Government Performance, Valence Judgments, and The Dynamics of Party Support

政府绩效、效价判断和政党支持的动态

• 批准号: 0351987
• 负责人: Marianne Stewart
• 金额: --
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0351987&HistoricalAwards=false
• 关键词: Government; Performance; Valence; Judgments; Dynamics

This research project advances knowledge of the dynamics and determinants of party support in democratic polities. One aspect of the research concerns dynamic relationships between public service delivery and aggregate party support. Acutely aware of the importance of these relationships, governing parties of varying ideological hues have made repeated attempts not only to bolster the supply of public services, but also to curb the electorate's demand for them. The latter efforts have met with relatively little success. Many voters remain convinced that government can, and should, be heavily involved in fields such as education, health, welfare, and transportation, that privatization schemes often go awry, and that government is responsible when public services go badly or are not delivered at all. To date, however, research on factors affecting the aggregate dynamics of party support has focused heavily, indeed almost exclusively, on the impact of economic conditions and various "one-off" political events. By restricting attention to economic conditions and salient events, existing studies have ignored the consequences of public reactions to government performance in a wide variety of highly salient policy areas such as health care, education, and national security. Building on the results of earlier research on the determinants of party support conducted by the principal investigator and colleagues, the study will specifies and tests rival models of how government performance evaluations in several important policy areas affect the dynamics of aggregate-level support for governing and opposition parties in a major mature democracy, Great Britain. A second aspect of the research concerns modeling the individual-level dynamics of party support. Here, the principal focus is gathering the large-N, multi-wave panel data needed to address longstanding controversies regarding the individual-level dynamics of partisan attachments. Although these controversies have major theoretical implications for understanding the nature of party support in democracies new and old alike, their resolution has been hindered by the lack of sufficiently large multi-wave panels, disputes regarding the proper measurement of partisan attachments, and the absence of suitable statistical tools for analyzing the latent-level dynamics of nominal-scale measures of partisanship. Such tools are now available, and the research gathers the requisite large N panel data needed to analyze individual-level latent variable dynamics of partisan attachments measured using both the traditional British Election Study (BES) party identification question sequence and an alternative party supporter battery. The aggregate-level time series and individual-level panel data needed to conduct the research are gathered in 48 consecutive monthly surveys of the British electorate. Surveys are be conducted by YouGov, Britain's premier internet survey firm. Each monthly survey is conducted with a national sample of 1,000 persons 18 years of age or older, yielding a total N of 48,000 cases. Multi-wave national panels, including a four-wave panel with an N of approximately 5,000 cases will be embedded in the surveys. The large size of the cross-sectional and panel surveys facilitate theoretically interesting sub-group analyses. Aggregate time series analyses will be informed by recent work by the principal investigator and colleagues on the specification and testing of rival fractional error correction models. Individual- and aggregate-level data gathered in the study will be deposited annually with the ICPSR Data Archive, and also will be available for downloading from the project website. The website also will provide monthly "DataCam" updates of the evolution of time series variables. Project findings will be presented at major scholarly conferences, and papers and technical reports will be available for downloading from the website.

该研究项目促进了对民主政治中政党支持的动态和决定因素的知识。 研究的一个方面涉及公共服务交付与总体支持之间的动态关系。 敏锐地意识到这些关系的重要性，管理各种意识形态色调的当事方不仅重复尝试增强公共服务的供应，而且还遏制了选民对他们的需求。 后者的努力取得了相对较少的成功。 许多选民仍然相信，政府可以并且应该大量参与教育，健康，福利和运输等领域，即私有化计划经常出现问题，并且当公共服务遭受严重运行或根本不交付时，政府将负责。 然而，迄今为止，对影响党支持总体动态的因素的研究已经重点关注经济状况和各种“一次性”政治事件的影响。 通过限制对经济状况和显着事件的关注，现有研究忽略了公众对政府绩效的影响，在各种高度显着的政策领域，例如医疗保健，教育和国家安全。 基于对主要研究者和同事进行政党支持决定因素的较早研究结果，该研究将指定并测试竞争模型，即几个重要政策领域的政府绩效评估如何影响对大英国大英国大英国大英国民主党中政治和反对派的总体支持和反对派的动态。 研究的第二个方面涉及建模政党支持的个体级别动态。 在这里，主要重点是收集大N多波面板数据，以解决有关党派附件的个人级别动态的长期争议。 尽管这些争议对于理解新的和老民主的政党支持的性质具有重大理论意义，但由于缺乏足够大的多波浪小组，关于党派依恋的适当测量以及缺乏适当的统计工具来分析综合级别的标准级别测量值的统计动态的争议，他们的解决方案受到了阻碍。 现在可以使用此类工具，研究收集了使用传统的英国选举研究（BES）政党识别问题序列和替代政党支持者电池进行测量的党派依恋的个人级别潜在可变动态所需的大型N面板数据。进行研究所需的汇总时间序列和个人级别的面板数据连续48次对英国选民进行了48次调查。 调查由英国主要互联网调查公司YouGov进行。 每个月的调查都是由18岁或以上的1,000人的全国样本进行的，总共产生48,000例案件。 多波国家面板，包括一个四波面板，其中大约5,000例案件的N将嵌入调查中。 横截面和面板的大尺寸调查有助于理论上有趣的亚组分析。 主要研究者和同事的最新工作将为竞争对手分数误差校正模型的规范和测试提供汇总时间序列分析。 研究中收集的个人和汇总级别的数据将每年与ICPSR数据存档一起存放，并且还可以从项目网站下载。该网站还将提供时间序列变量演变的每月“数据录”更新。 项目结果将在主要的学术会议上介绍，并且将从网站下载论文和技术报告。