气候变化领域集成服务门户(CCPortal): Improving election prediction internationally

CCPortal

DOI	10.1126/science.aal2887
	Improving election prediction internationally
	Kennedy R.; Wojcik S.; Lazer D.
发表日期	2017
ISSN	0036-8075
起始页码	515
结束页码	520
卷号	355 期号:6324
英文摘要	This study reports the results of a multiyear program to predict direct executive elections in a variety of countries from globally pooled data.We developed prediction models by means of an election data set covering 86 countries and more than 500 elections, and a separate data set with extensive polling data from 146 election rounds.We also participated in two live forecasting experiments. Our models correctly predicted 80 to 90% of elections in out-of-sample tests. The results suggest that global elections can be successfully modeled and that they are likely to become more predictable as more information becomes available in future elections. The results provide strong evidence for the impact of political institutions and incumbent advantage. They also provide evidence to support contentions about the importance of international linkage and aid. Direct evidence for economic indicators as predictors of election outcomes is relatively weak. The results suggest that, with some adjustments, global polling is a robust predictor of election outcomes, even in developing states. Implications of these findings after the latest U.S. presidential election are discussed. Copyright 2016 by the American Association for the Advancement of Science; all rights reserved.
英文关键词	climate prediction; data set; economic analysis; election; experimental study; international relations; participatory approach; political ideology; Article; election; forecasting; human; machine learning; prediction; priority journal; United States; United States
语种	英语
来源期刊	Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/244256
作者单位	Center for International and Comparative Studies, University of Houston, Houston, TX, United States; Lazer Lab, Northeastern University, Boston, MA, United States; Institute for Quantitative Social Science, Harvard University, Cambridge, MA, United States
推荐引用方式 GB/T 7714	Kennedy R.,Wojcik S.,Lazer D.. Improving election prediction internationally[J],2017,355(6324).
APA	Kennedy R.,Wojcik S.,&Lazer D..(2017).Improving election prediction internationally.Science,355(6324).
MLA	Kennedy R.,et al."Improving election prediction internationally".Science 355.6324(2017).