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These estimated overall effects mask interesting heterogeneity. We begin by cutting the <br />data on two dimensions. First, we cut the data by age, sorting individuals into two groups, <br />a young group who were aged 20-39 in 1993 and an old group who were aged 40-65 in 1993. <br />We also sort the data based on the number of years the individual has been living at their <br />1993 address. We create a "low turnover" group of individuals who had been living at their <br />address for greater than or equal to four years and a "high turnover" group of individuals <br />who had been living at; their address for between four and fourteen years. Finally, we form <br />four subsamples by taking the 2 x 2 cross across each of these two dimensions and re -estimate <br />our effects for each subsample. <br />The results are reported in Figure 4. We summarize the key implications. First, we find <br />that the effects are weaker for younger individuals. We believe this is intuitive. Younger <br />households are more likely to face larger idiosyncratic shocks to their neighborhood and <br />housing preferences (such as changes in family structure and employment opportunities) <br />which make staying in their current location particularly costly, relative to the types of shocks <br />older households receive. Thus, younger households may feel more inclined to give up the <br />benefits afforded by rent control to secure housing more appropriate for their circumstances. <br />Moreover, among older individuals, there is a large gap between the estimated effects <br />based on turnover. Older, low turnover households have a strong, positive response to rent <br />control. That is, they are more likely to remain at their 1993 address relative to the control <br />group. In contrast, older, high turnover individuals are estimated to have a negative response <br />to rent control. They are less likely to remain at their 1993 address relative to the control <br />group. <br />To further explore the mechanism behind this result, we do another cut of the data, <br />sorting individuals based on the 1990-2000 rent appreciation of their 1993 zipcode. Individ- <br />uals are then sorted into two groups based on whether their zipcode experienced above or <br />below median rent appreciation. We now estimate our effects by age, turnover, and zipcode <br />rent appreciation. The results are in Figure 5 and Figure 6. Among older, lower turnover <br />14 <br />