Selection of the optimal Box–Cox transformation parameter for modelling and forecasting age-specific fertility

Han Lin Shang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

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 languageEnglish
Pages (from-to)69-79
Number of pages11
JournalJournal of Population Research
Volume32
Issue number1
DOIs
Publication statusPublished - Mar 2015
Externally publishedYes

Keywords

  • Age-specific fertility rates
  • Data transformation
  • Principal component analysis
  • Mean absolute forecast error
  • Interval score

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