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A New Non-Parametric Matching Method for Bias Adjustment with Applications to Economic Evaluations Sekhon, Jasjeet Uploaded 05-11-2008 Keywords semiparametric and nonparametric matching methods observational studies randomized controlled trials health economic evaluation Abstract In health economic studies that use observational data, a key concern is how to adjust for imbalances in baseline covariates due to the non-random assignment of the programs under evaluation. Traditional methods of covariate adjustment such as regression and propensity score matching are model dependent and often fail to replicate the results of randomized controlled trials. We demonstrate a new non-parametric matching method, Genetic Matching, which is a generalization of propensity score and Mahalanobis distance matching, using two contrasting case studies. In the first, an economic evaluation of a clinical intervention (Pulmonary Artery Catheterization), applying Genetic Matching to observational data replicates the substantive results of a corresponding randomized controlled trial unlike the extant literature. And in the second case study evaluating capitation versus fee-for service, Genetic Matching radically improves balance on baseline covariates and overturns previous conclusions based on traditional methods.

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Scaling the Critics: Uncovering the Latent Dimensions of Movie Criticism with An Item Response Approach Peress, Michael Spirling, Arthur Uploaded 07-04-2008 Keywords threshold utility model film ideal points Abstract We study the critical opinions of expert movie reviewers as an item response problem. We develop a framework that models an individual's decision to approve or disapprove of an item. Using this framework, we are able to recover the locations of movies and ideal points of critics in the same multi-dimensional space. We demonstrate that a three dimensional model captures much of the variation in critical opinions. The first dimension signifies movie 'quality' while the other two connote the nature and subject matter of the films. We then demonstrate that the dimensions uncovered from our 'threshold utility model' are statistically significant predictors of a movie's success, and are particularly useful in predicting the success of `independent' films.

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Is Matching Really Essential? Middleton, Joel Uploaded 07-11-2008 Abstract Conference poster

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What Can Be Learned from a Simple Table? Bayesian Inference and Sensitivity Analysis for Causal Effects from 2x2 and 2x2xK Tables in the Presence of Unmeasured Confounding Quinn, Kevin Uploaded 09-07-2008 Keywords causal inference bayesian inference sensitivity analysis unmeasured confounding Abstract What, if anything, should one infer about the causal effect of a binary treatment on a binary outcome from a $2 imes 2$ cross-tabulation of non-experimental data? Many researchers would answer ``nothing'' because of the likelihood of severe bias due to the lack of adjustment for key confounding variables. This paper shows that such a conclusion is unduly pessimistic. Because the complete data likelihood under arbitrary patterns of confounding factorizes in a particularly convenient way, it is possible to parameterize this general situation with four easily interpretable parameters. Subjective beliefs regarding these parameters are easily elicited and subjective statements of uncertainty become possible. This paper also develops a novel graphical display called the confounding plot that quickly and efficiently communicates all patterns of confounding that would leave a particular causal inference relatively unchanged.

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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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How Similar Are They? Rethinking Electoral Congruence Wittenberg, Jason Uploaded 07-05-2008 Keywords voting elections volatility persistence correlation concordance Abstract Electoral continuity and discontinuity have been a staple of voting research for decades. Most researchers have employed Pearson's r as a measure of congruence between two electoral outcomes across a set of geographic units. This paper argues that that practice should be abandoned. The correlation coefficient is almost always\r\nthe wrong measure. The paper recommends other quantities that better accord with\r\nwhat researchers usually mean by electoral persistence. Replications of prior studies in American and comparative politics demonstrate that the consequences of using r\r\nwhen it is inappropriate can be stark. In some cases what we think are continuities are actually discontinuities.

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Buying Votes with Public Funds in the US Presidential Election: Are Swing or Core Voters Easier to Buy Off? Chen, Jowei Uploaded 07-09-2008 Keywords distributive politics voting turnout elections Abstract In the aftermath of the summer 2004 Florida hurricane season, the Federal Emergency Management Agency (FEMA) distributed $1.2 billion in disaster aid among 2.6 million individual applications for assistance. This research measures the relative costs and benefits of using FEMA aid to buy votes from swing voters and core voters. First, I compare precinct-level vote counts and individual voter turnout records from the post-hurricane (November 2004) and pre-hurricane (2000 and 2002) elections to measure the effect of FEMA aid on Bush's vote share. Using a two-stage least squares estimator, with hurricane severity measures as instruments for FEMA aid, this analysis reveals that core Republican voters are most electorally responsive to FEMA aid -- $7,000 buys one additional vote for Bush. By contrast, in moderate precincts, each additional Bush vote costs $21,000, while voters in Democratic neighborhoods are unresponsive to receiving FEMA aid. Additionally, by tracking the geographic location of each aid recipient, the data reveal that FEMA favored applicants from Republican neighborhoods over those from Democratic or moderate neighborhoods, even conditioning on hurricane severity, average home values, and demographics. Collectively, these results demonstrate the Bush administration's disproportionate distribution of FEMA disaster aid toward core Republican areas was the optimal strategy for maximizing votes in the Presidential election.

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Estimating and Bounding Mechanism Specific Causal Effects Glynn, Adam Uploaded 07-03-2008 Keywords counterfactuals causal mechanism Abstract Political scientists often cite the importance of mechanism specific causal knowledge, both for its intrinsic scientific value and as a necessity for informed policy. However, outside the framework of additive linear regression models with homogenous causal effects, mechanism specific effects are, in general, not estimated explicitly. Counterfactual causal models allow the formal definition of such concepts as direct, indirect, and mechanism specific effects, and the derivation of conditions for their identification (point or interval). In this paper, I demonstrate the use of counterfactuals to decompose causal effects into mechanism specific effects, showing that estimation and bounding can be accomplished with minor adjustments to standard techniques. I illustrate this methodology with examples from American and Comparative Politics.

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The playing field shifts: predicting the seats-votes curve in the 2008 U.S. House election Kastellec, Jonathan Gelman, Andrew Chandler, Jamie Uploaded 06-01-2008 Keywords Congress incumbency partisan bias seats-votes curve Abstract This paper predicts the seats-votes curve for the 2008 U.S House elections. We document how the electoral playing field has shifted from a Republican advantage between 1996 and 2004 to a Democratic tilt today. Due to the shift in incumbency advantage from the Republicans to the Democrats, compounded by a greater number of retirements among Republican members, we show that the Democrats now enjoy a partisan bias, and can expect to win more seats than votes for the first time since 1992. While this bias is not as large as the advantage the Republicans held in 2006, it is likely to help the Democrats win more seats than votes and thus expand their majority.

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Adjusting Experimental Data Keele, Luke McConnaughy, Corrine White, Ismail Uploaded 07-06-2008 Keywords Experiments matching ANCOVA blocking Abstract Randomization in experiments allows researchers to assume that the treatment and control groups are balanced with respect to all characteristics except the treatment. Randomization, however, only makes balance probable, and accidental covariate imbalance can occur for any specific randomization. As such, statistical adjustments for accidental imbalance are common with experimental data. The most common method of adjustment for accidental imbalance is to use least squares to estimate the analysis of covariance (ANCOVA) model. ANCOVA, however, is a poor choice for the adjustment of experimental data. It has a strong functional form assumption, and the least squares estimator is notably biased in sample sizes of less than 500 when applied to the analysis of treatment effects. We evaluate alternative methods of adjusting experimental data. We compare ANCOVA to two different techniques. The first technique is a modified version of ANCOVA that relaxes the strong functional form assumption of this model. The second technique is matching, and we test the differences between two matching methods. For the first, we match subjects and then randomize treatment across pairs. For the second, we randomize the treatment and match prior to the estimation of treatment effects. We use all three techniques with data from a series of experiments on racial priming. We find that matching substantially increases the efficiency of experimental designs.

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Learning from the Campaign Context: Multivariate Matching with Exposure Christenson, Dino Uploaded 07-14-2008 Keywords multivariate matching non-bipartite matching signed rank test sensitivity analysis political information presidential campaigns Abstract PolMeth XXV poster.

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Cosponsorship in the U.S. Senate: A Multilevel Approach to Detecting Subtle Social Predictors of Legilslative Support Gross, Justin Uploaded 09-14-2008 Keywords Congress cosponsorship social network analysis multilevel models mixed effects GLMM Abstract Why do members of Congress choose to cosponsor legislation proposed by their colleagues and what can we learn from their patterns of cosponsorship? To answer these questions properly requires models that respect the relational nature of the relevant data and the resulting interdependence among observations. We show how the inclusion of carefully selected random effects can capture network-type dependence, allowing us to more confidently investigate senators' propensity to support colleagues' proposals. To illustrate, we examine whether certain social factors such as demographic similarities, opportunities for interaction, and institutional roles are associated with varying odds of cosponsorship during the 2003-04 (108th) Senate.

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Objections to Bayesian statistics Gelman, Andrew Uploaded 06-01-2008 Keywords comparison of methods foundations of statistics Abstract Bayesian inference is one of the more controversial approaches to statistics. The fundamental objections to Bayesian methods are twofold: on one hand, Bayesian methods are presented as an automatic inference engine, and this raises suspicion in anyone with applied experience. The second objection to Bayes comes from the opposite direction and addresses the subjective strand of Bayesian inference. This article presents a series of objections to Bayesian inference, written in the voice of a hypothetical anti-Bayesian statistician. The article is intended to elicit elaborations and extensions of these and other arguments from non-Bayesians and responses from Bayesians who might have different perspectives on these issues.

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Binary and Ordinal Time Series with AR(p) Errors: Bayesian Model Determination for Latent High-Order Markovian Processes Pang, Xun Uploaded 07-06-2008 Keywords Autoregressive Errors Auxiliary Particle Filter Fixed-lag Smoothing Markov Chain Monte Carlo (MCMC) Political Science Sampling Importance Resampling(SIR) Abstract To directly and adequately correct serial correlation in binary and ordinal response data, this paper proposes a probit model with errors following a pth-order autoregressive process, and develops simulation-based methods in the Bayesian context to handle computational challenges of posterior estimation, model comparison, and lag order determination. Compared to the extant methods, such as quasi-ML, GCM, and and simulation-based ML estimators, the current method does not rely on the properties of the big variance-covariance matrix or the shape of the likelihood function. In addition, the present model efficiently handles high-order autocorrelated errors that raise computationally formidable difficulties to the conventional methods. By applying a mixed sampler of the Gibbs and Metropolis-Hastings algorithm, the posterior distributions of the parameters do not depend on initial observations. The auxiliary particle filter, complemented by the fixed-lag smoothing, is extended to approximate Bayes Factors for models with latent high-order Markov processes. Computational methods are tested with empirical data. Energy cooperation policies of the International Energy Agency are analyzed in terms of their effects on global oil-supply security. The current model with different lag orders, together with other competitive models, is estimated and compared.

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Investigate at extreme right : Between total immersion and participant observations, the example of French National Front (2006-2008) Mermat, Djamel Uploaded 07-18-2008 Keywords France Far right electoral campaigns Methodology Immersion Participant observation Political party. Abstract There is a particular situation involving the NF that has been noticeably neglected to date in France: the capture live of the motivations and actions of these new partisans who rallied to the movement during the last three years (Glenn, 2005: 35-43). We must also recognize that enabling us to understand this party in "campaigning mode," there is insufficient knowledge. Nonetheless, if we hope to remedy these basic two weaknesses, what methods could researchers employ? Consequently, what can political science methodology eventually learn from an adjustment in the status of the researcher on the ground and at the time of the inquiry? More precisely: what advantages do participant observation employed almost daily offer? What are the basic contributions of total immersion in the "Frontist" environment? Given these questions, we wanted, based on comparative qualitative research, to explain what fund the validity of the results obtained (Kent, 2001), through establishing a cost-benefit analysis of the use of two different methods, of two inherently quite distinct presentations. Indeed, the result very rarely mentions the researcher's many ups and downs. However, the successes and inevitable failures of the ethnographic investigation condition the nature of the data collected. Therefore, this is an attempt to address several methodological deficiencies or silences, and to reverse certain epistemological biases, through returning to concepts whose substance needs clarification: "participant observation," "empathy," "total immersion," and "infiltration." All the underpinnings of the research do, however, draw attention to the manner in which the political analyst created his methodology and analytical categories, as well as his own approach to the subject under study. As a result, at first we will emphasize the difference in scale between our two research fields, since it led to our adoption of another approach to the subject (I). Thus, we first chose as our research location the North Flanders Federation from June 2006 to the start of November 2007, the beginning of the presidential campaign, up to the presentation of the assessment of the local councillors. Still, from the month of June 2007, and without abandoning our initial site, we progressively accorded increasing attention to the "new partisans" supporting Marine Le Pen and Steeve Briois in the 14th constituency of Pas-de-Calais, in particular in the city of Henin-Beaumont. In the first week of December 2007, this led us to commence our exploration of the diversity of actors of the General Headquarters of the "Henin-Beaumont pour Vous" list campaign. Henin-Beaumont belongs to the Federation of Mayors of Mid-Sized Cities. Well, to date, no study on the NF has been interested in its "propaganda" strategy (Kalinowski, 2005) for a mid-sized city and during an election campaign, even less for a municipal. The idea was to slide, over a period of several weeks from Flanders to Pas-de-Calais, from the status of participant observer outside of the group, to that of active member at the periphery of the central group, thus, integrated in the group (Strauss, Corbin, and Soulet, 2004). This process offered the researcher the opportunity to situate himself somewhere between simply "taking part" and being "uncovered." Thus, the necessity of reacting, at the spur of the moment, when confronted with the unexpected (II), was the most challenging aspect. Moreover, it is this absence, of a recent localized investigation through direct observation over an extended period, of a political enterprise still provoking concerns and anathemas that propelled us to study what the FN electoral campaigns do to the researcher and his analytical tools.

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Just Plain Data Analysis: Common Statistical Fallacies in Analyses of Social Indicator Data Klass, Gary Uploaded 09-17-2008 Keywords Teaching statistical fallacies social indicators Abstract This paper presents a short summary of the most common statistical fallacies found in public debates employing social indicator data as the evidentiary premises of arguments about politics and public affairs. The purpose is to offer students a convenient framework for evaluating, and developing the own, arguments relying on social indicator data.

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Why we (usually) don't have to worry about multiple comparisons Gelman, Andrew Hill, Jennifer Yajima, Masanao Uploaded 06-01-2008 Keywords Bayesian inference hierarchical modeling multiple comparisons type S error statistical significance Abstract The problem of multiple comparisons can disappear when viewed from a Bayesian perspective. We propose building multilevel models in the settings where multiple comparisons arise. These address the multiple comparisons problem and also yield more efficient estimates, especially in settings with low group-level variation, which is where multiple comparisons are a particular concern. Multilevel models perform partial pooling (shifting estimates toward each other), whereas classical procedures typically keep the centers of intervals stationary, adjusting for multiple comparisons by making the intervals wider (or, equivalently, adjusting the p-values corresponding to intervals of fixed width). Multilevel estimates make comparisons more conservative, in the sense that intervals for comparisons are more likely to include zero; as a result, those comparisons that are made with confidence are more likely to be valid.

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Registration and Voting under Rational Expectations Achen, Christopher Uploaded 07-07-2008 Keywords turnout registration Heckman Dubin-Rivers expectations Abstract Alone among modern democracies, the United States makes voter registration a personal responsibility rather than a governmental function. In almost all states, registration deadlines occur well before elections. Failure to register by the deadline makes the probability of voting exactly zero. This sequential feature of the registration and voting decisions has been skipped over by most researchers, who simply ignore registration. Others, notably Timpone (1998), have used the seemingly appropriate Heckman-style selection model, but have arrived at findings difficult to believe. This paper investigates the appropriate choice of a registration model under a rational expectations assumption about the desire to vote, showing that, rather surprisingly, conventional selection models will generally perform less well than ignoring the selection effect of registration entirely. However, neither is quite correct. Finally then, the paper proposes and tests a flexible model for registration as a step toward substantively appropriate joint modeling of registration and voting.

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The Persuasive Effects of Direct Mail: A Regression Discontinuity Approach Meredith, Marc Kessler, Daniel Gerber, Alan Uploaded 07-21-2008 Keywords regression discontinuity direct mail persuasion turnout Abstract During the contest for Kansas attorney general in 2006, an organization sent out 6 pieces of mail criticizing the incumbent's conduct in office. We exploit a discontinuity in the rule used to select which households received the mailings to identify the causal effect of mail on vote choice and voter turnout. We find these mailings had both a statistically and politically significant effect on the challenger's vote share. Our estimates suggest that a ten percentage point increase in the amount of mail sent to a precinct increased the challenger's vote share by approximately three percentage points. Furthermore, our results suggest that the mechanism for this increase was persuasion rather than mobilization.

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Causal Inference with Differential Measurement Error: Nonparametric Identification and Sensitivity Analyses of a Field Experiment on Democratic Deliberations Imai, Kosuke Yamamoto, Teppei Uploaded 06-30-2008 Keywords differential misclassification nonparametric bounds retrospective studies sensitivity analysis survey measurements Abstract Political scientists have long been concerned about the validity of survey measurements. Although many have studied classical measurement error in linear regression models where the error is assumed to arise completely at random, in a number of situations the error may be correlated with the outcome. We analyze the impact of differential measurement error on causal estimation. The proposed nonparametric identification analysis avoids arbitrary modeling decisions and formally characterizes the roles of additional assumptions. We show the serious consequences of differential misclassification and offer a new sensitivity analysis that allows researchers to evaluate the robustness of their conclusions. Our methods are motivated by a field experiment on democratic deliberations, in which one set of estimates potentially suffers from differential misclassification. We show that an analysis ignoring differential measurement error may considerably overestimate the causal effects. This finding contrasts with the case of classical measurement error which always yields attenuation bias.

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Going beyond the book: Toward critical reading in statistics teaching Gelman, Andrew Uploaded 06-01-2008 Keywords categorical and continuous variables handedness menstruation primary sources secondary sources sex ratio teaching textbooks traffic accidents Abstract We can improve our teaching of statistical examples from books by collecting further data, reading cited articles, and performing further data analysis. This should not come as a surprise, but what might be new is the realization of how close to the surface these research opportunities are: even influential and celebrated books can have examples where more can be learned with a small amount of additional effort. We discuss three examples that have arisen in our own teaching: an introductory textbook that motivated us to think more carefully about categorical and continuous variables; a book for the lay reader that misreported a study of menstruation and accidents; and a monograph on the foundations of probability that overinterpreted statistically insignificant fluctuations in sex ratios.

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Voter transition estimation in multiparty systems Andreadis, Ioannis Uploaded 07-07-2008 Keywords Elections Voter transition rates Ecological inference Multiparty systems Abstract Recent advances in the field of ecological inference have provided researchers with new tools to estimate voter transition in two-party systems. Although some researchers have dealt with the R x C ecological inference problem, voter transition estimation remains a difficult and tedious goal. As a result scholars of multi-party systems still struggle with their electoral data. In this paper we present a new approach and we propose a new method that deals with this issue.

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Exploiting a Rare Shift in Communication Flows to Document News Media Persuasion: The 1997 United Kingdom General Election Ladd, Jonathan Lenz, Gabriel Uploaded 07-30-2008 Keywords Media persuasion endorsements campaigns elections matching causal inference Abstract Using panel data and matching techniques, we exploit a rare change in communication flows -- the endorsement switch to the Labour Party by several prominent British newspapers before the 1997 United Kingdom general election -- to study the persuasive power of the news media. These unusual events provide an opportunity to test for news media persuasion while avoiding methodological pitfalls that have plagued previous studies. By comparing readers of newspapers that switched endorsements to similar individuals who did not read these newspapers, we estimate that these papers persuaded a considerable share of their readers to vote for Labour. Depending on the statistical approach, the point estimates vary from about 10 percent to as high as 25 percent of readers. These findings provide rare, compelling evidence that the news media exert a powerful influence on mass political behavior.

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Bayesian Combination of State Polls and Election Forecasts Lock, Kari Gelman, Andrew Uploaded 09-21-2008 Keywords election prediction pre-election polls Bayesian updating shrinkage estimation Abstract In February of 2008, SurveyUSA polled 600 people in each state and asked who they would vote for in either head-to-head match-up: Obama vs. McCain, and Clinton vs. McCain. Here we integrate these polls with prior information; how each state voted in comparison to the national outcome in the 2004 election. We use Bayesian methods to merge prior and poll data, weighting each by its respective information. The variance for our poll data incorporates both sampling variability and variability due to time before the election, estimated using pre-election poll data from the 2000 and 2004 elections. The variance for our prior data is estimated using the results of the past nine presidential elections. The union of prior and poll data results in a posterior distribution predicting how each state will vote, in turn giving us posterior intervals for both the popular and electoral vote outcomes of the 2008 presidential election. Lastly, these posterior distributions are updated with the most recent poll data as of August, 2008.

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Teaching Bayesian applied statistics to graduate students in political science, sociology, public health, education, economics, ... Gelman, Andrew Uploaded 06-13-2008 Keywords Bayesian statistics education Abstract I share some thoughts on teaching applied regression and Bayesian methods to students in political science and other fields.

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Research Opportunities - The 2009/10 British Election Study Clarke, Harold Sanders, David Stewart, Marianne Whiteley, Paul Uploaded 07-07-2008 Keywords electons experiments in-person internet public opinion Abstract The 2009/10 British Election Study (BES) will include significant research opportunities for students of voting, elections and public opinion. The BES will have three major components: (a) in-person pre-post election surveys; (b) rolling campaign internet panel survey (RCPS); (c) 48 inter-election monthly continuous monitoring surveys (CMS) with annual panel components. Each CMS survey will offer researchers opportunities to include question batteries including experiments. Participation is free and data release is very fast. Proposals for research modules reviewed by BES Advisory Board and P.I.s. Proposals also entertained for research modules on core and RCPS components.

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Friendships Moderate an Association Between a Dopamine Gene Variant and Political Ideology Settle, Jaime Dawes, Christopher Hatemi, Peter Christakis, Nicholas Fowler, James Uploaded 06-08-2008 Abstract Scholars in many fields have long noted the importance of social context in the development of political ideology. Recent work suggests that political ideology also has a heritable component, but no specific gene variant associated with political ideology has so far been identified. In this article we hypothesize that individuals with a genetic predisposition towards seeking out new experiences will tend to be more liberal, but only if they are embedded in a social context that provides them with multiple points of view. Using data from the National Longitudinal Study of Adolescent Health, we test this hypothesis by investigating an association between self-reported political ideology and the 7R variant of the dopamine receptor D4 gene (DRD4), which has previously been associated with novelty-seeking. We find that the number of friendships a person has in adolescence is significantly associated with liberal political ideology among those with DRD4-7R. Among those without the gene variant there is no association. This is the first study ever to elaborate a specific gene-environment interaction that contributes to ideological self-identification, and it highlights the importance of incorporating both nature and nurture into the study of politics.

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Design, Inference, and the Strategic Logic of Suicide Terrorism: A Rejoinder Clinton, Joshua Ashworth, Scott Ramsay, Kris Meirowitz, Adam Uploaded 09-25-2008 Keywords Research Design Terrorism Abstract In "Design, Inference, and the Strategic Logic of Suicide Terrorism", we show that Robert Papeâ??s work on suicide terrorism, particularly his 2003 American Political Science Review article, is deeply flawed. In "Methods and Findings in the Study of Suicide Terrorism" (2008), Pape claims that our criticisms of his work are incorrect. The bulk of his response, however, ignores the problem we identify in our comment; instead, he largely summarizes arguments from his later work, arguments that are irrelevant to our basic point. And when he eventually addresses the substance of our critique, Pape simply repeats the error that motivated our original comment.

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A Compositional-Hierarchical Model of Abstention under Compulsory Voting (poster) Katz, Gabriel Uploaded 06-18-2008 Keywords compulsory voting abstention compositional data hierarchical modelling MCMC. Abstract Invalid voting and electoral absenteeism are two important sources of abstention in compulsory voting systems. Previous studies in this area have not considered the correlation between both variables and ignored the compositional nature of the data, potentially leading to unfeasible results and discarding helpful information from an inferential standpoint. In order to overcome these problems, this paper develops a statistical model that accounts for the compositional and hierarchical structure of the data and addresses robustness concerns raised by the use of small samples that are typical in the literature. The model is applied to analyze invalid voting and electoral absenteeism in Brazilian legislative elections between 1945 and 2006 via MCMC simulations. The results show considerable differences in the determinants of both forms of non-voting; while invalid voting was strongly positively related both to political protest and to the existence of important informational barriers to voting, the influence of these variables on absenteeism is less evident. Comparisons based on posterior simulations indicate that the model developed in this paper fits the dataset better than several alternative modeling approaches and leads to different substantive conclusions regarding the effect of different predictors on the both sources of abstention.

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The Trouble with Tobit: A District-Level Sample Selection Model of Voting for Extreme Right Parties in Europe, 1980-2004 Bowyer, Benjamin Uploaded 07-07-2008 Keywords Tobit Heckman sample selection censored data aggregate data extreme right parties Abstract The growing electoral success of extreme right parties (ERPs) in many European countries has sparked academic interest in explaining variation in extreme right success. However, much of the extant research on the electoral success of extreme right parties suffers from at least two types of selection bias. The first involves the selection of cases and occurs when only those national elections that were contested by extreme right parties are included in the cross-national analysis. To address this problem, a growing number of scholars of ERP electoral support employ Tobit models to analyze national-level election results pooled across countries and election years. However, this approach conceals a second source of selection bias: ERPs are extremely selective about which election districts within a country they choose to contest. The correct specification of this process of self-selection requires the recognition of two fundamental points. First, the causal factors that determine whether an extreme right party contests an election are not identical to those that influence its share of the vote if it does appear on the ballot. Second, this decision about when and where to field candidates is one that is observable at the level of the election district. This paper argues that the appropriate way to model is as a Heckman sample selection model estimated at the level of electoral district. I present a preliminary analysis of a dataset that pools district-level election results for eighteen European countries from 1980-2004 (N=12,050), the results of which demonstrate the value of this approach.

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Giving Order to Districts: Estimating Voter Distributions with National Election Returns Kernell, Georgia Uploaded 07-07-2008 Keywords district ideology voter distribution election returns Abstract Correctly measuring district preferences is crucial for empirical research on legislative responsiveness and voting behavior. This article argues that the common practice of using presidential vote shares to measure congressional district ideology systematically produces incorrect estimates. I propose an alternative method that employs multiple election returns to estimate voters' ideological distributions within districts. I develop two estimation procedures -- a least squared error model and a Bayesian model -- and test each with simulations and empirical applications. The models are shown to outperform vote shares, and they are validated with direct measures of voter ideology and out of sample election predictions. Beyond estimating district ideology, these models provide valuable information on constituency heterogeneity, an important but understudied quality for understanding representatives' strategic behavior.

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Beyond "Fixed Versus Random Effects": A Framework for Improving Substantive and Statistical Analysis of Panel, TSCS, and Multilevel Data Bartels, Brandon Uploaded 09-30-2008 Keywords random effects fixed effects pooling time-series cross-sectional data panel data multilevel modeling Abstract Researchers analyzing panel, time-series cross-sectional, and multilevel data often choose between a random effects, fixed effects, or complete pooling modeling approach. While pros and cons exist for each approach, I contend that some core issues concerning clustered data continue to be ignored. I present a unified and simple modeling framework for analyzing clustered data that solves many of the substantive and statistical problems inherent in extant approaches. The approach: (1) solves the substantive interpretation problems associated with cluster confounding, which occurs when one assumes that within- and between-cluster effects are equal; (2) accounts for cluster-level unobserved heterogeneity via a random intercept model; (3) satisfies the controversial statistical assumption that level-1 variables be uncorrelated with the random effects term; (4) allows for the inclusion of level-2 variables; and (5) allows for statistical tests of cluster confounding. I illustrate this approach using three substantive examples: global human rights abuse, oil production for OPEC countries, and Senate voting on Supreme Court nominations. Reexaminations of these data produce refined interpretations of some of the core substantive conclusions.

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Using Item Response Theory to Estimate Ideology in Congress Kropko, Jonathan Uploaded 06-28-2008 Keywords Item Response Theory Congress Ideology Abstract I use item response theory (IRT) to estimate latent ideology from selected roll-call votes in the first session of the 110th House of Representatives. Votes are selected if they are divisive, unique, but not wholly explained by party loyalties. The method is similar to the one employed by Clinton et al (2004), but does not assume a spatial structure of voting. The results demonstrate that (1) although Democrats hold a majority of the seats in the 110th House, a majority of the members have conservative ideologies, (2) the Republican party leadership is much more conservative than the Democratic party leadership is liberal, and (3) that the House is far less ideologically polarized than DW-Nominate scores would indicate.

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The Strategic Interdependence of Foreign Aid: A Theoretically Informed Application of the Spatial Autoregressive Model Steinwand, Martin Uploaded 07-07-2008 Keywords Spatial Autoregressive Model Connectivity Matrix Public Goods Abstract Spatial statistical methods in political science provide a tool to deal with spatial and other forms of interdependence in observational data. However, political scientist have been slow to use theory in conceptualizing how political units interconnect other than through geography. In this paper, I use a game theoretic impure public good model to derive the connectivity matrix for a spatial autoregressive (SAR) statistical model. I estimate two SAR models with pure respectively impure public good weights and compare their performance in summarizing data on international aid commitments from 1974 to 2006. I find some evidence for impure public good characteristics of aid during the cold war, and strong evidence for pure public good characteristics after the end of the cold war.

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Estimating Treatment Effects in the Presence of Noncompliance and Nonresponse: The Generalized Endogenous Treatment Model Esterling, Kevin Neblo, Michael Lazer, David Uploaded 02-14-2008 Keywords Average Treatment Effects Principal Stratification Selection on Unobservables Latent Variable Models Deliberation Experiment Political Efficacy Abstract If ignored, non-compliance with a treatment and nonresponse on outcome measures can bias estimates of treatment effects in a randomized experiment. To identify treatment effects in the case where compliance and response are conditioned on unobservables, we propose the parametric generalized endogenous treatment (GET) model. As a multilevel random effect model, GET improves on current approaches to principal stratification by incorporating behavioral responses within an experiment to measure each subjects' latent compliance type. We use Monte Carlo methods to show GET has a lower MSE for treatment effect estimates than existing approaches to principal stratification that impute, rather than measure, compliance type for subjects assigned to the control. In an application, we use data from a recent field experiment to assess whether exposure to a deliberative session with their member of Congress changes constituents' levels of internal and external efficacy. Since it conditions on subjects' latent compliance type, GET is able to test whether exposure to the treatment is ignorable after balancing on covariates via matching methods. We show that internally efficacious subjects disproportionately select into the deliberative sessions, and that matching apparently does not break the latent dependence between treatment compliance and outcome. The results suggest that exposure to the deliberative sessions improves external, but not internal, efficacy.

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Can October Surprise? A Natural Experiment Assessing Late Campaign Effects Meredith, Marc Malhotra, Neil Uploaded 10-14-2008 Keywords Vote by mail natural experiment campaign effects momentum convenience voting regression discontinuity Abstract One consequence of the proliferation of vote-by-mail (VBM) in certain areas of the United States is the opportunity for voters to cast ballots weeks before Election Day. Understanding the ensuing effects of VBM on late campaign information loss has important implications for both the study of campaign dynamics and public policy debates on the expansion of convenience voting. Unfortunately, the self-selection of voters into VBM makes it difficult to casually identify the effect of VBM on election outcomes. We overcome this identification problem by exploiting a natural experiment, in which some precincts are assigned to be VBM-only based on an arbitrary threshold of the number of registered voters. We assess the effects of VBM on candidate performance in the 2008 California presidential primary via a regression discontinuity design. We show that VBM both increases the probability of selecting candidates who withdrew from the race in the interval after the distribution of ballots but before Election Day and affects the relative performance of candidates remaining in the race. Thus, we find evidence of late campaign information loss, pointing to the influence of campaign events and momentum in American politics, as well as the unintended consequences of convenience voting.

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Paper

Measurement Error as a Threat to Causal Inference: Acquiescence Bias and Deliberative Polling Weiksner, G. Michael Uploaded 06-29-2008 Keywords Causal inference experiments acquiescence bias deliberative polling measurement error questionnaire design Abstract Experiments, unlike observational studies, are rarely criticized for yielding invalid causal inferences. However, I identify measurement error as a threat to causal inference of an experiment. In particular, acquiescence bias, a common and substantial source of measurement error within surveys, may be correlated with experimental manipulations. Using data from a survey experiment embedded in a Deliberative Poll, I find that acquiescence bias causes significant measurement error and that the bias differs before and after deliberation. I conclude that even experimental researchers should heed the recommendation by questionnaire design researchers to refrain from asking agree/disagree questions completely and instead ask only construct-specific questions to avoid this threat to validity.

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Paper

Causal Inference of Repeated Observations: A Synthesis of the Propensity Score Methods and Multilevel Modeling Su, Yu-Sung Uploaded 07-03-2008 Keywords causal inference balancing score multilevel modeling propensity score time-series-cross-sectional data Abstract The fundamental problem of causal inference is that an individual cannot be simultaneously observed in both the treatment and control states (Holland 1986). The propensity score methods that compare the treatment and control groups by discarding the unmatched units are now widely used to deal with this problem. In some situations, however, it is possible to observe the same individual or unit of observation in the treatment and control states at different points in time. The data has the structure that is often refer to as time-series-cross-sectional (TSCS) data. While multilevel modeling is often applied to analyze TSCS data, this paper proposes that synthesizing the propensity score methods and multilevel modeling is preferable. The paper conducts a Monte Carlo simulation with 36 different scenarios to test the performance of the two combined methods. The result shows that synthesizing the propensity score matching with multilevel modeling performs better in that such method yields less biased and more efficient estimates. An empirical case study that reexamine the model of Przeworksi et al (2000) on democratization and development also shows the advantage of this synthesis.

39

Paper

Congressional Careers, Committee Assignments, and Seniority Randomization in the U.S. House of Representatives Kellermann, Michael Shepsle, Kenneth Uploaded 02-01-2008 Keywords Congress committees seniority randomization Abstract This paper estimates the effects of initial committee seniority on the career ooetcomes of Democratic members of the Hooese of Representatives from 1949 to 2006. When more than one freshman representative is assigned to a committee, positions in the seniority qoeeoee are established by lottery. This ensoeres that qoeeoee positions are oencorrelated in expectation with other legislator characteristics within these grooeps. This natoeral experiment allows oes to estimate the caoesal effect of seniority on a variety of ooetcomes. Lower ranked committee members are less likely to serve as soebcommittee chairs on their initial committee, are more likely to transfer to other committees, and have fewer sponsored bills passed in the joerisdiction of their initial committee. On the other hand, there is little evidence that the seniority randomization has a net effect on reelection, terms of service in the Hooese, or the total noember of sponsored bills passed.

40

Paper

What is the probability your vote will make a difference? Gelman, Andrew Silver, Nate Edlin, Aaron Uploaded 10-27-2008 Abstract One of the motivations for voting is that one vote can make a difference. In a presidential election, the probability that your vote is decisive is equal to the probability that your state is necessary for an electoral college win, times the probability the vote in your state is tied in that event. We compute these probabilities for each state in the 2008 presidential election, using state-by-state election forecasts based on the latest polls. The states where a single vote is most likely to matter are New Mexico, Virginia, New Hampshire, and Colorado, where your vote has an approximate 1 in 10 million chance of determining the national election outcome. On average, a voter in America has a 1 in 60 million chance of being decisive in the presidential election.

41

Paper

A Spatial Model of Electoral Platforms Elff, Martin Uploaded 07-01-2008 Keywords Parties party families electoral platforms party manifestos spatial models unobserved data latent trait models EM algorithm Monte Carlo integration Monte Carlo EM importance sampling SIR algorithm ideological dimensions Abstract The reconstruction of political positions of parties, candidates and governments has made considerable headway during the last decades, not the least due to the efforts of the Manifesto Research Group the and Comparative Manifestos Project, which compiled and published a data set on the electoral platforms of political parties from most major democracies for most of the post-war era. A central assumption underlying the coding of electoral platforms into quantitative data as done by the MRG/CMP is that parties take positions by selective emphases of policy objectives, which put their accomplishments in a most positive light (Budge 2001) or are representative for their current polital/ideological positions. Consequently, the MRG/CMP data consist of percentages of the respective manifesto texts that refer to various policy objectives. As a consequence both of this underlying assumption and of the structure of the CMP data, methods of classical multivariate analysis are not well suited to these data, due to the requirements to the data for an appropriate application of these methods (van der Brug 2001; Elff 2002). The paper offers an alternative method for reconstructing positions in political spaces based on latent trait modelling, which both reï¬?ects the assumptions underlying the coding of the texts and the peculiar structure of the data. Finally, the validity of the proposed method is demonstrated with respect to the average position of party families within reconstructed policy spaces. It turns out that communist, socialist, and social democrat parties differ clearly from â??bourgeoisâ?? parties with regards to their positions on an economic left/right dimension, while British and Scandinavian conservative parties can be distinguished from Christian democratic parties by their respective positions on a libertarian/authoritarian and a traditionalist/modernist dimension. Similarly, the typical political positions of green (or â??New Politicsâ??) parties can be distinguished from the positions of other party families.

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Paper

Problematic Choices: Testing for Correlated Unit Specific Effects in Panel Data Troeger, Vera Uploaded 07-07-2008 Abstract The (generalized) Hausman specification test (Hausman 1978) is the gold-standard for political scientists using time-series cross-section data to check whether unit specific effects are correlated with right-hand-side variables. More than 500 articles (published in SSCI journals) over the last 20 years in Economics and Political Science used the Hausman test to justify the model choice, e.g. whether to employ a fixed effects or random effects/ pooled OLS specification. The asymptotic properties of the Hausman test and its variants are well known and formal power analyses have shown that the Hausman test performs reasonably well. Yet, the differences in the estimates of fixed effects and random effects models in finite samples can originate from two different sources: On the one hand, the Hausman test might rightly pick up differences that are caused by the inconsistency of the random effects estimator if unit specific effects are correlated with any of the explanatory variables and the random effects model therefore produces biased coefficients. On the other hand, differences might also stem from the inefficiency of the fixed effects estimator if explanatory variables are rarely changing and therefore only have a very small within variation. This inefficiency does not only lead to large standard errors but also to very unreliable point estimates that might be far away from the true relationship. While the Hausman test (and especially more recent variants and augmentations of the specification test) acknowledge the inefficiency of the fixed effects model and control for the differences in the asymptotic variances of the two estimators, this inefficiency in combination with correlated unit effects might still lead to unreliable test results. In International Relations and International and Comparative Political Economy where many of our explanatory variables measure institutions which do not change much over time this result might be especially harmful since the fixed effects model in this case produces very unreliable point estimates. This paper analyses the finite sample properties and power of the Hausman specification test by using Monte Carlo experiments. It shows under what conditions, e.g. the size of the correlation between unit specific effects and explanatory variables, and the between-within variance ratio of right-hand-side variables, the Hausman test generates misleading results.

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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

What will we know on Tuesday at 7pm? Gelman, Andrew Silver, Nate Uploaded 11-03-2008 Abstract Using 10,000 simulations from a probabilistic election forecast, we compute the conditional distribution of the Obama and McCain's vote margins and electoral vote totals, given the outcomes of the states whose polls are the first to close. We consider the scenario in which the vote margins are available in each state, and separately consider the possibility that we are only told each state's winner.

45

Paper

Bayesian Model Averaging: Theoretical developments and practical applications Montgomery, Jacob Nyhan, Brendan Uploaded 01-22-2008 Keywords Bayesian model averaging BMA model robustness specification uncertainty Abstract Political science researchers typically conduct an idiosyncratic search of possible model configurations and then present a single specification to readers. This approach systematically understates the uncertainty of our results, generates concern among readers and reviewers about fragile model specifications, and leads to the estimation of bloated models with huge numbers of controls. Bayesian model averaging (BMA) offers a systematic method for analyzing specification uncertainty and checking the robustness of one's results to alternative model specifications. In this paper, we summarize BMA, review important recent developments in BMA research, and argue for a different approach to using the technique in political science. We then illustrate the methodology by reanalyzing models of voting in U.S. Senate elections and international civil war onset using software that respects statistical conventions within political science.

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Paper

Non-ignorable abstentions in roll call data analysis Rosas, Guillermo Shomer, Yael Uploaded 07-02-2008 Keywords ignorability IRT model roll call data legislative voting Abstract How should we deal with abstentions in roll-call data analysis? Abstentions are very common in decision-making bodies around the world, and very often obey to a strategic rationale. Methods to recover ideal points from roll-call datasets -- such as Nominate and MCMC IRT -- are based on assumptions about the ignorability of the abstention- generating mechanism. However, the strategic character of abstentions makes the assumption of ignorability difficult to meet in practice. We discuss different abstention-generating mechanisms to understand the conditions under which they may be deemed ignorable, and extend the MCMC IRT model so as to incorporate information from abstention patterns into inference about legislators' ideal points.

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Paper

Ecological Inference with Covariates Park, Won-ho Uploaded 07-08-2008 Keywords ecological inference Thomsen voter transition South Korean democratization Abstract The building block of ecological inference strategies is to construct a two-by-two table that describes the individual-level relationship from aggregate information. Extensions to this baseline model, whichever particular technique is employed, have been developed in the context of constructing bivariate R-by-C tables. However, another important and substantively interesting extension is a model that would let the researcher include additional covariates into the model and is yet to be fully discussed and developed. In the paper, I propose a method of moment estimator that incorporates covariates into the ecological inference process by extending Thomsen (1987)'s voter transition model. I apply the developed model to estimate the impact of demographic variables on turnout in South Korean voters over time, especially around democratization, using precinct-level electoral returns and census records.

48

Paper

Public Opinion and Senate Confirmation of Supreme Court Nominees Kastellec, Jonathan Lax, Jeffrey Phillips, Justin Uploaded 08-22-2008 Keywords Supreme Court nominations public opinion multilevel models poststratification Abstract We study the relationship between state-level public opinion and the roll call votes of senators on Supreme Court nominees. Applying recent advances in multilevel modeling, we use national polls on nine recent Supreme Court nominees to produce state-of-the-art estimates of public support for the confirmation of each nominee in all 50 states. We show that greater public support strongly increases the probability that a senator will vote to approve a nominee, even after controlling for standard predictors of roll call voting. We also find that the impact of opinion varies with context: it has a greater effect on opposition party senators, on ideologically opposed senators, and for generally weak nominees. These results establish a systematic and powerful link between constituency opinion and voting on Supreme Court nominees.

49

Paper

Foreign Media and Protest Diffusion in Authoritarian Regimes: The Case of the 1989 East German Revolution Kern, Holger Uploaded 11-25-2008 Keywords Germany media causal inference matching authoritarian collective action social movement Abstract Does access to foreign media facilitate the diffusion of protest in authoritarian regimes? Apparently for the first time, I test this hypothesis by exploiting a natural experiment in communist East Germany. I take advantage of the fact that West German television broadcasts could be received in most but not all parts of East Germany and conduct a matched analysis in which counties without access to West German television are matched to a comparison group of counties with West German television. Comparing these two groups of East German counties, I find no evidence that West German television affected the speed or depth of protest diffusion during the 1989 East German revolution.

50

Paper

Partisanship, Voting, and the Dopamine D2 Receptor Gene Dawes, Christopher Fowler, James Uploaded 02-01-2008 Keywords partisanship voting turnout genetic association dopamine DRD2 Abstract Previous studies have found that both political orientations (Alford, Funk & Hibbing 2005) and voting behavior (Fowler, Baker & Dawes 2007, Fowler & Dawes 2007) are significantly heritable. In this article we study genetic variation in another important political behavior: partisan attachment. Using the National Longitudinal Study of Adolescent Health, we show that individuals with the A1 allele of the D2 dopamine receptor gene are significantly less likely to identify as a partisan than those with the A2 allele. Further, we find that this gene's association with partisanship also mediates an indirect association between the A1 allele and voter abstention. These results are the first to identify a specific gene that may be responsible for the tendency to join political groups, and they may help to explain correlation in parent and child partisanship and the persistence of partisan behavior over time.