ABSTRACT
The distribution of industrial activities across urban neighborhoods is dictated by a host of external and internal factors. In the study of central-city neighborhoods, it is worthwhile to test a simultaneous model that explores the determinants of neighborhood industry dimensions by incorporating the spatial lag effect. The spatial lag effect may be due to the overall level of industry activities in adjacent neighborhoods. To examine the effects of neighborhood characteristic dimensions on industry clustering while incorporating spatially lagged industry clustering, the authors specify a two-stage least square (2SLS) equation. In the neighborhood clustering of strip shopping and neighborhood retail, no variable on the right side of the equation is statistically significant. However; the spatial lag has positive signs in both specifications for the strip shopping model. It is also positive in lag specification of the maximum value of nearby neighborhoods for the neighborhood retail model.
