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.

这项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了解。这项研究的一个方面涉及公共服务提供和政党支持总量之间的动态关系。执政党敏锐地意识到这些关系的重要性，具有不同意识形态色彩的执政党一再尝试不仅增加公共服务的供应，而且遏制选民对公共服务的需求。后一种努力收效甚微。许多选民仍然相信，政府可以而且应该大力参与教育、卫生、福利和交通等领域，私有化计划经常出错，当公共服务变得糟糕或根本没有提供时，政府应该负责。然而，到目前为止，对影响政党支持总体动态的因素的研究主要集中在经济状况和各种“一次性”政治事件的影响上，实际上几乎完全集中在经济状况的影响上。现有研究将注意力局限在经济状况和重大事件上，忽视了公众对政府在各种高度突出的政策领域的表现的反应的后果，如医疗保健、教育和国家安全。在首席调查员及其同事早先对政党支持决定因素进行研究的基础上，这项研究将具体说明并测试几个重要政策领域的政府绩效评估如何影响主要成熟民主国家英国执政党和反对党的总体支持动态的竞争模型。这项研究的第二个方面涉及对政党支持的个人层面的动态进行建模。这里，主要的关注点是收集大N、多波的面板数据，以解决关于党派依恋的个人层面动态的长期争议。尽管这些争议对理解新旧民主国家中政党支持的性质具有重大的理论意义，但这些争议的解决受到以下因素的阻碍：缺乏足够大的多波小组，关于正确衡量党派依恋的争议，以及缺乏适当的统计工具来分析名义尺度的党派之争的潜在动态。这样的工具现在已经可用，研究收集了必要的大型N面板数据，以分析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测量的党派依恋的个人层面潜在变量动态。进行这项研究所需的总体水平的时间序列和个人水平的面板数据是在连续48次对英国选民进行的月度调查中收集的。调查由英国首屈一指的互联网调查公司YouGov进行。每项月度调查在全国范围内抽样调查1,000名18岁或以上的人，共产生48,000个病例。多波国家小组，包括N个约5,000个病例的四波小组，将被纳入调查。大量的横断面调查和小组调查促进了理论上有趣的分组分析。综合时间序列分析将由首席调查员和同事最近在竞争对手分数误差修正模型的规范和测试方面所做的工作提供信息。研究中收集的个人和综合层面的数据将每年存入太平洋岛屿发展中国家国际研究中心数据档案馆，也可从项目网站下载。该网站还将每月提供“DataCam”更新的时间序列变量的演变。项目成果将在主要学术会议上发表，论文和技术报告将可从该网站下载。