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首页> 外文期刊>Journal of Economic Behavior & Organization >Google Trends and reality: Do the proportions match? Appraising the informational value of online search behavior: Evidence from Swiss tourism regions
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Google Trends and reality: Do the proportions match? Appraising the informational value of online search behavior: Evidence from Swiss tourism regions

机译：Google趋势与现实：比例匹配吗？评估在线搜索行为的信息价值：来自瑞士旅游地区的证据

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摘要

This study examines the extent to which real-world economic activity is reflected in aggregate online search behavior on Google Search. As opposed to previous studies, being subject to potential mismeasurement problems when examining search queries along their longitudinal dimension, we apply an alternative investigative approach that exploits the cross-sectional instead of the longitudinal informational content embodied in Googles data. Moreover, while previous studies most often examine a single Google Trends series, our analyses are based on over 60 distinct series, which allow us to assess how informative the data are, not only within each series, but also between series. Finally, our Google Trends indices are based on the recently launched Google Knowledge Graph technology, allowing for a remarkably accurate measurement of relevant search query volumes. We assess the informational value of the data as strong, semi-strong, or weak based on unbiasedness and efficiency considerations in a Mincer-Zarnowitz-type regression model. Here, the context of (Swiss) tourism demand proves particularly useful, and we find that search-based tourism demand predictions are, on average, highly accurate approximations of reality. This indicates that search-based indicators may serve as valuable real-time complements for the guidance of economic policy. (C) 2017 Elsevier B.V. All rights reserved.
机译：这项研究研究了现实世界中经济活动在Google搜索上的总体在线搜索行为中得到反映的程度。与先前的研究相反，在沿纵向查询搜索查询时会遇到潜在的计量错误问题，我们采用了另一种调查方法，该方法利用横截面而不是Google数据中体现的纵向信息内容。此外，虽然以前的研究通常只检查一个Google趋势系列，但我们的分析基于60多个不同的系列，这使我们不仅可以评估每个系列中的数据，还可以评估系列之间的数据的信息量。最后，我们的Google趋势索引基于最近推出的Google知识图技术，可对相关搜索查询量进行非常精确的测量。我们基于Mincer-Zarnowitz类型回归模型中的无偏和效率考虑，将数据的信息价值评估为强，半强或弱。在这里，（瑞士）旅游需求的背景被证明特别有用，并且我们发现基于搜索的旅游需求预测平均而言是对现实的高度精确近似。这表明基于搜索的指标可以作为经济政策指导的有价值的实时补充。 （C）2017 Elsevier B.V.保留所有权利。

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