Abstract
The Box–Cox transformation can sometimes yield noticeable improvements in model simplicity, variance homogeneity and precision of estimation, such as in modelling and forecasting age-specific fertility. Despite its importance, there have been few studies focusing on the optimal selection of Box–Cox transformation parameters in demographic forecasting. A simple method is proposed for selecting the optimal Box–Cox transformation parameter, along with an algorithm based on an in-sample forecast error measure. Illustrated by Australian age-specific fertility, the out-of-sample accuracy of a forecasting method can be improved with the selected Box–Cox transformation parameter. Furthermore, the log transformation is not adequate for modelling and forecasting age-specific fertility. The Box–Cox transformation parameter should be embedded in statistical analysis of age-specific demographic data, in order to fully capture forecast uncertainties.
Original language | English |
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Pages (from-to) | 69-79 |
Number of pages | 11 |
Journal | Journal of Population Research |
Volume | 32 |
Issue number | 1 |
DOIs | |
Publication status | Published - Mar 2015 |
Externally published | Yes |
Keywords
- Age-specific fertility rates
- Data transformation
- Principal component analysis
- Mean absolute forecast error
- Interval score