||Stewardship of the built environment must include assessment of what contributes to economic sustainability and resilience. Preservation and reuse of buildings trigger social, environmental, and economic outcomes that have long-term sustainability and resiliency implications. The built environment includes building and neighborhood characteristics that can foster greater economic sustainability and resiliency. By identifying significant characteristics, we can implement policies that replicate positive characteristics and diminish negative characteristics. A thin and conjectural literature reveals that: (1) No one has used hierarchical linear modeling (HLM), which nests predicted property values over time within single-family, detached house (SFDH) characteristics and then within neighborhood characteristics, to analyze historic districts. (2) No one has used the natural experiment of the Great Recession of 2008-2012 to assess resiliency in historic districts. (3) Studies are needed that review how qualitative variables affect property value. I configure a mixed model comprised of quantitative and qualitative analyses to identify characteristics that predict property value. I obtain quantitative data from the Salt Lake County Assessor's Property Tax database for 2002-2014 that describes neighborhood and SFDH characteristics. I interview 21 planners, architects, preservation administrators and advocates, realtors, and property owners to identify primary qualities. I compare eight neighborhoods in a Tuden-Thompson matrix and adapt binomial dummy-variable equivalents for HLM modeling. I then develop a method to assess economic sustainability and resiliency of SFDHs in historic districts. I apply the method to 29 Salt Lake City neighborhoods as a case study to demonstrate that the method works. I divide the study into three periods: prerecession (2002-2008), recession (2008-2012), and postrecession (2012-2014). This produces HLM growth curves of historic designation value as well as cross sectional tests of housing and neighborhood predictors of SFDH property value at each time period. Most qualitative and quantitative variables drop out due to lack of variability, collinearity, or statistical insignificance. I identify building size, lot size, and above-average building condition as key variables. Overall, I show that for SFDHs, historic designation is a semiotic reflection of the people who live in those neighborhoods because they understand them as more than just a collection of buildings and land uses.