First Advisor

Barry Edmonston

Term of Graduation

Summer 2001

Date of Publication

Summer 6-28-2001

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.) in Urban Studies

Department

Urban Studies

Language

English

Subjects

Area planning & development; Demographics, Demography, Urban planning

Physical Description

1 online resource (xii, 306 pages)

Abstract

This dissertation uses 1980 and 1990 United States census and administrative data to analyze interstate migration during 1975–80 and 1985–90, and to assess the effects of several determinants on state-to-state migration by age, race, sex, and education. Descriptions are presented of migration rates, migration stream volumes and efficiency ratios, indexes of differential migration, and regional fixed-effects regression models using theories, techniques, and methodologies from recent migration literature. Regression analysis shows race, education, age, and sex having independent effects on interstate migration rates. A polytomous logistic regression model is used to investigate how selected variables affect the probability of state-to-state migration among 36 groups defined by age, race, sex, and education. A gravity model is used to investigate the possibility of censoring in state-to-state migration data. The analysis shows that interstate migration rates vary widely, relative to the national rates of 9.9 percent in 1980 and 9.6 percent in 1990. Bogue indexes show evidence of differential migration among the groups and among the 50 states and the District of Columbia. Migration stream volumes and efficiency ratios show that interstate migration during 1975–80 and 1985–90 proceeded along well-defined streams. Decomposition of the major streams by education shows that the largest proportions of migration streams tend to be the more than high school proportions. Regression estimates show that the national response to interstate migration determinants is not always consistent with disaggregated responses to the same determinants. Limited dependent variables regression estimates show that zero flows have little or no impact on aggregate migration whereas zero flows have some impact on disaggregated migration. The findings have at least four implications. First, to better understand state-to-state migration requires analysis beyond the national information on migration determinants. Second, policy makers should anticipate migration's redistribution of human capital. Third, policy makers interested in attracting certain population sub-groups to particular areas of the United States should learn from this study's analyses of migration response by 36 groups to labor market, fiscal, and fixed-effects variables. Fourth, state-to-state migration researchers should be aware that zero-flows (consequences of finer disaggregation) are a source of potential bias, the minimization of which is a serious research issue.

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Comments

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Persistent Identifier

https://archives.pdx.edu/ds/psu/43172

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