Volume 6 - Article 15 | Pages 409–454

Why population forecasts should be probabilistic - illustrated by the case of Norway

By Nico Keilman, Dinh Quang Pham, Arve Hetland

Print this page  Facebook  Twitter

 

 
Date received:17 Jan 2002
Date published:28 May 2002
Word count:9686
Keywords:cohort-component method, forecast errors, forecasting, simulation, stochastic population forecast, time series, uncertainty
DOI:10.4054/DemRes.2002.6.15
Weblink:Technical documentation for Norwegian stochastic forecast
 

Abstract

Deterministic population forecasts do not give an appropriate indication of forecast uncertainty. Forecasts should be probabilistic, rather than deterministic, so that their expected accuracy can be assessed.
We review three main methods to compute probabilistic forecasts, namely time series extrapolation, analysis of historical forecast errors, and expert judgement. We illustrate, by the case of Norway up to 2050, how elements of these three methods can be combined when computing prediction intervals for a population’s future size and age-sex composition. We show the relative importance for prediction intervals of various sources of variance, and compare our results with those of the official population forecast computed by Statistics Norway.

Author's Affiliation

Nico Keilman - Universitetet i Oslo, Norway [Email]
Dinh Quang Pham - Statistisk sentralbyrå (Statistics Norway), Norway [Email]
Arve Hetland - Statistisk sentralbyrå (Statistics Norway), Norway [Email]

Other articles by the same author/authors in Demographic Research

» Editorial: The past, present, and future of Demographic Research
Volume 41 - Article 41

» Mortality shifts and mortality compression in period and cohort life tables
Volume 41 - Article 40

» Probabilistic household forecasts based on register data- the case of Denmark and Finland
Volume 28 - Article 43

» An editorial on plagiarism
Volume 24 - Article 17

Most recent similar articles in Demographic Research

» Subnational population forecasts: Do users want to know about uncertainty?
Volume 41 - Article 13    | Keywords: forecast errors, uncertainty

» A Guide to Global Population Projections
Volume 4 - Article 8    | Keywords: forecasting, uncertainty

» Variations in male height during the epidemiological transition in Italy: A cointegration approach
Volume 48 - Article 7    | Keywords: time series

» Leveraging deep neural networks to estimate age-specific mortality from life expectancy at birth
Volume 47 - Article 8    | Keywords: forecasting

» Now-casting Romanian migration into the United Kingdom by using Google Search engine data
Volume 45 - Article 40    | Keywords: time series