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Below results based on the criteria 'Comparative Politics'
Total number of records returned: 6
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.
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.
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 difficulties—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.
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.