Accounting for Neighboring E¤ects in Measures of Spatial Concentration1

the paper. A common problem with spatial economic concentration measures (e.g. Gini, Her ndhal, entropy and Ellison-Glaeser indices) is accounting for the position of regions in space. While they purport to measure spatial clustering, these statistics are con\u85ned to calculations within individual areal units. They are insensitive to the proximity of regions to neighboring e¤ects. Clearly, economic clusters may cross the boundaries of the regions. Yet with cur-rent measures, any industrial agglomeration that traverses boundaries will be chopped into two or more pieces. Activity in adjacent spatial units is treated in exactly the same way as activity in far-ung, non-adjacent areas. This paper shows how some popular measures of spatial concentration re-lying on areal data can be modi\u85ed to account for neighboring e¤ects and spatial autocorrelation. With a U.S. application, we also show that the new instruments we propose are useful and easy to implement. JEL classi\u85cation: R12, R39, C49.