Utrecht University School of Economics, Utrecht, the Netherlands.
Department of Economics, Leiden University, Leiden, the Netherlands.
Big Data. 2021 Dec;9(6):443-453. doi: 10.1089/big.2020.0183.
This study aims at providing insights into the correct usage of Google search data, which are available through Google Trends. The focus is on the effect of sampling errors, which has not received the attention that it deserves. A housing market application is used to demonstrate the effects. For this purpose, the relationship between online search activity for mortgages and real housing market activity is investigated. A simple time series model, which explains transactions by an online mortgage search, is estimated. The results show that the effect of sampling errors is substantial. Thus, although the application of Google Trends data in research remains promising, far more attention should be given to the limitations of these data.
本研究旨在深入了解可通过 Google Trends 获取的 Google 搜索数据的正确使用方法。重点关注采样误差的影响，而这一影响尚未得到应有的重视。本文以住房市场应用为例来展示其影响。为此，研究了抵押贷款在线搜索活动与实际住房市场活动之间的关系。通过估计一个简单的时间序列模型，该模型用在线抵押贷款搜索来解释交易。结果表明，采样误差的影响是巨大的。因此，尽管 Google Trends 数据在研究中的应用仍然具有很大的潜力，但应更加关注这些数据的局限性。
