
1 
Paper

Mixed Logit Models in Political Science
Glasgow, Garrett

Uploaded 
07082001

Keywords 
mixed logit discrete choice heterogeneity

Abstract 
Mixed logit (MXL) is a general discrete choice model that is
applicable to a wide range of political science problems.
Mixed logit assumes the unobserved portions of utility are a
mixture of an IID extreme value term and another multivariate
distribution selected by the researcher. This general
specification allows MXL to avoid imposing the independence
of irrelevant alternatives (IIA) property on the choice
probabilities. Further, and more importantly, MXL is a
flexible tool for examining heterogeneity in individual
behavior through randomcoefficients specifications.
Three empirical examples are presented. Two are drawn
from studies of voting behavior. The first uses data
from the 1987 British general election and examines heterogeneity
in the impact of social class on voting, and the second uses
data from the 1992 U.S. presidential election and examines
heterogeneity in the impact of union membership on voting.
A third example examines heterogeneity in the factors that
lead to various Congressional career decisions. These empirical
examples demonstrate the utility of mixed logit in political
science research.
This paper has both a methodological and substantive contribution
for political science. Methodologically, it expands the tool set
available to researchers for studying various phenomena in
political science. More importantly, this paper contributes
substantively by allowing for more realistic models of individual
behavior. Most models currently used in political science
assume the independent variables have a homogeneous effect on the
dependent variable. This assumption is usually made to keep
models tractable, even though few believe it is an accurate
description of behavior. MXL is a tractable way to relax this
assumption and study heterogeneity in a variety of settings. 

2 
Paper

The Resurgence of Nativism in California? The Case of Proposition 187 and Illegal Immigration
Alvarez, R. Michael
Butterfield, Tara L.

Uploaded 
09251997

Keywords 
twostage probit discrete choice binary probit propositions and initiatives economic voting illegal immigration immigration reform California politics

Abstract 
We argue that support among California voters for Proposition 187 in 1994
was an example of cyclical nativism. This nativism was provoked
primarily by California's economic downturn during the early
1990s. We develop four specific hypotheses to
explain how poor economic conditions in California and the
consequent nativistic sentiments would result in support for
Proposition 187: 1) voters who believe that California's
economic condition is poor will be more likely to support Proposition 187;
2) voters who perceive themselves as being economically
threatened by illegal immigrants will be more likely to support
Proposition 187; 3) voters with lower levels of education are more
economically vulnerable and will be more likely to support
Proposition 187; 4) voters in Southern California feel more
directly affected by illegal immigration and will be more likely to support
Proposition 187. To test these hypotheses, we analyze
voter exit poll data from the 1994 California election. We utilize
a twostage probit model to allow for the endogeneity which
results from the politicization of illegal immigration during
this election. We find support for our hypotheses
in the data. These findings cause us to conclude that nativism,
fueled by economic conditions, was a salient factor leading many
Californians to support Proposition 187. 

4 
Paper

Testing Theories Involving Strategic Choice: The Example of Crisis Escalation
Smith, Alastair

Uploaded 
07231997

Keywords 
Strategic choice Bayesian model testing Markov chain Monte Carlo simulation multivariate probit crisis escalation war

Abstract 
If we believe that politics involves a significant
amount of strategic interaction then classical
statistical tests, such as Ordinary Least Squares,
Probit or Logit, cannot give us the right answers.
This is true for two reasons: The dependent variables
under observation are interdependent that is the
essence of game theoretic logic and the data is
censored  that is an inherent feature of off the
path expectations that leads to selection effects.
I explore the consequences of strategic decision making
on empirical estimation in the context of international
crisis escalation. I show how and why classical
estimation techniques fail in strategic settings.
I develop a simple strategic model of decision making
during crises. I ask what this explanation implies about
the distribution of the dependent variable: the level of
violence used by each nation. Counterfactuals play a key
role in this theoretical explanation. Yet, conventional
econometric techniques take no account of unrealized
opportunities. For example, suppose a weak nation (B) is
threatened by a powerful neighbor (A). If we believe that
power strongly influences the use of force then the weak
nation realizes that the aggressor's threats are probably
credible. Not wishing to fight a more powerful opponent,
nation B is likely to acquiesce to the aggressor's demands.
Empirically, we observe A threaten B. The actual level of
violence that A uses is low. However, the theoretical model
suggests that B acquiesced precisely because A would use force.
Although the theoretical model assumes a strong relationship
between strength and the use of force, traditional techniques
find a much weaker relationship. Our ability to observe whether
nation A is actually prepared to use force is censored when nation
B acquiesces. I develop a Strategically Censored Discrete Choice
(SCDC) model which accounts for the interdependent and censored
nature of strategic decision making. I use this model to test
existing theories of dispute escalation. Specifically, I analyze
Bueno de Mesquita and Lalman's (1992) dyadically coded version of
the Militarized Interstate Dispute data (Gochman and Moaz 1984).
I estimate this model using a Bayesian Markov chain Monte Carlo
simulation method. Using Bayesian model testing, I compare the
explanatory power of a variety of theories. I conclude that strategic
choice explanations of crisis escalation far outperform nonstrategic
ones. 

5 
Paper

The VoteStealing and Turnout Effects of ThirdParty Candidates in U.S. Presidential Elections, 19681996
Lacy, Dean
Burden, Barry C.

Uploaded 
03032000

Keywords 
vote choice turnout third parties multinomial probit

Abstract 
A multinomial probit model of electoral choice in the 1968, 1980, 1992,
and 1996 U.S. presidential elections, estimated using data from the
American National Election Studies, reveals similarities and differences
in electoral support for George Wallace, John Anderson, and Ross Perot.
Estimates from the models are used to simulate the outcomes of the
elections in the absence of the thirdparty candidate and under full
turnout. In three of the four elections, the thirdparty candidates
stole more votes from the challengers than from the incumbents. Only in
1996 did the thirdparty candidate take more votes away from the
incumbent than the challenger. None of the four thirdparty candidacies
increased turnout by more than 2.3 percentage points, and Perot's 1996
candidacy had the smallest impact on turnout of all of the thirdparty
candidacies. Under full turnout, the outcome of only one election  1968 
may have changed. All four thirdparty candidates increase their vote
share under full turnout, and Democratic candidates gain vote share under
full turnout in all elections except 1980. The paper also describes a
new method for estimating the error variances and covariances in an MNP
model. 

6 
Paper

Estimation and Strategic Interaction in Discrete Choice Models of International Conflict
Signorino, Curtis S.

Uploaded 
07231997

Keywords 
discrete choice strategic QRE logit international relations

Abstract 
Typical applications of logit and probit to theories of
international conflict do not capture the structure of the
strategic interdependence implied by those theories. In this
paper I demonstrate how to use a gametheoretic solution concept,
the quantal response equilibrium (QRE), to derive strategic
discrete choice models of international conflict, where the
structure of the strategic interaction is incorporated directly
in the statistical model. I demonstrate this for a crisis
interaction model and use monte carlo analysis to show that logit
provides estimates with incorrect substantive interpretations and
fitted values that are often far from the true values. Finally,
I reanalyze a wellknown gametheoretic model of war, Bueno de
Mesquita and Lalman's (1992) international interaction game, using
this method. My results indicate that their model does not
explain international interaction as well as they claim. 

7 
Paper

Measuring the Relative Impact of Issues and the Economy in Democratic Elections
Alvarez, R. Michael
Nagler, Jonathan
Willette, Jennifer R.

Uploaded 
01121999

Keywords 
multinomial probit discrete choice multiparty elections multicandidate elections Canadian elections

Abstract 
It is generally accepted that issues and economic outcomes influence
elections. In this paper we analyze the relative importance of issues
and the economy in Canadian elections. We estimate a model of the
1988 and 1993 Canadian elections in which we include voter evaluations
of the parties on a variety of issues, and voter evaluations of the
national economy and their personal finances. We demonstrate that
it is possible to compare the effects of issues and the econocy on election outcomes. And we put this in the context of the impact of issues and elections in several other democracies. We show that even in
elections where other factors are dominant, we can still see the
impact of economic voting. And we argue that given the tenuous
connection between the actions of elected officials and macroeconomic
outcomes, this suggests that voters may be giving elected officials
undue leeway in their noneconomic policymaking functions. 

8 
Paper

NonParametric Analysis of Binary Choice Data
Poole, Keith T.

Uploaded 
06161997

Keywords 
discrete choice analysis nonparametric unfolding

Abstract 
This paper shows a general nonparametric technique for maximizing
the correct classification of binary choice or twocategory data.
Two general classes of data are analyzed. The first consists of
binary choice matrices such as congressional roll calls or
preferential rank ordering of stimuli gathered from individuals. For
this class of data a general nonparametric unfolding procedure is
developed. To unfold binary choice data two subproblems must be
solved. First, given a set of chooser or legislator points a cutting
plane through the space for the binary choice must be found such that
it divides the legislators into two sets that reproduce the actual
choices as closely as possible. Second, given a set of cutting
planes for the binary choices a point for each chooser or legislator
must be found that reproduces the actual choices as closely as
possible. Solutions for these two problems are shown in this paper.
The second class of data analyzed consists of a twocategory
dependent variable and a set of independent variables. This class of
data is a subset of the binary choice unfolding problem. The cutting
plane procedure can be used to estimate a cutting plane through the
space of the independent variables that maximizes the number of
correct classifications. The normal vector to this cutting plane
closely corresponds to the beta vector from a standard probit, logit,
or linear probability analysis. 

10 
Paper

A Simulated Maximum Likelihood application to the 1988 Democratic Primary
Lawrence, Eric D.

Uploaded 
03281997

Keywords 
simulated maximum likelihood multinomial probit vote choice models

Abstract 
The multinomial probit model has some appealing
advantages over models that do not allow for
correlated errors, such as multinomial logit and
conditional logit. With a few exceptions, however,
multinomial probit models have not been estimated
for vote choice models because of the computational
costs inherent in evaluating high dimensional integrals.
This paper explains one recently developed approach,
simulated maximum likelihood combined with the GHK simulator,
that makes it feasible to accurately estimate multinomial
probit models. The method is demonstrated on a model of
the 1988 Democratic Super Tuesday primary. 

12 
Paper

Estimating the Probability of Events That have Never Occurred: When Does Your Vote Matter?
Gelman, Andrew
King, Gary
Boscardin, John

Uploaded 
02141997

Keywords 
conditional probability decision analysis elections electoral campaigning forecasting political science presidential elections rare events rational choice subjective probability voting power

Abstract 
Researchers sometimes argue that statisticians have little to
contribute when few realizations of the process being estimated are
observed. We show that this argument is incorrect even in the extreme
situation of estimating the probabilities of events so rare that they
have never occurred. We show how statistical forecasting models allow
us to use empirical data to improve inferences about the probabilities
of these events.
Our application is estimating the probability that your vote will be
decisive in a U.S. presidential election, a problem that has been
studied by researchers in political science for more than two decades.
The exact value of this probability is of only minor interest, but the
number has important implications for understanding the optimal
allocation of campaign resources, whether states and voter groups
receive their fair share of attention from prospective presidents, and
how formal ``rational choice'' models of voter behavior might be able
to explain why people vote at all.
We show how the probability of a decisive vote can be estimated
empirically from statelevel forecasts of the presidential election
and illustrate with the example of 1992. Based on generalizations of
standard political science forecasting models, we estimate the
(prospective) probability of a single vote being decisive as about 1
in 10 million for close national elections such as 1992, varying by
about a factor of 10 among states.
Our results support the argument that subjective probabilities of many
types are best obtained via empiricallybased statistical prediction
models rather than solely mathematical reasoning. We discuss the
implications of our findings for the types of decision analyses that
are used in public choice studies. 

13 
Paper

Reconsidering Tests for Ambivalence in Political Choice Survey Data
Glasgow, Garrett

Uploaded 
03212004

Keywords 
ambivalence heteroskedastic discrete choice

Abstract 
The concept of ambivalence challenges the assumption that
individuals combine their positive and negative attitudes
towards objects in their choice set into unidimensional
attitudes, instead maintaining that individuals can
simultaneously hold conflicting attitudes. Unfortunately,
most tests for ambivalence in political choice survey
data are inconclusive. In particular, the empirical
results of these tests could also be explained by a choice
model with unidimensional attitudes. There are two related
reasons for this. First, individuals who appear to be close
to neutrality or indifference in a choice model with
unidimensional attitudes are expected to have observed choice
behavior identical to that expected from ambivalent
individuals. Second, the measures of ambivalence developed
and used in surveybased studies of ambivalence in political
choice are closely related to measures of neutrality or
indifference in a unidimensional attitude choice model.
Taken together, these two observations point out the need to
reconsider our empirical tests of ambivalence if we wish to
determine if and how ambivalence influences individual
political choice behavior. 

14 
Paper

Logistic Regression in Rare Events Data
King, Gary
Zeng, Langche

Uploaded 
05201999

Keywords 
rare events logit logistic regression binary dependent variables bias correction casecontrol choicebased endogenous selection selection bias

Abstract 
Rare events are binary dependent variables with dozens to thousands
of times fewer ones (events, such as wars, vetoes, cases of
political activism, or epidemiological infections) than zeros
(``nonevents''). In many literatures, rare events have proven
difficult to explain and predict, a problem that seems to have at
least two sources. First, popular statistical procedures, such as
logistic regression, can sharply underestimate the probability of
rare events. We recommend corrections that outperform existing
methods and change the estimates of absolute and relative risks by
as much as some estimated effects reported in the literature.
Second, commonly used data collection strategies are grossly
inefficient for rare events data. The fear of collecting data with
too few events has led to data collections with huge numbers of
observations but relatively few, and poorly measured, explanatory
variables, such as in international conflict data with more than a
quarter million dyads, only a few of which are at war. As it turns
out, easy procedures exist for making valid inferences when sampling
all available events (e.g., wars) and a tiny fraction of nonevents
(peace). This enables scholars to save as much as 99% of their
(nonfixed) data collection costs, or to collect much more
meaningful explanatory variables. We provide methods that link
these two results, enabling both types of corrections to work
simultaneously, and software that implements the methods developed. 

16 
Paper

Macro vs. MicroLevel Perspectives on Economic Voting: Is the MicroLevel Evidence Endogenously Induced?
Erikson, Robert S.

Uploaded 
07102004

Keywords 
economic voting vote choice

Abstract 
Many of the findings regarding economic voting derive from the
microlevel analyses of survey data, in which respondents' survey
evaluations of the economy are shown to predict the vote. This paper
investigates the causal nature of this relationship and argues that
crosssectional consistency between economic evaluations and vote choice
is mainly if not entirely due to vote choice influencing the survey
response. Moreover, the evidence suggest that apart from this
endogenously induced partisan bias, almost all of the crosssectional
variation in survey evaluations of the economy is random noise rather
than actual beliefs about economic conditions In surveys, the mean
evaluations reflect the economic signal that predicts the aggregate
vote. Following Kramer (1983), economic voting is best studied at the
macrolevel rather than the microlevel. 

17 
Paper

Statistical Analysis of Finite Choice Models in Extensive Form
Signorino, Curtis S.

Uploaded 
07091999

Keywords 
random utility discrete choice strategic equilibrium finite choice game theory

Abstract 
Social scientists are often confronted with theories where one or
more actors make choices over finite sets of options leading to a
finite set of outcomes. Such theories have addressed everything from
whether states go to war, to how citizens or senators vote, to the
form of transportation taken by commuters. Over the last thirty
years, the most common way to analyze finite (or discrete) choice
data has been to use nonstrategic random utility models, even when
the theory posited as generating the data is explicitly strategic.
Moreover, the source of uncertainty  what makes the utility random
 is often paid little attention.
In this paper, I generalize an entire class of statistical finite
choice models, with both wellknown and new nonstrategic and
strategic special cases. I demonstrate how to derive statistical
models from theoretical finite choice models and, in doing so, I
address the statistical implications of three sources of uncertainty:
agent error, private information about payoffs, and unobserved
variation in regressors. I provide conditions for the types of choice
structures that result in observationally equivalent statistical
models. For strategic choice models, the type of uncertainty matters,
resulting in observationally nonequivalent statistical models.
Moreover, misspecifying the type of uncertainty in strategic models
leads to biased and inconsistent estimates.
Version: June 22, 1999 

19 
Paper

Models of Intertemporal Choice
Wand, Jonathan

Uploaded 
07262004

Keywords 
choice extremal process utility maximizing dynamic discrete lagged dependent variable panel

Abstract 
In this paper, I consider the behavior of individuals making repeated
choices over a finite set of discrete alternatives. Individuals are
assumed to maximize utility each time they are faced with a choice,
without affecting the utility or availability of future choices. I
build on a class of models where serial correlation in choices is due
to a process of learning over time about the merits of alternatives,
rather than due to unobserved persistent effects. I provide new
analytical results for characterizing transition probabilities between
choices without imposing restrictions on how the systematic component
of utilities may change over time. 

20 
Paper

Inference from ResponseBased Samples with Limited Auxiliary Information
King, Gary
Zeng, Langche

Uploaded 
07091999

Keywords 
rare events logit logistic regression binary dependent variables bias correction casecontrol choicebased endogenous selection selection bias epidemiology

Abstract 
This paper is for the methods conference;
it is related to "Logistic Regression in
Rare Events Data," also by us; the conference
presentation will be based on both papers.
We address a disagreement between epidemiologists and
econometricians about inference in responsebased (a.k.a.
casecontrol, choicebased, retrospective, etc.) samples.
Epidemiologists typically make the rare event assumption (that the
probability of disease is arbitrarily small), which makes the
relative risk easy to estimate via the odds ratio. Econometricians
do not like this assumption since it is false and implies that
attributable risk (a.k.a. a first difference) is zero, and they
have developed methods that require no auxiliary information. These
methods produce bounds on the quantities of interest that,
unfortunately, are often fairly wide and always encompass a
conclusion of no treatment effect (relative risks of 1 or
attributable risks of 0) no matter how strong the true effect is.
We simplify the existing bounds for attributable risk, making it
much easier to estimate, and then suggest one possible resolution of
the disagreement by providing a method that allows researchers to
include easily available information (such as that the fraction of
the population with the disease falls within at most [.001,.05]);
this method considerably narrows the bounds on the quantities of
interest. We also offer software to implement the methods
suggested.
We would very much appreciate any comments you might have! 

21 
Paper

Unanticipated Delays: A Unified Model of Position Timing and Position Content
Boehmke, Frederick

Uploaded 
12092003

Keywords 
duration discrete choice seemingly unrelated position taking NAFTA

Abstract 
On potentially contentious votes or when the margin of an upcoming vote
is expected to be small, public position announcements by elected
representatives may be strategically linked to position content and
ultimately, to vote choice. Strategic position timing may occur when
legislators announce early in order to sway others' vote choice; it may
occur late when legislators stall in order to gain more information or
are hoping that a close margin will make their vote valuable to
participants willing to make side payments. Since intentions behind
delay may often be unobserved or even unobservable, existing empirical
analyses are unable to capture them. In this paper I argue that
unobserved factors that influence position timing are related to
unobserved factors influencing position content. To test this
prediction, I develop a seemingly unrelated discretechoice duration
model that estimates the relationship between unobserved factors in the
two processes. I then estimate this model using data on position timing
and position content from the vote for the North American Free Trade
Agreement. The results provide clear evidence that the two processes are
linked and are consistent with my arguments about the sources of
unanticipated delay. 

22 
Paper

Coordination, Moderation and Institutional Balancing in American House Elections at Midterm
Mebane, Walter R.
Sekhon, Jasjeet

Uploaded 
09021999

Keywords 
congressional elections rational expectations voter equilibrium midterm cycle stochastic choice model turnout

Abstract 
Individuals' turnout decisions and vote choices for the House of
Representatives have been coordinated in recent midterm election years, with
each eligible voter (each elector) using a strategy that features policy
moderation. Coordination is defined as a rational expectations equilibrium
among electors, in which each elector has both common knowledge and private
information about the election outcome. Stochastic choice models estimated
using individuallevel data from the American National Election Study
PostElection Surveys of years 19781998 support coordination, but a model
in which electors act nonstrategically to moderate policy has very similar
behavioral implications and also works well. The empirical coordinating
model satisfies the fixed point condition that defines the common knowledge
expectation electors have about the election outcome in the equilibrium of
the theoretical model. Both the coordinating and nonstrategic models are
capable of generating a midterm cycle in which the President's party usually
loses vote share at midterm. Both models correctly flag 1998 as an
exception to that pattern: the Republican party had policy positions that
were too conservative for most electors. Moderation at midterm has usually
been based on electors' expectations that the House will dominate the
President in determining postelection policy. 

23 
Paper

New Empirical Strategies to Model the Government
Formation Process
Glasgow, Garrett
Golder, Matt
Golder, Sona

Uploaded 
07152010

Keywords 
discrete choice mixed logit IIA random coefficients government formation

Abstract 
Over the past decade, a "standard approach" to the quantitative study of government formation has developed. This approach involves the use of a conditional (CL) logit model to examine government choice with the government formation opportunity as the unit of analysis. In this paper, we reconsider this approach and
make three methodological contributions. First, we demonstrate that the existing procedure used to test for the independence of irrelevant alternatives (IIA) is ﬂawed and severely biased against ﬁnding IIA violations.
Our new testing procedure reveals that many government alternatives share unobserved attributes, thereby violating the IIA assumption and making the CL model inappropriate. Second, we employ a mixed logit with random coefficients that allows us to take account of unobserved heterogeneity and IIA violations. Third, we return to a question that originally motivated this literature, namely, what determines the likelihood that
a particular party enters government? Although scholars have generally abandoned this question due to perceived methodological limitations in our ability to address it, we demonstrate that calculating probabilities
for parties entering ofﬁce rather than governments is straightforward in a mixed logit framework. 

26 
Paper

Causal Inference in Conjoint Analysis: Understanding MultiDimensional Choices via Stated Preference Experiments
Hainmueller, Jens
Hopkins, Daniel
Yamamoto, Teppei

Uploaded 
12122012

Keywords 
potential outcomes average marginal component effects fractional factorial design orthogonal design randomized design survey experiments public opinion vote choice immigration

Abstract 
For decades, market researchers have used conjoint analysis to understand how consumers make decisions when faced with multidimensional choices. In such analyses, respondents are asked to score or rank a set of alternatives, where each alternative is defined by multiple attributes which are varied randomly or intentionally. Political scientists are frequently interested in parallel questions about decisionmaking, yet to date conjoint analysis has seen little use within the field. In this manuscript, we demonstrate the potential value of conjoint analysis in political science, using examples about vote choice and immigrant admission to the United States. In doing so, we develop a set of statistical tools for drawing causal conclusions from stated preference data based on the potential outcomes framework of causal inference. We discuss the causal estimands of interest and provide a formal analysis of the assumptions required for identifying those quantities. Prior conjoint analyses have typically used designs which limit the number of unique conjoint profiles. We employ a survey experiment to compare this approach to a fully randomized approach. Both our formal analysis of the causal estimands and our empirical results highlight the potential biases of common approaches to conjoint analysis which restrict the number of profiles. 

27 
Paper

Political Preference Formation: Competition, Deliberation, and the (Ir)relevance of Framing Effects
Druckman, Jamie

Uploaded 
07092003

Keywords 
framing effects experiments rational choice theory political psychology

Abstract 
A framing effect occurs when different, but logically equivalent, words or phrases such as
95% employment or 5% unemployment cause individuals to alter their preferences.
Framing effects challenge the foundational assumptions of much of the social sciences
(e.g., the existence of coherent preferences or stable attitudes), and raise serious normative
questions about democratic responsiveness. Many scholars and pundits assume that
framing effects are highly robust in political contexts. Using a new theory and an
experiment with more than 550 participants, I show that this is not the case framing
effects do not occur in many political settings. Elite competition and citizens inter
personal conversations often vitiate and eliminate framing effects. However, I also find that
when framing effects persist, they can be even more pernicious than often thought not
only do they suggest incoherent preferences but they also stimulate increased confidence in
those preferences. My results have broad implications for preference formation, rational
choice theory, political psychology, and experimental design. 

28 
Paper

Correlated Disturbances in Discrete Choice Models:A Comparison of Multinomial Probit Models
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 
01011995

Keywords 
econometrics logit multinomial probit gev discretechoice montecarlo

Abstract 
Correlated Disturbances in Discrete Choice Models:
A Comparison of Multinomial Probit Models and Logit Models
In political science, there are many cases where individuals make
discrete choices from more than two alternatives. This paper uses
Monte Carlo analysis to examine several questions about one class of
discrete choice models  those involving both alternativespecific
and individualspecific variables on the righthand side  and
demonstrates several findings.
First, the use of estimation techniques assuming uncorrelated disturbances
across alternatives in discrete choice models can lead to significantly
biased parameter estimates. This point is tempered by the observation that
probability estimates based on the full choice set generated from such
estimates are not likely to be biased enough to lead to incorrect inferences.
However, attempts to infer the impact of altering the choice set  such as
by removing one of the alternatives  will be less successful.
Second, the Generalized Extreme Value (GEV) model is extremely unreliable
when the pattern of correlation among the disturbances is not as restricted
as the GEV model assumes. GEV estimates may suggest grouping among the choices
that is in fact not present in the data.
Third, in samples the size of many typical political science applications
 1000 observations  Multinomial Probit (MNP) is capable of recovering
precise estimates of the parameters of the systemic component of the model,
though MNP is not likely to generate precise estimates of the relationship
among the disturbances in samples of this size.
Paradoxically, MNP's primary benefit is its ability to uncover relationships
among alternatives and to correctly estimate the affect of removing an
alternative from the choice set. Thus this paper suggests the increased
use of MNP by political scientists examining discrete choice problems when
the central question of interest is the effect of removing an alternative
from the choice set. We demonstrate that for other questions, models
positing independent disturbances may be `close enough.' 

29 
Paper

An Integrated Perspective on Party Platforms and Electoral Choice
Elff, Martin

Uploaded 
08192002

Keywords 
electoral behavior party platforms party manifestos ideology social cleavages class voting religious voting comparative politics principal curves generalized additive models dimensional analysis discrete choice

Abstract 
There are several perspectives on voting behavior that usually
constitute separate strands of research: the impact of social
background on vote choice, the relation between policy positions
of parties and policy preferences of voters, and the effect of
party platforms on the electoral success of parties. Although they
all apply to the same entities, that is, to voters and parties,
these different perspectives seem to have divergent implications.
Thus we are in need of a way to reconcile these perspectives.
The empirical results presented in this paper suggest a way what
such a reconciliation should look like. They could be summarized
as follows: In party platforms, several ideological dimensions can
be distinguished that are connected with different cleavages in
the LispetRokkan sense. Second, it is shown that individuals from
different social groups differ in the way they evaluate party
platforms and choose among parties. Third, the way these
individuals evaluate party platforms conforms to spatial notions
of voting. Fourth, a general pattern of platform evaluation
established on the base of pooled data of several countries
accounts to a large degree for differences between levels of
religious voting in these countries. 

30 
Paper

When Politics and Models Collide: Estimating Models of MultiPartyElections
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 
00000000

Keywords 
elections parties probit logit multinomial logit modelspecification spatial model multinomial probit discretechoice

Abstract 
Theory: The spatial model of elections can better be represented by
using conditional logit than by multinomial logit. The spatial model,
and random utility models in general, suffer from a failure to
adequately consider the substitutability of candidates sharing similar
or identical issue positions.
Hypotheses: Multinomial logit is not much better than successive
applications of binomial logit. Conditional logit allows for
considering more interesting political questions than does multinomial
logit. The spatial model may not correspond to voter decisionmaking
in multiplecandidate settings. Multinomial probit allows for a
relaxation of the IIA condition and this should improve estimates of
the effect of adding or removing parties.
Methods: Comparisons of binomial logit, multinomial logit, conditional
logit, and multinomial probit on simulated data and survey data from a
threeparty election.
Results: Multinomial logit offers almost no benefits
over binomial logit. Conditional logit is capable of examining
movements by parties, whereas multinomial logit is not. Multinomial
probit performs better than conditional logit when considering the
effects of altering the set of choices available to voters. 

31 
Paper

Rational Voting
Gelman, Andrew
Kaplan, Noah
Edlin, Aaron

Uploaded 
08022002

Keywords 
elections rational choice sociotropic voting turnout

Abstract 
By separating the assumptions of ``rationality'' and ``selfishness,''
we show that it can be rational to vote if one is motivated by the
effects of the election on society as a whole. For voters with
``social'' preferences the expected utility of voting is approximately
independent of the size of the electorate, suggesting that rational
voter turnouts can be substantial even in large elections. Less
important elections are predicted to have lower turnout, but a
feedback mechanism keeps turnout at a reasonable level under a wide
range of conditions. We show how this feedback mechanism
distinguishes voting from other freerider problems.
Our theory is consistent with several empirical findings in political
science, including survey results that suggest that people vote based
on perceived social benefit, the positive relation between turnout and
(anticipated) closeness of the election, other forms of political
participation, and declining response rates in opinion polls. Since
our ''social'' theory of rational voting is instrumental, it creates a
rich foundation to study {em how} people vote as well as why. A
rational person should make voting decisions almost entirely based on
perceived social benefits of the election outcome. 

32 
Paper

Information and American Attitudes Toward Bureaucracy
Alvarez, R. Michael
Brehm, John

Uploaded 
00000000

Keywords 
discrete choice logit probit heteroskedasticity ordered logit Internal Revenue Service ambivalence uncertainty

Abstract 
The exploration of American attitudes towards the Internal Revenue
Service joins an unusual pair of research domains: public opinion
and public administration. Public administration scholars contend
that the hostility Americans show towards ``bureaucracy'' stems from
the contradictory expectations Americans have for bureaucratic
performance. Drawing upon a survey commissioned by the IRS and
conducted in 1987 just after the passage of the Tax Reform Act, we
explore attitudes towards the performance of the IRS in eight
categories. Using a new heteroskedastic ordinal logit technique, we
demonstrate (1) that it is overwhelmingly a single expectation of
flexibility that governs attitudes towards the IRS; (2) that these
expectations are not in contradiction; and (3) that domainspecific
information sharply focuses respondent attitudes towards
bureaucracy. 

33 
Paper

Heterogeneity in Discrete Choice Models
Glasgow, Garrett

Uploaded 
12122001

Keywords 
heterogeneity discrete choice logit probit ambivalence

Abstract 
Nearly all empirical studies of individual behavior in political science have sought to
estimate the mean relationship between some variables of interest. While such studies are
vital for determining aggregate relationships between variables of interest, they are an
incomplete picture of individual behavior. In particular, we generally do not pay attention
to the possibility of heterogeneity, or individuallevel variation in the relationships
we estimate. Ignoring heterogeneity in our models means we are ignoring valuable information
about individual behavior. This paper demonstrates that examining heterogeneity in
discrete choice models is both important substantively and feasible methodologically.
Possible sources of heterogeneity are discussed, and it is shown that these sources
of heterogeneity are observationally equivalent in most cases, meaning it is generally
not possible to determine the source of heterogeneity in our empirical models.
Several empirical models for examining heterogeneity are described. An empirical example
studying heterogeneity in union voting in the 1992 US presidential election demonstrates the 

34 
Paper

A Bayesian Method for the Analysis of Dyadic Crisis Data
Smith, Alastair

Uploaded 
11041996

Keywords 
Bayesian model testing Censored data Crisis data Gibbs sampling Markov chain Monte Carlo Ordered discrete choice model Strategic choice

Abstract 
his paper examines the level of force that nations use during
disputes. Suppose that two nations, A and B, are involved in a
dispute. Each nation chooses the level of violence that it is prepared
to use in order to achieve its objectives. Since there are two
opponents making decisions, the outcome of the crisis is determined by
a bivariate rather than univariate process. I propose a bivariate
ordered discrete choice model to examine the relationship between
nation A's decision to use force, nation B's decision to use force,
and a series of explanatory variables. The model is estimated in the
Bayesian context using a Markov chain Monte Carlo simulation
technique. I analyze Bueno de Mesquita and Lalman's (1992) dyadically
coded version of the Militarized Interstate Dispute data (Gochman and
Moaz 1984). Various models are compared using Bayes Factors. The
results indicate that nation A's and nation B's decisions to use force
can not be regarded as independent. Bayesian model comparison show
that variables derived from Bueno de Mesquita's expected utility
theory (1982, 1985; Bueno de Mesquita and Lalman 1986, 1992) provide
the best explanatory variables for decision making in crises. 

35 
Paper

An Estimator for Some BinaryOutcome Selection Models without Exclusion Restrictions
Sartori, Anne E.

Uploaded 
07092001

Keywords 
selection bias discrete choice smallsample properties

Abstract 
This paper provides a new estimator for selection models with dichotomous
dependent variables when identical factors affect the selection equation and
the equation of interest. Such situations arise naturally in gametheoretic models
where selection is typically nonrandom and identical explanatory variables
influence all decisions under investigation. When its own identifying assumption
is reasonable, the estimator allows the researcher to avoid the painful choice
among identifying from functional form alone (using a Heckmantype estimator),
adding a theoretically unjustified variable to the selection equation in a mistaken
attempt to "boost" identification, or giving upon estimation entirely. The paper
compares the smallsample properties of the estimator with those of the Heckman
type estimator and ordinary probit using Monte Carlo methods. A brief analysis of
the causes of enduring rivalries and war, following Lemke and Reed (2001), 

36 
Paper

Estimating the Probability of Events That have Never Occurred: When Does Your Vote Matter?
Gelman, Andrew
King, Gary
Boscardin, John

Uploaded 
10271997

Keywords 
conditional probability decision analysis elections electoral campaigning forecasting political science presidential elections rare events rational choice subjective probability voting power

Abstract 
Researchers sometimes argue that statisticians have little to
contribute when few realizations of the process being estimated are
observed. We show that this argument is incorrect even in the
extreme situation of estimating the probabilities of events so rare
that they have never occurred. We show how statistical forecasting
models allow us to use empirical data to improve inferences about
the probabilities of these events.
Our application is estimating the probability that your vote will be
decisive in a U.S. presidential election, a problem that has been
studied by political scientists for more than two decades. The
exact value of this probability is of only minor interest, but the
number has important implications for understanding the optimal
allocation of campaign resources, whether states and voter groups
receive their fair share of attention from prospective presidents,
and how formal ``rational choice'' models of voter behavior might be
able to explain why people vote at all.
We show how the probability of a decisive vote can be estimated
empirically from statelevel forecasts of the presidential election
and illustrate with the example of 1992. Based on generalizations
of standard political science forecasting models, we estimate the
(prospective) probability of a single vote being decisive as about 1
in 10 million for close national elections such as 1992, varying by
about a factor of 10 among states.
Our results support the argument that subjective probabilities of
many types are best obtained via empiricallybased statistical
prediction models rather than solely mathematical reasoning. We
discuss the implications of our findings for the types of decision
analyses that are used in public choice studies. 

