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Military enlistments : what can we learn from geographic variation?

Author: Charles Brown; U.S. Army Research Institute for the Behavioral and Social Sciences.; University of Maryland, College Park.; National Bureau of Economic Research.
Publisher: Alexandria, Va. : U.S. Army Research Institute for the Behavioral and Social Sciences, [1984]
Series: Technical report (U.S. Army Research Institute for the Behavioral and Social Sciences), 620.
Edition/Format:   Print book : National government publication : EnglishView all editions and formats
Summary:
Continued success of the all-volunteer force depends upon the ability of the military services to meet their enlistment goals consistently. This report measures the effects of economic factors on Army enlistments of nonprior-service high school graduates. The author uses a multiple-regression, pooled cross-section/time-series model to measure Army enlistments by mental category. He concludes that unemployment, pay,  Read more...
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Additional Physical Format: Online version:
Brown, Charles.
Military enlistments
(OCoLC)902678038
Microfiche version:
Brown, Charles.
Military enlistments, what can we learn from geographic variation?
(OCoLC)15643793
Material Type: Government publication, National government publication
Document Type: Book
All Authors / Contributors: Charles Brown; U.S. Army Research Institute for the Behavioral and Social Sciences.; University of Maryland, College Park.; National Bureau of Economic Research.
OCLC Number: 13677992
Notes: "University of Maryland and National Bureau of Economic Research."
Distributed to depository libraries in microfiche.
"February 1984."
Description: ix, 37 pages ; 28 cm.
Series Title: Technical report (U.S. Army Research Institute for the Behavioral and Social Sciences), 620.
Responsibility: Charles Brown ; submitted by Curtis L. Gilroy.

Abstract:

Continued success of the all-volunteer force depends upon the ability of the military services to meet their enlistment goals consistently. This report measures the effects of economic factors on Army enlistments of nonprior-service high school graduates. The author uses a multiple-regression, pooled cross-section/time-series model to measure Army enlistments by mental category. He concludes that unemployment, pay, and the number of Army recruiters are important variables in the enlistment decision.

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