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27
A Simple DistributionFree Test for Nonnested Hypotheses
, 2004
"... In this paper, we more fully develop the properties of the distributionfree test for nonnested model discrimination introduced by Clarke (2003). We prove that the test is both consistent and unbiased. We demonstrate that the test is asymptotically more efficient for highly leptokurtic distributions ..."
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Cited by 31 (1 self)
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In this paper, we more fully develop the properties of the distributionfree test for nonnested model discrimination introduced by Clarke (2003). We prove that the test is both consistent and unbiased. We demonstrate that the test is asymptotically more efficient for highly leptokurtic distributions than the wellknown Vuong test. Using a Monte Carlo experiment, we then establish that the distribution of individual loglikelihood ratios (the data to which both tests are applied) is highly leptokurtic. Finally, we use the same Monte Carlo to measure the performance of the distributionfree test and the Vuong test. The Monte Carlo advances previous efforts in that it allows for two misspecified models that vary in distance from a true, but “unknown,” data generating process. The results indicate that the power of the new test is as great as or, for many alternatives, significantly greater than the power of the Vuong test.
Comparable Preference Estimates across Time and Institutions for the Court
 Congress, and Presidency.” American Journal of Political Science
"... Empirically oriented scholars often struggle with how to measure preferences across time and institutional contexts. This article characterizes these difficulties and provides a measurement approach that incorporates information that bridges time and institutions in a Bayesian Markov Chain Monte Car ..."
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Cited by 29 (1 self)
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Empirically oriented scholars often struggle with how to measure preferences across time and institutional contexts. This article characterizes these difficulties and provides a measurement approach that incorporates information that bridges time and institutions in a Bayesian Markov Chain Monte Carlo approach to ideal point measurement. The resulting preference estimates for presidents, senators, representatives, and Supreme Court justices are comparable across time and institutions. These estimates are useful in a variety of important research projects, including research on statutory interpretation, executive influence on the Supreme Court, and Senate influence on court appointments. Scholars comparing preferences across institutionsmust confront this hard fact of life: even the bestmeasure of congressional preferences based only on votes in Congress is not directly comparable to even the best measure of judicial preferences based only on Supreme Court votes. Scholars comparing preferences across time face a similar reality: if they observe a change in voting patterns, is it because preferences have shifted or because the agenda has shifted? Such challenges have left several substantive research agendas waiting upon methodological advances. For ex
The phantom menace: Omitted variable bias in econometric research
 Conflict Management and Peace Science
"... Quantitative political science is awash in control variables. The justification for these bloated specifications is usually the fear of omitted variable bias. A key underlying assumption is that the danger posed by omitted variable bias can be ameliorated by the inclusion of relevant control variabl ..."
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Cited by 25 (1 self)
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Quantitative political science is awash in control variables. The justification for these bloated specifications is usually the fear of omitted variable bias. A key underlying assumption is that the danger posed by omitted variable bias can be ameliorated by the inclusion of relevant control variables. Unfortunately, as this article demonstrates, there is nothing in the mathematics of regression analysis that supports this conclusion. The inclusion of additional control variables may increase or decrease the bias, and we cannot know for sure which is the case in any particular situation. A brief discussion of alternative strategies for achieving experimental control follows the main result. Keywords omitted variable bias, specification, control variables, research design Quantitative political science is awash in control variables. It is not uncommon to see statistical models with 20 or more independent variables. An article in the August 2004 issue of the American Political Science Review, for example, reports a model with 22 independent variables (Duch & Palmer, 2004). 1 The situation is no different if we consider
Bayesian model averaging: Theoretical developments and practical applications. Working paper, Society for Political Methodology
, 2008
"... Political science researchers typically conduct an idiosyncratic search of possible model configurations and then present a single specification to readers. This approach systematically understates the uncertainty of our results, generates fragile model specifications, and leads to the estimation of ..."
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Cited by 15 (5 self)
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Political science researchers typically conduct an idiosyncratic search of possible model configurations and then present a single specification to readers. This approach systematically understates the uncertainty of our results, generates fragile model specifications, and leads to the estimation of bloated models with too many control variables. Bayesian model averaging (BMA) offers a systematic method for analyzing specification uncertainty and checking the robustness of one’s results to alternative model specifications, but it has not come into wide usage within the discipline. In this paper, we introduce important recent developments in BMA and show how they enable a different approach to using the technique in applied social science research. We illustrate the methodology by reanalyzing data from three recent studies using BMA software we have modified to respect statistical conventions within political science. 1
A statistical method for empirical testing of competing theories
, 2010
"... Empirical testing of competing theories lies at the heart of social science research. We demonstrate that a wellknown class of statistical models, called finite mixture models, provides an effective way of rival theory testing. In the proposed framework, each observation is assumed to be generated ..."
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Cited by 8 (1 self)
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Empirical testing of competing theories lies at the heart of social science research. We demonstrate that a wellknown class of statistical models, called finite mixture models, provides an effective way of rival theory testing. In the proposed framework, each observation is assumed to be generated either from a statistical model implied by one of the competing theories or more generally from a weighted combination of multiple statistical models under consideration. Researchers can then estimate the probability that a specific observation is consistent with each rival theory. By modeling this probability with covariates, one can also explore the conditions under which a particular theory applies.We discuss a principled way to identify a list of observations that are statistically significantly consistent with each theory and propose measures of the overall performance of each competing theory. We illustrate the relative advantages of our method over existing methods through empirical and simulation studies. Empirical testing of competing theories lies at the heart of social science research. Since there typically exist alternative theories explaining the same phenomena, researchers can often increase the plausibility of their theory by empirically demonstrating its superior explanatory power over rival theories. In political
1 Reconciling Institutions: Nested, Horizontal, Overlapping, and Independent Institutions
, 2005
"... This memo is divided into three parts. The first concerns the origins of the concept of nesting and the literature on nested systems and nested regimes/institutions. Per the focus of the conference, the second section considers the political process of bargaining strategies within the context of exi ..."
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This memo is divided into three parts. The first concerns the origins of the concept of nesting and the literature on nested systems and nested regimes/institutions. Per the focus of the conference, the second section considers the political process of bargaining strategies within the context of existing institutions,1 be they sectoral or regional. In the third section, I go beyond the static analysis of bargaining within a preset institutional context, and focus on the politics of institutional change as a key strategy. Because new or significantly modified institutions may create institutional overlap, I consider the question of institutional reconciliation by looking at what I have termed nested, horizontal, and independent institutions in the context of institutional design.
Discriminating methods: tests for non nested discrete choice models
, 2003
"... We consider the problem of choosing between rival statistical models that are nonnested in terms of their functional forms.We assess the ability of two tests, one parametric and one distribution free, to discriminate between such models. Our Monte Carlo simulations demonstrate that both tests are, ..."
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Cited by 2 (0 self)
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We consider the problem of choosing between rival statistical models that are nonnested in terms of their functional forms.We assess the ability of two tests, one parametric and one distribution free, to discriminate between such models. Our Monte Carlo simulations demonstrate that both tests are, to varying degrees, able to discriminate between strategic and nonstrategic discrete choice models. The distributionfree test appears to have greater relative power in small samples. The empirical study of political science has, in the last ten years, undergone something akin to a sea change.Where it was once common for political scientists to employ a linear functional form regardless of the theory being tested,we now see new attention being paid to the connection between theory and model (Morton, 1999; Signorino, 1999; Signorino and Yilmaz, 2003). The result of this attention has been an expansion in the number of different functional forms being employed by quantitative political scientists. This increase in the number of modeling choices available to researchers has brought with it new challenges. For example, although Signorino (1999) demonstrates that traditional specifications of statistical models are generally inconsistent with strategic theories of political science, no rigorous framework has emerged for comparing strategic models
The Effect of Priors on Approximate Bayes Factors from MCMC Output.” Unpublished manuscript
"... The MCMC approach to calculating approximate Bayes factors is considered. The calculation, consisting of a loglikelihood, a prior, and a posterior, presents an excellent opportunity to observe directly the effects of priors on Bayes factors. Three empirical examples demonstrate that Bayes factors a ..."
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Cited by 2 (2 self)
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The MCMC approach to calculating approximate Bayes factors is considered. The calculation, consisting of a loglikelihood, a prior, and a posterior, presents an excellent opportunity to observe directly the effects of priors on Bayes factors. Three empirical examples demonstrate that Bayes factors are sensitive to a combination of the prior variance and the difference in the number of parameters between the rival models. a I thank Susan Murphy for helpful discussions and Paul Huth, Christopher Gelpi, D.
Provocation and the strategy of terrorist and guerilla attacks. International Organization, Forthcoming
, 2015
"... Violent nonstate groups are usually weaker than the states they target. Accordingly, theory suggests that groups carefully condition their choice of tactics on anticipated state response. Yet, we know very little about whether and how groups strategically plan attacks in anticipation of state respo ..."
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Violent nonstate groups are usually weaker than the states they target. Accordingly, theory suggests that groups carefully condition their choice of tactics on anticipated state response. Yet, we know very little about whether and how groups strategically plan attacks in anticipation of state response. We do not know if and under what conditions groups employ violent tactics to provoke or avoid a forceful state response, although extant theory is consistent with both possibilities. Relatedly, there is little systematic evidence about why groups choose terrorist or guerilla tactics and how this choice relates to anticipated state response. I develop a theoretical and empirical model of the interaction between groups and states that generates unique evidence on all three fronts. Using data on attacks in Western Europe from 1950–2004, I show that guerilla attacks are associated with provocation of forceful state response, while terrorist attacks are associated with avoiding forceful response. Furthermore, I show that groups effectively choose their tactics to avoid forceful state responses that are too damaging for themselves but provoke forceful responses that disproportionately harm civilians. These findings survive several difficult robustness and model specification tests.
2012. “Democracy and Multilateralism: The Case of Vote Buying
 in the UN General Assembly.” Working
"... Democracies are more supportive of U.S. positions on important votes in the UN General Assembly than nondemocracies. Is this because democracies share common perspectives, or does this pattern reflect coercion? Since 1985, U.S. law has stipulated that the State Department identify important votes ..."
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Democracies are more supportive of U.S. positions on important votes in the UN General Assembly than nondemocracies. Is this because democracies share common perspectives, or does this pattern reflect coercion? Since 1985, U.S. law has stipulated that the State Department identify important votes and that aid disbursements reflect voting decisions. To unravel these alternative explanations, we introduce a strategic statistical model that allows us to estimate voting preferences, vulnerability to influence, and credibility of linkage, which are theoretical quantities of interest that are not directly observable. The results reject the hypothesis of shared democratic values: poor democracies have voting preferences that are more oppositional to U.S. positions than autocracies, and they are more willing than autocracies to take symbolic stands that may cost them foreign aid. Democracies support U.S. positions, however, because U.S. aid linkages are more credible when directed towards democratic countries. Splitting the sample into Cold War and postCold War segments, we find that the end of the Cold War changed the way U.S. linkage strategies treated allies and left and rightleaning governments, but the effects of democracy remained constant. ∗Data replication materials are available at