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Below results based on the criteria 'comparative'
Total number of records returned: 13
Modeling Multilevel Data Structures
Jones, Bradford S.
Steenbergen, Marco R.
Although integrating multiple levels of data into an analysis can often yield better inferences about the phenomenon under study, traditional methodologies used to combine multiple levels of data are problematic. In this paper, we discuss several methodologies under the rubric of multilevel analysis. Multilevel methods, we argue, provide researchers, particularly researchers using comparative data, substantial leverage in overcoming the typical problems associated with either ignoring multiple levels of data, or problems associated with combining lower-level and higher-level data (including overcoming implicit assumptions of fixed and constant effects). The paper discusses several variants of the multilevel model and provides an application of individual-level support for European integration using comparative political data from Western Europe.
Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program
comparative case studies
Building on an idea in Abadie and Gardeazabal (2003), this article investigates the application of synthetic control methods to comparative case studies. We discuss the advantages of these methods and apply them to study the effects of Proposition 99, a large-scale tobacco control program that California implemented in 1988. We demonstrate that following Proposition 99 tobacco consumption fell markedly in California relative to a comparable synthetic control region. We estimate that by the year 2000 annual per-capita cigarette sales in California were about 26 packs lower than what they would have been in the absence of Proposition 99. Given that many policy interventions and events of interest in social sciences take place at an aggregate level (countries, regions, cities, etc.) and affect a small number of aggregate units, the potential applicability of synthetic control methods to comparative case studies is very large, especially in situations where traditional regression methods are not appropriate. The methods proposed in this article produce informative inference regardless of the number of available comparison units, the number of available time periods, and whether the data are individual (micro) or aggregate (macro). Software to compute the estimators proposed in this article is available at the authors web-pages.
Estimating Party Policy Positions with Uncertainty Based on Manifesto Codings
Comparative Manifesto Project
Mapping party positions
Spatial models of party competition are central to modern political science. Before we can elaborate such models empirically, we need reliable and valid measurements of agents' positions on salient policy dimensions. The primary empirical times series of estimated party positions in many countries derives from the content analysis of party manifestos by the Comparative Manifesto Project (CMP). Despite widespread use of the CMP data, and despite the fact that estimates in these data arise from documents coded once, and once only, by a single human researcher, the level of error in the CMP estimates has never been estimated or even fully characterized. This greatly undermines the value of the CMP dataset as a scientific resource. It is in many ways remarkable that so much has been published in the best professional journals using data that almost certainly has substantial, but completely uncharacterized, error. We remedy this situation. We outline the process of generating CMP document codings and positional estimates. Error in this process arises, not only from the obvious source of coder unreliability, but also from fundamental variability in the stochastic process by which latent party positions are translated into observable manifesto texts. Using the quasi-sentence codings from the CMP project, we reproduce the error-generating process by simulating coder unreliability and bootstrapping analyses of coded quasi-sentences to reproduce both forms of error. Using our estimates of these errors, we suggest and demonstrate ways to correct otherwise biased inferences derived from statistical analyses of the CMP data.
Noughts and Crosses. Challenges in Generating Political Positions from CMP-Data.
The Comparative Manifesto Project (CMP) dataset is the only dataset providing information about the positions of parties for comparative researchers across time and countries. This article evaluates its structure and finds a peculiarity: A high number of zeros and their unequal distribution across items, countries and time. They influence the results of any procedure to build a scale, but especially those using factor analyses. The article shows that zeroes have different meanings: Firstly, there are substantial zeroes in line with saliency theory. Secondly, zeroes exist for non-substantial reasons: The length of a manifesto and the percentage of uncoded sentences, both strongly varying across time and country. We quantify the problem and propose a procedure to identify data points containing non-substantial zeroes. For the future comparative use of the dataset we plead for a theoretical selection of items combined with the information about the likelihood that zeroes are substantially meaningful.
Balancing Competing Demands: Position-Taking and Election Proximity in the European Parliament
Vander Wielen, Ryan
Parties value unity, yet, members of parliament face competing demands, giving them incentives to deviate from the party. For members of the European Parliament (MEPs), these competing demands are national party and European party group pressures. Here, we look at how MEPs respond to those competing demands. We examine ideological shifts within a single parliamentary term to assess how European Parliament (EP) election proximity affects party group cohesion. Our formal model of legislative behavior with multiple principals yields the following hypothesis: When EP elections are proximate, national party delegations shift toward national party positions, thus weakening EP party group cohesion. For our empirical test, we analyze roll call data from the fifth EP (1999-2004) using Bayesian item response models. We find significant movement among national party delegations as EP elections approach, which is consistent with our theoretical model, but surprising given the existing literature on EP elections as second-order contests.
An Integrated Perspective on Party Platforms and Electoral Choice
generalized additive models
There are several perspectives on voting behavior that usually constitute separate strands of research: the impact of social background on vote choice, the relation between policy positions of parties and policy preferences of voters, and the effect of party platforms on the electoral success of parties. Although they all apply to the same entities, that is, to voters and parties, these different perspectives seem to have divergent implications. Thus we are in need of a way to reconcile these perspectives. The empirical results presented in this paper suggest a way what such a reconciliation should look like. They could be summarized as follows: In party platforms, several ideological dimensions can be distinguished that are connected with different cleavages in the Lispet-Rokkan sense. Second, it is shown that individuals from different social groups differ in the way they evaluate party platforms and choose among parties. Third, the way these individuals evaluate party platforms conforms to spatial notions of voting. Fourth, a general pattern of platform evaluation established on the base of pooled data of several countries accounts to a large degree for differences between levels of religious voting in these countries.
Monotone Comparative Statics in Models of Politics: A Method for Simplifying Analysis and Enhancing Empirical Content
Bueno de Mesquita, Ethan
empirical implications of theoretical models
We elucidate a powerful yet simple method for deriving comparative statics conclusions for a wide variety of models: Monotone Comparative Statics (Milgrom and Shannon, 1994). Monotone comparative static methods allow researchers to extract robust, substantive empirical implications from formal models that can be tested using ordinal data and simple non-parametric tests. They also replace a diverse range of more technically di±cult mathematics (facilitating richer, more realistic models), a large set of assumptions that are hard to understand or justify substantively (highlighting the political intuitions underlying a model's results), and a complicated set of methods for extracting implications from models. We present an accessible introduction to the central monotone comparative statics results and a series of practical tools for using these techniques in applied models (with reference to original sources, when relevant). Throughout we demonstrate the techniques with examples drawn from political science.
Parties, Issue Spaces, and Voting: A Comparative Perspective
Alvarez, R. Michael
Willette, Jennifer R.
An important property of any party system is the set of choices it presents to the electorate. In this paper we analyze the distribution of the parties in the multidimensional issue space, and introduce the notion of compactness of the party system. We show how compactness can be measured using standard survey items found on national election surveys. By measuring the spacing of the parties relative to the distribution of the voters, we are able to compute a metric-free measure of compactness of the party system. Comparing the compactness of party systems across countries allows us to determine the relative amount of issue choice afforded voters in different polities. We test the impact compactness of the party space has on voter choice in four countries: the United States, the Netherlands, Canada, and Great Britain. We demonstrate that the more compact the issue space on any issue, the less voters weight that issue in making their vote decision. Thus we provide evidence for theories of issue voting.
Democracy and Exchange Rates: An Experimental Study
Freeman, John R.
Markov switching model
The world's financial markets are becoming increasingly liberalized and interconnected. There is much debate about whether this development is socially desirable. Of increasing interest in this debate are the implications of the globalization of finance for democracy. The relationship between the workings of currency markets and democratic institutions is studied. The economic literature on exchange rate determination is briefly reviewed. The Markov switching model is considered as one of the most useful with which to analyze the politics of exchange rate determination. Next, the political science literature is discussed, including the research on electoral systems and comparative democracy. Out of this discussion emerge several competing propositions about how political (re)equilibration affects currency markets, more specifically, what the Markov switching framework should show about the impact of electoral outcomes and political polls on compound returns (the log difference of the exchange rate) in some or all democracies. A design for testing these propositions then is laid out and implemented. The results support the view that democratic politics affects currency markets. In particular, opinion polls about chief executive and government performance have a direct effect on the probabilities of switches between currency regimes. This suggests that these polls cause currency traders to revise their expectations about the stability of governments and (or) the content of public policy. In addition, the results refute claims that pluralist and majoritarian forms of democracy are more likely to be a source of trader uncertainty and hence regime shifts than corporatist and consensual forms of democracy. There is some evidence that (democratic) institutional "incoherency" (Garrett, 1998) is a source of market uncertainty and therefore that the effects of opinion polls and other political variables on the probabilities of regime shifts are greater in the respective countries.
Using the Predicted Responses from List Experiments as Explanatory Variables in Regression Models
Greene, Kenneth F.
Item count technique
The list experiment, also known as the item count technique, is becoming increasingly popular as a survey methodology for eliciting truthful responses to sensitive questions. Recently, multivariate regression techniques have been developed to predict the unobserved response to sensitive questions using respondent characteristics. Nevertheless, no method exists for using this predicted response as an explanatory variable in another regression model. We address this gap by first improving the performance of a naive two-step estimator. Despite its simplicity, this improved two-step estimator can only be applied to linear models and is statistically inefficient. We therefore develop a maximum likelihood estimator that is fully efficient and applicable to a wide range of models. We use a simulation study to evaluate the empirical performance of the proposed methods. We also apply them to the Mexico 2012 Panel Study and examine whether vote-buying is associated with increased turnout and candidate approval. The proposed methods are implemented in open-source software.
Embracing Methodological Pluralism in Comparative Politics: Game Theory, Data Inspection, and Case Studies
Inferring causal relationships from cross national data poses inherent difficultiesâ€”an unsolvable problem. But the staple method of multiple regression obscures as much as it illuminates. We can do better with the data we have to generate more reliable statistical findings. This poster examines how game theory, simple data inspection, and case studies can provide additional support for well-substantiated arguments and expose concerns with problematic regression results. I draw examples from my substantive research focused mainly on civil wars and authoritarian regimes. Thus, this poster also summarizes methodological themes from my dissertation.
â€śMeaning Structuresâ€ť in Political Discourse: Measuring Institutional Dynamics of a Hybrid Democracy via the Topic Modeling from Contested Concepts in Newspaper Articles
Can topic modeling be a method for understanding the Realpolitik of â€śforeignâ€ť countries, while ensuring the objectivity and validity of oneâ€™s sources? Mohr (1998) prescribed that the analysis of meaning structures be applicable for cultural and institutional relations alike. We take this as an invitation to extend his suggestion to political discourse that reflects long-run histories and short-run rationality. Using categorized data, our topic models deconstruct polarized politics into a clash of cultural lineages (long-run histories) within institutional competition (short-run rationality). Transferring the approaches offered by teams of social/computer scientists (DiMaggio et al., 2013; Mohr et al., 2013; Mohr and Bogdanov, 2013), we analyze the changing meanings of democratic topics in the â€śhybridâ€ť democracy of South Korea, which has transitioned only relatively recently, in 1987. We posit the question: Is political representation coherent on democratization-related topics despite the political institutionalization over time? We test our assumption that strategic topics will create meaning structures that overlap or contradict, which would reflect institutional structures and divulge the causes for the status quo. Our hypothesis states that diametrical newspapers assemble different words for the same topics during the presidential election campaigns in 2012, where the ambiguous topic of â€śeconomic democratizationâ€ť elicited unparalleled and unanimous attention among politicians and media. By considering three newspaper sources that cover the left-center-right spectrum, we implement topic modeling to reverse-engineer from diverse representations back to one shared topic. Overall, we devise an inductive-deductive strategy, which reverses inductive topic modeling into a deductive (quantitative) method which serves to complement and validate inductive (ad hoc) analysis. The ad hoc style of analysis is a hypothetical standard procedure in area studies, where specialists are often specialized towards singular instead of comprehensive viewpoints. Demonstrating the logic of deductive validation through comprehensive data sources, our research design follows the below steps. First, we derive the traditional left-right topics and preferred interpretations from qualitative research. These are pre-validation meaning structures in themselves. Next, we crawl two corpora that are superset and subset topics respectively: economy and economic democratization. We differentiate these corpora by describing simple term and document frequencies. Now, we can begin the validation of aforementioned inductive meaning structures via topic modeling: We infer the top words of each topic and measure the similarities/distances between newspapers. Lastly, we discuss the competitive dynamics between political positions that arise from the results. The necessary step of validation is embodied in the matching of results against the inductive meaning structures that we established prior to running the topic models. Our goal is to present reliable meaning structures that counteract weaknesses of objectivity and source scope. For political science, it is also crucial to incorporate the dynamism of evolving discourse while including the rational aspect of political representation.
Conditional Relationships in Dynamic Models
Autoregressive distributed lag (ADL) and error correction models (ECMs) are commonly used in the analysis of time series data. Several recent papers have extended these models to include interaction terms, but the theory of conditional relationships in dynamic settings is underdeveloped. Three problems result. First, scholars cannot be sure OLS will produce consistent estimates. Second, both ADLs and ECMs have complicated structures of lags and differences, making it difficult to translate theory to specification. Scholars risk estimating restricted models, with unintended constraints on dynamic relationships among variables. Third, interactions change the calculation of important quantities such as long-run effects, but scholars are unable to account for these differences, leading to incomplete or incorrect inferences. This project provides theoretical and practical guidance to address these problems. I demonstrate that existing diagnostic tests can ensure consistent estimates from OLS. I then argue that scholars should proceed from a general specification where conditional relationships are modeled as interactions across stochastic series, without restrictions on how they work their way through the dynamic system. I also provide a general approach to inference for models with interactions, and discuss how various parameter restrictions affect calculating and interpreting quantities of interest. Finally, I illustrate the importance of these results using work by Blaydes and Kayser (2011) on democracy, growth, and inequality. Using a more general specification, I conclude that there is little difference across regime types in translating growth into lower inequality.