Political Analysis最新文献_第8页

Balance as a Pre-Estimation Test for Time Series Analysis 平衡作为时间序列分析的预估计检验

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-04-20 DOI: 10.1017/pan.2022.4

Mark Pickup, Paul M. Kellstedt

引用次数: 6

Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs 使用多个预处理周期改善差异中的差异和交错采用设计

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-03-30 DOI: 10.1017/pan.2022.8

Naoki Egami, S. Yamauchi

{"title":"Using Multiple Pretreatment Periods to Improve Difference-in-Differences and Staggered Adoption Designs","authors":"Naoki Egami, S. Yamauchi","doi":"10.1017/pan.2022.8","DOIUrl":"https://doi.org/10.1017/pan.2022.8","url":null,"abstract":"Abstract While a difference-in-differences (DID) design was originally developed with one pre- and one posttreatment period, data from additional pretreatment periods are often available. How can researchers improve the DID design with such multiple pretreatment periods under what conditions? We first use potential outcomes to clarify three benefits of multiple pretreatment periods: (1) assessing the parallel trends assumption, (2) improving estimation accuracy, and (3) allowing for a more flexible parallel trends assumption. We then propose a new estimator, double DID, which combines all the benefits through the generalized method of moments and contains the two-way fixed effects regression as a special case. We show that the double DID requires a weaker assumption about outcome trends and is more efficient than existing DID estimators. We also generalize the double DID to the staggered adoption design where different units can receive the treatment in different time periods. We illustrate the proposed method with two empirical applications, covering both the basic DID and staggered adoption designs. We offer an open-source R package that implements the proposed methodologies.","PeriodicalId":48270,"journal":{"name":"Political Analysis","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42521787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels 一种无地面实况标签的提示工程信息论方法

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-03-21 DOI: 10.1017/pan.2023.2

Lisa P. Argyle, E. Busby, Nancy Fulda, Joshua R Gubler, Christopher Rytting, Taylor Sorensen, D. Wingate

引用次数: 93

Taking Distributions Seriously: On the Interpretation of the Estimates of Interactive Nonlinear Models 认真对待分布:关于相互作用非线性模型估计的解释

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-03-18 DOI: 10.1017/pan.2022.9

A. Zhirnov, Mert Moral, Evgeny Sedashov

{"title":"Taking Distributions Seriously: On the Interpretation of the Estimates of Interactive Nonlinear Models","authors":"A. Zhirnov, Mert Moral, Evgeny Sedashov","doi":"10.1017/pan.2022.9","DOIUrl":"https://doi.org/10.1017/pan.2022.9","url":null,"abstract":"Abstract In recent decades, political science literature has experienced significant growth in the popularity of nonlinear models with multiplicative interaction terms. When one or more constitutive variables are not binary, most studies report the marginal effect of the variable of interest at its sample mean while allowing the other constitutive variable/s to vary along its range and holding all other covariates constant at their means, modes, or medians. In this article, we argue that this conventional approach is not always the most suitable since the marginal effect of a variable at its sample mean might not be sufficiently representative of its prevalent effect at a specific value of the conditioning variable and might produce excessively model-dependent predictions. We propose two procedures to help researchers gain a better understanding of how the typical effect of the variable of interest varies as a function of the conditioning variable: (1) computing and plotting the marginal effects at all in-sample combinations of the values of the constitutive variables and (2) computing and plotting what we call the “Distribution-Weighted Average Marginal Effect” over the values of the conditioning variable.","PeriodicalId":48270,"journal":{"name":"Political Analysis","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41839871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

PAN volume 30 issue 2 Cover and Front matter PAN第30卷第2期封面和封面

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-03-10 DOI: 10.1017/pan.2022.6

Emily M. Farris

引用次数: 0

PAN volume 30 issue 2 Cover and Back matter PAN第30卷第2期封面和封底

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-03-10 DOI: 10.1017/pan.2022.7

引用次数: 0

Geographic Boundaries and Local Economic Conditions Matter for Views of the Economy 地理边界和当地经济条件对经济观至关重要

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-02-22 DOI: 10.1017/pan.2021.50

James Bisbee, J. Zilinsky

引用次数: 0

Quantifying Bias from Measurable and Unmeasurable Confounders Across Three Domains of Individual Determinants of Political Preferences 量化政治偏好个体决定因素三个领域中可测量和不可测量的混淆者的偏差

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-02-22 DOI: 10.1017/pan.2022.2

Rafael Ahlskog, Sven Oskarsson

{"title":"Quantifying Bias from Measurable and Unmeasurable Confounders Across Three Domains of Individual Determinants of Political Preferences","authors":"Rafael Ahlskog, Sven Oskarsson","doi":"10.1017/pan.2022.2","DOIUrl":"https://doi.org/10.1017/pan.2022.2","url":null,"abstract":"Abstract A core part of political research is to identify how political preferences are shaped. The nature of these questions is such that robust causal identification is often difficult to achieve, and we are not seldom stuck with observational methods that we know have limited causal validity. The purpose of this paper is to measure the magnitude of bias stemming from both measurable and unmeasurable confounders across three broad domains of individual determinants of political preferences: socio-economic factors, moral values, and psychological constructs. We leverage a unique combination of rich Swedish registry data for a large sample of identical twins, with a comprehensive battery of 34 political preference measures, and build a meta-analytical model comparing our most conservative observational (naive) estimates with discordant twin estimates. This allows us to infer the amount of bias from unobserved genetic and shared environmental factors that remains in the naive models for our predictors, while avoiding precision issues common in family-based designs. The results are sobering: in most cases, substantial bias remains in naive models. A rough heuristic is that about half of the effect size even in conservative observational estimates is composed of confounding.","PeriodicalId":48270,"journal":{"name":"Political Analysis","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47468189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Polls, Context, and Time: A Dynamic Hierarchical Bayesian Forecasting Model for US Senate Elections 民调、背景和时间：美国参议院选举的动态分层贝叶斯预测模型

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-01-18 DOI: 10.1017/pan.2021.42

Yehua Chen, R. Garnett, J. Montgomery

引用次数: 1

An Improved Method of Automated Nonparametric Content Analysis for Social Science 一种改进的社会科学非参数内容自动分析方法

IF 5.4 2区社会学

Political Analysis Pub Date : 2022-01-07 DOI: 10.1017/pan.2021.36

Gary King, Connor Jerzak, Anton Strezhnev

引用次数: 5