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Adaptive Matrix Sampling for the Consumer Expenditure Interview Survey

Jeffrey M. Gonzalez and John L. Eltinge

Abstract

The Consumer Expenditure Interview Survey is an ongoing panel survey of U.S. households in which sample units typically receive the same survey protocol during each interview. Because of the high burden associated with the survey request, the BLS is exploring alternative designs that, if implemented, would change many features of the data collection process. One such alternative is adaptive matrix sampling. Matrix sampling involves dividing a survey into sections and then administering each to subsamples of the main sample. To potentially compensate for the resulting loss of information, we can adapt section assignment probabilities based on data from the first interview. We use historical data to explore potential efficiency gains incurred by the use of adaptive matrix sampling, develop point estimators for expenditures collected under this design and evaluate their variance properties. .