Moran's I Tests for Spatial Dependence in Panel Data Models with Time Varying Spatial Weights Matrices

Abstract

Abstract. Moran's I statistic is the most popular test for spatial dependence. When spatial weights matrices are substantially varying over time, Moran's I test based on a time invariant spatial weights matrix may cause substantial bias. This paper first investigates Moran's I tests for spatial dependence in panel data models where spatial weights matrices can be time varying. Based on time varying and time invariant spatial weights matrices, the empirical size and power of Moran's I tests for spatial dependence are evaluated and compared. Monte Carlo results indicate that size of Moran's I tests based on time varying and misspecification of time invariant spatial weights matrices have not significant difference, especially compared with misspecification time invariant spatial weights matrices, power of Moran's I tests for spatial dependence with time varying spatial weights matrices is much higher. TV-Moran tests are superior to NTV-Moran tests with the misspecification of invariant spatial weights matrix, with larger power.