TY - JOUR
T1 - The Interdependent Forces of Local Growth
T2 - A County-Level Study, 2001-2011
AU - Clement, Matthew Thomas
AU - Dede-Bamfo, Nathaniel
AU - DeWaard, Jack
AU - Kim, Seoyoun
N1 - Publisher Copyright:
© 2023 MSS.
PY - 2023
Y1 - 2023
N2 - Perspectives in human ecology and political economy present local growth as a syndrome of interdependent changes happening over time within municipalities. This quantitative study examines the reciprocal relationship between three core concepts of growth: employment, land development, and migration. To assess these associations across the United States, covering the years 2001–2011, we merge county-level data (n = 3,108) from three sources: USA Counties’ Employment Data; satellite imagery from the National Land Cover Database; and the Internal Revenue Service’s County-to-County Migration Data. In structural equation models (SEMs) with cross-lagged associations, we estimate the reciprocal relationship between first-difference change scores for three variables: the unemployment rate, the area of human constructed impervious surfaces (i.e. land development), and the ratio of in/out migration. While land development and migration are in an asymmetric, positive feedback loop, the reciprocal association between unemployment and migration is positive in one direction and negative in the other. With SEM, the analysis contributes to the literature by highlighting the social forces of local growth as an interdependent system of reciprocal change, although not fully recursive.
AB - Perspectives in human ecology and political economy present local growth as a syndrome of interdependent changes happening over time within municipalities. This quantitative study examines the reciprocal relationship between three core concepts of growth: employment, land development, and migration. To assess these associations across the United States, covering the years 2001–2011, we merge county-level data (n = 3,108) from three sources: USA Counties’ Employment Data; satellite imagery from the National Land Cover Database; and the Internal Revenue Service’s County-to-County Migration Data. In structural equation models (SEMs) with cross-lagged associations, we estimate the reciprocal relationship between first-difference change scores for three variables: the unemployment rate, the area of human constructed impervious surfaces (i.e. land development), and the ratio of in/out migration. While land development and migration are in an asymmetric, positive feedback loop, the reciprocal association between unemployment and migration is positive in one direction and negative in the other. With SEM, the analysis contributes to the literature by highlighting the social forces of local growth as an interdependent system of reciprocal change, although not fully recursive.
KW - Growth machine
KW - land development
KW - migration
KW - reciprocal
KW - structural equation model
KW - unemployment
UR - http://www.scopus.com/inward/record.url?scp=85159141951&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159141951&partnerID=8YFLogxK
U2 - 10.1080/00380253.2023.2191657
DO - 10.1080/00380253.2023.2191657
M3 - Article
AN - SCOPUS:85159141951
SN - 0038-0253
VL - 64
SP - 564
EP - 586
JO - Sociological Quarterly
JF - Sociological Quarterly
IS - 4
ER -