There has recently been a dramatic increase in the number of papers that have combined quasi-experimental methods with hedonic property models. This is largely due to the concern that cross-sectional hedonic methods may be severely biased by omitted variables. While the empirical literature has developed extensively, there has not been a consistent treatment of the theory and methods of combining hedonic property models with quasi-experiments. The purpose of this chapter is to fill this void. An effort is made to provide background information on the traditional hedonic theory, the traditional cross-sectional hedonic methods as well as the newer quasi-experimental hedonic methods that use program evaluation techniques. By connecting these two literatures, the underlying theoretical and empirical assumptions necessary to derive welfare measures or capitalization rates become more apparent. The chapter also provides a practical "how to" guide on implementing a quasi-experimental hedonic analysis. This is done by focusing on a series of steps that can help to ensure the reliability of a quasi-experimental identification strategy. We illustrate this process using several recent papers from the literature.