The effect of military base closures on rural county economies: An empirical evaluation

Monday, 13 October 2014: 2:55 PM
David J. Sorenson, Ph.D. , Economics, Augustana College, Sioux Falls, SD
Peter L. Stenberg, Ph.D. , United States Department of Agriculture, Washingon, DC
Recent announcements of a recommended downsizing of U.S. armed forces, likely to include proposed base closures, will bring new focus on the effect of previous base realignments and closures (BRACs) on the economies of counties hosting military bases.  This research provides a new analysis of the effects of base closures on counties which lost military bases or had significant losses due to realignment in the 1988 through 1995 rounds of military base restructuring.  BRACs occurred in 1988, 1991, 1993, and 1995, with 97 major closures and several major realignments which entailed significant local job loss.  This study examines eight counties which satisfied the criteria of experiencing a major loss of jobs (1500 or more total military and civilian jobs as reported by DOD) and being located in non-metropolitan areas. 

To assess the effect of the base closure, the study employs a quasi-experimental methodology in which counter-factual control groups were selected to evaluate the effects of the base closures.  Mahalanobis Distance is used to select the control groups, with a priori elimination of urban counties and counties that experienced similar economic shocks or were in proximity to the BRAC event.  The factors used in the procedure included several sectoral earnings percentages and income characteristics, growth rates in population and income, nearness to urban areas, population potential, and coefficient of specialization. 

Impact assessment is based on the median of the control group, using the median growth rate among the control counties to calculate the expected employment by sector and year for the treated county.  The expected value is then compared to the actual employment to assess the impact by sector of the military base job loss.  Statistical significance is assessed by the rank among the controls and the treated county of the treated county growth rate.