Disregarding spatial dependence can invalidate methods for analyzing cross-sectional and panel data. We discuss ongoing work on developing methods that allow for, test for, or estimate, spatial dependence. Much of the stress is on nonparametric and semiparametric methods

The central limit theorem for nonparametric kernel estimates of a smooth trend, with linearly-generated errors, indicates asymptotic independence and homoscedasticity across fixed points, irrespective of whether disturbances have short memory, long memory, or antipersistence. However, the...