quality assessment tools at the aggregate level and “memory joggers” at the household level.

Use of aggregate data. Aggregate retail data from scanner receipts can provide greater chronological and item detail, with potentially greater accuracy, than traditional data collection methods—offering opportunities for significant quality improvements for CPI budget shares and aggregate spending tables. The potential benefits include more data with less variance, as well as better data, leading to less bias. That said, use of aggregate data is not likely to yield sufficient coverage of all goods required by BLS; therefore, aggregate data cannot replace the current interview process in whole. Several areas need further exploration, including use of aggregate data in the CE process to (1) replace some of the detail (and hence burden) of the current CE interview process, (2) inform weighting controls, or (3) provide data quality checks for specific retail goods or sets of items (i.e., channels). Within specific channels or particular types of products, these data may be quite good and sufficient for weighting or assessment purposes. Retail data on item, price, and quantity could be obtained via two avenues: (1) directly from the retailers, with BLS serving as the data aggregator, or (2) via third-party companies that specialize in the aggregation of retail information.

Collection of these data by BLS directly from retailers has appeal in that the methods can be clear and well defined and the agency can exert direct control over the operation, ensuring suitable levels of quality and standardization. There are several downsides, however, to such an approach. First, it would require development of a considerable infrastructure, including retailer sampling, recruitment, regular data capture, considerable data cleaning/processing, and verification. The data requested from retailers would not be “plug-and-play” because retailers have their own (often unique) methods, units, formats, time frames, coding schemes, and standards of quality for the information they retain for business purposes. It is often the role of the data aggregator (in this case, BLS) to assume the responsibilities of translating collected data into a standardized useful form. The associated logistics and costs would likely be substantial. Undertaking such an endeavor not only would be expensive and time-consuming, but also would introduce an incremental data collection system with its own set of issues and problems, while not eliminating or even meaningfully reducing some of the current issues experienced with the CE survey approach.

Alternatively, several third-party vendors exist who specialize in the collection, cleaning, and distribution of retail information. These organizations could likely provide data on type, quantity, price, distribution channel, location, and other information at a far lower cost relative to that associated with BLS collecting the same data on its own. Unfortunately, these vendors vary considerably in the retail products and channels they

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