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Below results based on the criteria 'logit'
Total number of records returned: 38

1
Paper
Have Turnout Effects Really Declined? Testing the Partisan Implications of Marginal Voters
Gill, Jeff
Martinez, Michael

Uploaded 08-09-2002
Keywords voting
turnout

simulation
multinomial logit
Abstract In this paper, we review the theoretical foundations of the debate about whether higher election turnout advantages left parties, suggest a method of assessing the effects of turnout within a single election, and provide evidence from four U.S. elections that the partisan effects of turnout are contingent on the strength and polarity of the short-term forces. Our methodological approach to addressing whether the Democrats would have benefited from higher turnout (and whether the Republicans would have benefited from lower turnout) in a given election is to employ a new type of simulation based on multinomial logit estimates of the choices made by individual citizens. Our substantive approach is similar to Lacy and Burden (1999), in that we posit that U.S. citizens have three unordered choices in each election: vote Democratic, vote Republican, or abstain. We first estimate vote choice (including the abstention category) as an unordered multinomial logit function of standard variables associated with both candidate preference and the likelihood of voting. From that estimation, we derive probabilities for each respondent's selection of each of the three choices (abstain, vote Democratic, or vote Republican). From those probabilities, we simulate several levels of turnout. Higher turnout is simulated by progressively adding to the pool of voters actual abstainers with the lowest probability of abstaining of those remaining in the pool of abstainers. Whereas lower turnout is simulated by progressively subtracting from the electorate actual voters with the highest probability of abstaining. Our results across the four elections provide partial support for both the conventional SES-based model and the alternative defection-based model, though neither model's predictions are completely borne out empirically. As predicted by the conventional model, we find that the electorate has a greater Democratic tilt at higher levels of turnout, although that relationship has significantly weakened over time.

2
Paper
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.

3
Paper
Testing for Interaction in Binary Logit and Probit Models: Is a Product Term Essential?
Berry, William
Esarey, Justin
DeMeritt, Jacqueline

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

4
Paper
State-Level Opinions from National Surveys: Poststratification using Hierarchical Logistic Regression
Park, David K.
Gelman, Andrew
Bafumi, Joseph

Uploaded 07-12-2002
Keywords Bayesian Inference
Hierarchical
Logit
Poststratification
Public Opinion
States
Elections
Abstract Previous researchers have pooled national surveys in order to construct state-level opinions. However, in order to overcome the small n problem for less populous states, they have aggregated a decade or more of national surveys to construct their measures. For example, Erikson, Wright and McIver (1993) pooled 122 national surveys conducted over 13 years to produce state-level partisan and ideology estimates. Brace, Sims-Butler, Arceneaux, and Johnson (2002) pooled 22 surveys over a 25-year period to produce state-level opinions on a number of specific issues. We construct a hierarchical logistic regression model for the mean of a binary response variable conditional on poststratification cells. This approach combines the modeling approach often used in small-area estimation with the population information used in poststratification (see Gelman and Little 1997). We produce state-level estimates pooling seven national surveys conducted over a nine-day period. We first apply the method to a set of U.S pre-election polls, poststratified by state, region, as well as the usual demographic variables and evaluate the model by comparing it to state-level election outcomes. We then produce state-level partisan and ideology estimates by comparing it to Erikson, Wright and McIver's estimates.

5
Paper
Operationalizing and Testing Spatial Theories of Voting
Quinn, Kevin M.
Martin, Andrew D.

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

6
Paper
Estimating Binary Dependent Variable Models Under Conditions of Specification Uncertainty
Berry, William
DeMeritt, Jacqueline
Esarey, Justin

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

7
Paper
Turnout Effects on the Composition of the Electorate: A Multinomial Logit Simulation of the 2000 Presidential Election
Martinez, Michael

Uploaded 03-18-2002
Keywords turnout
multinomial logit
simulation
Abstract Conventional wisdom among pundits and some scholars posits that higher turnout should benefit liberal parties, since lower socioeconomic classes comprise a disproportionate share of the nonvoting population. Empirical tests of this prediction across elections have produced a wide variety of results, ranging from support for the conventional wisdom to suggestions that Republicans benefit from higher turnout to null findings. In this paper, we provide a simulation of the possible impact of increasing or decreasing turnout in a single election. Using data from the 2000 American National Election Study, we find that Gore would have benefitted slightly from higher turnout and would have been harmed slightly by lower turnout, but the overall magnitude of the effects of turnout on Gore's share of the two party vote is small. At higher levels of turnout, Democrats comprise a larger share of the electorate, but they also have a higher defection rate.

8
Paper
The Problem with Quantitative Studies of International Conflict
Beck, Nathaniel
King, Gary
Zeng, Langche

Uploaded 07-15-1998
Keywords Conflict
logit
neural networks
forecasting
Bayesian analysis
Abstract Despite immense data collections, prestigious journals, and sophisticated analyses, empirical findings in the literature on international conflict are frequently unsatisfying. Statistical results appear to change from article to article and specification to specification. Very few relationships hold up to replication with even minor respecification. Accurate forecasts are nonexistent. We provide a simple conjecture about what accounts for this problem, and offer a statistical framework that better matches the substantive issues and types of data in this field. Our model, a version of a ``neural network'' model, forecasts substantially better than any previous effort, and appears to uncover some structural features of international conflict.

9
Paper
New Empirical Strategies to Model the Government Formation Process
Glasgow, Garrett
Golder, Matt
Golder, Sona

Uploaded 07-15-2010
Keywords discrete choice
mixed logit
IIA
random coefficients
government formation
Abstract Over the past decade, a "standard approach" to the quantitative study of government formation has developed. This approach involves the use of a conditional (CL) logit model to examine government choice with the government formation opportunity as the unit of analysis. In this paper, we reconsider this approach and make three methodological contributions. First, we demonstrate that the existing procedure used to test for the independence of irrelevant alternatives (IIA) is flawed and severely biased against finding IIA violations. Our new testing procedure reveals that many government alternatives share unobserved attributes, thereby violating the IIA assumption and making the CL model inappropriate. Second, we employ a mixed logit with random coefficients that allows us to take account of unobserved heterogeneity and IIA violations. Third, we return to a question that originally motivated this literature, namely, what determines the likelihood that a particular party enters government? Although scholars have generally abandoned this question due to perceived methodological limitations in our ability to address it, we demonstrate that calculating probabilities for parties entering office rather than governments is straightforward in a mixed logit framework.

10
Paper
Heterogeneity in Discrete Choice Models
Glasgow, Garrett

Uploaded 12-12-2001
Keywords heterogeneity
discrete choice
logit
probit
ambivalence
Abstract Nearly all empirical studies of individual behavior in political science have sought to estimate the mean relationship between some variables of interest. While such studies are vital for determining aggregate relationships between variables of interest, they are an incomplete picture of individual behavior. In particular, we generally do not pay attention to the possibility of heterogeneity, or individual-level variation in the relationships we estimate. Ignoring heterogeneity in our models means we are ignoring valuable information about individual behavior. This paper demonstrates that examining heterogeneity in discrete choice models is both important substantively and feasible methodologically. Possible sources of heterogeneity are discussed, and it is shown that these sources of heterogeneity are observationally equivalent in most cases, meaning it is generally not possible to determine the source of heterogeneity in our empirical models. Several empirical models for examining heterogeneity are described. An empirical example studying heterogeneity in union voting in the 1992 US presidential election demonstrates the

11
Paper
Modeling Direction and Intensity in Ordinal Scales with Midpoints
Jones, Bradford S.
Sobel, Michael E.

Uploaded 07-21-1998
Keywords adjacent category logit
log-linear models
public opinion
Congress
Abstract Political opinion analysts are frequently work with semantically balanced ordinal scales. Such survey items are frequently used to measure candidate evaluations, public spending preferences, positions on social issues, and candidate and party placement. Because of the special nature of these survey items (semantically balanced about a midpoint), researchers may be interested in understanding how both the response direction and response intensity varies over time and/or across covariate classes. That is, trends may be found in the tendency for respondents to choose categories above vs. below the midpoint (the response direction) and trends may be found in the tendency for respondents to choose between or among category labels above or below the midpoint. And while political analysts are commonly interested in response intensity and direction, traditional methods used to model distributions on semantically balanced ordinal scales are problematic. In this paper, we discuss a class of models originally developed by Sobel (1995, 1997, 1998) that allows researchers to simultaneously model direction and intensity in ordinal scales with midpoints. Specifically, we parameterize the model as an adjacent category logit model. Numerous parsimonious models may be arrived at that describe trends in the response direction and response intensity. Because the adjacent category logit model is linear in the logits, we estimate the model using log-linear models. We present an application of the models to data on approval ratings of House incumbents. We find that the trends in response directions (the tendency for respondents to evaluate the incumbent favorably or not favorably) increase through the 1980s, peaking in the late Eighties, and are now declining over the 1990s. With regard to response intensity, (that is, the tendency to respond in the extreme categories vs. the moderate categories), we find that intensity increases during most presidential election cycles and vanishes during midterm election years. We argue this finding is related to the different levels of political information citizens are exposed to in presidential vs. midterm election cycles.

12
Paper
Modeling History Dependence in Network-Behavior Coevolution
Franzese, Robert
Hays, Jude
Kachi, Aya

Uploaded 07-21-2010
Keywords path dependence
history dependence
network
coevolution
spatial econometrics
selection
homophily
SIENA
RSIENA
markov chain
logit
p-star
military alliance
conflict behavior
Abstract Spatial interdependence--the dependence of outcomes in some units on those in others--is substantively and theoretically ubiquitous and central across the social sciences. Spatial association is also omnipresent empirically. However, spatial association may arise from three importantly distinct processes: common exposure of actors to exogenous external and internal stimuli, interdependence of outcomes/behaviors across actors (contagion), and/or the putative outcomes may affect the variable along which the clustering occurs (selection). Accurate inference about any of these processes generally requires an empirical strategy that addresses all three well. From a spatial-econometric perspective, this suggests spatiotemporal empirical models with exogenous covariates (common exposure) and spatial lags (contagion), with the spatial weights being endogenous (selection). From a longitudinal network-analytic perspective, we can identify the same three processes as potential sources of network effects and network formation. From that perspective, actors' self-selection into networks (by, e.g., behavioral homophily) and actors' behavior that is contagious through those network connections likewise demands theoretical and empirical models in which networks and behavior coevolve over time. This paper begins building such modeling by, on the theoretical side, extending a Markov type-interaction model to allow endogenous tie-formation, and, on the empirical side, merging a simple spatial-lag logit model of contagious behavior with a simple p-star logit model of network formation, building this synthetic discrete-time empirical model from the theoretical base of the modified Markov type-interaction model. One interesting consequence of network-behavior coevolution--identically: endogenous patterns of spatial interdependence--emphasized here is how it can produce history-dependent political dynamics, including equilibrium phat and path dependence (Page 2006). The paper explores these implications, and then concludes with a preliminary demonstration of the strategy applied to alliance formation and conflict behavior among the great powers in the first half of the twentieth century.

13
Paper
An Agenda for New Political Methodology: Microfoundations and ART
Achen, Christopher H.

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

14
Paper
The Spatial Model and Specification of Choice Models
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 01-01-1995
Keywords Multinomial Logit
Spatial Model
Conditional Logit
Elections
Abstract The spatial model has been in use in political science for close to 30 years, and in that period it has achieved a place of prime importance as our paradigm of the process of candidate-choice used by voters. For much of this time political scientists have estimated models of candidate-choice using binary logit or probit, even in cases where there were more than two choices facing voters. Recently discrete choices models beyond binary logit and probit have been making their way into use in political science with increasing frequency. The properties of these models, and their relationship to the spatial model, are frequently misunderstood. This paper demonstrates four essential points. First, the popular multinomial logit model is in fact equivalent to running a series of binary logit models. It involves nothing more than pairwise comparisons of the choices. Second, despite containing no information about the choices, the multinomial logit model provides reduced form estimates of the effect of characteristics of choices that are equivalent to the estimates of such effects provided by the conditional logit model - which does utilize information about the characteristics of the choices. Third, the multinomial logit model cannot offer any inferences as to effects of changing the characteristics of the choices, or introducing additional choices; whereas the conditional logit model can offer such inferences. Fourth, the classic spatial model has a flaw in multi-candidate settings that has been overlooked, with more than two candidates the spatial model explicitly contradicts an aspect of voter behaviour widely believed to be prevalent: the tendency of voters to view certain candidates as `similar' alternatives, and thus for the presence of additional candidates to effect asymettrically the probability of existing candidates being chosen.

15
Paper
Mixed Logit Models in Political Science
Glasgow, Garrett

Uploaded 07-08-2001
Keywords mixed logit
discrete choice
heterogeneity
Abstract Mixed logit (MXL) is a general discrete choice model that is applicable to a wide range of political science problems. Mixed logit assumes the unobserved portions of utility are a mixture of an IID extreme value term and another multivariate distribution selected by the researcher. This general specification allows MXL to avoid imposing the independence of irrelevant alternatives (IIA) property on the choice probabilities. Further, and more importantly, MXL is a flexible tool for examining heterogeneity in individual behavior through random-coefficients specifications. Three empirical examples are presented. Two are drawn from studies of voting behavior. The first uses data from the 1987 British general election and examines heterogeneity in the impact of social class on voting, and the second uses data from the 1992 U.S. presidential election and examines heterogeneity in the impact of union membership on voting. A third example examines heterogeneity in the factors that lead to various Congressional career decisions. These empirical examples demonstrate the utility of mixed logit in political science research. This paper has both a methodological and substantive contribution for political science. Methodologically, it expands the tool set available to researchers for studying various phenomena in political science. More importantly, this paper contributes substantively by allowing for more realistic models of individual behavior. Most models currently used in political science assume the independent variables have a homogeneous effect on the dependent variable. This assumption is usually made to keep models tractable, even though few believe it is an accurate description of behavior. MXL is a tractable way to relax this assumption and study heterogeneity in a variety of settings.

16
Paper
Correlated Disturbances in Discrete Choice Models:A Comparison of Multinomial Probit Models
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 01-01-1995
Keywords econometrics
logit
multinomial probit
gev
discrete-choice
monte-carlo
Abstract Correlated Disturbances in Discrete Choice Models: A Comparison of Multinomial Probit Models and Logit Models In political science, there are many cases where individuals make discrete choices from more than two alternatives. This paper uses Monte Carlo analysis to examine several questions about one class of discrete choice models --- those involving both alternative-specific and individual-specific variables on the right-hand side --- and demonstrates several findings. First, the use of estimation techniques assuming uncorrelated disturbances across alternatives in discrete choice models can lead to significantly biased parameter estimates. This point is tempered by the observation that probability estimates based on the full choice set generated from such estimates are not likely to be biased enough to lead to incorrect inferences. However, attempts to infer the impact of altering the choice set -- such as by removing one of the alternatives -- will be less successful. Second, the Generalized Extreme Value (GEV) model is extremely unreliable when the pattern of correlation among the disturbances is not as restricted as the GEV model assumes. GEV estimates may suggest grouping among the choices that is in fact not present in the data. Third, in samples the size of many typical political science applications -- 1000 observations -- Multinomial Probit (MNP) is capable of recovering precise estimates of the parameters of the systemic component of the model, though MNP is not likely to generate precise estimates of the relationship among the disturbances in samples of this size. Paradoxically, MNP's primary benefit is its ability to uncover relationships among alternatives and to correctly estimate the affect of removing an alternative from the choice set. Thus this paper suggests the increased use of MNP by political scientists examining discrete choice problems when the central question of interest is the effect of removing an alternative from the choice set. We demonstrate that for other questions, models positing independent disturbances may be `close enough.'

17
Paper
Issue Voting and Ecological Inference
Thomsen, Soren R.

Uploaded 09-14-2000
Keywords issue voting
ecological inference
electoral geography
multinomial logit
Abstract This article proposes a unifying framework for individual and aggregate voting behavior. The proposed individual level model is a version of the multinomial logit model that applies to both issue voting, ideological voting and normative voting providing a close fit to survey data. The aggregate model is derived by using the binary logit model as an approximation to the multinomial logit model. The aggregate model is useful for modeling electoral change and for identification of homogenous political regions. Further, the unifying framework derives a method for ecological inference that applies to large tables and gives estimates of voter transitions close to survery results.

18
Paper
When Politics and Models Collide: Estimating Models of Multi-PartyElections
Alvarez, R. Michael
Nagler, Jonathan

Uploaded 00-00-0000
Keywords elections
parties
probit
logit
multinomial logit
model-specification
spatial model
multinomial probit
discrete-choice
Abstract Theory: The spatial model of elections can better be represented by using conditional logit than by multinomial logit. The spatial model, and random utility models in general, suffer from a failure to adequately consider the substitutability of candidates sharing similar or identical issue positions. Hypotheses: Multinomial logit is not much better than successive applications of binomial logit. Conditional logit allows for considering more interesting political questions than does multinomial logit. The spatial model may not correspond to voter decision-making in multiple-candidate settings. Multinomial probit allows for a relaxation of the IIA condition and this should improve estimates of the effect of adding or removing parties. Methods: Comparisons of binomial logit, multinomial logit, conditional logit, and multinomial probit on simulated data and survey data from a three-party election. Results: Multinomial logit offers almost no benefits over binomial logit. Conditional logit is capable of examining movements by parties, whereas multinomial logit is not. Multinomial probit performs better than conditional logit when considering the effects of altering the set of choices available to voters.

19
Paper
Is There a Gender Gap in Fiscal Political Preferences
Alvarez, R. Michael
McCaffery, Edward J.

Uploaded 08-12-2000
Keywords Gender gap
fiscal politics
taxation
budget surplus
multinomial logit
missing data
imputation
framing
survey experiments
Abstract This paper examines the relationship between attitudes on potential uses of the budget surplus and gender. Survey results show relatively weak support overall for using a projected surplus to reduce taxes, with respondents much likelier to prefer increased social spending on education or social security. There is a significant gender gap with men being far more likely than women to support tax cuts or paying down the national debt. Given a menu of particular types of tax cuts, women are marginally more likely to favor child-care relief or working poor tax credits whereas men are marginally more likely to favor capital gains reduction or tax rate cuts. When primed that the tax laws are biased against two-worker families, men significantly change their preferences, moving from support for general tax rate cuts to support for working poor tax relief, but not to child-care relief. One of the strongest results to emerge is that women are far more likely than men not to express an opinion or to confess ignorance about fiscal matters. Both genders increase their ``no opinion'' answer in the face of priming, but men more so than women. Further research will explore this no opinion/uncertainty aspect.

20
Paper
Information and American Attitudes Toward Bureaucracy
Alvarez, R. Michael
Brehm, John

Uploaded 00-00-0000
Keywords discrete choice
logit
probit
heteroskedasticity
ordered logit
Internal Revenue Service
ambivalence
uncertainty
Abstract The exploration of American attitudes towards the Internal Revenue Service joins an unusual pair of research domains: public opinion and public administration. Public administration scholars contend that the hostility Americans show towards ``bureaucracy'' stems from the contradictory expectations Americans have for bureaucratic performance. Drawing upon a survey commissioned by the IRS and conducted in 1987 just after the passage of the Tax Reform Act, we explore attitudes towards the performance of the IRS in eight categories. Using a new heteroskedastic ordinal logit technique, we demonstrate (1) that it is overwhelmingly a single expectation of flexibility that governs attitudes towards the IRS; (2) that these expectations are not in contradiction; and (3) that domain-specific information sharply focuses respondent attitudes towards bureaucracy.

21
Paper
Mixed Logit Models for Multiparty Elections
Glasgow, Garrett

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

22
Paper
An Empirical Model of Government Formation in Parliamentary Democracies
Martin, Lanny W.
Stevenson, Randolph T.

Uploaded 00-00-0000
Keywords coalition theory
government formation
conditional logit
econometrics
Abstract The study of coalition politics in parliamentary democracies has led to the construction of several sophisticated theories of government formation, but it has thus far failed to lead to the development of a reliable method that will permit us to verify these theories empirically. In this paper, we propose a solution to the problems plaguing the application of multivariate statistical analysis in this area. Specifically, we advocate use of the conditional logit technique to model the government formation process. We use this model to test various hypotheses from coalition theory on an original data set consisting of information on every potential government that could have formed in 285 separate instances of coalition bargaining in 14 post-war parliamentary democracies. We then illustrate further uses of this method by examining three real-world cases of government formation.

23
Paper
Government Formation in Parliamentary Democracies
Martin, Lanny W.
Stevenson, Randolph T.

Uploaded 01-27-2000
Keywords government formation
coalition politics
conditional logit
Abstract The literature on cabinet formation in parliamentary democracies is replete with theoretical explanations of why some cabinets form and others do not. This theoretical richness, however, has not led to the development of a healthy empirical literature designed to choose between competing theories. In this paper, we try to rectify this problem by developing an empirical model that can adequately capture the kind of choice situation that is inherent in cabinet selection and then using it to evaluate the leading theories of cabinet formation that have been advanced in the literature. For example, this analysis allows us to make conclusions about the relative importance in cabinet formation of traditional variables like size and ideology, as well as to evaluate the impact that recent new-institutionalist theories (such as Laver and Shepsle 1996) have on our ability to predict and explain cabinet formation over and above the more traditional explanations.

24
Paper
Uncertainty and Ambivalence in the Ecology of Race
Alvarez, R. Michael
Brehm, John

Uploaded 08-22-1996
Keywords racial policy
affirmative action
ecological inference
heteroskedastic ordered logit
value conflict
uncertainty
ambivalence
equivocation
Abstract Since Myrdal (1944), scholars have regarded American attitudes towards racial policy as a conflict between values, groups, and interests. Although Myrdal viewed the conflict as a state internal to individuals, it begins as aggregate conflict. This mix of ecologies---individual and aggregate---carries forth to the present. This paper takes the question of different ecologies for racial politics seriously, developing tools to compare conflict at individual and aggregate level. We demonstrate that individual racial policy choices stems principally from racial resentment, and that the variability of that choice indicates a state of uncertainty, not ambivalence or equivocation. We further demonstrate that racial resentment does not surface as a predictor of aggregate racial policy choice, even though individual choices about racial policies appear to be more strongly influenced by the level of political informedness.

25
Paper
Testing for Interaction in Models with Binary Dependent Variables
Berry, William D.

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

26
Paper
Beyond Ordinary Logit: Taking Time Seriously in Binary Time-Series--Cross-Section Models
Beck, Nathaniel
Katz, Jonathan
Tucker, Richard

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

27
Paper
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.

28
Paper
Conflict, Information, and Lobbying Coalitions
Esterling, Kevin M.

Uploaded 08-18-1997
Keywords Policy Alliances
Organizational Deliberation
Nested Logit
Abstract This paper explains lobbying organizations' choice to join alliances on policy matters with respect to 1) the degree of the organization's access to external information sources, and 2) the amount of internal organizational conflict and deliberation. An informational view of lobbying suggests that the more informed an organizational actor is, the more likely it will gain access to governmental decision makers; and greater access to the government will decrease the utility of joining a cooperative lobbying effort. In addition, internal conflict in the definition of a policy position will limit an organization's ability to take any position on a policy issue, while successful internal deliberation will augment a lobbying organization's ability to find cooperation partners. Outcome and explanatory data are taken from an existing dataset housed at ICPSR. Nested logit maximum likelihood estimates for the trichotomous-choice cooperation model are presented and interpreted. Support is lent to both the internal conflict and the informational theories of cooperation in policy lobbying. In particular, the model results suggest that organizations predisposed to internal conflict find both non-policy lobbying and cooperative lobbying appealing, suggesting that these organizations only sometimes successfully deliberate over policy. And consistent with the information view of lobbying, greater access to information sharply decreases the utility of lobbying cooperatively.

29
Paper
Logistic Regression in Rare Events Data (revised)
King, Gary
Zeng, Langche

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

30
Paper
Heterogeneity, Salience, and Voter Decision Rules for Candidate Preference
Glasgow, Garrett

Uploaded 08-10-1997
Keywords voter behavior
decision rules
rank ordered logit
salience
issue voting
Abstract Voters in American Presidential elections display a wide variety of decision rules when choosing a candidate. One form of this heterogeneity is differential weighting of issues used to make a vote choice. The structure of this heterogeneity and differential salience of issues has important implications for the American political process. Determining the nature of these heterogeneous preferences is vital to understanding electoral politics in the United States. An empirical technique for modeling and exploring heterogeneity is developed and applied to the 1980 NES Panel Study. I show that heterogeneity in voter decision rules is widespread, and that while many voters rely on non-issue considerations when determining candidate preference, issue voting does play a role in the decision rules of many voters.

31
Paper
Logistic Regression in Rare Events Data
King, Gary
Zeng, Langche

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

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

Uploaded 07-23-1997
Keywords discrete choice
strategic
QRE
logit
international relations
Abstract Typical applications of logit and probit to theories of international conflict do not capture the structure of the strategic interdependence implied by those theories. In this paper I demonstrate how to use a game-theoretic solution concept, the quantal response equilibrium (QRE), to derive strategic discrete choice models of international conflict, where the structure of the strategic interaction is incorporated directly in the statistical model. I demonstrate this for a crisis interaction model and use monte carlo analysis to show that logit provides estimates with incorrect substantive interpretations and fitted values that are often far from the true values. Finally, I reanalyze a well-known game-theoretic model of war, Bueno de Mesquita and Lalman's (1992) international interaction game, using this method. My results indicate that their model does not explain international interaction as well as they claim.

33
Paper
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!

34
Paper
Coordinating Voting in American Presidential and House Elections
Mebane, Walter R.

Uploaded 07-21-1997
Keywords coordinating voting
moderating voting
probabilistic voting
spatial voting
retrospective voting
presidential elections
congressional elections
split-ticket voting
pivotal voter theorem
beta distribution
multinomial logit
maximum likelihood
Abstract I describe and estimate a probabilistic voting model designed to test whether individuals' votes for President and for the House of Representatives are coordinated with respect to two cutpoints on a single spatial dimension, in the way that Alesina and Rosenthal's pivotal voter theorem suggests they should be. In my model the cutpoints are random variables about which each individual has a subjective probability distribution. Each person's probabilistic coordinating voting behavior occurs relative to the cutpoints' expected values under the distribution. The model implements the idea the pattern of coordination depends on an individual's evaluation of the economy. The economic bias in the coordinating pattern implies that voters punish a Democratic President for success in improving the economy. The economically successful Democratic President can avoid losses only if the voters who rate the economy as having improved also believe that the policy position of the Democratic party has shifted to the right.

35
Paper
Negotiated Compliance: Social Solutions to the 'Principal's Problem'
Whitford, Andrew B.
Miller, Gary J.
Bottom, William P.

Uploaded 07-11-2003
Keywords principal-agency theory
experiments
incentives
trust
hierarchical logit
Abstract Principal-agency theory has typically analyzed the principal's problem1: how to write a contract with incentives that will induce an agent to provide the principal with the maximum feasible expected gain. In practice, principal-agent contracts are typically negotiated, not imposed. Experiments indicate that agent compliance is determined less by the negotiated terms of the contract than by expectations created by the negotiation process itself. We interpret this as justification for a renewed interest in the politics of negotiation and bureaucratic politics.

36
Paper
A Panel Probit Analysis of Campaign Contributions and Roll Call Votes
Wawro, Gregory

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

37
Paper
Statistical Backwards Induction: A Simple Method for Estimating Statistical Strategic Models
Bas, Muhammet
Signorino, Curtis
Walker, Robert

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

38
Poster
The Design of National Human Rights Institutions: A Comparative Analysis
Welch, Ryan
Welch, Ryan

Uploaded 07-22-2014
Keywords National Human Rights Institutions
Human Rights
Domestic Institutions
Executive
Institutional Design
Bayesian Logit
Abstract How do national human rights institutions (NHRIs) differ? Why do these differences occur? This study aims to answer those questions by developing a theory of executive power to influence institution design. Specifically, the executive wishes to keep NHRIs from holding him accountable. He does so by exerting his political and legal advantages vis–a–vis the legislature to keep the NHRI from being able to levy punishment against him, essentially leaving the NHRI toothless. The legislature will press back more or less based on the political and legal circumstances making the executive’s preferences harder or easier to achieve. By estimating a linear Bayesian logistic regression on the global population of NHRIs from 1991–2012, I confirm the theory that the executive’s ability to exert his will affects the design of NHRIs.


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