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Recent housing-market studies have modeled slow stock and price adjustment with some success. However, the empirical procedures used in these models break down if housing stocks or prices are driven by stochastic growth. In this paper I suggest an error-correction model for analyzing housing supply and demand under conditions of stochastic growth for a regional housing market. The model is applied to the housing market in Boulder, Colorado from 1981 through 1995—a period of rapid growth in housing values in the area. Long-run housing supply and demand are shown to be inelastic with respect to changes in the price of housing. The results indicate that developers respond more accurately to housing-market disequilibrium attributable to supply-side disturbances than to disturbances generated by changes in the demand for housing. On the other hand, price appreciation is driven primarily by demand disturbances. [ABSTRACT FROM AUTHOR]