| Housing hedonic studies typically assume that individuals or households are similar enough to aggregate into a single demand equation for analysis, typically relying on ordinary least squares (OLS) or some other single-line equation estimator. In these models, heterogeneity 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 sorted into more than one "type." If the latter, then a single equation estimate may not be the most appropriate technique for a hedonic model that structurally accounts for household diversity. My technique, the seemingly unrelated regression (SUR) model, allows for more than one demand curve 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. |
