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Alternative Models of Dynamics in Binary Time-Series--Cross-Section Models: The Example of State Failure Beck, Nathaniel Jackman, Simon Epstein, David O'Halloran, Sharyn Uploaded 07-14-2001 Keywords dynamic probit btscs state failure Gibbs sampling MCMC transitional models discrete data ROC correlated binary data generalized residuals Abstract This paper investigates a variety of dynamic probit models for time-series--cross-section data in the context of explaining state failure. It shows that ordinary probit, which ignores dynamics, is misleading. Alternatives that seem to produce sensible results are the transition model and a model which includes a lagged emph{latent} dependent variable. It is argued that the use of a lagged latent variable is often superior to the use of a lagged realized dependent variable. It is also shown that the latter is a special case of the transition model. The relationship between the transition model and event history methods is also considered: the transition model estimates an event history model for both values of the dependent variable, yielding estimates that are identical to those produced by the two event history models. Furthermore, one can incorporate the insights gleaned from the event history models into the transition analysis, so that researchers do not have to assume duration independence. The conclusion notes that investigations of the various models have been limited to data sets which contain long sequences of zeros; models may perform differently in data sets with shorter bursts of zeros and ones.

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Operationalizing and Testing Spatial Theories of Voting Quinn, Kevin M. Martin, Andrew D. Uploaded 04-15-1998 Keywords spatial voting factor analysis multinomial probit multinomial logit Bayesian inference model comparison Bayes factors MCMC Dutch politics Danish politics Abstract Spatial models of voting behavior provide the foundation for a substantial number of theoretical results. Nonetheless, empirical work involving the spatial model faces a number of potential difficulties. First, measures of the latent voter and candidate issue positions must be obtained. Second, evaluating the fit of competing statistical models of voter choice is often more complicated than previously realized. In this paper, we discuss precisely these issues. We argue that confirmatory factor analysis applied to mass-level issue preference questions is an attractive means of measuring voter ideal points. We also show how party issue positions can be recovered using a variation of this strategy. We go on to discuss the problems of assessing the fit of competing statistical models (multinomial logit vs. multinomial probit) and competing explanations (those based on spatial theory vs. those derived from other theories of voting such as sociological theories). We demonstrate how the Bayesian perspective not only provides computational advantages in the case of fitting the multinomial probit model, but also how it facilitates both types of comparison mentioned above. Results from the Netherlands and Denmark suggest that even when the computational cost of multinomial probit is disregarded, the decision whether to use multinomial probit (MNP) or multinomial logit (MNL) is not clear-cut.

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A New Approach for Modeling Strategic Voting in Multiparty Systems Alvarez, R. Michael Nagler, Jonathan Uploaded 04-04-1997 Keywords multinomial probit strategic voting Abstract Whether voters vote strategically, using their vote to best further their interests, or vote sincerely, voting for their first choice among the alternatives, is a question of longstanding interest. We offer two innovations in searching for the answer to this question. First, we begin with a more consistent model of sincere voting in multiparty democratic systems than has been presented in the literature to date. Second, we incorporate new operationalizations of the objective potential for strategic behavior than have been used in the past. We offer a test of strategic voting in the 1987 British General Election based on the varience in strategic setting across constituencies in Britain. Prepared for presentation at the Annual Meeting of the Midwest Political Science Association. This is one of many papers by the authors; the ordering of names reflects alphabetic convention. We thank Jonathan Katz and Guy Whitten for supplying helpful data for this project. We also thank Gary Cox and Jonathan Katz for discussions of this subject. Last, we thank Shaun Bowler for his work with us on a related project.

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Selection Bias in Studies of Sanctions Efficacy Nooruddin, Irfan Uploaded 04-05-2001 Keywords sanctions strategic censoring censored probit Abstract Sanctions rarely work but they continue to be used frequently by policymakers. Previous research on the determinants of sanctions identifies various factors that are thought to contribute to sanctions success but do not give us an answer to the original puzzle of why this ineffective policy is so commonly used. I argue that this is because studies of sanctions have ignored the problem of strategic censoring by focusing only on cases of observed sanctions. In this paper, I develop a unified model of sanction imposition and success and test it using a simultaneous equation censored probit model. The selection- corrected sanction model finds that the process by which sanctions are imposed is linked to the process by which some succeed while others fail, and that the unmeasured factors that lead to sanction imposition are negatively related to their success.

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Uncertainty and Candidate Personality Traits Alvarez, R. Michael Glasgow, Garrett Uploaded 04-16-1998 Keywords uncertainty direct measures of uncertainty survey response ordered probit candidate evaluation candidate traits presidential elections Abstract Recently, some scholars have focused attention on the role of uncertainty in elections (Alvarez 1997, Bartels 1986, Franklin 1991). They reveal that there is a great deal of uncertainty about the issue positions of candidates, and thus the costs of issue voting are burdensome for the average citizen. Further, this uncertainty affects how voters evaluate candidates in two ways. First, voters are less likely to evaluate a candidate in terms of an issue when they are uncertain about the candidate's position on that issue. Second, uncertainty about candidate issue positions has a negative impact on voter evaluations of a candidate. However, it is important to realize that for most individuals, information about the personality traits of candidates comes from the same sources as information about the issue positions of the candidates, generally media outlets. This means that information about the the personalities of candidates is passed through the same noisy channels as information about their issue positions, and is thus subject to the same types of distortions and biases that contribute to the cost of issue information. Although it is likely easier to interpret than issue information, trait information is still subject to uncertainty. In this paper we introduce direct survey measures of candidate personality trait uncertainty. Using survey data drawn from the 1995 and 1996 National Election Studies, we first establish that the direct measure of uncertainty used in this paper is a valid measure. We then examine the effect of trait opinions on candidate evaluations and test the effects that uncertainty about those opinions has on the use of traits in candidate evaluation.

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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.

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Anatomy of a Third-Party Victory: Electoral Support for Jesse Ventura in the 1998 Minnesota Gubernatorial Election Lacy, Dean Monson, Quin Uploaded 04-24-2000 Keywords vote-stealing turnout third-party Condorcet winner multinomial probit Abstract [not transcribed]

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Economic Performance, Job Insecurity, and Electoral Choice Lacy, Dean Mughan, Anthony Uploaded 09-17-1998 Keywords economic voting economic insecurity Perot turnout multinomial probit 1996 election Abstract The mass political economy literature concentrates on egocentric and sociotropic evaluations of short-term economic performance. Scant attention is paid to other economic concerns people may have. In a neo-liberal economic climate characterized by a downsized labor market and the retrenchment of government welfare entitlements, one such widely-publicized concern is job insecurity. We show that job insecurity is a novel form of discontent that is independent of the retrospective evaluations of short-term performance that are the stuff of the mainstream mass political economy literature. At the same time, the political effects of job insecurity are distinctive. In a multinomial probit model of electoral choice in the 1996 U.S. presidential election, job insecurity is associated with support for the third-party candidate, Ross Perot, but, contrary to conventional wisdom, has no implications for turnout. Traditional retrospective evaluations of economic performance explain the major-party vote and abstention.

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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.

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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.

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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.'

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A Bayesian analysis of the multinomial probit model using marginal data augmentation Imai, Kosuke van Dyk, David A. Uploaded 08-21-2002 Keywords Bayesian analysis Data augmentation Prior distributions Probit models Rate of convergence Abstract We introduce a set of new Markov chain Monte Carlo algorithms for Bayesian analysis of the multinomial probit model. Our Bayesian representation of the model places a new, and possibly improper, prior distribution directly on the identifiable parameters and thus is relatively easy to interpret and use. Our algorithms, which are based on the method of marginal data augmentation, involve only draws from standard distributions and dominate other available Bayesian methods in that they are as quick to converge as the fastest methods but with a more attractive prior specification.

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Mixed Logit Models for Multiparty Elections Glasgow, Garrett Uploaded 02-24-2000 Keywords mixed logit random parameters logit multinomial probit IIA Abstract This is a significantly updated version of my February 24 submission, with several mathematical errors corrected and new information on multinomial probit models and IIA violations. In this paper I introduce the mixed logit (MXL), a flexible discrete choice model based on random utility maximization. Mixed logit is the most flexible discrete choice model available for the study of multiparty and multicandidate elections --- even more flexible than multinomial probit (MNP), the discrete choice model currently favored for the study of elections of this type. Like MNP, MXL does not assume IIA, and can thus estimate realistic substitution patterns between alternatives. In fact, MXL can be specified to estimate the same substitution patterns as any specification of MNP. Further, since the unobserved components of MXL are not constrained to follow a normal distribution, and are not estimated as elements in a covariance matrix, MXL can include any number of random coefficients or error components that can follow any distribution. MXL is no more difficult to estimate than MNP. An empirical example using data from the 1987 British general election demonstrates the utility of MXL in the study of multicandidate and multiparty elections.

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Economics, Issues and the Perot Candidacy: Voter Choice in the 1992 Presidential Election Alvarez, R. Michael Nagler, Jonathan Uploaded 01-01-1995 Keywords Elections Campaigns Perot Multinomial Probit Economic Voting Angry Voters Abstract Theory: Theories of presidential elections (economic voting and spatial issue and ideology models), combined with the popular explanation of "angry voting", are used to account for voter choice in the 1992 Presidential Election. Hypotheses: Voter choice in this three-candidate race is a function of economic perceptions, issue and ideological positions of voters and candidates, or ``voter anger.'' Methods: Multinomial probit analysis of 1992 National Election Studies data including individual-specific and alternative-specific variables. Simulations based on counterfactual scenarios of ideological positions of the candidates and of voter perceptions of the economy. Results: The economy was the dominant factor in accounting for voter decisions in 1992, and Clinton, not Perot, was the beneficiary of economic discontent. While issues (mainly abortion) and ideology did play some role, Clinton was not perceived by the electorate as a ``New Democrat.'' We find little support for the hypothesis of ``angry voting.'' Last, Perot took more votes from Bush than from Clinton.

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Expressive Bayesian Voters, their Turnout Decisions, and Double Probit Achen, Christopher Uploaded 07-17-2006 Keywords turnout expressive Bayesian probit scobit EITM Abstract Voting is an expressive act. Since people are not born wanting to express themselves politically, the desire to vote must be acquired, either by learning about the candidates, by using party identification as a cognitive shortcut, or by contact from a trusted source. Modeled as Bayesian updating, this simple explanatory framework has dramatic implications for the understanding of voter turnout. It mathematically implies the main empirical generalizations familiar from the literature, it predicts hitherto unnoticed patterns that appear in turnout data, it provides a better fitting statistical model (double probit) for sample surveys of turnout, and it allows researchers to forecast turnout patterns in new elections when circumstances change. Thus the case is strengthened for the Bayesian voter model as a central organizing principle for public opinion and voting behavior.

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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.

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Issues, Economics and the Dynamics of Multi-Party Elections: The British 1987 General Election Alvarez, R. Michael Nagler, Jonathan Bowler, Shaun Uploaded 00-00-0000 Keywords Elections Multinomial Probit Economic Voting Issue Voting Spatial Model Multicandidate Elections British Elections Abstract This paper offers a model of three-party elections which allows voters to combine retrospective economic evaluations with considerations of the positions of the parties in the issue-space as well as the issue-preferences of the voters. We describe a model of British elections which allows voters to consider simultaneously all three parties, rather than limiting voters to choices among pairs of parties as is usually done. Using this model we show that both policy issues and the state of the national economy matter in British elections. We also show how voters framed their decisions. Voters first made a retrospective evaluation of the Conservative party based on economic performance; and those voters that rejected the Conservative party chose between Labour and Alliance based on issue positions. Through simulations of the effects of issues -- we move the parties in the issue space and re-estimate vote-shares -- and the economy -- we hypothesize an alternative distribution of views of the economy for voters -- we show that Labour has virtually no chance to win with the Alliance as a viable alternative. Even if the Alliance (or the Liberal Democrats) disappears, Labour will need to significantly moderate its policy positions to have a chance of competing with the Conservative party. We argue that the methodological technique we employ, multinomial probit, is a superior mechanism for studying three-party elections as it allows for a richer formulation of politics than do competing methods.

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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 Leblang’s (2003) study of speculative attacks by financial markets and government responses to these attacks.

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Gender and Tax Alvarez, R. Michael McCaffery, Edward J. Uploaded 02-17-1999 Keywords taxation gender gender gap marriage penalty probit issue preferences Abstract This paper addresses two empirical questions in the literature on taxation and law. The first is whether women support redistributive tax policies more than men do. The second is why there exists a strong bias in the current tax code against modern, two-earner families, a bias which is usually understood as falling primarily on women. Our analysis of data from the 1996 presidential election suggests a single answer to both questions. Women and men often answer direct survey questions about their attitudes towards matters of tax similarly, while continuing to show a marked gender gap in their actual voting behavior when tax is one of several issues to be considered.

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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.

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Testing for Interaction in Binary Logit and Probit Models: Is a Product Term Essential? Berry, William Esarey, Justin DeMeritt, Jacqueline Uploaded 05-06-2007 Keywords interaction logit probit Abstract Political scientists presenting binary dependent variable (BDV) models often offer hypotheses that independent variables interact in their influence on the probability that an event Y occurs, Pr(Y). A consensus appears to have evolved on how to test such hypotheses: (i) estimate a logit or probit model including product terms to specify the interaction, (ii) test the hypothesis by determining whether the coefficients for these terms are statistically significant, and (iii) if they are, describe the nature of the interaction by estimating how the marginal effect of one independent variable on Pr(Y) varies with the value of the other independent variables. We contend that in the BDV context, statistically significant product term coefficients are neither necessary nor sufficient for concluding that there is substantively meaningful interaction among variables in their influence on Pr(Y). Even when no product terms are included in a logit or probit model, if the marginal effect of one variable on Pr(Y) is related to another independent variable then substantively meaningful interaction is present, and describing such interaction is essential to an accurate portrayal of the data generating process at work. We propose a strategy for studying interaction in the BDV context that is consistent with the recent emphasis in the discipline on casting hypotheses in terms of effects on the probability of an event's occurrence and reporting estimated marginal effects on this probability.

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Two-Stage Estimation of Non-Recursive Choice Models Alvarez, R. Michael Glasgow, Garrett Uploaded 03-02-1999 Keywords two-stage estimation probit endogeneity two-stage probit least squares two-stage conditional maximum likelihood Abstract Questions of causation are important issues in empirical research on political behavior. Most of the discussion of the econometric problems associated with multi-equation models with reciprocal causation has focused on models with continuous dependent variables (e.g. Markus and Converse 1979; Page and Jones 1979). Yet many models of political behavior involve discrete or dichotomous dependent variables; this paper describes two techniques which can consistently estimate reciprocal relationships between dichotomous and continuous dependent variables. The first, two-stage probit least squares (2SPLS), is very similar to two-stage instrumental variable techniques. The second, two-stage conditional maximum likelihood (2SCML), may overcome problems associated with 2SPLS, but has not been used in the political science literature. First, we demonstrate the potential pitfalls of ignoring the problems of reciprocal causation in non-recursive choice models. Then, we show the properties of both techniques using Monte Carlo simulations: both the two-stage models perform well in large samples, but in small samples the 2SPLS model has superior statistical properties. However, the 2SCML model offers an explicit statistical test for endogeneity. Last, we apply these techniques to an empirical example which focuses on the relationship between voter preferences in a presidential election and the voter's uncertainty about the policy positions taken by the candidates. This example demonstrates the importance of these techniques for political science research.

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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.

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The Spatial Probit Model of Interdependent Binary Outcomes: Estimation, Interpretation, and Presentation Franzese, Robert Hays, Jude Uploaded 07-20-2007 Keywords Spatial Probit Bayesian Gibbs-Sampler Estimator Recursive Importance-Sampling Estimator Interdependence Diffusion Contagion Emulation Abstract We have argued and shown elsewhere the ubiquity and prominence of spatial interdependence in political science research and noted that much previous practice has neglected this interdependence or treated it solely as nuisance to the serious detriment of sound inference. Previously, we considered only linear-regression models of spatial and/or spatio-temporal interdependence. In this paper, we turn to binary-outcome models. We start by stressing the ubiquity and centrality of interdependence in binary outcomes of interest to political and social scientists and note that, again, this interdependence has been ignored in most contexts where it likely arises and that, in the few contexts where it has been acknowledged, the endogeneity of the spatial lag has not be recognized. Next, we explain some of the severe challenges for empirical analysis posed by spatial interdependence in binary-outcome models, and then we follow recent advances in the spatial-econometric literature to suggest Bayesian or recursive-importance-sampling (RIS) approaches for tackling estimation. In brief and in general, the estimation complications arise because among the RHS variables is an endogenous weighted spatial-lag of the unobserved latent outcome, y*, in the other units; Bayesian or RIS techniques facilitate the complicated nested optimization exercise that follows from that fact. We also advance that literature by showing how to calculate estimated spatial effects (as opposed to parameter estimates) in such models, how to construct confidence regions for those (adopting a simulation strategy for the purpose), and how to present such estimates effectively.

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Testing for Interaction in Models with Binary Dependent Variables Berry, William D. Uploaded 04-08-1999 Keywords probit logit scobit interaction binary dependent variables Abstract Over the last decade, political scientists have proposed several strategies for testing hypotheses about interaction in models with binary dependent variables. I argue that these strategies are incomplete, and propose an alternative approach. Consistent with Nagler's (1991; 1994) and Frant's (1991) advice, this approach involves including multiplicative terms in probit, logit and scobit models to specify interaction. However, the information used to test the hypotheses about interaction depends on whether the dependent variable of conceptual interest is the observed dichotomous variable or a latent, unbounded, continuous variable which the observed dichotomy is assumed to measure. In the latter case, hypotheses about interaction are tested by examining directly the maximum likelihood estimates of the coefficients for the multiplicative terms. In the former situation, the propositions are tested by analyzing changes in the predicted probability that the observed dependent variable will equal one of its values associated with changing values of the independent variables.

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Senate Voting on NAFTA: The Power and Limitations of MCMC Methods for Studying Voting across Bills and across States Smith, Alastair McGillivray, Fiona Uploaded 07-09-1996 Keywords NAFTA MCMC Gibbs sampling bivariate probit Senate Abstract We examine similarities in senate voting within states and across two senate bills: the 1991 fast track authorization bill and the 1993 NAFTA implementation bill. A series of bivariate probit models are estimated by Markov Chain Monte Carlo simulation. We discuss the power of MCMC techniques and how the output of these sampling procedures can be used for Bayesian model comparisons. Having separately explored the similarities in votes across bills and within states, we develop a 4-variate probit model to explain voting on NAFTA. The power of MCMC techniques to estimate this complicated model is demonstrated with two different MCMC procedures. We conclude by discussing the data requirements for these techniques.

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Democratic Compromise: A Latent Variable Analysis of Ten Measures of Regime Type Pemstein, Daniel Meserve, Stephen Melton, James Uploaded 02-07-2008 Keywords democracy measurement democracy measurement regime regime type latent variable analysis Bayesian latent variable analysis UDS Unified Democracy Scores multi-rater ordinal probit Abstract Using a Bayesian latent variable approach, we synthesize a new measure of democracy, the Unified Democracy Scores (UDS), from ten extant scales. We accompany this new scale with quantitative estimates of uncertainty, provide estimates of the relative reliability of the constituent indicators, and quantify what the ordinal levels of each of the existing measures mean in relationship to one another. Our method eschews the difficult -- and often arbitrary -- decision to use one existing democracy scale over another in favor of a cumulative approach that allows us to simultaneously leverage the measurement efforts of numerous scholars.

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The Timing of Voting Decisions in Presidential Campaigns Box-Steffensmeier, Janet M. Kimball, David Uploaded 04-12-1999 Keywords heteroskedastic probit time of vote decision voting presidential elections 1988 election Abstract Voting analysts often make a distinction between "long-term" and "short-term" forces that influence the voting decision in presidential elections (Campbell et al. 1960). Long-term forces reflect information and considerations that are available to voter before the presidential campaign starts, such as party identification, demographic attributes, and the record each candidate has established previously in government. In contrast, short-term forces refer more specifically to the campaign. We posit that there is variation in the way voters integrate the long- and short-term forces into a voting decision. Furthermore, the long-term forces are smaller in number and thus easier for researchers to identify and measure. For example, much attention has been devoted to conceptualization and measurement of party identification. However, short-term forces are nearly infinite in number and are much harder to measure and link up to the voting decision. This means that voting models should perform well when predicting the choices of voters who are guided primarily by long-term forces. In contrast, voting models should not perform as well for citizens who are strongly influenced by short-term forces. In statistical terms, there will be heteroskedastic error variance in common vote models due to the differing influence of short- and long-term forces. We examine the variation among voters by using the standard NES question that asks citizens how long before the election they made their voting decisions and test our expectations using the heteroskedastic probit technique (Brehm and Alvarez 1995), which is like a standard probit model except that there is a separate equation to model the error variance (the errors in prediction). By using the timing of the vote decision to help model the error variance, we produce unbiased estimates and improve our ability to explain voting behavior and the impact of campaigns.

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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.

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Estimating Binary Dependent Variable Models Under Conditions of Specification Uncertainty Berry, William DeMeritt, Jacqueline Esarey, Justin Uploaded 01-25-2007 Keywords logit probit binary dependent variable specification uncertainty interaction Monte Carlo analysis Abstract Political scientists routinely use logit or probit models when their data involve binary dependent variables (BDVs). Yet the hypotheses we test with logit and probit are rarely specific enough to justify that one of these models is the correct functional form for the process (or true model) generating the data. In this situation of specification uncertainty, it is reasonable to assume that the model being estimated is misspecified. The only issue is the severity of the resulting distortion in results, i.e., whether logit or probit approximates the true model well enough to yield estimated effects that are acceptably close to the true ones. To study estimation in the presence of specification uncertainty, we conduct Monte Carlo analysis using a strategy of purposeful misspecification: we use various logit and probit models with different terms on data sets generated from a wide range of known true models involving a BDV, none of which takes the exact form of a logit or probit model. We find that a widely-employed approach for using logit or probit to test the hypothesis that an independent variable has a positive (or negative) effect on the probability that some event will occur-­by estimating the effect of the variable at central values of the independent variables­-is highly forgiving of specification uncertainty, yielding reasonably accurate inferences even when the true model is not logit or probit. Unfortunately, other applications of logit and probit­-including a common approach to testing a hypothesis that independent variables interact in influencing the probability of event occurrence­-are not nearly as forgiving of the uncertainty. In some situations of specification uncertainty, we can improve the quality of estimated effects by relying on the Akaike Information Criterion [AIC] to choose the terms to be included in a model, but even these improved estimates leave much to be desired.

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Statistical Estimation in the Presence of Multiple Causal Paths Braumoeller, Bear F. Uploaded 04-13-1999 Keywords multiple paths equifinality statistics probit Abstract Large-N statistical methodology has in the past been criticized for its inability to model a phenomenon believed to be fundamental to social science research: equifinality, or multiple causal paths. I examine this claim and demonstrate that, although multiple causal paths are often hypothesized in political science research, tests rarely if ever reflect their logic. I then describe a procedure for constructing likelihood functions directly from the logic of multiple causal path theories so that the truth-status of such theories can be correctly evaluated with maximum likelihood techniques.

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Beyond Ordinary Logit: Taking Time Seriously in Binary Time-Series--Cross-Section Models Beck, Nathaniel Katz, Jonathan Tucker, Richard Uploaded 08-22-1997 Keywords binary time-series--cross-section data logit/probit temporal dependence grouped duration models complementary log-log cubic spline economic interdependence democratic peace war Abstract Researchers typically analyze time-series--cross-section data with a binary dependent variable (BTSCS) using ordinary logit or probit. However, BTSCS observations are likely to violate the independence assumption of the ordinary logit or probit statistical model. It is well known that if the observations are temporally related that the results of an ordinary logit or probit analysis may be misleading. In this paper, we provide a simple diagnostic for temporal dependence and a simple remedy. Our remedy is based on the idea that BTSCS data is identical to grouped duration data. This remedy does not require the BTSCS analyst to acquire any further methodological skills and it can be easily implemented in any standard statistical software package. While our approach is suitable for any type of BTSCS data, we provide examples and applications from the field of International Relations, where BTSCS data is frequently used. We use our methodology to re-assess Oneal and Russett's (1997) findings regarding the relationship between economic interdependence, democracy, and peace. Our analyses show that 1) their finding that economic interdependence is associated with peace is an artifact of their failure to account for temporal dependence and 2) their finding that democracy inhibits conflict is upheld even taking duration dependence into account.

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Paper

Endogeneity in Probit Response Models Freedman, David Sekhon, Jasjeet Uploaded 05-28-2008 Keywords Bivariate probit sample selection identification indefinite Hessian optimization Abstract In this paper, we look at conventional methods for removing endogeneity bias in regression models, including the linear model and the probit model. The usual Heckman two-step procedure should not be used in the probit model: from a theoretical perspective, this procedure is unsatisfactory, and likelihood methods are superior. However, serious numerical problems occur when standard software packages try to maximize the biprobit likelihood function, even if the number of covariates is small. The log likelihood surface may be nearly flat, or may have saddle points with one small positive eigenvalue and several large negative eigenvalues. We draw conclusions for statistical practice. Finally, we describe the conditions under which parameters in the model are identifable; these results appear to be new.

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Paper

Economic Perceptions and Information in a Heterogeneous Electorate Willette, Jennifer R. Uploaded 04-18-1999 Keywords economic voting ordered probit economic perceptions Abstract he relationship between vote choice and voter evaluations of national economic conditions is well established. There is little attention paid to the formation of those economic evaluations, however. This oversight is important since we know that economic perceptions are not direct reflections of objective economic conditions. To address this issue, I develop a model of economic perceptions which considers that the impact of media information on economic evaluations will differ based upon the `information capability' of the individual. I use 1992 American National Election Survey data to estimate an ordered probit model of economic perceptions allowing the impact of personal economic information and media information to vary based upon the respondents information capability. I test the hypothesis that individuals with higher information capability will give greater weight to media information when evaluating the economy. As information capability decreases, respondents will weight personal economic conditions more heavily.

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Paper

Economics, Entitlements and Social Issues: Voter Choice in the 1996 Presidential Election Alvarez, R. Michael Nagler, Jonathan Uploaded 08-21-1997 Keywords elections issues ideology economic voting economy multinomial probit Abstract In this paper we examine three sets of explanations for the outcome of the 1996 presidential election campaign. First, we look at the effects of voter perceptions of the national economy on voter support for Clinton. Second we look at the effects of candidate and voter positions on a number of issues and on ideology. Last, we seek to understand whether other issues --- social issues such as abortion as well as issues revolving around entitlements and taxation --- played significant roles in this election. Thus this work extends the work of Alvarez and Nagler (1995), and enriches it with analysis of a more comprehensive set of issues considered. In the end, we are able to pull together each of these different sets of explanations into a consistent analysis of the 1996 presidential election which shows why Clinton won this race, but which also helps us understand why it was that both Dole and Perot fell so far from electoral victory.

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Paper

Nonparametric Priors For Ordinal Bayesian Social Science Models: Specification and Estimation Gill, Jeff Casella, George Uploaded 08-21-2008 Keywords generalized linear mixed model ordered probit Bayesian approaches nonparametric priors Dirichlet process mixture models nonparametric Bayesian inference Abstract A generalized linear mixed model, ordered probit, is used to estimate levels of stress in presidential political appointees as a means of understanding their surprisingly short tenures. A Bayesian approach is developed, where the random effects are modeled with a Dirichlet process mixture prior, allowing for useful incorporation of prior information, but retaining some vagueness in the form of the prior. Applications of Bayesian models in the social sciences are typically done with ``noninformative'' priors, although some use of informed versions exists. There has been disagreement over this, and our approach may be a step in the direction of satisfying both camps. We give a detailed description of the data, show how to implement the model, and describe some interesting conclusions. The model utilizing a nonparametric prior fits better and reveals more information in the data than standard approaches.

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Paper

Primaries and Turnout Kanthak, Kristen Morton, Becky Uploaded 07-09-2003 Keywords primaries turnout bivariate probit selection model treatment effects Abstract We consider the effects of differences in primary systems on voter turnout in primaries as well as the effect of holding primaries on general election turnout and support for candidates chosen in primaries. The analysis is based on a group majority voting model of turnout where candidates from two major parties simultaneously make strategic entry decisions and mobilize voters strategically in primaries and general elections if they choose to enter. We evaluate the model's predictions using data from midterm Congressional primaries and general elections in the 1980s. We use a two-stage estimation process. First, the model's predictions concerning the effects of primary system differences on whether primaries occur and the vote totals in primaries is estimated using a maximum likelihood bivariate probit selection model. We find that primary system variables do have significant effects on whether primaries are held and to some extent affect vote totals in primaries, although there are interesting party specific differences suggesting that Republicans see advantages from mobilizing voters in open primary systems while Democrats benefit in semi-closed primary systems. Second, the estimated vote totals in the primaries are used as treatment variables via an instrumental variables approach in a simultaneous equation system with two dependent variables general election vote totals and the vote share of the Democratic party's candidate. We find that voting in primaries has a positive and significant effect on voting in general elections and significantly increase the vote share of the party holding the primary, suggesting that the arguments that primaries by their existence decrease voter turnout and hurt parties holding them have no support.

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Paper

Representation and Salient Issues: Legislator Responsiveness to the Service Constituency Bennett, Sherry L. Smith, Renee M. Uploaded 04-21-1999 Keywords service constituency opinion activation U.S. trade policy ordered probit IV estimation Abstract ormal models of the supply of public policy and of information transmission between lobbyists and legislators imply that the preferences of both organized and informed, but unorganized, interests influence legislators' vote choices. Denzau and Munger (1986) refer to these citizens as a legislator's service constituency. In this paper, we provide argument and evidence to show that the concept of a service constituency is crucial to theoretical explanations and empirical investigations of a legislator's responsiveness to constituent demands on salient issues. We also provide theory and evidence to account for the process by which unorganized citizens become part of a service constituency. Our argument emphasizes the effects of interest group competition on information accessibility and opinion activation for diffuse, unorganized citizens. Our empirical evidence provides strong support for our hypotheses about opinion activation and the effects of the service constituency on legislative behavio

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Paper

The Consequences of Majority-Minority Districts for Representation: Evidence of Partisan Mobilization, Countermobilization and Demobilization Brandt, Patrick T. Bailey, Michael Uploaded 08-21-1997 Keywords Multinomial probit panel data methods simulated maximum likelihood probability simulation redistricting Abstract Few analyses of the effects of race-based congressional redistricting have used survey data to analyze the implications of redistricting. This type of micro-level data can add significant intuition to aggregate data analysis. This paper looks at whether voters respond to redistricting by mobilizing, demobilizing, or countermobilizing using panel data from the 1990-1992 National Election Study. A 2-period vote choice model is estimated using a multiperiod multinomial probit model, and controlling for the effects of redistricting. Results show that the presence of black Democratic candidates in majority-minority districts after redistricting reduces turnout by white voters for the Democratic candidates.

40

Paper

Estimation in Dirichlet Random Effects Models Kyung, Minjung Gill, Jeff Casella, George Uploaded 04-28-2009 Keywords generalized linear mixed model Dirichlet process random effects model precision parameter likelihood Gibbs sampling importance sampling probit mixed Dirichlet random effects model Abstract We develop a new Gibbs sampler for a linear mixed model with a Dirichlet process random effect term, which is easily extended to a generalized linear mixed model with a probit link function. Our Gibbs sampler exploits the properties of the multinomial and Dirichlet distribution, and is shown to be an improvement, in terms of operator norm and efficiency, over other commonly used MCMC algorithms. We also investigate methods for the estimation of the precision parameter of the Dirichlet process, finding that maximum likelihood may not be desirable, but a posterior mode is a reasonable approach. Examples are given to show how these models perform on real data. Our results complement both the theoretical basis of the Dirichlet process nonparametric prior and the computational work that has been done to date. Forthcoming: Annals of Statistics.

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Paper

Connecting Interest Groups and Congress: A New Approach to Understanding Interest Group Success Victor, Jennifer Nicoll Uploaded 07-16-2002 Keywords Interest Groups Congress Multiple Imputation Bayesian Information Criterion Ordinal Probit Non-nested Models Legislative Context Abstract The primary challenge in explaining interest group legislative success in Congress has been methodological. The discipline requires at least two critical elements to make progress on this important question. First, we need a theory that accounts for the highly interactive spatial game between interest groups and legislators. Second, the discipline needs an empirical model that associates interest groups and their activities with specific congressional bills. In this project I begin to contribute to our understanding of the complex relationship between interest groups and Congress. I develop a theory of group success that is based upon the strategies in which groups engage, the groups' organizational capacity, and the strategic context of legislation. I predict that groups will tailor their activities (and strategically spend their resources) in Congress based upon two critical factors: whether the group supports or opposes the legislation, and the legislative environment for the bill. To test this model I develop a unique sampling procedure and survey design. I use legislative hearings to generate a sample of groups that are associated with specific issues and survey them about their activities on those issues. Then, I associate each group's issue with a specific bill in Congress. I then track the bill to discern its final status. I create a dependent variable of interest group success that is based on the group's position (favor or oppose) and the final status of the bill. This sampling procedure and dependent variable allow me to make inferences about group behavior over specific legislative proposals. I develop independent variables of group activity, group organizational capacity, and legislative context from the survey instrument and objective information about the bills. To fill in gaps in the survey data set, I use a multiple imputation method that generates plausible values based on given distributions of data. I estimate two models-one for groups in favor of legislation, and one for opposition groups. The ordinal probit models generally support the theoretical expectations. In sum, I find that groups can best expend their resources in pursuit of rules that advantage their position rather than fighting for bill content.

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Paper

Estimation and Inference by Bayesian Simulation: an on-line resource for social scientists Jackman, Simon Uploaded 08-30-1999 Keywords Markov chain Monte Carlo Bayesian statistics how-to BUGS ordinal probit time series Abstract http://tamarama.stanford.edu/mcmc a Web-based on-line resource for Markov chain Monte Carlo, specifically tailored for social scientists. MCMC is probably the most exciting development in statistics in the last ten years. But to date, most applications of MCMC methods are in bio-statistics, making it difficult for social scientists to fully grasp the power of MCMC methods. In providing this on-line resource I aim to overcome this deficiency, helping to put MCMC in the reach of social scientists. The resource comprises: (*) a set of worked examples (*) data and programs (*) links to other relevant web sites (*) notes and papers At the meetings in Atlanta, I will present two of the worked examples, which are part of this document: (*) Cosponsor: computing auxiliary quantities from MCMC output (e.g., percent correctly predicted in a logit/probit model of legislative behavior; cf Herron 1999). (*) Delegation: estimating a time-series model for ordinal data (e.g., changes to the U.S. president's discretionary power in trade policy, 1890-1990; cf Epstein and O'Halloran 1996).

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Paper

The "Miracle" Revisited: An Examination of The Micro-Foundations of Aggregate Public Opinion Berinsky, Adam Uploaded 08-18-1997 Keywords public opinion heteroskedastic probit ordered probit selection bias item non-response Abstract One of the best-known findings in the public opinion literature is that individual responses to survey questions, by and large, both exhibit little constraint and are highly unstable over time. One response to this bleak finding has been to search for coherence and stability at the aggregate level. Scholars who adopt this approach -- most notably Page and Shapiro (1992) -- argue that though most individuals are poorly informed about politics and may have unstable attitudes, the "miracle TRUNCATED.

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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

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Paper

A Panel Probit Analysis of Campaign Contributions and Roll Call Votes Wawro, Gregory Uploaded 09-07-1999 Keywords campaign finance panel data methods logit probit random effects GMM estimators Abstract Political scientists have long been concerned with the effects of campaign contributions on roll call voting. However, methodological problems have hampered attempts to assess the degree to which contributions affect voting. One of the key problems is that it is difficult to untangle the effect of contributions from the effect of a member's predisposition to vote one way or another. That is, political action committees (PACs) contribute to members of Congress who are likely to vote the way the PACs favor even in the absence of contributions. A PAC donation to a friendly member might be misconstrued as causing a member to vote a particular way, when in reality the member would have voted that way to begin with. It is therefore crucial to account for a member's propensity to vote in a particular way in order to assess the influence of contributions. One way that studies have done this is to use ideological ratings developed by interest groups. This approach is problematic, however, because the ratings are built from roll call votes and thus will introduce bias if campaign contributions affect the votes used to compute the ratings. In order to circumvent the problem of accounting for voting predispositions, I use panel data methods which, unfortunately, have seen almost no application in political science. These methods enable us to account for individual specific effects which are difficult or impossible to measure, such as the predisposition to vote for or against a particular type of legislation. To employ these methods, I build panels of roll call votes on legislation that business and labor groups have indicated are important for their interests. Using panel data estimators, I determine the effects of contributions from corporate and labor PACs on the probability of voting ``aye'' or ``nay'', while accounting for members' propensities to vote in particular directions. I find that contributions have minimal to no effects on roll call votes, while short-term factors including monthly unemployment and support for the president in the district have substantial effects.

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Paper

The Political Entropy of Vote Choice: An Empirical Test of Uncertainty Reduction Gill, Jeff Uploaded 08-05-1997 Keywords Entropy Voting Under Uncertainty Proximity Spatial Voting Model Heteroscedastic Probit Abstract Recent literature in voting theory has developed the idea that individual voting preferences are probabilistic rather than strictly deterministic. This work builds upon spatial voting models (Enelow and Hinich 1981, Ferejohn and Fiorina 1974, Davis, DeGroot and Hinich 1972, Farquharson 1969) by introducing probabilistic uncertainty into the calculus of voting decision on an individual level. Some suggest that the voting decision can be modeled with traditional probabilistic tools of uncertainty (Coughlin 1990, Coughlin and Nitzen 1981). Entropy is a measure of uncertainty that originated in statistical thermodynamics. Essentially, entropy indicates the amount of uncertainty in probability distributions (Soofi 1992), or it can be thought of as signifying a lack of human knowledge about some random event (Denbigh and Denbigh, 1985). Entropy in statistics developed with Kolmogorov (1959), Kinchin (1957), and Shannon (1948), but has rarely been applied to social science problems. Exceptions include Darcy and Aigner's (1980) use of entropy to analyze categorical survey responses in political science, and economic applications by Theil (1967) and Theil and Fiebig (1984). I examine voters' uncertainty as they assess candidates, and measure policy positions. I then test whether or not these voters minimize the cost of voting (specifically the cost of information) by determining a maximum entropy selection. Except for the inclusion of entropy terms, this approach is similar to others in the recent literature. In this paper I develop a measure to aggregate evaluation of issue uncertainty and corresponding vote choice where the uncertainty parameterization is derived from an entropy calculation on a set of salient election issues. The primary advantage of this approach is that it requires very few assumptions about the nature of the data. Using 1994 American National Election Study survey data from the Center for Political Studies, I test the hypothesis that the ``Contract with America'' reduced voter uncertainty about the issue positions of Republican House candidates. The entropic model suggests that voters used the written and explicit Republican agenda as a means of reducing issue uncertainty without substantially increasing time spent evaluating candidate positions.

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Paper

An Agenda for New Political Methodology: Microfoundations and ART Achen, Christopher H. Uploaded 08-29-2001 Keywords logit probit scobit microfoundations Abstract The last two decades have brought revolutionary change to the field of political methodology. Steady gains in theoretical sophistication have combined with explosive increases in computing power to produce a profusion of new estimators for applied political researchers. Attendance at the annual Summer Meeting of the Methodology Section has multiplied many times, and section membership is among the largest in APSA. All these are signs of success. Yet there are warning signs, too. This paper, written to appear in the {em Annual Review of Political Science}, attempts to critically summarize current developments in the young field of political methodology. It focuses on recent generalizations of dichotomous dependent variable estimators like logit and probit, arguing that even our best new work stands in need of firmer connection to credible models of human behavior and more sophisticated work habits for discovering reliable empirical generalizations.

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Paper

The Two Faces of Public Opinion Berinsky, Adam Uploaded 04-13-1998 Keywords public opinion selection bias item non-response social desirability bivariate probit Abstract In this paper I trace out the aggregate effects of the social forces in the survey interview that might influence the opinions which individuals express. First, I advance the "Mediated Communication" theory of the survey response, which builds on existing models of public opinion in the political science literature by accounting for effects related to the social context of the survey setting. I then discuss how the aggregation process could compound these individual-level effects to create an opinion signal which is a poor representation of the collective public's policy preferences. As an illustration of these effects and the resulting difficulties involved in measuring aggregate opinion on socially sensitive issues, I use National Elections Study (NES) data from 1990-1994 to show that public opinion polls overstate support for school integration. Specifically, individuals who harbor anti-integration sentiments are likely to hide their socially unacceptable opinions behind a mask of indifference. Finally, in order to confirm the validity of these findings, I show that the same methods which predict that opinion polls understate true opposition to government involvement in school integration also predict the results of the 1989 New York City mayoral election -- an election where the charged racial atmosphere made accurate polling difficult, if not impossible -- more accurately than the marginals of the pre-election polls taken in the weeks leading to the election. All told, these results suggests that survey questions on school integration -- and more generally questions on racial attitudes -- may provide an inaccurate picture of true public sentiment on such sensitive issues.

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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.

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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.