Literature DB >> 12155386

The relationship between the length of the base period and population forecast errors.

S K Smith, T Sincich.   

Abstract

"The base period of a population forecast is the time period from which historical data are collected for the purpose of forecasting future population values. The length of the base period is one of the fundamental decisions made in preparing population forecasts, yet very few studies have investigated the effects of this decision on population forecast errors. In this article the relationship between the length of the base period and population forecast errors is analyzed, using three simple forecasting techniques and data from 1900 to 1980 for states in the United States. It is found that increasing the length of the base period up to 10 years improves forecast accuracy, but that further increases generally have little additional effect. The only exception to this finding is long-range forecasts of rapidly growing states, in which a longer base period substantially improves forecast accuracy for two of the forecasting techniques." excerpt

Keywords:  Americas; Developed Countries; Error Sources; Estimation Technics; Evaluation; Evaluation Methodology; Historical Survey; Measurement; North America; Northern America; Population Forecast; Population Projection; Research Methodology; United States

Mesh:

Year:  1990        PMID: 12155386     DOI: 10.1080/01621459.1990.10476209

Source DB:  PubMed          Journal:  J Am Stat Assoc        ISSN: 0162-1459            Impact factor:   5.033


  5 in total

1.  An empirical analysis of the effect of length of forecast horizon on population forecast errors.

Authors:  S K Smith; T Sincich
Journal:  Demography       Date:  1991-05

2.  Bayesian probabilistic projections of life expectancy for all countries.

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Journal:  Demography       Date:  2013-06

3.  Indirect estimates of total fertility rate using child woman/ratio: a comparison with the Bogue-Palmore method.

Authors:  Matt Hauer; Jack Baker; Warren Brown
Journal:  PLoS One       Date:  2013-06-24       Impact factor: 3.240

4.  Evaluating Population Forecast Accuracy: A Regression Approach Using County Data.

Authors:  Jeff Tayman; Stanley K Smith; Stefan Rayer
Journal:  Popul Res Policy Rev       Date:  2010-06-16

5.  The accuracy of general practitioner workforce projections.

Authors:  Malou Van Greuningen; Ronald S Batenburg; Lud Fj Van der Velden
Journal:  Hum Resour Health       Date:  2013-07-16
  5 in total

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