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Tables Appendix 1-A through 1-7 are the source material for Tables 6a, b and c. While there is no need to review these Tables in detail, it is valuable to interpret the coefficients on other right-hand side variables. Since every Table represents the same regression model applied to a different subset of the aggregate data set, it is only necessary to review a representative table, for example, the first Table, Appendix 1-A. The intercept term is usually close to 1.0 and significant reflecting the fact that the dependant variable is 1 + the growth rate and the right hand side variables are covariates which should cause deviation from the baseline growth rate for the pooled data or for individual counties. Log value of original price (constant $, 1996) in all cases has a negative and negative and significant impact on the average growth rate; prices that started lower grew more. The coach's size in square feet (Log value of units size (sq. It.)) increases the growth rate of value of the unit and the width of the coach, whether a `double' or a `triple' unit (standard descriptors of mobile home size), also increases the growth rate of the value of a unit. In general, the coefficients on these variables have the expected sign and are significant. Sample sizes vary significantly among the counties. Because multiple sales are necessary to compute the growth rates there may be some sample selection bias. Communities or neighborhoods in which there are relatively more repeat sales are likely to be overrepresented in the population of repeat sale transactions. In communities in which coach prices have increased at a greater rate, there is probably a greater likelihood of resale relative to communities in which coach prices have declined. This phenomenon is likely to be exacerbated by rent control policies which reduce the mobility of tenants who are benefiting from reduced rents. Reduced mobility is a well documented negative by-product of rent control policies which may impact the results. Almost all of the estimations yield adjusted R-squared measures in the range of 0.10 to 0.25. A small number of cases yield R-squared measures between 0.05 and 0.10. CONCLUSIONS Mobile homes are usually owned by households that pay a periodic rent for the land in a mobile home park (a pad) on which the coach is located. Economic theory suggests that because mobile homes tend not to be mobile but rather fixed to the pad on which they are initially located, and since the pads are rented, the