Using a Geographic Segmentation to Understand, Predict, and Plan for Census and Survey Mail Nonresponse
Nancy Bates, Mary H. Mulry
The 2010 U.S. Census used a multimode response model with the first phase being a mailout/mailback and the second being a personal visit follow-up. Knowing which segments of the population are predisposed to mail back a form is essential to develop methods to maximize census participation and to plan for and monitor areas of nonresponse. In this article, we describe a geographic segmentation of survey and census response focused on the underlying constructs behind census tracts with historically low mail response rates. We perform a cluster analysis based on twelve demographic, housing, and socioeconomic variables used to calculate a hard-to-count score. This yielded eight mutually exclusive geographic clusters of the population that varied across the spectrum of mailback propensities. Each segment is distinguished by unique demographic, housing, and socioeconomic characteristics and several segments are closely aligned to three different hard-to-count profiles.
To gauge how the segments performed in terms of recent mail response behavior, we examine several outcome measures with data from the 2010 Census and the American Community Survey collected in 2009 and 2010. To conclude, we discuss the usefulness of extending this geographic segmentation model beyond the census to targeted experiments and other applications in demographic surveys.
Hard-to-count populations, social marketing, cluster analysis