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Raymond, E. L., et al. (2018). "From foreclosure to eviction: Housing insecurity in corporate-owned single-family rentals." Cityscape 20(3): 159-188.

• "We also expect that tenant characteristics will affect housing insecurity. Using census block group data, we impute tenant characteristics, measuring household income, race, gender, education, and rents to control for tenant characteristics. This technique is commonly used in the public health literature (Geronimus and Bound, 1998; Geronimus, Bound, and Neidert, 1996; Greenwald, Polissar, Borgatta, and McCorkle, 1994; Kaufman, 2017; Krieger, 1992; Soobader, LeClere, Hadden, and Maury, 2001). There are some caveats to be noted with regard to this approach. In two influential papers, Geronimus et al. (1996) and Geronimus and Bound (1998) found weaker associations between socioeconomic status and outcome variables when aggregate variables were used as compared to individual measures. Unlike this study, they used census tract and zip-code level aggregates which are at a higher geography and typically less homogenous than block groups. Summarizing the methodological literature, Kaufman (2017) still recommends the use of aggregate data, arguing that individual measures fail to capture the latent variable of socioeconomic status and that accounting for location allows for a more complete measure of this factor. Given that we use tenant socioeconomic status as a control variable here, and are less interested in precise estimates of the separate impacts of individual characteristics versus neighborhood level impacts than in adequately controlling for the confounding effects of both, using area level aggregate data as a proxy for tenant characteristics meets our needs in this study. The literature commonly describes using census tract or zip code socioeconomic data as a proxy for individuals; however, Soobader et al. (2001) have found that block group data systematically reduced the amount of bias introduced by geographic aggregates, particularly with regard to the confounding of race and income; and provide closer estimates than census tracts to actual coefficients for individual socioeconomic characteristics. In this article, we use block group data from the 2012-2016 ACS to proxy for individual tenant socioeconomic status."

Geronimus, Arline T., and John Bound. 1998. "Use of Census-Based Aggregate Variables to Proxy for Socioeconomic Group: Evidence from National Samples," American Journal of Epidemiology 148 (5): 475-486.

Geronimus, Arline T., John Bound, and Lisa Neidert. J. 1996. "On the Validity of Using Census Geocode Characteristics to Proxy Individual Socioeconomic Characteristics," Journal of the American Statistical Association 91 (434): 529-537.

Kaufman, Jay S. 2017. Methods in Social Epidemiology. San Francisco, CA: John Wiley & Sons.

Soobader, Mah-Jabeen, Felicia B. LeClere, Wilbur Hadden, and Brooke Maury. 2001. "Using Aggregate Geographic Data to Proxy Individual Socioeconomic Status: does Size Matter?" American Journal of Public Health 91 (4): 632.