Access the full text.
Sign up today, get DeepDyve free for 14 days.
Ronald Lee, L. Carter (1992)
Modeling and forecasting U. S. mortalityJournal of the American Statistical Association, 87
João Saboia (1977)
Autoregressive Integrated Moving Average (ARIMA) Models for Birth ForecastingJournal of the American Statistical Association, 72
J. Hajnal (1955)
THE PROSPECTS FOR POPULATION FORECASTSJournal of the American Statistical Association, 50
I. Lowry (1964)
A model of metropolis
J. Alho (1984)
Probabilistic forecasts. The case of population projections, 1
(1993)
1990 census of population and housing, population and housing unit counts: California
Stanley Smith (1987)
Tests of forecast accuracy and bias for county population projections.Journal of the American Statistical Association, 82 400
N. Keyfitz (1981)
The limits of population forecasting.Population and Development Review, 7
J. Tayman, S. Kunkel (1989)
Improvements to the projective land use model for producing small area forecasts.
(1980)
Estimating population and income for small places
L. Carter, Ronald Lee (1986)
Joint Forecasts of U.S. Marital Fertility, Nuptiality, Births, and Marriages Using Time Series ModelsJournal of the American Statistical Association, 81
A. Isserman (1977)
The Accuracy of Population Projections for Subcounty AreasJournal of The American Planning Association, 43
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
S. Smith (1987)
Tests of accuracy and bias for county population projectionsJournal of the American Statistical Association, 82
W. Williams, M. Goodman (1971)
A Simple Method for the Construction of Empirical Confidence Limits for Economic ForecastsJournal of the American Statistical Association, 66
Z. Sykes (1969)
Some Stochastic Versions of the Matrix Model for Population DynamicsJournal of the American Statistical Association, 64
S. Smith, T. Sincich (1988)
Stability over time in the distribution of forecast errorsDemography, 25
G. Hahn, W. Meeker, Luis Escobar (1991)
Statistical Intervals: A Guide for Practitioners
A. Isserman (1977)
The accuracy of population projections for subcounty areasJournal of the American Institute for Planners, 43
S. Smith, T. Sincich (1992)
Evaluating the forecast accuracy and bias of alternative population projections for states.International journal of forecasting, 8 3
M. Stoto (1983)
The accuracy of population projections.Journal of the American Statistical Association, 78 381
W. Gouldner, S. Rosenthal, J. Meredith (1972)
Projective land use modelPLUM: Theory and application
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. Leistriz, R. Hamm, S. Hwang, B. Parpia (1984)
An assessment of the accuracy of a regional economicdemographic projection modelDemography, 21
J. Tayman (1996)
The accuracy of small area population forecasts based on a spatial interaction land use modelJournal of the American Planning Association, 62
J. Cohen (1986)
Population forecasts and confidence intervals for Sweden: A comparison of modelbased and empirical approachesDemography, 23
S. Smith, T. Sincich (1992)
Evaluating the forecast accuracy and bias of alternative projections for statesInternational Journal of Forecasting, 8
N. Keyfitz (1972)
On future population.Journal of the American Statistical Association, 67 338
J. Pollard (1966)
On the use of the direct matrix product in analysing certain stochastic population modelsBiometrika, 53
R. Lee (1974)
Forecasting births in post-transition population: stochastic renewal with serially correlated fertility.Journal of the American Statistical Association, 69 347
Producers of population forecasts acknowledge the uncertainty inherent in trying to predict the future and should warn about the likely error of their forecasts. Confidence intervals represent one way of quantifying population forecast error. Most of the work in this area relates to national forecasts; although, confidence intervals have been developed for state and county forecasts. A few studies have examined subcounty forecast error, however, they only measured point estimates of error. This paper describes a technique for making subcounty population forecasts and for generating confidence intervals around their forecast error. It also develops statistical equations for calculating point estimates and confidence intervals for areas with different population sizes. A non-linear, inverse relationship between population size and forecast accuracy was found and we demonstrate the ability to accurately predict average forecast error and confidence intervals based on this relationship.
Population Research and Policy Review – Springer Journals
Published: Oct 7, 2004
Access the full text.
Sign up today, get DeepDyve free for 14 days.