Abstract
Census mail response rates (MRRs) constitute one implementation aspect of collecting census data. Low MRRs across geographic space inevitably lead to increased costs in collecting such data. MRRs that have been tabulated for multiple censuses over time allow an assessment of methods utilized to model space-time aspects of these data. This paper summarizes an analysis of the MRRs for three decennial United States censuses – 1990, 2000, and 2010 – in terms of time lags, eigenvector spatial filtering, eigenvector space-time filtering, and a random effects model specification framework. In doing so, this paper implements an extension of the eigenvector spatial filtering principal to eigenvector space-time filtering in order to describe space-time structure latent in the MRRs. Results of these analyses provide insights into census data collection issues, insights anticipated to be beneficial to the formulation of a strategic plan for subsequent census data collection.
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Notes
- 1.
A US county map shapefile is available at http://www.census.gov/geo/www/, and county level data for the three decennial census MRRs are available at http://2010.census.gov/2010census/take10map/ and http://www.census.gov/dmd/www/mailresp.html
- 2.
A stepwise linear regression was employed that used the Bonferroni adjusted selection significance level of 0.10/770.
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Acknowledgements
We wish to thank Parmanand Sinha for helping check the data retrieved from selected internet sources. D. Griffith is an Ashbel Smith Professor.
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Griffith, D.A., Chun, Y. (2015). Spatial Analysis of Census Mail Response Rates: 1990–2010. In: Kwan, MP., Richardson, D., Wang, D., Zhou, C. (eds) Space-Time Integration in Geography and GIScience. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9205-9_9
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