Recent research has focused attention on the concerns of migration in and out of Florida and within the counties themselves. In 1949, Cape Canaveral was established and the boom was on. The character of the state dramatically transformed after 1965, when plans were announced to convert twenty-seven thousand acres of swampland into Walt Disney World. Since then, Orlando's evolution is divided into two eras: before and after Walt Disney World. Orlando has changed from a quiet town whose function was to service the surrounding citrus growing regions in a sparsely populated Orange County to a booming metropolis. Has the growth been for the best? While geographical mobility is frequently analyzed in terms of in-migration, out-migration, and net migration, this thesis will examine the population churn, the sum of in- and out-migration divided by population size. The simple descriptive questions in this thesis are, first, how do Orange County and the Orlando metro area "stack up" against other Florida cities, counties, and metro areas such as: Tampa, Jacksonville, and Miami. Secondly, across 67 Florida counties, what county level characteristics predict the rate of churn? The sample will consist of intra-migration and intermigration movers from a dataset drawn from the 2000 U. S. Census, IRS data, and local data by county, such as, F Cat, Index Crime Rate, and Domestic Violence Rate. The U.S. Census data are compiled from the Census of 2000; most estimates come from data collected by the CPS (Current Population Survey), which the U.S. Census conducts. The Internal Revenue Service migration flow data shows migration patterns by county based on changes in the addresses entered on individual tax returns. Correlation analysis is used to show the strength of association between population churn and the other variables.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-1165 |
| Date | 01 January 2004 |
| Creators | Cashen, Marguerite |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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