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Measuring Temporal Stability in Regression Models of Population Estimation

Bibliographic Data

ID10970532
AuthorsMarylou Mandell (Bureau of Economic and Business Research, University of Florida, Gainesville, Florida 32611, corresponding author), Jeffrey Tayman (Office of Financial Management, State of Washington, Olympia, Washington 98504), Jeffrey M Tayman
Year1982
Volume19
Issue1
Pages135-146
Publication date1982-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueDemography (JOURNAL)
Journal identifiersISSN: 0070-3370 • E-ISSN: 1533-7790
PublisherDuke University Press (PUBLISHER • US)
DOI10.2307/2061133
PMID7067867
OpenAlexW1988280372
LanguageEN
Citations received5
References cited18

This paper introduces an empirical indicator designed to measure the temporal stability of regression models used to produce subnational population estimates. Analysis of 67 counties in Florida centers on 1970 total population estimates generated from ratio-correlation and difference-correlation models. Comparisons are made between eight different regression specifications and employ a quantitative measure of relative estimate accuracy. The major findings of this study are that (a) variable measurement and type are important determinants of estimate accuracy, and (b) although temporal stability of the coefficients impacts estimation errors, the influence is not as pervasive as is suggested in the literature

Econometrics · Economics · Estimation · Geography · Machine learning · Population · Regression · Regression analysis · Sociology · Stability (learning theory · Statistics · Advanced Statistical Methods and Models · Census and Population Estimation · Computer Science · Demography · Mathematics · Survey Sampling and Estimation Techniques

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Unique citing works5
Citations per year0,12
Citation span1984 - 2014 (31)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 5

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