the stereotypic nature of the outparty candidate
(that is, the candidate from the party in which the subject
did not "register") running in the general election campaign
in one of our experiments. In the stereotypic condition
this candidate was a moderate slightly to the left
(if a Democrat) or right (if a Republican) of center. In
the nonstereotypic condition the outparty candidate
took a very liberal stand on some issues, a very conservative
stand on others, and a moderate stand on the remaining
issues. On average, the objective issue stands of
the stereotypic and nonstereotypic candidates were indistinguishable
(and their qualifications for the presidency
on other dimensions were quite comparable), but
the ideological range of views expressed by the nonstereotypic
candidate was much greater-so much
greater, in fact, that this candidate might very well take
18Space precludes a detailed report on correct voting in the general
election campaign experiments. Suffice it to say that the results
conceptually replicate those just presented from the primary election.
The crucial sophistication by heuristic use interaction is significant,
p < .05. Again, the complete results are available from the
authors upon request.
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HEURISTICS AND POLITICAL DECISION MAKING 965
FIGURE 3 Effect of Political Sophistication and Heuristic Use on
Correct Voting in Primary Election Campaign
0.9
Q)
o 0.8
2 0.7
0
wo0.6/0
0.5
06
LD 0.5
? 04/
0.3Low HighPolitical Sophistication
High Heuristic Use
Low Heuristic Use
several issue stands that a voter preferred to the stands of
the inparty candidate.19
Table 5 presents the results of an analysis in which
correct voting is regressed on the difficulty of choice control
variable, the nonstereotypic candidate manipulation,
political sophistication, use of a party heuristic, and interactions
between the last three factors. We focus on use
of the party heuristic because the nonstereotypic candidate
violated partisan stereotypes. The positive .72 interaction
between Heuristic Use and Sophistication suggests
that, as we have seen already, political heuristics are particularly
efficacious for politically sophisticated votersat
least when the candidates conform to the expected
norms of their parties. This interaction is not quite statistically
significant at conventional levels (p < .09, onetailed).20
As shown by the significant three-way interaction
between the experimental manipulation, political
sophistication, and heuristic use, however, this advantage
disappears when nonstereotypic candidates are running
190ne item available for access about every candidate was their
"Basic Social/Political Philosophy." For the stereotypic candidate
from each party, this item read " [Candidate's name] is usually considered
a moderate on most issues." For the two nonstereotypic
candidates, this item read "It is difficult to label [candidate's name]
as a traditional liberal or conservative."
20The two-way interaction between the Nonstereotypic Candidate
manipulation and Sophistication (which we did not predict) suggests
that among voters who rarely use political heuristics, politically
sophisticated voters are more likely than less sophisticated voters
to vote correctly when the outparty candidate is nonstereotypic.
in the campaign. Now sophisticated voters who employ
heuristics are noticeably less likely to vote correctly. As
Figure 4 illustrates, when the outparty candidate is stereotypic
(as is typically the case), using heuristics increases
the probability of a correct vote among sophisticated
voters from about .55 to .81. But when the outparty
candidate is nonstereotypic, using heuristics actually decreases
the probability of a correct vote from .77 to .58
TABLE 5 Heuristic Use in Inappropriate Situations
Variable B S.E.
Constant .41 .32Nonstereotypic Manipulation .29 .46
Political Sophistication -.43 .38
Difficulty of Choice .12 .72
Party Heuristic Use -.27 .43
Nonstereotypic x Heuristic .23 .65
Nonstereotypic x Sophist. 1.41* .57
Heuristic x Sophist. .72 .53
Nonstereotypic x Heuristic -2.39* .81
X Sophistication
-2 * Log Likelihood 224.95
Model Chi-Square (8 df) 12.75
Percent Correctly Classified 62.9%
N 178*p < .01
Note: Table entries are logistic regression coefficients. Dependent variable
is voting correctly.
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966 RICHARD R. LAU AND DAVID P. REDLAWSK
FIGURE 4 When Relying on Heuristics Hurts the Decision Making
of Politically Sophisticated Voters
High PoNcal Sophlstlntlon
0.9
> 0.8
0)
D 0.740 v*
0.6
0
p0.5
CU
0.40
0.3
Stereotypic Nonst&eotypic
Nature of Outparty Candidate
* Heuristic Use High
* Heuristic Use Low
Low Political Sophliticatlon
0.9
> 0.8
t 0.7
0
'.0- 0.6
0
0.3
Sterypic N tereApic
Nature of Outparty Canddate
* Heuristic Use High
E Heuristic Use Low
among sophisticated voters. The effects of heuristic use
are opposite in direction, and noticeable smaller in magnitude,
among unsophisticated voters.
Discussion
To summarize our most important findings, cognitive
heuristics are not a panacea for all the ills of popular democracies.
Although the five political heuristics considered
here were used by almost everyone (at least outside
of the "ideal world" of a static information board), they
did not substitute for political sophistication in predicting
correct voting. In fact, heavy reliance on political
heuristics actually made decision making less accurate
among those low in political sophistication. Only relative
experts appear to be generally helped in their decision
making by using heuristics. Thus our results should give
pause to those who assert that heuristics are the answer
to the problems of low information voting. We join in
Bartels' (1996) skepticism that voters who are relatively
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HEURISTICS AND POLITICAL DECISION MAKING 967
unaware of politics can make decisions as if they had full
information, simply by employing cognitive shortcuts.
Ironically, heuristics are most valuable to those who
might in fact need them least. Sophisticated voters, who
understand the political environment, can use these
shortcuts to their advantage. But even they can be misled
when the political environment is not structured according
to their prior expectations.
These conclusions are based on our being able to directly
observe the information processing of voters. This
increased observational power comes at a cost, however,
in the realism of our experimental setting. While our
simulation captures crucial aspects of modern election
campaigns, we would not pretend that it captures all of
them. As in any experiment, subjects in our "campaigns"
knew they were being studied, which might alter their
decision making strategies in unknown ways. Voters were
unfamiliar with all of the candidates before the election
began, which at best is not the case when an incumbent is
running for reelection. The "campaign" itself lasted little
more than half an hour, leaving no time for reflection on
any of the information learned about any of the candidates.
All information about all of the candidates was obtained
from a computer-a highly unusual experience
for subjects (at least when we began running these experiments)-and
all information was obtained in social
isolation, without the opportunity to talk about the candidates
and their views with other people. Thus in certain
very important ways, the "mundane realism" of our
campaign simulation was fairly low.
We would not argue with this assessment; our dynamic
process-tracing methodology, as with any research
technique, involves real tradeoffs between internal and
external validity. On the other hand, we would argue that
information boards are far less intrusive methods for
conducting process tracing research than the alternatives
("think aloud" protocols, or monitoring eye movements;
see Abelson and Levy 1985). As more and more people
have access to computers and the internet at work and at
home, and as more and more of us turn more regularly
to internet sources for our political information, what
five years ago was a relatively unusual manner of obtaining
political information may soon become the norm.
Furthermore, what our research design lacked in mundane
realism, it made up for in experimental realism
(Aronson, Wilson, and Brewer 1998). That is, with few
exceptions subjects in our experiments truly cared about
the mock election campaigns and took the task of deciding
who to vote for quite seriously. Some subjects
cheered if their candidate "won" their party's primary
campaign, and many expressed disappointment when, at
the end of the experiment, we did not tell them who
"won" the general election campaign. During the debriefing
we asked how realistic the candidates seemed,
and only three subjects (of over 600 run) responded
"Very Unrealistic."'2' Thus while we should never forget
that our data come from subjects participating in a controlled
laboratory experiment, we believe that our experimental
procedure was sufficiently engaging, and the
decision task facing voters sufficiently realistic, that our
results should be take seriously. Certainly the great majority
of our subjects took the task seriously.
Cognitive heuristics are not the only psychological
mechanism used by people to "stem the tide" of political
information, of course, and it would be remiss of us to
not mention the work of Lodge and his colleagues at
Stony Brook (Lodge, McGraw, and Stroh 1989; Lodge,
Steenbergen, and Brau 1995). Lodge and colleagues argue
that people typically form impressions of politicians
by continually updating a "running tally" evaluation.
Once any new information has been processed and the
tally updated, the information itself can be (and often is)
forgotten. Thus Lodge and his colleagues argue that the
vote decision is often much better "informed" than
would by inferred from the low levels of political information
that can typically be recalled by everyday citizens.
Although we do not agree with every aspect of the online
model (see Lau and Redlawsk, in press; Redlawsk 200 lb),
it seems clear that evaluations of political candidates are
based on exposure to and the processing of much more
information than can typically be recalled at some later
date. Indeed, our dynamic process-tracing methodology
is another technique for providing evidence to test the
online model. The point we want to make here is to acknowledge
that remembering the implications of some
new information about a candidates (i.e., remembering
the updated running tally) but forgetting the details of
that new information is another way in which cognitively
limited information processors cope with an overwhelmingly
rich social environment.
We should also mention several relatively new theories
within social psychology which distinguish between
two largely distinct routes to attitude change (Chaiken
1980, 1987; Petty and Cacioppo 1986). Such theories
should be of great relevance to political scientists, for what
is a political campaign other than an elaborate, often quite
expensive attempt at mass attitude change? According to
these theories, when the recipient of a message is highly
motivated (e.g., the message is personally relevant) and
2'These three subjects were eliminated from the analysis. A somewhat
larger number of subjects (eighteen) responded "Somewhat
Unrealistic" to this question. These subjects' responses are included
in the data reported here.
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968 RICHARD R. LAU AND DAVID P. REDLAWSK
able (they have the intelligence and background knowledge
to place the message in an appropriate context, and
the immediate context is not too distracting) to think
about the message, they will engage in relatively more
effortful, systematic or "central route" processing of the
message. This is the type of processing that most candidates
(and most political scientists) wish citizens would
engage in during a political campaign-but we know very
few do. On the other hand, when motivation and/or ability
are low, relatively more shallow, "heuristic," or "peripheral
route" processing will occur. The latter process better
describes most political information processing, and the
simple heuristics that are studied in these attitude change
experiments (e.g., experts are usually correct; someone
arguing against her own self-interest really believes what
she is saying) serve some of the same functions as the political
heuristics examined in our study.
There is one important difference between how attitude
theorists think about heuristic or peripheral route
processing, however, and how we think about the political
heuristics we have studied: how actively people seek
out information relevant to the heuristics they do employ.
Our method (with the exception of the candidate
appearance heuristic) generally requires voters to actively
decide to use any particular heuristic, while the attitude
change theories under consideration here view heuristic
processing as a much more automatic, almost unconscious
"default" type of processing when motivation is
low. This difference is more apparent than real, however,
driven more by methodological than theoretical considerations.
Even subjects in the "heuristic" or "peripheral
route" conditions of these attitude change experiments
must somehow learn that the communicator was attractive,
say, or an expert. These experiments simply do not
give subjects the option of not "accessing" this information,
which from our perspective makes it appear much
more "automatic" than in fact may be the case.
More recently political scientists have begun to examine
the information environment in which processing
occurs as a determinant of shifting processing
modes. Whether the cause is the processor's emotional
state of mind derived from an assessment of the relative
familiarity and safety of the environment (Marcus,
Neuman, and MacKuen 2000; Marcus and MacKuen,
1993) or the motivated reasoner's unexpected encounter
with information that is affectively incongruent with
previous expectations (Lodge and Taber 2000; Redlawsk
200 lb) information processing may shift from routine,
relatively thoughtless processing to processing under
heightened awareness, where information is considered
more carefully. In the agitated emotional state of mind
as is characterized by anxiety, processors are expected to
pay more attention to information, and would presumably
be less likely to use heuristic-based processing.
Thus, for some voters, our experimental environment
might not represent the political environment in which
they operate, in that it is not embedded in an environment
of anxiety or uncertainty. We might expect that if
the environment were emotionally challenging that heuristic
use would be lessened. Likewise, encountering
negative information about a liked candidate (or positive
information about a disliked candidate) might also
cause the voter to stop and think, at least temporarily focusing
processing more carefully than otherwise would
be the case, and thus decreasing reliance on heuristics.
However, we believe that the political environment for
most voters, most of the time, is not one of high emotional
anxiety, given that the average citizen pays relatively
little attention to politics in the first place. And the
likelihood that motivated reasoners will actually encounter
very much incongruent information is relatively
low, since among other things, such processors are motivated
towards preferential search for information that
confirms rather than challenges existing evaluations. So
while our findings may not apply in every environment
all the time, we believe they are applicable to the peripheral
route processing which represents the larger portion
of political information processing voters carry out on a
routine basis.
In conclusion, as a new technique for exploring political
behavior, the experimental simulation described
here-and its dynamic process-tracing methodologyoffers
an exciting new avenue for research. If political decisions
are based at least in part on the information at
hand when the decision is made, then it is time for political
scientists to begin studying explicitly how information
is gathered and how it is combined into a decision.
Our answers to these questions have important implications
for our theories of political behavior, and any practical
recommendations we might make based on those
theories.
For instance, the distinction between using a particular
heuristic, and the apparent effect that use has on decision
making, is important because the evidence from political
science might lead policy makers to pursue very
different courses of action if they were trying to improve
voters' ability to make reasonable, coherent decisions. If
we believed that cognitive shortcuts helped virtually everyone
and consequently wanted to ensure that voters
had sufficient heuristic cues available to make reasonable
vote decisions, we might try to make sure that party and
ideological labels, well-known group or elite endorsements,
"characteristic images" of the candidates, and
even reputable poll results were widely available before
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HEURISTICS AND POLITICAL DECISION MAKING 969
the election. This information is not too hard to come by
in presidential elections,22 at least for the politically motivated,
but it is not nearly so prevalent for elections to
lower offices. Although this idea would certainly require
much more thought and research, some of this information
could be provided in the voting booth when citizens
go to the polls. Party labels already are a common part of
the ballot for many types of elections; why not a picture
of each candidate as well? Modern voting machines already
have this capability, and it is currently employed in
several countries around the world (e.g., Brazil). Why not
provide the endorsements of a dozen broadly representative
groups as well? Some states are already experimenting
with internet voting, and consequently almost limitless
information could be at voters' fingertips (mouse
clicks?) as they make their web-based vote choices.
Our findings suggest, however, that were this path to
be followed, it would aid the decision-making capabilities
primarily of those already more interested and knowledgeable
about politics. There is nothing wrong with aiding
the decision making of this portion of the general
public, as long as the capabilities of the remainder of the
public are not harmed. Our findings raise an important
cautionary flag here. But if the goal is to improve the decision
making of less sophisticated voters, pursuing the
road to cognitive shortcuts may prove to be a dead end.
The political heuristics of all voters are not equal. "Republican"
or "liberal" means one thing to a relatively naive
citizen, and something much richer, more meaningful,
and more nuanced to a politically sophisticated citizen.
The cognitive revolution will not allow us to get away
from the importance of civic engagement and attention to
politics in the mind of a successful citizen.
Manuscript submitted December 28, 2000.
Final manuscript received May 11, 2001.
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