Migration is an intensely personal decision, but mathematical models are useful for quantifying the larger, economic aspects of it. The goal of this research is to use spatial and multiple regression models to study the influence of economic variables on net migration rates in Iowa counties. To achieve this data for many variables was collected from several sources and centered on the year 2000. S-plus software was used to create neighborhood structures, run spatial correlations and regressions, and run multiple regressions and residual diagnostics. The results showed that it is possible to develop a good regression model of migration using net migration as the dependent variable along with various economic covariates. Results also emphasized the rural nature of Iowa, as outliers were often the larger and more urban counties. Two counties in particular, Dallas and Woodbury, were extreme cases for the state of Iowa. This research shows that despite migration\u27s subjective nature, regression models are applicable to the study of migration and can lead to a better understanding of why migration occurs
