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Below results based on the criteria 'choice'
Total number of records returned: 37

1
Paper
Logistic Regression in Rare Events Data (revised)
King, Gary
Zeng, Langche

Uploaded 07-09-1999
Keywords rare events
logit
logistic regression
binary dependent variables
bias correction
case-control
choice-based
endogenous selection
selection bias
Abstract This paper is for the \r\nmethods conference; it \r\nis a revised version of \r\na paper that was \r\npreviously sent to the \r\npaper server.

2
Paper
Estimating the Probability of Events That have Never Occurred: When Does Your Vote Matter?
Gelman, Andrew
King, Gary
Boscardin, John

Uploaded 02-14-1997
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 state-level 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 empirically-based 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.

3
Paper
Reconsidering Tests for Ambivalence in Political Choice Survey Data
Glasgow, Garrett

Uploaded 03-21-2004
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 survey-based 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.

4
Paper
Logistic Regression in Rare Events Data
King, Gary
Zeng, Langche

Uploaded 05-20-1999
Keywords rare events
logit
logistic regression
binary dependent variables
bias correction
case-control
choice-based
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 non-events (peace). This enables scholars to save as much as 99% of their (non-fixed) 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.

5
Paper
Difficult Choices: An Evaluation of Heterogenous Choice Models
Keele, Luke
Park, David K.

Uploaded 10-14-2004
Keywords probit
discrete choice
heteroskedasticity
heteroskedastic probit
Abstract While the derivation and estimation of heterogeneous choice models appears straightforward, the properties of such models are not well understood. Using a series of Monte Carlo experiments, we focus on the properties of both heteroskedastic probit and heteroskedastic ordered probit models. We also test how robust these models are to both specification and measurement error. We find that estimates in heterogeneous choice models tend to be biased in all but ideal conditions, and can often lead to incorrect inferences.

6
Paper
Macro vs. Micro-Level Perspectives on Economic Voting: Is the Micro-Level Evidence Endogenously Induced?
Erikson, Robert S.

Uploaded 07-10-2004
Keywords economic voting
vote choice
Abstract Many of the findings regarding economic voting derive from the micro-level 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 cross-sectional 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 cross-sectional 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 macro-level rather than the micro-level.

7
Paper
Statistical Analysis of Finite Choice Models in Extensive Form
Signorino, Curtis S.

Uploaded 07-09-1999
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 well-known 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

8
Paper
Statistical Backwards Induction: A Simple Method for Estimating Statistical Strategic Models
Bas, Muhammet
Signorino, Curtis
Walker, Robert

Uploaded 09-22-2006
Keywords discrete choice
strategic
QRE
logit
probit
statistical backwards induction
limited information estimation
Abstract We present a simple method for estimating regressions based on extensive-form games. Our procedure, which can be implemented in most standard statistical packages, involves sequentially estimating standard logits (or probits) in a manner analogous to backwards induction. We demonstrate that the technique produces consistent parameter estimates and show how to calculate consistent standard errors using model-dependent analytical and general simulation techniques. To illustrate the method, we replicate Leblangs (2003) study of speculative attacks by financial markets and government responses to these attacks.

9
Paper
Models of Intertemporal Choice
Wand, Jonathan

Uploaded 07-26-2004
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.

10
Paper
Inference from Response-Based Samples with Limited Auxiliary Information
King, Gary
Zeng, Langche

Uploaded 07-09-1999
Keywords rare events
logit
logistic regression
binary dependent variables
bias correction
case-control
choice-based
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 response-based (a.k.a. case-control, choice-based, 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!

11
Paper
Unanticipated Delays: A Unified Model of Position Timing and Position Content
Boehmke, Frederick

Uploaded 12-09-2003
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 discrete-choice 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.

12
Paper
Coordination, Moderation and Institutional Balancing in American House Elections at Midterm
Mebane, Walter R.
Sekhon, Jasjeet

Uploaded 09-02-1999
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 individual-level data from the American National Election Study Post-Election Surveys of years 1978-1998 support coordination, but a model in which electors act non-strategically 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 non-strategic 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 post-election policy.

13
Paper
New Empirical Strategies to Model the Government Formation Process
Glasgow, Garrett
Golder, Matt
Golder, Sona

Uploaded 07-15-2010
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.

14
Paper
Discriminating Methods: Tests for Nonnested Discrete Choice Models
Clarke, Kevin A.
Signorino, Curtis S.

Uploaded 07-15-2003
Keywords discrete choice
nonnested testing
strategic choice
Vuong test
nonparametric test
Abstract We consider the problem of choosing between rival models that are nonnested in terms of their functional forms. We discuss both a parametric and distribution-free procedure for making this choice, and demonstrate through a monte carlo simulation that discrimination is possible. The results of the simulation also allow us to compare the relative power of the two tests.

15
Paper
The Revolution Against Affirmative Action in California: Politics, Economics, and Proposition 209
Alvarez, R. Michael
Butterfield, Tara L.

Uploaded 04-14-1998
Keywords discrete choice
endogeneity
generalized extreme value
affirmative action
race and politics
California politics
Abstract We consider two possible explanations --- economic anxiety and racial division --- for the appeal of Proposition 209 to California voters during the 1996 election. To test these hypotheses, we analyze voter exit poll data from teh 1996 California election. We utiliize a two--stage logit model to allow for the endogeneity of candidate endorsements. We find support for the second of our two hypotheses, which leads us to conclude that racial division fueled by a fear of arbitrary exclusion prompted voter support for Proposition 209.

16
Paper
Causal Inference in Conjoint Analysis: Understanding Multi-Dimensional Choices via Stated Preference Experiments
Hainmueller, Jens
Hopkins, Daniel
Yamamoto, Teppei

Uploaded 12-12-2012
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 multi-dimensional 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 decision-making, 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.

17
Paper
Political Preference Formation: Competition, Deliberation, and the (Ir)relevance of Framing Effects
Druckman, Jamie

Uploaded 07-09-2003
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.

18
Paper
Correlated Disturbances in Discrete Choice Models:A Comparison of Multinomial Probit Models
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 01-01-1995
Keywords econometrics
logit
multinomial probit
gev
discrete-choice
monte-carlo
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 alternative-specific and individual-specific variables on the right-hand 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.'

19
Paper
An Integrated Perspective on Party Platforms and Electoral Choice
Elff, Martin

Uploaded 08-19-2002
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 Lispet-Rokkan 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.

20
Paper
When Politics and Models Collide: Estimating Models of Multi-PartyElections
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 00-00-0000
Keywords elections
parties
probit
logit
multinomial logit
model-specification
spatial model
multinomial probit
discrete-choice
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 decision-making in multiple-candidate 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 three-party 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.

21
Paper
Rational Voting
Gelman, Andrew
Kaplan, Noah
Edlin, Aaron

Uploaded 08-02-2002
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 free-rider 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.

22
Paper
Information and American Attitudes Toward Bureaucracy
Alvarez, R. Michael
Brehm, John

Uploaded 00-00-0000
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 domain-specific information sharply focuses respondent attitudes towards bureaucracy.

23
Paper
Heterogeneity in Discrete Choice Models
Glasgow, Garrett

Uploaded 12-12-2001
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 individual-level 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

24
Paper
A Bayesian Method for the Analysis of Dyadic Crisis Data
Smith, Alastair

Uploaded 11-04-1996
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.

25
Paper
An Estimator for Some Binary-Outcome Selection Models without Exclusion Restrictions
Sartori, Anne E.

Uploaded 07-09-2001
Keywords selection bias
discrete choice
small-sample 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 game-theoretic 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 Heckman-type 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 small-sample 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),

26
Paper
Estimating the Probability of Events That have Never Occurred: When Does Your Vote Matter?
Gelman, Andrew
King, Gary
Boscardin, John

Uploaded 10-27-1997
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 state-level 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 empirically-based 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.

27
Paper
Mixed Logit Models in Political Science
Glasgow, Garrett

Uploaded 07-08-2001
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 random-coefficients 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.

28
Paper
The Resurgence of Nativism in California? The Case of Proposition 187 and Illegal Immigration
Alvarez, R. Michael
Butterfield, Tara L.

Uploaded 09-25-1997
Keywords two-stage 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 two-stage 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.

29
Paper
Binding the Frame: How Important are Frames for Survey Response?
Alvarez, R. Michael
Brehm, John

Uploaded 08-26-2000
Keywords framing
survey experiments
heteroskedastic choice
Abstract [not transcribed]

30
Paper
Testing Theories Involving Strategic Choice: The Example of Crisis Escalation
Smith, Alastair

Uploaded 07-23-1997
Keywords Strategic choice
Bayesian model testing
Markov chain Monte Carlo simulation
multi-variate 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 out-perform non-strategic ones.

31
Paper
The Vote-Stealing and Turnout Effects of Third-Party Candidates in U.S. Presidential Elections, 1968-1996
Lacy, Dean
Burden, Barry C.

Uploaded 03-03-2000
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 third-party candidate and under full turnout. In three of the four elections, the third-party candidates stole more votes from the challengers than from the incumbents. Only in 1996 did the third-party candidate take more votes away from the incumbent than the challenger. None of the four third-party 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 third-party candidacies. Under full turnout, the outcome of only one election - 1968 - may have changed. All four third-party 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.

32
Paper
Estimation and Strategic Interaction in Discrete Choice Models of International Conflict
Signorino, Curtis S.

Uploaded 07-23-1997
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 game-theoretic 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 well-known game-theoretic 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.

33
Paper
Measuring the Relative Impact of Issues and the Economy in Democratic Elections
Alvarez, R. Michael
Nagler, Jonathan
Willette, Jennifer R.

Uploaded 01-12-1999
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 non-economic policy-making functions.

34
Paper
Non-Parametric Analysis of Binary Choice Data
Poole, Keith T.

Uploaded 06-16-1997
Keywords discrete choice analysis
non-parametric unfolding
Abstract This paper shows a general non-parametric technique for maximizing the correct classification of binary choice or two-category 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 non-parametric 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 two-category 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.

35
Paper
Statistical Analysis of Finite Choice Models in Extensive Form
Signorino, Curtis S.

Uploaded 03-23-1999
Keywords random utility
discrete choice
strategic
equilibrium
finite choice
game theory
Abstract (not transcribed)

36
Paper
A Simulated Maximum Likelihood application to the 1988 Democratic Primary
Lawrence, Eric D.

Uploaded 03-28-1997
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.

37
Poster
A Comparison of Instrumental Variable Estimators in Models of Discrete Choice
Quiroz Flores, Alejandro

Uploaded 07-08-2010
Keywords instrumental variables
discrete choice
probit model
continuous endogenous regressors
MLE
Newey
Two-step
GMM
Abstract Comparison of three instrumental variable estimators applicable to probit models. The first estimator uses conditional probabilities and MLE. The second estimator uses Newey’s two-step minimum chi-squared estimator. A new estimator presented here uses GMM to approach probit models as non-linear regression. These models are compared in a simulation experiment. Results show that conditional probability MLE model has superior performance both in terms of bias and efficiency, although the GMM estimator follows closely.


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