{"title":"经济自由与总统选举：贝叶斯空间概率分层建模方法","authors":"Donald J. Lacombe, Timothy Shaughnessy","doi":"10.1111/ajes.12616","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>There is a growing consensus that spatial effects can help to explain electoral outcomes. Additionally, the concept of economic freedom is also correlated with many different economic outcomes. This paper combines these two ideas using a Bayesian hierarchical spatial probit econometric model. Hierarchical models have a long history in the Bayesian literature and allow for the estimation of Level 1 (county) and Level 2 (state) variables. In this study, we use county-level data on county-level votes for Donald Trump in the 2020 presidential election and control for state-level economic freedom using a newly developed Bayesian hierarchical spatial probit model. The results indicate that state-level economic freedom contributed positively to Donald Trump's vote at the county level.</p>\n </div>","PeriodicalId":47133,"journal":{"name":"American Journal of Economics and Sociology","volume":"84 3","pages":"497-502"},"PeriodicalIF":0.9000,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Economic Freedom and Presidential Elections: A Bayesian Spatial Probit Hierarchical Modeling Approach\",\"authors\":\"Donald J. Lacombe, Timothy Shaughnessy\",\"doi\":\"10.1111/ajes.12616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>There is a growing consensus that spatial effects can help to explain electoral outcomes. Additionally, the concept of economic freedom is also correlated with many different economic outcomes. This paper combines these two ideas using a Bayesian hierarchical spatial probit econometric model. Hierarchical models have a long history in the Bayesian literature and allow for the estimation of Level 1 (county) and Level 2 (state) variables. In this study, we use county-level data on county-level votes for Donald Trump in the 2020 presidential election and control for state-level economic freedom using a newly developed Bayesian hierarchical spatial probit model. The results indicate that state-level economic freedom contributed positively to Donald Trump's vote at the county level.</p>\\n </div>\",\"PeriodicalId\":47133,\"journal\":{\"name\":\"American Journal of Economics and Sociology\",\"volume\":\"84 3\",\"pages\":\"497-502\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Economics and Sociology\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/ajes.12616\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Economics and Sociology","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ajes.12616","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
Economic Freedom and Presidential Elections: A Bayesian Spatial Probit Hierarchical Modeling Approach
There is a growing consensus that spatial effects can help to explain electoral outcomes. Additionally, the concept of economic freedom is also correlated with many different economic outcomes. This paper combines these two ideas using a Bayesian hierarchical spatial probit econometric model. Hierarchical models have a long history in the Bayesian literature and allow for the estimation of Level 1 (county) and Level 2 (state) variables. In this study, we use county-level data on county-level votes for Donald Trump in the 2020 presidential election and control for state-level economic freedom using a newly developed Bayesian hierarchical spatial probit model. The results indicate that state-level economic freedom contributed positively to Donald Trump's vote at the county level.
期刊介绍：
The American Journal of Economics and Sociology (AJES) was founded in 1941, with support from the Robert Schalkenbach Foundation, to encourage the development of transdisciplinary solutions to social problems. In the introduction to the first issue, John Dewey observed that “the hostile state of the world and the intellectual division that has been built up in so-called ‘social science,’ are … reflections and expressions of the same fundamental causes.” Dewey commended this journal for its intention to promote “synthesis in the social field.” Dewey wrote those words almost six decades after the social science associations split off from the American Historical Association in pursuit of value-free knowledge derived from specialized disciplines. Since he wrote them, academic or disciplinary specialization has become even more pronounced. Multi-disciplinary work is superficially extolled in major universities, but practices and incentives still favor highly specialized work. The result is that academia has become a bastion of analytic excellence, breaking phenomena into components for intensive investigation, but it contributes little synthetic or holistic understanding that can aid society in finding solutions to contemporary problems. Analytic work remains important, but in response to the current lop-sided emphasis on specialization, the board of AJES has decided to return to its roots by emphasizing a more integrated and practical approach to knowledge.
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