Forecasting Political Events

Michael C. Horowitz
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引用次数: 1

Abstract

Forecasting political events is a critical activity for social scientists. Forecasting can help test competing theories, let researchers grapple with the true substantive effects of their models, and bridge the gap between academia and the policy world. Forecasting is an academic activity with direct relevance for policymakers. Yet, a variety of cognitive biases can make forecasting challenging, even for experts. Despite these limitations, interest in forecasting is growing. This chapter describes several different approaches to forecasting political events, especially international political events. These methods include game theory, machine learning, statistical analysis, and event data algorithms. Recent research also suggests the way models drawing on the wisdom of the crowds, forecasting teams, and prediction markets can generate large improvements in accuracy when forecasting geopolitical events. All have strengths and weaknesses, given the inherent uncertainty that exists in the political world.
预测政治事件
对社会科学家来说,预测政治事件是一项重要的活动。预测可以帮助测试相互竞争的理论,让研究人员努力解决其模型的真正实质性影响,并弥合学术界和政策界之间的差距。预测是一项与政策制定者直接相关的学术活动。然而,各种各样的认知偏见会使预测变得具有挑战性,即使对专家来说也是如此。尽管有这些限制,人们对预测的兴趣正在增长。本章描述了预测政治事件,特别是国际政治事件的几种不同方法。这些方法包括博弈论、机器学习、统计分析和事件数据算法。最近的研究还表明,在预测地缘政治事件时,利用群体智慧、预测团队和预测市场的模型可以大大提高准确性。鉴于政治世界中存在固有的不确定性,所有这些都有优点和缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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