Blowin' Down the Road: Investigating Bilateral Causality Between Dust Storms and Population in the Great Plains

Blowin' Down the Road: Investigating Bilateral Causality Between Dust Storms and Population in... Recently, the National Academy of Sciences concluded “it is clear thatpopulation and the environment are usually interrelated . . . ”. This paper directlytests the expected interrelationship using annual county-level population estimatesprovided by the U.S. Census Bureau and annual counts of dust storms from the1960s, '70s, and '80s at weather stations situated throughout the U.S. GreatPlains. In doing so, it implements a research design that extends methods (farremoved from conventional demography) for pure time series analysis withmultilevel regression models. The result is a method for causal modeling in paneldata that produces, in this application, evidence of bilateral causality betweenpopulation size and deleterious environmental conditions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Population Research and Policy Review Springer Journals

Blowin' Down the Road: Investigating Bilateral Causality Between Dust Storms and Population in the Great Plains

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Publisher
Springer Journals
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Geography; Demography; Economic Policy; Population Economics
ISSN
0167-5923
eISSN
1573-7829
D.O.I.
10.1023/A:1027374330129
Publisher site
See Article on Publisher Site

Abstract

Recently, the National Academy of Sciences concluded “it is clear thatpopulation and the environment are usually interrelated . . . ”. This paper directlytests the expected interrelationship using annual county-level population estimatesprovided by the U.S. Census Bureau and annual counts of dust storms from the1960s, '70s, and '80s at weather stations situated throughout the U.S. GreatPlains. In doing so, it implements a research design that extends methods (farremoved from conventional demography) for pure time series analysis withmultilevel regression models. The result is a method for causal modeling in paneldata that produces, in this application, evidence of bilateral causality betweenpopulation size and deleterious environmental conditions.

Journal

Population Research and Policy ReviewSpringer Journals

Published: Oct 17, 2004

References

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