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N. Jaspen, Norman Draper, Harry Smith (1968)
Applied Regression AnalysisMathematics of Computation, 22
Stanley Smith, T. Sincich (1990)
The relationship between the length of the base period and population forecast errors.Journal of the American Statistical Association, 85 410
Stanley Smith (1987)
Tests of forecast accuracy and bias for county population projections.Journal of the American Statistical Association, 82 400
Evaluating Population Forecast Accuracy 261
N. Keyfitz (1981)
The limits of population forecasting.Population and Development Review, 7
J. Long (1995)
Complexity, accuracy, and utility of official population projectionsMathematical Population Studies, 5
G. Chi (2009)
Can knowledge improve population forecasts at subcounty levels?Demography, 46
A. Isserman (1977)
The Accuracy of Population Projections for Subcounty AreasJournal of The American Planning Association, 43
6E-05 *** 1.2E-08 *** 2.7E-05 *** Prior-Alg -0
J. Tayman (1996)
The Accuracy of Small-Area Population Forecasts Based On A Spatial Interaction Land-Use Modeling SystemJournal of The American Planning Association, 62
A. Apituley (1997)
Assessment of Accuracy
G. Hahn (2012)
Applied Regression Analysis (2nd Ed.)Technometrics, 24
S. Rayer (2008)
Population Forecast ErrorsJournal of Planning Education and Research, 27
H. White (1954)
Empirical Study of the Accuracy of Selected Methods of Projecting State PopulationsJournal of the American Statistical Association, 49
J. Díaz-García, G. González-Farías, V. Alvarado-Castro
SENSITIVITY ANALYSIS IN LINEAR REGRESSION
D. Lenze (2000)
Forecast Accuracy and Efficiency: An Evaluation of Ex Ante Substate Long-Term ForecastsInternational Regional Science Review, 23
S. Smith, T. Sincich (1992)
Evaluating the forecast accuracy and bias of alternative population projections for states.International journal of forecasting, 8 3
Stanley Smith, J. Tayman, D. Swanson (2001)
State and Local Population Projections: Methodology and Analysis
M. Stoto (1983)
The accuracy of population projections.Journal of the American Statistical Association, 78 381
David Belsley, E. Kuh, R. Welsch (1980)
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
J. Tayman, E. Schafer, L. Carter (1998)
The role of population size in the determination and prediction of population forecast errors: An evaluation using conifidence intervals for subcounty areasPopulation Research and Policy Review, 17
Stanley Smith, Mohammed Shahidullah (1995)
An evaluation of population projection errors for census tracts.Journal of the American Statistical Association, 90 429
S. Murdock, F. Leistritz, R. Hamm, Sean-Shong Hwang, B. Parpia (1984)
An assessment of the accuracy of a regional economic-demographic projection modelDemography, 21
Stanley Smith, T. Sincich (1988)
Stability over time in the distribution of population forecast errorsDemography, 25
(1954)
Empirical study of the accuracy of selected methods of projecting state populationJournal of the American Statistical Association, 49
Multivariate Regression Models: Unstandardized Coefficients and Adjusted R 2 Values, Model 5 (Algebraic % Errors) 10 Year Horizons 20 Year Horizons All Reduced All Reduced Ln Size 0
Irwin Levin (1999)
Tests of Significance
Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places. Using decennial census data from 1900 to 2000 for 2,482 counties in the US, we construct a large number of county population forecasts and calculate forecast errors for 10- and 20-year horizons. Then, we develop and evaluate several alternative functional forms of regression models relating population size and growth rate to forecast accuracy; investigate the impact of adding several other explanatory variables; and estimate the relative contributions of each variable to the discriminatory power of the models. Our results confirm several findings reported in previous studies but uncover several new findings as well. We believe regression models based on data for individual places provide powerful but under-utilized tools for investigating the determinants of population forecast accuracy.
Population Research and Policy Review – Springer Journals
Published: Jun 16, 2010
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