Housing hedonic studies typically assume that individuals or households are similar enough to aggregate into a single demand equation for analysis, usually relying on ordinary least squares (OLS) or some other single-line equation estimator. Diversity itself is managed by non-spherical disturbance corrections, typically spatial autocorrelation or heteroskedasticity in the single line OLS estimate. This paper tests whether households in the same neighborhood can be theoretically and empirically treated as a single type or if households can be assigned into more than one type; multiple types suggests distinguishable local housing sub-markets. Our technique, a combination of the method of principal components and the seemingly unrelated regression (SUR) model, allows for one or more demand curves to represent housing demand and allows several types to compete over a fixed housing stock in a given residential neighborhood. As such, the SUR is the empirical translation of a theory that different household types can coexist in the same neighborhood.