The stability of regression coefficients over the observation set (“regional homogeneity”) is typically assessed by means of a Chow test or within a seemingly unrelated regression (SUR) framework. When spatial error autocorrelation is present in cross‐sectional equations the traditional tests are no longer applicable. I evaluate this both in formal terms as well as empirically. I introduce a taxonomy of spatial effects in models for structural instability, and discuss its implication for testing. I compare the performance of traditional tests, robust approaches, maximum‐likelihood procedures and pretest techniques by means of a series of simple Monte Carlo experiments.
|Original language||English (US)|
|Number of pages||23|
|Journal||Journal of Regional Science|
|State||Published - May 1990|
ASJC Scopus subject areas
- Environmental Science (miscellaneous)