This thesis calls for a twofold shift in the training in and practice of historic preservation: first, increased data literacy and use of data in the discipline, and second, for a higher degree of skepticism about the implications of data-driven findings. Even if the results of quantitative studies are less definitive in their findings than preservation advocates would like, these grey areas can serve a valuable purpose of forcing stakeholders to become more deeply engaged in why effects might be what they are, and how policy can intervene to achieve more desirable outcomes. Following a review of previous studies and their methodologies, this project looks to Philadelphia as a case study for the quantitative analysis of the association between local historic district designation and residential property values, exploring whether it is possible to develop a straightforward and meaningful methodology for assessing the economic impact of local historic district designation on residential property values. Transaction prices serve as the dependent variable in three separate models, each corresponding to a locally designated historic district and a similar but undesignated neighborhood. Limitations are explored in detail, and future directions for study are outlined in order to offer insight to others who might undertake similar work going forward.