Blended Data for the Advance Monthly Retail Trade Survey (MARTS) State Estimates

Thomas M. Menino Convention & Exhibition Center 

Since January 2019, the US Census Bureau has produced an experimental data product of estimated Monthly State Retail Sales by combining Monthly Retail Trade Survey (MRTS) data, administrative data on company payrolls, and third-party retail sales data. Unique data features include (1) multi-state companies report aggregate sales across states to MRTS, not state-specific sales; and (2) some of the third-party data is aggregated across companies within states. In collaboration with the Census Bureau, NORC at the University of Chicago has developed alternative monthly state retail sales estimates. Among the many possible alternative approaches for blending data to create monthly state-level estimates, we focus on three general estimation methodologies: direct estimation, based almost entirely on data from the state and month of interest; model-assisted estimation, which brings in synthetic predictions from a regression model fitted to historical data; and area-level small area estimation (SAE), which models the direct estimates and uses available auxiliary information to borrow strength across industries, states, and months. Preliminary results show that the direct estimates effectively combine the various data sources and that the model-assisted and SAE methods have considerable promise in reducing mean squared error for monthly estimates of state-level retail sales by industry.

Establishment Surveys

Third Party Data