Forecasting elections with non-representative polls
Forecasting elections with non-representative polls
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DOI：
10.1016/j.ijforecast.2014.06.001
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发表时间：
2015-07-01
影响因子：
7.9
通讯作者：
Gelman, Andrew
中科院分区：
文献类型：
--
作者：
Wang, Wei;Rothschild, David;Gelman, Andrew
传统上，选举预测是基于代表性民意调查，即随机抽样的个人被问及他们打算投票给谁。虽然历史证明代表性投票是相当有效的，但它需要花费相当多的时间和金钱。此外，由于答复率在过去几十年中下降，代表性抽样的统计效益也减少了。在本文中，我们表明，通过适当的统计调整，非代表性的民意调查可以用来产生准确的选举预测，这往往可以实现更快，更少的费用比传统的调查方法。我们通过从一个新颖且高度非代表性的调查数据集创建预测来演示这种方法：在Xbox游戏平台上进行的2012年总统选举的一系列每日选民意向民意调查。在通过多水平回归和后分层调整Xbox响应后，我们获得了与领先的民意调查分析师的预测一致的估计，这些分析师基于汇总选举周期期间进行的数百项传统民意调查。最后，我们认为，非代表性的民意调查显示，不仅对选举预测的承诺，但也为衡量广泛的社会，经济和文化问题上的民意。(C)2014年国际预测协会。Elsevier B.V.出版，保留所有权利。
Election forecasts have traditionally been based on representative polls, in which randomly sampled individuals are asked who they intend to vote for. While representative polling has historically proven to be quite effective, it comes at considerable costs of time and money. Moreover, as response rates have declined over the past several decades, the statistical benefits of representative sampling have diminished. In this paper, we show that, with proper statistical adjustment, non-representative polls can be used to generate accurate election forecasts, and that this can often be achieved faster and at a lesser expense than traditional survey methods. We demonstrate this approach by creating forecasts from a novel and highly non-representative survey dataset: a series of daily voter intention polls for the 2012 presidential election conducted on the Xbox gaming platform. After adjusting the Xbox responses via multilevel regression and poststratification, we obtain estimates which are in line with the forecasts from leading poll analysts, which were based on aggregating hundreds of traditional polls conducted during the election cycle. We conclude by arguing that non-representative polling shows promise not only for election forecasting, but also for measuring public opinion on a broad range of social, economic and cultural issues. (C) 2014 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.