在线搜索能预测销量吗?来自德国和英国汽车市场大数据的证据

ERN: Search Pub Date : 2016-08-15 DOI:10.2139/ssrn.2832004
Georg von Graevenitz, C. Helmers, V. Millot, Oliver D N Turnbull
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引用次数: 10

摘要

我们使用在线搜索数据来预测德国和英国汽车行业的汽车销量。搜索数据包含了几个不同的搜索动机,这些动机是不能单独观察到的。我们开发了一个模型,将搜索动机与可观察的搜索数据和销售联系起来。该模型表明,依赖可观察搜索数据作为预购搜索代理的销售预测将是有偏差的。我们展示了如何消除偏见并估计预购买搜索对销售的影响。为了帮助识别这种影响,我们使用2008/2009年引入的汽车报废补贴作为准自然实验。我们还表明,在线搜索数据(i)随着时间的推移具有高度持久性,(ii)可能受到永久性冲击,以及(iii)不同产品之间存在相关性,但程度不同。我们通过使用大N,大T面板的最新计量经济学方法来解决这些估计和推断的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Does Online Search Predict Sales? Evidence from Big Data for Car Markets in Germany and the UK
We use online search data to predict car sales in the German and UK automobile industries. Search data subsume several distinct search motives, which are not separately observable. We develop a model linking search motives to observable search data and sales. The model shows that predictions of sales relying on observable search data as a proxy for prepurchase search will be biased. We show how to remove the biases and estimate the effect of pre-purchase search on sales. To assist identification of this effect, we use the introduction of scrappage subsidies for cars in 2008/2009 as a quasi-natural experiment. We also show that online search data are (i) highly persistent over time, (ii) potentially subject to permanent shocks, and (iii) correlated across products, but to different extent. We address these challenges to estimation and inference by using recent econometric methods for large N, large T panels.
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