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Recording discrepancies in Nielsen Homescan data: Are they present and do they matter?

机译:在Nielsen Homescan数据中记录差异:它们是否存在并且有关系吗?

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We report results from a validation study of the Nielsen Homescan consumer panel data. We use data from a large grocery retailer to match transactions that were recorded by the retailer (at the store) and by the Homescan panelist (at home). The matched data allow us to identify and document discrepancies between the two data sets in reported shopping trips, products, prices, and quantities. We find that the discrepancies are largest for the price variable, and show that they are due to two effects: the firstrnseems like standard recording errors (by Nielsen or the panelists), while the second is likely due to the way Nielsen imputes prices. We present two simple applications to illustrate the impact of recording differences, and we use one of the applications to illustrate how the validation study can be used to adjust estimates obtained from Nielsen Homescan data. The results suggest that while recording discrepancies are clearly present and potentially impact results, corrections, like the one we employ, can be adopted by users of Homescan to investigate the robustness of their results to such potential recording differences.
机译:我们报告了Nielsen Homescan消费者面板数据的验证研究结果。我们使用来自大型杂货店零售商的数据来匹配零售商(在商店)和Homescan小组成员(在家)记录的交易。匹配的数据使我们能够识别并记录报告的购物行程,产品,价格和数量这两个数据集之间的差异。我们发现,价格变量的差异最大,并且表明它们是由于两种影响:第一种似乎是标准记录错误(由Nielsen或小组成员),而第二种可能是由于Nielsen估算价格的方式。我们提供了两个简单的应用程序来说明记录差异的影响,并且使用其中一个应用程序来说明如何使用验证研究来调整从Nielsen Homescan数据获得的估计值。结果表明,尽管记录差异明显存在并且可能影响结果,但Homescan的用户可以采用我们所采用的校正方法来调查其结果对此类潜在记录差异的稳健性。

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