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An Event Data Set for the Arabian/Persian Gulf Region 1979-1997 Schrodt, Philip A. Gerner, Deborah J. Uploaded 04-12-1999 Keywords event data Middle East Persian Gulf automated coding Abstract This paper discusses a WEIS-coded event data set covering the Arabian/Persian Gulf region (Iran, Iraq, Kuwait, Oman, Saudi Arabia, Yemen, and the smaller Gulf states) for the period 15 April 1979 to 10 June 1997. The coded events cover international interactions among these states, as well as interactions with any other states or major international organizations. The data set is generated from Reuters news reports downloaded from the NEXIS data service and coded using the Kansas Event Data System (KEDS) machine-coding program. The paper begins with a review of the process of generating a machine-coded data set, including a discussion of software we have developed to partially automate the development of dictionaries to code new geographical regions. The Gulf data are coded using a standard set of verb phrases (rather than phrases specifically adapted to the Gulf) and an actors dictionary that has been augmented only with the actors identified by a utility program that examines the source texts for actors not already found in the KEDS dictionary. The Reuters reports generate 264,421 events when full stories are coded and 48,721 events when only lead sentences are coded. An examination of the time series that are generated when the events are aggregated by month using the Goldstein scale shows that they capture the major features of the behavior that we know to have occurred in the region. There is generally a high correlation (r > 0.75) between the series generated from lead-sentences and from full stories when the major actors of the region (Iran, Iraq, Saudi Arabia and USA) are studied. An exception to this pattern is found in interactions involving a relatively minor actor, the United Arab Emirates. Here the full-story coding provides far more events than the lead-sentence coding and shows greater variance even for interactions between major actors. We expect this will also be the case for other small Gulf states, suggesting that full-story coding may be necessary for a complete analysis of these actors. Paper was presented a year ago at the International Studies Association, Minneapolis, 18 - 22 March 1998 The file includes the papers in Postscript and PDF formats. The data set has been updated through March, 1999 and is available at the KEDS project web site, http://www.ukans.edu/~keds.

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Logistic Regression in Rare Events Data King, Gary Zeng, Langche Uploaded 05-20-1999 Keywords rare events logit logistic regression binary dependent variables bias correction case-control choice-based endogenous selection selection bias Abstract Rare events are binary dependent variables with dozens to thousands of times fewer ones (events, such as wars, vetoes, cases of political activism, or epidemiological infections) than zeros (``nonevents''). In many literatures, rare events have proven difficult to explain and predict, a problem that seems to have at least two sources. First, popular statistical procedures, such as logistic regression, can sharply underestimate the probability of rare events. We recommend corrections that outperform existing methods and change the estimates of absolute and relative risks by as much as some estimated effects reported in the literature. Second, commonly used data collection strategies are grossly inefficient for rare events data. The fear of collecting data with too few events has led to data collections with huge numbers of observations but relatively few, and poorly measured, explanatory variables, such as in international conflict data with more than a quarter million dyads, only a few of which are at war. As it turns out, easy procedures exist for making valid inferences when sampling all available events (e.g., wars) and a tiny fraction of non-events (peace). This enables scholars to save as much as 99% of their (non-fixed) data collection costs, or to collect much more meaningful explanatory variables. We provide methods that link these two results, enabling both types of corrections to work simultaneously, and software that implements the methods developed.

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Measuring Voter Turnout in the National Election Studies Burden, Barry C. Uploaded 08-26-1999 Keywords voter turnout NES overreport response rates Abstract Though the overreport of voter turnout in the National Election Study (NES) is widely known, this paper documents that the bias has become increasingly severe. The gap between NES and official estimates of presidential election has more than doubled from 11 points in 1952 to 28 points 1996. This occurred because official voter turnout fell steadily from 1960 onward while NES turnout did not. In contrast, the bias in House election turnout is always smaller and has increased only marginally over time, mostly due to inflation in presidential election years. I find that worsening presidential turnout estimates are mostly the result of declining response rates rather than instrumentation, question wording changes, or other factors. Adjusting official turnout estimates to more accurately measure real turnout does not account for the growing gap. Rather, as more peripheral voters elude interviewers in recent years, the NES sample becomes more saturated with self-reported voters, thus inflating reported turnout. The paper concludes by calling for a reevaluation of the NES in the wake of these and other changes that have taken place.

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Public Opinion Shocks and Government Termination Martin, Lanny W. Uploaded 11-16-1999 Keywords government survival public opinion discrete-hazard model logit Abstract Abstract. The ability of a government to remain in power depends partially upon its vulnerability to unexpected changes occurring in the outside political environment. In this paper, I examine the relationship between government termination and changes in the electoral expectations of political parties in the legislature, as reflected by shifts in popular support for the government. I find that the decision to terminate the government is related in complex ways to changes in public opinion. Governments are more likely to collapse as certain members of the incumbent coalition expect to gain more ministerial portfolios, and in cases of minority government, when the opposition expects to gain more legislative seats. Further, I show that these effects increase with the approach of regularly-scheduled elections.

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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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Policy, Personality, and Presidential Performance Aldrich, John Gronke, Paul Grynaviski, Jeff Uploaded 04-12-1999 Keywords Policy Personality and Presidential Performance Abstract The importance of personality and performance assessments for candidate evaluations and choice has been well established, most prominently in the work on presidential prototypes by Kinder and colleagues, and the social cognitive model of vote choice by Rahn and colleagues. This paper takes a revisionist look at the effect of personality assessments for understanding presidential elections. Most of the experimental and survey data were collected in a relatively brief period, particularly between 1980 and 1984. Among the unique aspects of the 1980s was the impact of the distinctive personality of Ronald Reagan, sometimes called the "teflon president," because of the degree to which the public admired him as an individual, regardless of political events. His persona therefore might reasonably be assumed to have uniquely influenced the times and thus the models and results. We examine this question primarily by replicating the Rahn, et al. models using the NES surveys from 1984 through 1996, allowing us to evaluate the structure and performance of presidential prototypes and their role in candidate assessments over a longer period of time and greater variety of candidates and presidents.

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Federal Elections Project: A Grant Proposal Lublin, David Uploaded 07-09-1999 Keywords grant proposals data data collection election data EI ecological inference Abstract The central goal of the Federal Elections Project is to collect the 2000 federal election results at the precinct level and match them with demographic data from the 2000 U.S. Census. D. Stephen Voss of the University of Kentucky and I plan to gather data for all federal elections, specifically for president and vice president, senator, and representative. Although the focus is on federal offices, the data set will also include results from the eleven states holding gubernatorial elections in 2000. The matching of election and demographic data are especially critical now that new techniques of ecological inference allow the study of numerous political questions utilizing aggregate data. Gary King's (1997) EI makes it possible to estimate with standard errors the voting behavior of units like precincts and counties utilizing election and census data.

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Trade and Conflict in the Cold War Era: An Empirical Analysis Beck, Nathaniel Uploaded 08-30-1999 Keywords trade conflict MIDs generalized additive model smooth Abstract What is the relationship between trade and conflict in the post-World War II era. Using a dyad-year design, and studying both all dyads and politically relevant dyads, this paper uses the generalized additive model to study the relationship between dyadic trade and militarized interstate disputes (both all disputes and those involving casualties only). For all dyads, moving from no trade to a small amount of trade increases the likelihood of conflict, though that mostly reflects the fact that non-traders also are likely to have little conflict in any arena. Moving from zero to low trade decreases the likelihood of conflict among politically relevant dyads, though this may simply reflect the nature of the Cold War world where dyads made up of Cold War opponents did not trade but did fight. In any event, there is little evidence for a causal pacific impact of trade, but also little evidence that trade is inherently conflictual, other than being an obvious necessary condition for trade disputes and also signalling that dyadic partners are in some interesting relationship.

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Cointegration and Military Rivalry: Some Evidence on 5 Modern Rivalries Gerace, Michael P. Uploaded 11-29-1999 Keywords cointegration military rivalry military expenditures arms race time series Johansen Method Abstract his article investigates the possibilities for stability in arms races, with its starting point being Richardson's discussion of stability conditions. Most discussions of stability focus on whether armaments levels become stable, but there could also be a stable relationship between the armaments of rivals. By employing a time series approach, the behavioral aspects of a model and underlying stability conditions can be related clearly to data characteristics, which clarifies the possibilities for a model. The military expenditures of 5 sets of rivals are then investigated for stationarity, the nature of the trend, and for cointegration. Whether the data are stationary and, if not, the nature of the trend, have implications for what kind of stability can exist over the long-run (or whether the models are explosive). The Johansen method is used for the cointegration tests, and VEC models are evaluated for two cases. While the results are mixed, there is some support for cointegrating relationships among rivals, there is no indication of stability in the level of expenditures or of explosive instability over the long-run.

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The Insignificance of Null Hypothesis Significance Testing Gill, Jeff Uploaded 02-06-1999 Keywords hypothesis testing inverse probability Fisher Neyman-Pearson Bayesian approaches confidence sets meta-analysis Abstract The current method of hypothesis testing in the social sciences is under intense criticism yet most political scientists are unaware of the important issues being raised. Criticisms focus on the construction and interpretation of a procedure that has dominated the reporting of empirical results for over fifty years. There is evidence that null hypothesis significance testing as practiced in political science is deeply flawed and widely misunderstood. This is important since most empirical work in political science argues the value of findings through the use of the null hypothesis significance test. In this article I review the history of the null hypothesis significance testing paradigm in the social sciences and discuss major problems, some of which are logical inconsistencies while others are more interpretive in nature. I suggest alternative techniques to convey effectively the importance of data-analytic findings. These recommendations are illustrated with examples using empirical political science publications.

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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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Statistical Analysis of Finite Choice Models in Extensive Form Signorino, Curtis S. Uploaded 07-09-1999 Keywords random utility discrete choice strategic equilibrium finite choice game theory Abstract Social scientists are often confronted with theories where one or more actors make choices over finite sets of options leading to a finite set of outcomes. Such theories have addressed everything from whether states go to war, to how citizens or senators vote, to the form of transportation taken by commuters. Over the last thirty years, the most common way to analyze finite (or discrete) choice data has been to use nonstrategic random utility models, even when the theory posited as generating the data is explicitly strategic. Moreover, the source of uncertainty --- what makes the utility random --- is often paid little attention. In this paper, I generalize an entire class of statistical finite choice models, with both well-known and new nonstrategic and strategic special cases. I demonstrate how to derive statistical models from theoretical finite choice models and, in doing so, I address the statistical implications of three sources of uncertainty: agent error, private information about payoffs, and unobserved variation in regressors. I provide conditions for the types of choice structures that result in observationally equivalent statistical models. For strategic choice models, the type of uncertainty matters, resulting in observationally nonequivalent statistical models. Moreover, misspecifying the type of uncertainty in strategic models leads to biased and inconsistent estimates. Version: June 22, 1999

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Candidate Viability and Voter Learning in the Presidential Nomination Process Paolino, Philip Uploaded 08-30-1999 Keywords beta distribution maximum likelihood heterogeneity Bayesian Abstract Candidates' viability and momentum are important features of the presidential nomination process in the United States, and much work has examined how both influence the outcome of the nomination campaign (e.g. Aldrich 1980a, Aldrich 1980b, Bartels 1988, Brady and Johnston 1987) Previous treatments, however, have focused upon candidates' expectations of winning or losing the nomination. A critical feature that has been mentioned, but not addressed directly is the volatility of these expectations. In this paper, I use a view of viability and momentum that considers both expectations and the variance of the public's perceptions about candidates' viability which allows us to examine how voters use new information to update their beliefs about both elements of candidates' viability and provides a basis for assessing candidates' potential momentum.

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The Government Agenda in Parliamentary Democracies Martin, Lanny W. Uploaded 12-06-1999 Keywords agenda politics survival analysis nonproportional hazard Abstract In this paper, I examine the effects of party ideology and legislative institutions on the organization of the government agenda in parliamentary democracies. Analyzing data on the timing and policy content of over eight hundred government bills from the 1980s for four European democracies, I show that cabinets schedule bills earlier on the legislative agenda the greater their saliency to the prime minister and to those ministers responsible for their formulation and implementation. Moreover, I show that cabinets tend to delay bills that impose ideological compromise on cabinet members or that create conflict between the cabinet and parties in the opposition, particularly in periods of minority government. I find that all of these effects are greater at the beginning of a government’s tenure and decline by varying degrees over time.

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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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Time Series Models for Compositional Data Brandt, Patrick T. Monroe, Burt L. Williams, John T. Uploaded 04-13-1999 Keywords compositional data vector autoregression macropartisanship Abstract Who gets what? When? How? Data that tell us who got what are compositional data - they are proportions that sum to one. Political science is, unsurprisingly, replete with examples: vote shares, seat shares, budget shares, survey marginals, and so on. Data that also tell us when and how are compositional time series data. Standard time series models are often used, to detrimental consequence, to model compositional time series. We examine methods for modeling compositional data generating processes using vector autoregression (VAR). We then use such a method to reanalyze aggregate partisanship in the United States.

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Inference from Response-Based Samples with Limited Auxiliary Information King, Gary Zeng, Langche Uploaded 07-09-1999 Keywords rare events logit logistic regression binary dependent variables bias correction case-control choice-based endogenous selection selection bias epidemiology Abstract This paper is for the methods conference; it is related to "Logistic Regression in Rare Events Data," also by us; the conference presentation will be based on both papers. We address a disagreement between epidemiologists and econometricians about inference in response-based (a.k.a. case-control, choice-based, retrospective, etc.) samples. Epidemiologists typically make the rare event assumption (that the probability of disease is arbitrarily small), which makes the relative risk easy to estimate via the odds ratio. Econometricians do not like this assumption since it is false and implies that attributable risk (a.k.a. a first difference) is zero, and they have developed methods that require no auxiliary information. These methods produce bounds on the quantities of interest that, unfortunately, are often fairly wide and always encompass a conclusion of no treatment effect (relative risks of 1 or attributable risks of 0) no matter how strong the true effect is. We simplify the existing bounds for attributable risk, making it much easier to estimate, and then suggest one possible resolution of the disagreement by providing a method that allows researchers to include easily available information (such as that the fraction of the population with the disease falls within at most [.001,.05]); this method considerably narrows the bounds on the quantities of interest. We also offer software to implement the methods suggested. We would very much appreciate any comments you might have!

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Coordination, Moderation and Institutional Balancing in American House Elections at Midterm Mebane, Walter R. Sekhon, Jasjeet Uploaded 09-02-1999 Keywords congressional elections rational expectations voter equilibrium midterm cycle stochastic choice model turnout Abstract Individuals' turnout decisions and vote choices for the House of Representatives have been coordinated in recent midterm election years, with each eligible voter (each elector) using a strategy that features policy moderation. Coordination is defined as a rational expectations equilibrium among electors, in which each elector has both common knowledge and private information about the election outcome. Stochastic choice models estimated using individual-level data from the American National Election Study Post-Election Surveys of years 1978-1998 support coordination, but a model in which electors act non-strategically to moderate policy has very similar behavioral implications and also works well. The empirical coordinating model satisfies the fixed point condition that defines the common knowledge expectation electors have about the election outcome in the equilibrium of the theoretical model. Both the coordinating and non-strategic models are capable of generating a midterm cycle in which the President's party usually loses vote share at midterm. Both models correctly flag 1998 as an exception to that pattern: the Republican party had policy positions that were too conservative for most electors. Moderation at midterm has usually been based on electors' expectations that the House will dominate the President in determining post-election policy.

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Regression Analysis and the Philosophy of Social Sciences -- a Critical Realist View Ron, Amit Uploaded 12-20-1999 Keywords Regression analysis empiricism critical realism philosophy of social science Abstract This paper challenges the connection conventionally made between regression analysis and the empiricist philosophy of science and offers an alternative explication for the way regression analysis is being practiced. The alternative explication is based on critical realism, a competing approach to empiricism in the field of philosophy of science. The paper argues that critical realism can better explicate the way in which scientists ‘play’ with the data as part of the process of inquiry. The practice of regression analysis is understood by the critical realist explication as a post hoc attempt to identify a restricted closed system. The gist of successful regression analysis is not being able to offer a law-like statement but to bring forth evidence of an otherwise hidden mechanism. Through the study methodological debates regarding regression analysis, it is argued that critical realism can offer conceptual tools for better understanding the core issues that are at stake in these debates.

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Analysis of Crossover Voting Alvarez, R. Michael Uploaded 02-26-1999 Keywords crossover voting strategic voting ecological inference exit poll analysis Abstract We undertake the analysis of primary elections from 1980 through 1996 using both academic individual level survey data, media exit-polls, and aggregate election returns on a county by county basis. We come to the following conclusions: 1. there is very little crossover voting in general in United States primaries; 2. the difference in the amount of crossover voting between states with open primaries and closed primaries is not substantively large; 3. thee amount of strategic behavior on the part of voters is extremely small.

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Deliberation and Voting at the Federal Convention of 1787 Londregan, John B. Uploaded 04-13-1999 Keywords Scaling Valence Constitution Identification Abstract This paper examines the deliberative voting of the Federal Convention of 1787, and contrasts this type of voting with the more commonly observed position taking behavior observed in most legislatures. The analysis constructs an empirical model that incorporates proposal valence and uses information contained in the authorship of proposals to overcome the identification problems that plague empirical spatial models of voting. The estimated issue positions of the state delegations reveal a significant cleavage on an issue dimension that appears to correspond to the balance between the states and the central government in the proposed constitution.

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Iterative Approaches to R x C Ecological Inference Problems: Where They Can Go Wrong Ferree, Karen E. Uploaded 07-10-1999 Keywords Ecological Inference South Africa. R x C Tables Coloured Voting Abstract King's iterative approach to R x C ecological inference problems involves aggregating groups into broad conglomerate categories like "non-whites" or "non-Christians." Under certain general conditions, this can introduce aggregation bias and multimodality to the data, even when these problems are not present in the original data. The paper develops this argument abstractly and illustrates it with the example of coloured voting during the 1994 South African elections. It then explores methods for averting the problem, both "quick fixes" within the context of King's program, as well ones that move in new directions.

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Coordination, Moderation and Institutional Balancing in American House Elections at Midterm Mebane, Walter R. Wand, Jonathan Uploaded 09-02-1999 Keywords campaign finance itemized contributions congressional elections generalized linear mixed model Monte Carlo EM random effects conditional compound Poisson process Abstract We use Federal Election Commission itemized contributions data from 1984 to estimate a model of campaign contributions in U.S. House elections. The model is a dynamic system of conditional compound Poisson processes in which there are contributions from both individuals and political action committees (PACs). The model includes random effects to allow for unobserved heterogeneity among districts and candidates. The dynamic effects measure how contributions to one candidate react to contributions to other candidates, as well as how contributions from individuals interact with contributions from PACs. We test the hypothesis that some candidates received higher contributions because of PAC endorsements. We also test whether national expectations about presidential election outcomes affect contributions to House candidates, as predicted by a policy moderating model. We use a Monte Carlo EM algorithm to optimize the likelihood of the model in specifications that include more than one random effect.

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Measurement Models for Time Series Analysis: Estimating Dynamic Linear Errors in Variables McAvoy, Gregory Uploaded 07-12-1999 Keywords measurement models time series analysis errors-in-variables Rolling Thunder Abstract This paper uses state space modelling and Kalman filtering to estimate a dynamic linear errors-in-variables model with random measurement error in both the dependent and independent variables. I begin with a general description of the dynamic errors-in-variables model, translate it into state space form, and show how it can be estimated via the Kalman filter. I then use the model in a substantive example to examine the effects of aggregate partisanship on evaluations of President Reagan's job performance using data from the 1984 primary campaign and compare the OLS estimates for this example to those derived from maximum likelihood estimates of the dynamic shock-error setup. Next, I report the results of a simulation in which the amount of random measurement error is varied and, thus, demonstrate the importance of estimating measurement error models and the superiority that Kalman filtering has over regression. Finally, I estimate a dynamic linear errors-in-variables model using multiple indicators for the latent variables.

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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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Heterogeneity in the Impact of Issues on Vote Choice Glasgow, Garrett Uploaded 04-18-1999 Keywords random parameters logit heterogeneity issue salience Abstract There is a great deal of diversity in the issues than members of the American electorate are concerned with. It seems logical that these different concerns will lead voters to evaluate political candidates in different ways when voting. Unfortunately, the models currently employed by political scientists ignore the possibility of heterogeneity in the weights that individuals place on issues when voting. In order to create a tractable model of vote choice, most researchers assume that the weights placed on issues are homogeneous across voters. Estimating such a model tells us if an issue was salient to the electorate on average, but gives us no information about heterogeneity in the use of the issue. Allowing for heterogeneity in issue weights allows for a much more complete picture of the impact of issues on vote choice. I assume that issue weights are distributed among voters by some known probability distribution, and estimate the parameters of that distribution. This assumption leads to random parameters logit. I present the results of a random parameters logit model for the 1996 presidential election, and compare these results to those from a conditional logit model with the homogeneity assumption. I show that random parameters logit contains all of the information that models that assume homogeneity do, plus I uncover evidence of heterogeneity in the weights placed on issues by voters.

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The MAP-B Program with Macro and Micro Applications Hinich, Melvin J. Ghobarah, Hazen Uploaded 07-11-1999 Keywords spatial maps maximum likelihood resampling Abstract We present and apply a general methodology for obtaining a multi-dimensional map of the 'political space' in a given country based on the rating by members of the public of a set candidates or parties. This methodology produces spatial ideology maps of the stimuli (candidates or parties) and the distribution of ideal points of the public. Earlier versions of this methodology, have been applied to American presidential elections (e.g. Enelow and Hinich, 1984:169-216), and to elections in Taiwan (Lin, Chu and Hinich, in World Politics, 1996), Germany (Pappi and Eckstein, in Public Choice, 1998), Ukraine (Hinich, Khmelko and Ordeshook, in Post-Soviet Affairs, 1999), and Russia (Myagkov and Ordeshook, in Public Choice, 1998) among others. This methodology allows for the specification of a valence dimension to capture non-policy characteristics of parties and candidates. The new version (MapB) is capable of recovering the distribution of the estimates of the candidate/party positions in the ideological space through a modified resampling technique. Moreover, it is available as a standalone user-friendly program for the PC/Windows platform.

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The `Turnout Twist' in Japanese Elections Horiuchi, Yusaku Uploaded 09-07-1999 Keywords voter turnout Japanese elections local elections multiple imputation random-effect model simulation Abstract In the United States, as well as in most other democracies, national elections usually attract more votes than local elections. In Japan, they attract more votes in large municipalities but attract less votes in small municipalities. This paper attempts to explain such a puzzling turnout pattern, which is defined as the ``turnout twist''. The random-effect model estimation and the post-estimation simulation find that the most important variable explaining the turnout twist is the voting-age population per seat. The simulation analysis shows that if this variable did not have any significant effect, national elections would attract more votes than local elections in all municipalities. Since this variable itself and its effect on turnout are largely determined by the disproportional apportionment of seats in both national and local elections, the restrictive regulations to mobilizational activities, and the minimal roles played by political parties in mobilizing votes under the multimember constituency system, the paper concludes that the puzzling turnout twist observed in Japanese elections is a product of Japan's unique institutional arrangements.

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Detecting United States Mediation Styles in the Middle East, 1979-1998 Schrodt, Philip A. Uploaded 03-04-1999 Keywords event data mediation Middle East time series hidden Markov models Abstract This research is part of the "Multiple Paths to Knowledge Project" sponsored by the James A. Baker III Institute for Public Policy, Rice University, and the Program in Foreign Policy Decision Making, Texas A&M University. The paper deals with the problem of determining whether the mediation styles used by four U.S. Secretaries of State -- George Schultz, James Baker, Warren Christopher and Madeline Albright -- are sufficiently distinct that they can be detected in event data. The mediation domain is the Israel-Palestinian conflict from April 1979 to December 1998, the event data are coded from the Reuters news service reports using the WEIS event coding scheme, and the classification technique is hidden Markov models. The models are estimated for each of the four Secretaries based on 16 randomly chosen 32-events sequences of USA>ISR and USA>PAL events during the term of the Secretary. Each month in the data set is then assigned to one of the four Secretarial styles based on the best-fitting model. The models differentiate the mediation styles quite distinctly and this method of detecting styles yields quite different results when applied to ISR-PAL data or random data. The "Baker" and "Albright" styles are most distinctive; the "Schultz" style is least; both results are consistent with many qualitative characterizations of these periods. A series of t-tests is then done on Goldstein-scaled scores to determine whether the mediation styles translate into statistically distinct interactions in the ISR>USA, ISR>PAL, PAL>USA and PAL>ISR dyads. While there are a number of statistically-significant differences when the full sample is used, these may be due simply to the overall changes Israel-Palestinian relations over the course of the time series. When tests are done on months that are out-of-term -- in other words, where the style of one Secretary is being employed during the term of another -- few statistically-significant differences are found, though there is someindication of a lag of a month or so between the change in style and the behavioral response. It appears that the effects of the differing styles are not captured by changes in aggregated data, possibly because these scales force behavior into a single conflict-cooperation dimension. Consistent with other papers in the "Multiple Paths to Knowledge" project, the paper contains commentary on how the research project was actually done, as well as the conventional presentation of results. The file includes the papers in Postscript and PDF formats, the event data (Levant, April 1979 to December 1998) used in the analysis, the C source code for estimating the hidden Markov models. This paper was presented at the International Studies Association meetings, Washington, 16-21 February 1999

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Economic Voting: Enlightened Self-Interest and Economic Reference Nagler, Jonathan De Boef, Suzanna Uploaded 04-18-1999 Keywords elections economic voting sociotropic voting Abstract This research tests a new theoretical perspective on economic voting. There is a longstanding debate on whether voters are: `sociotropic' voters', i.e., basing their vote on the state of the national economy; or `pocketbook' voters, i.e., basing their vote on the state of their own finances (Kiewiet 1983, Kinder and Kiewiet 1979). We believe that this debate can be reduced to asking what information voters use to form expectations about their own pocketbooks in the future. We argue that voters use information about the economic fortunes of their own economic reference group, rather than the national economy, to form expectations about the impact of government on their own economic fortunes. This allows voters to evaluate both the economic competence of incumbents, as well as the distributive tendencies of incumbents. Allowing voters to evaluate distributional consequences of alternative parties in power is consistent with research showing that left and right parties pursue different economic policies with different distributional consequences (Hibbs 1977, Alesina, Roubini and Cohen 1997}. Thus it allows for a theoretically richer model of voter behavior; and allows us to synthesize the distinct literatures on sociotropic voting and political business cycles. This work is motivated in part by the divergence of wages for different groups of workers since the 1970s. As variance in economic performance increases across groups, we would expect to see more reliance on economic reference groups and less on the national economy as an indicator of the incumbent's likelihood of providing favorable voter-specific economic performance in the future. We examine presidential approval over time across different demographic groups of voters, and show that those approval ratings are influenced both by national economic performance and by group economic performance measured by the change in the group's mean hourly wage.

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Modeling Heterogeneity in Duration Models Box-Steffensmeier, Janet M. Zorn, Christopher Uploaded 07-11-1999 Keywords heterogeneity survival models split-population variance correction frailty random effects Abstract As increasing numbers of political scientists have turned to event history models to analyze duration data, there has been growing awareness of the issue of heterogeneity: instances in which subpopulations in the data vary in ways not captured by the systematic components of standard duration models. We discuss the general issue of heterogeneity, and offer techniques for dealing with it under various conditions. One special case of heterogeneity arises when the population under study consists of one or more subpopulations which will never experience the event of interest. Split-population, or "cure" models, account for this heterogeneity by permitting separate analysis of the determinants of whether an event will occur and the timing of that event, using mixture distributions. We use the split-population model to reveal additional insights into the strategies of political action committees' allocation decisions, and compare split-population and standard duration models of Congressional responses to Supreme Court decisions. We then go on to explore the general issue of heterogeneity in survival data by considering two broad classes of models for dealing with the lack of independence among failure times: variance correction models and "frailty" (or random effects) duration models. The former address heterogeneity by adjusting the variance matrix of the estimates to allow for correct inference in the presence of that heterogeneity, while the latter approach treats heterogeneity as an unobservable, random, multiplicative factor acting on the baseline hazard function. Both types of models allow us to deal with heterogeneity that results, for example, from correlation at multiple levels of data, or from repeated events within units of analysis. We illustrate these models using data on international conflicts. In sum, we explore the issue of heterogeneity in event history models from a variety of perspectives, using a host of examples from contemporary political science. Our techniques and findings will therefore be of substantial interest to both political methodologists and others engaged in empirical work across a range of subfields.

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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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The Initiative as a Catalyst for Policy Change Boehmke, Frederick Uploaded 03-08-1999 Keywords Initiative political theory event history analysis Abstract In this paper I develop and test a theoretical model of the role that the initiative process plays in shaping policy outcomes. My model builds on Gerber (1996) by introducing uncertainty over the median voter's ideal point and by allowing the interest group to lobby the legislature before a potential initiative is proposed. Successful lobbying may occur due to the uncertainty over the outcome of an initiative. Besides the possibility of lobbying, the results differ from Gerber's since proposal of an initiative is an equilibrium outcome for certain parameter values. I then turn to an event history analysis of state lottery adoptions to test the model's prediction that the initiative process should make it more likely that a state adopt a lottery. This is related to work by Berry and Berry (1990). The empirical hypothesis is found to be supported in the post 1980 period, which I believe is a result of the well-documented resurgence in its use after California's Proposition 13 in 1978. An indirect effect of the initiative in non-initiative states is also found through the importance of neighbors' adoptions. This confirms the view that initiative states are often policy leaders, which I argue may lead to less effective policy choices since they have less information about how to implement then.

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Time Series Models for Compositional Data Brandt, Patrick T. Monroe, Burt L. Williams, John T. Uploaded 07-09-1999 Keywords compositional data VAR time series analysis bootstrap Monte Carlo simulation macropartisanship Abstract Who gets what? When? How? Data that tell us who got what are compositional data - they are proportions that sum to one. Political science is, unsurprisingly, replete with examples: vote shares, seat shares, budget shares, survey marginals, and so on. Data that also tell us when and how are compositional time series data. Standard time series models are often used, to detrimental consequence, to model compositional time series. We examine methods for modeling compositional data generating processes using vector autoregression (VAR). We then use such a method to reanalyze aggregate partisanship in the United States.

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Poisson-Normal Dynamic Generalized Linear Mixed Models of U.S. House Campaign Contributions Mebane, Walter R. Wand, Jonathan Uploaded 07-11-1999 Keywords GLMM MCEM count model heterogeneity FEC campaign contributions campaign finance U.S. House of Representatives 1984 election Abstract We develop generalized linear mixed models to analyze itemized contributions to U.S. House campaigns. Our basic model is a system of Poisson processes that have means that are log-linear functions of normally distributed random effects. Our model permits multiple random effects, including serially correlated effects. The mixed model specification involves an integration over the random effects that is analytically intractable. When there is only one, serially independent random effect, the model may be estimated using quadrature to evaluate the integral. With multiple random effects, quadrature is infeasible but the model may be estimated using the Monte Carlo EM (MCEM) algorithm proposed by McCulloch (1997). We illustrate these various estimation methods. The system we analyze includes contributions to Democratic and Republican candidates from different sources, including individuals and PACs. We estimate dynamic effects both within and across contributions series. The cross-series dynamics measure how contributions to one candidate react to contributions to the other. The cross-series dynamics also measure how contributions to a candidate from one source can mobilize contributions from other sources. We use a combination of observed variables and random effects to test the hypothesis of dynamic mobilization against several hypotheses that imply constant differences between candidates and between districts. One such hypothesis is that some candidates received persistently higher contributions from all sources because of PAC endorsements. Another is that some candidates are simply better at raising money than others. We also test how national expectations about presidential election outcomes affect contributions. We apply our model to itemized contributions data for open seat races in the 1984 election.

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Campaign Timing and Vote Determinants Peterson, David A.M. Uploaded 09-07-1999 Keywords Campaign effects hierarchical models random coefficient Markov chain Monte Carlo Abstract Questions about the role of campaigns in making different considerations more important for voters have been central to the study of political behavior for fifty years (Lazardsfeld et al 1948). The basic concern is does the information presented during the campaign alter how voters evaluate and choose between candidates. This paper develops a random coefficient or hierarchical logit model to analyze the 1984 NES Continuous Monitoring Survey. The specification treats the effect of partisanship, policy distance and candidate character traits as a function of the campaign timing. Of the theories tested in this paper, the attitude strength model best predicts the changes in vote determinants across the campaign.

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Tests of the Validity of Complete-Unit Analysis in Surveys Subject to Item Nonresponse or Attrition Sherman, Robert P. Uploaded 03-12-1999 Keywords MCAR MAR item nonresponse attrition odds-ratios Abstract nalysts of cross-sectional or panel surveys often base inferences about relationships between variables on complete units, excluding units that are incomplete due to item nonresponse or attrition. This practice is justifiable if exclusion is ignorable in an appropriate sense. This paper characterizes certain types of ignorable exclusion in surveys subject to item nonresponse and develops tests based on these characterizations. These tests are applied to data from several National Election Study (NES) panels and evidence is found of violations of assumptions of ignorable exclusion. Characterizations and tests of ignorable attrition in standard panel surveys are also presented.

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Logistic Regression in Rare Events Data (revised) King, Gary Zeng, Langche Uploaded 07-09-1999 Keywords rare events logit logistic regression binary dependent variables bias correction case-control choice-based endogenous selection selection bias Abstract This paper is for the \r\nmethods conference; it \r\nis a revised version of \r\na paper that was \r\npreviously sent to the \r\npaper server.

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The Robustness of Statistical Abstractions: A Look Under the Hood of Statistical Models and Software Altman, Micah McDonald, Michael P. Uploaded 07-13-1999 Keywords computational abstractions numerical accuracy benchmark replication random numbers Abstract Models rest upon abstractions that are accepted, prima facie, as routine and robust. In the course of model development and estimation, political methodologists routinely assume the reliability of the computational that abstractions they use. All computational abstractions can fall short in their implementation; some because their implementation is complicated and the precision of computation is limited, others because they assume knowledge of solutions to mathematical problems that are inherently difficult to solve. We measure the accuracy of statistical abstractions as implemented in statistical packages popular among political methodologists, such as Gauss, Stata, SST and Excel. We evaluate the use of these abstractions in the context of evaluating complex statistical procedures, such as Jonathan Nagler's (1994) scobit estimator and Gary King's (1997) solution to ecological inference. We find that widely used implementations of common statistical abstractions are at times prone to error. We show that errors in inference in complex models can result from failures to understand the implementation and limitations of computation. We then offer tools to test statistical results to improve the accuracy of many statistical implementations and to test the implementation-robustness of many statistical results. We conclude by offering recommendations to help users of statistical software avoid the pitfalls of computational abstractions and offer guidelines to aid replication

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What's Your Temperature? Thermometer Ratings and Political Analysis Berinsky, Adam Winter, Nicholas Uploaded 09-09-1999 Keywords thermometer rating measurement NES group evaluations interpersonal comparability Abstract This paper considers the measurement properties of the NES’ feeling thermometer ratings of political groups and individuals. We explore the degree to which the thermometer contains interval-level information, the degree to which t-scores are interpersonally comparable, and discuss the measure’s use in political analysis. nwinter@umich.edu

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Respondent Uncertainty of Candidate Issue Positions and Its Effects on Estimates of Issue Salience Glasgow, Garrett Uploaded 03-23-1999 Keywords issue salience uncertainty coefficient bias spatial models Abstract (not transcribed)

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Learning in Campaigns: A Policy Moderating Model of Individual Contributions to House Candidates Wand, Jonathan Mebane, Walter R. Uploaded 04-18-1999 Keywords FEC campaign contributions campaign finance policy moderation GLM generalized linear model negative binomial time series bootstrap U.S. House of Representatives 1984 election Abstract We propose a policy moderating model of individual campaign contributions to House campaigns. Based on a model that implies moderating behavior by voters, we hypothesize that individuals use expectations about the Presidential election outcome when deciding whether to donate money to a House candidate. Using daily campaign contributions data drawn from the FEC Itemized Contributions files for 1984, we estimate a generalized linear model for count data with serially correlated errors. We expand on previous empirical applications of this type of model by comparing standard errors derived from a sandwich estimator to confidence intervals produced by a nonparametric bootstrap.

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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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The Influence of the Initiative Process on Interest Groups and Lobbying Techniques Boehmke, Frederick Uploaded 09-22-1999 Keywords Initiative direct democracy survey analysis interest groups lobbying selection bias Abstract I use survey data on interest groups and their activities drawn from four state populations to test hypotheses about the implications of direct democracy for the characteristics and strategic choices of interest groups. I use this data to test predictions about direct democracy's effect for group populations, confirming previous work (Boehmke 1999b) and extending it by exploring more detailed characteristics such as membership and resources. I then link these characteristics to lobbying techniques to test if the initiative process has an impact at the group level. As expected, groups involved in initiative campaigns tend to accentuate outside lobbying strategies, but even groups not currently involved in initiatives are influenced by the possibility of its use. This is because the initiative process alters the characteristics that can be effectively used when attempting to influence policy. The analysis makes use of a technique to correct for heterogeneous response rates across group types. By gathering information about a high percentage of an additional, smaller sample, I am able to correct for this response rate differential through a weighting procedure. The correction is found to have a substantial effect on the results: its absence would leave the researcher to conclude that the initiative plays little role in state interest group activities. This data will also be used to test and correct for possible sample selection bias.

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Statistical Analysis of Finite Choice Models in Extensive Form Signorino, Curtis S. Uploaded 03-23-1999 Keywords random utility discrete choice strategic equilibrium finite choice game theory Abstract (not transcribed)

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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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Selection Bias in a Model of Candidate Entry Decisions Kanthak, Kristen Morton, Becky Gerber, Elisabeth R. Uploaded 07-13-1999 Keywords selection bias Poisson estimation population uncertainty Abstract In recent years, several states have changed or considered changing their laws regulating how political parties nominate candidates for office. We focus on one potentially important consequence of these changes: How do primary election laws affect candidate entry decisions? We have constructed and solved a formal model of individual candidate behavior in which potential candidates can choose to: 1) enter the electoral competition as major party candidates; 2) enter as minor party candidates; 3) enter as independents; or 4) not enter. Based on our analysis of the model, we hypothesize that the expected utility of each choice is a function, in part, of a state's primary election laws. We test our hypotheses with data on candidate choice from recent US Congressional elections. Estimation of our model is complicated, however, by the fact that we do not observe the choices of potential candidates who choose not to enter (i.e., the sample is truncated) and the observed dependent variable (i.e., candidate choices to run as major party, minor party, or independent candidates) is measured as a discrete, unordered polychotomous choice. We employ a two-stage Heckman (1979)-type estimation procedure that utilizes a Poisson framework for estimating candidate entry rates. We find that our estimates of the effects of electoral institutions on the partisan affiliation decisions of independent candidates are unaffected by sample selection. Our estimates of the partisan affiliation decisions of minor party candidates, however, change when we account for non-random sample selection.

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Populists in the Pluralist Heaven: How Direct Democracy Reduces Bias in Interest Representation Boehmke, Frederick Uploaded 10-15-1999 Keywords Initiative direct democracy interest groups lobbying fixed effects representation Abstract This paper explores the effect of direct democracy on state interest group populations, providing an empirical test of a formal model of how access to the initiative process affects group formation and activities (Boehmke 1999), which predicts that more groups will mobilize and become active in initiative states. This prediction is supported by the findings in this paper, which also suggest that the effect of the initiative on group mobilizations has increased from the late 1970s to 1990. The prediction that groups that face a greater collective action problem are influenced more by the initiative is also confirmed since government and social groups are among those most affected. Counterfactual analysis indicates that the initiative process makes a state's interest group population more diverse, though the gains are decreasing from 1975 to 1990.

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Multiculturalism, Diversity, and Prejudice Branton, Regina P. Jones, Bradford S. Uploaded 03-27-1999 Keywords random coefficients multilevel analysis multiculturalism racial politics Abstract In this paper, we consider the relationship between racial and ethnic diversity and individuals' assessments of racial and ethnic groups measured on several public opinion items. To examine these issues, we merge 1992 National Election Study data with U.S. Census Bureau demographic data measured at the congressional district level. We then develop an index of diversity that is based on the distribution of racial and ethnic groups in the congressional district. To examine the relationship between diversity and individual-level attitudes toward racial and ethnic groups, we estimate a series of models treating the response variable as a function of both individual-level attributes and district-level attributes. This approach allows us to assess, among other things, if diversity is associated with more positive or negative evaluations of racial and ethnic groups. The models herein are all estimated as mixed effects models to account for the clustering of observations within congressional districts. We find that diversity is associated with group affect and individuals' placement on policy issues; however, in contrast to some of the extant literature, we find that racial and ethnic diversity is nonlinearly associated with group affect: extremely low and extremely high levels of racial and ethnic diversity are associated with lower racial and ethnic group evaluations, while districts that are moderately diverse are associated with higher evaluations. This result also holds for some of the policy items examined. Specifically, we find that support for government assistance to blacks, and to a lesser extent, support for affirmative action, exhibits this nonlinearity with regard to racial and ethnic diversity. We also find this pattern for individuals' assessment of welfare recipients.

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Does Size Matter? Exploring the Small Sample Properties of Maximum Likelihood Estimation Hart, Jr., Robert A. Clark, David H. Uploaded 04-20-1999 Keywords small samples ML Type II errors bootstrap Abstract The last two decades have witnessed an explosion in the use of computationally intensive methodologies in the social sciences as computer technology has advanced. Among these empirical methods are Maximum Likelihood (ML) procedures. ML estimators possess a variety of desirable qualities, perhaps most prominent of which is the asymptotic efficiency of the standard errors. However, the behavior of the estimators in general, of the estimates of the standard errors in particular, and thus of inferential hypothesis tests are uncertain in small sample analyses. In political science research, small samples are routinely the subject of empirical investigation using ML methods, yet little is known regarding what effect sample size has on a researcher's ability to draw inferences This paper explores the behavior of ML estimates in probit models across differing sample sizes and with varying numbers of independent variables in Monte Carlo simulations. Our experimental results allow us to conclude that: a) the risk of making Type I errors does not change appreciably as sample size descends; b) the risk of making Type II errors increases dramatically in smaller samples and as the number of regressors increases.