survey are constructed (thus modules are sampled, rather than questions) and respondents randomly (although not necessarily with equal probability) assigned to one survey form.

Evaluate the utility and the ability to obtain data from additional sources. Attempts can be made to retrieve expenditure data either from other sources or directly from records that the respondents have retained. These may include credit card/bank account statements, utility statements, pay stubs, and tax records. Some guidance may be obtained from other surveys such as the Residential Energy Consumption Survey (RECS) in how to obtain permission to access these records. Most of this evaluation, however, may need to be tailored to the CE.

Augment sample with wealthy households. The wealthiest households tend to be nonrespondents at a higher rate, causing substantial problems for some uses of the CE data. A potential remedy is to augment the CE with additional samples of wealthy households, such as based on IRS records or income data linked to small geographic areas. BLS has possibilities to link the CE sample of households to existing administrative data sources, such as IRS records, that can provide some better information about nonrespondents. Design C has a base survey that would easily facilitate the selection of additional higher income households in its follow-on components.

Identify and evaluate sources of auxiliary data (e.g., retailer data). Replacement of some CE data with data from other sources, such as retailer data or data from other surveys such as the RECS, is a risky expectation, but certain survey or diary data elements may be replaced or augmented using other sources of data. More likely uses of auxiliary data, due to the different error properties and reasons for their collection, are as benchmarks that can help evaluate the CE estimates and changes in the CE estimates, and to aid in sampling, post-survey adjustments, and estimation. One example would be to leverage auxiliary data (such as income) obtainable on sampled households from the Census Bureau to estimate nonresponse bias and improve nonresponse adjustments. A broad range of auxiliary data can be considered, such as IRS data, for a multitude of uses. Permission may be needed from a household to access these data, and research could explore “opt-out” permission (rather than “opt-in”) for the CE surveys, which would allow access to a household’s data unless they receive a “no access” notification. Research by Pascale (2011) and Singer, Bates, and Hoewyk (2011) on the use of administrative records in other contexts provides useful background for conducting such research. Furthermore, these data sources change over time, and investigation of such sources needs to be ongoing rather than at one point in time.

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