A Statistical Model for Party-Systems Analysis
Bibliographic Data
| ID | 6332131 |
|---|---|
| Authors | Arturas Rozenas (0000-0003-3510-0012, Duke University), R Michael Alvarez (0000-0002-8113-4451, Duke University) |
| Year | 2012 |
| Volume | 20 |
| Issue | 2 |
| Pages | 235-247 |
| Publication date | 2012-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Analysis (JOURNAL) |
| Journal identifiers | ISSN: 1047-1987 • E-ISSN: 1476-4989 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1093/pan/mpr041 |
| OpenAlex | W2062290584 |
| Language | EN |
| Citations received | 7 |
| References cited | 24 |
Empirical researchers studying party systems often struggle with the question of how to count parties. Indexes of party system fragmentation used to address this problem (e.g., the effective number of parties) have a fundamental shortcoming: since the same index value may represent very different party systems, they are impossible to interpret and may lead to erroneous inference. We offer a novel approach to this problem: instead of focusing on index measures, we develop a model that predicts theentire distributionof party vote-shares and, thus, does not require any index measure. First, a model of party counts predicts the number of parties. Second, a set of multivariatetmodels predicts party vote-shares. Compared to the standard index-based approach, our approach helps to avoid inferential errors and, in addition, yields a much richer set of insights into the variation of party systems. For illustration, we apply the model on two data sets. Our analyses call into question the conclusions one would arrive at by the index-based approach. Software is provided to implement the proposed model
Data mining · Econometrics · Economics · Index (typography · Inference · Measure (data warehouse · Set (abstract data type · Statistical inference · Statistics · Computer Science · Electoral Systems and Political Participation · Mathematics · Media Influence and Politics · Political Influence and Corporate Strategies · Artificial Intelligence
A Cross-National Measure of Electoral Competitiveness
What Makes Party Systems Different? A Principal Component Analysis of 17 Advanced Democracies 1970–2013
Literacy, Information, and Party System Fragmentation in India
Does Party-System Fragmentation Affect the Quality of Democracy
Factories for Votes? How Authoritarian Leaders Gain Popular Support Using Targeted Industrial Policy
Decision period and Duverger's psychological effect in FPTP elections
Crossing the Line
Making Votes Count
Bayesian Data Analysis
The Statistical Analysis of Compositional Data
Counting the Number of Parties
Modeling New Party Performance
The Measurement of Cross-cutting Cleavages and Other Multidimensional Cleavage Structures
An Easy and Accurate Regression Model for Multiparty Electoral Data
A Fast, Easy, and Efficient Estimator for Multiparty Electoral Data
Party System Compactness
A Seemingly Unrelated Regression Model for Analyzing Multiparty Elections
Constructing the Number of Parties
The Effective Number of Parties
Counting parties and identifying dominant party systems in Africa
Comparing Party Systems
Effective” Number of Parties
Rehabilitating Duverger’s Theory
Ethnic Heterogeneity, District Magnitude, and the Number of Parties
United we stand
A Theory of Voting Equilibria
A Statistical Model for Multiparty Electoral Data
| Unique citing works | 7 |
|---|---|
| Citations per year | 0,54 |
| Citation span | 2013 - 2024 (12) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |