Details
| Original language | English |
|---|---|
| Pages (from-to) | 593-613 |
| Number of pages | 21 |
| Journal | Population Research and Policy Review |
| Volume | 34 |
| Issue number | 4 |
| Publication status | Published - 23 May 2015 |
Abstract
Population projections commonly suffer from a decreasing accuracy with a higher degree of disaggregation. We suggest combining the cohort-component model and an averaged projection technique to improve precision of forecasts for small areas. Calculating ex-post population projections, we evaluate the precision and bias of the proposed method by contrasting error patterns of commonly used techniques using official population data from 46 districts of a German state for the years 1980–2013. In comparison to the individual methods considered, the combined approach results in the highest accuracy and lowest bias both for the total population and for age groups. The proposed method is also more robust regarding past growth.
Keywords
- Cohort-component model, Forecast accuracy, Small area population projection
ASJC Scopus subject areas
- Social Sciences(all)
- Demography
- Environmental Science(all)
- Management, Monitoring, Policy and Law
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In: Population Research and Policy Review, Vol. 34, No. 4, 23.05.2015, p. 593-613.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Subnational Population Projections by Age
T2 - An Evaluation of Combined Forecast Techniques
AU - Reinhold, Mario
AU - Thomsen, Stephan L.
PY - 2015/5/23
Y1 - 2015/5/23
N2 - Population projections commonly suffer from a decreasing accuracy with a higher degree of disaggregation. We suggest combining the cohort-component model and an averaged projection technique to improve precision of forecasts for small areas. Calculating ex-post population projections, we evaluate the precision and bias of the proposed method by contrasting error patterns of commonly used techniques using official population data from 46 districts of a German state for the years 1980–2013. In comparison to the individual methods considered, the combined approach results in the highest accuracy and lowest bias both for the total population and for age groups. The proposed method is also more robust regarding past growth.
AB - Population projections commonly suffer from a decreasing accuracy with a higher degree of disaggregation. We suggest combining the cohort-component model and an averaged projection technique to improve precision of forecasts for small areas. Calculating ex-post population projections, we evaluate the precision and bias of the proposed method by contrasting error patterns of commonly used techniques using official population data from 46 districts of a German state for the years 1980–2013. In comparison to the individual methods considered, the combined approach results in the highest accuracy and lowest bias both for the total population and for age groups. The proposed method is also more robust regarding past growth.
KW - Cohort-component model
KW - Forecast accuracy
KW - Small area population projection
UR - http://www.scopus.com/inward/record.url?scp=84938967703&partnerID=8YFLogxK
U2 - 10.1007/s11113-015-9362-0
DO - 10.1007/s11113-015-9362-0
M3 - Article
AN - SCOPUS:84938967703
VL - 34
SP - 593
EP - 613
JO - Population Research and Policy Review
JF - Population Research and Policy Review
SN - 0167-5923
IS - 4
ER -