Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States

This study examines aggregate county income growth across the 48 contiguous states from 1990 to 2005. To control for endogeneity we estimate a two-stage spatial error model and infer parameter significance by implementing a number of spatial bootstrap algorithms. We find that outdoor recreation and natural amenities favor positive growth in rural counties, densely populated rural areas enjoy stronger growth, and property taxes correlate negatively with rural growth. We also compare estimates from the aggregate county income growth model with per capita income growth and find that these two growth processes can be quite different.