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key insight is to use realized values of agents' future expected utility as a noisy measure of agents' expectations. This method allows us to avoid needing to make explicit assumptions about how agents form expectations. Further, we do not need to assume how all state variables transition over time. Both of these assumptions are typically needed to estimate dynamic discrete choice models. Scott leverages "renewal" actions in tenants' choice sets which allows estimation to focus on specific actions in agents' choice sets which exhibit finite dynamic dependence, greatly simplifying the dynamic problem (Arcidiacono and Miller (2011), Arcidiacono and Ellickson (2011)). Our contribution is to show how Scott's method can be generalized to a set of difference -in -difference style linear and instrumental variable regressions that can be used in combination with a natural experiment to identify the model parameters. Finally, our paper is related to a separate strand of literature on community attachment in sociology. Kasarda and Jauowitz (1974) provide survey evidence that length of residence is correlated with various self-reported indicators of neighborhood attachment. We estimate households' attachments to their neighborhoods, as revealed by their migration decisions. Consistent with survey evidence, we find community attachment grows with years living in one's neighborhood, but it accumulates quite slowly over time. One additional year of residence increases one's community attachment by the equivalent of $300. The remainder of the paper proceeds as follows. Section 2 discusses the history of rent control in San Francisco. Section 3 discusses the data used for the analysis. Section 4 presents our reduced form results. Section 5 develops and estimates a dynamic discrete choice structural model. Section 6 discusses the welfare impacts of rent control. Section 7 concludes. 6