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Table 1 Some broad approaches to regional mortality forecasting

From: Evaluation of simple methods for regional mortality forecasts

Approach Examples
1. Use national or State, or region-type, mortality forecasts Simply use national or State mortality forecasts for all regions (e.g. Pittenger 1976; CSO 2013), or apply forecasts for broad region types to all regions of that type
2. Trend regional mortality age schedules towards a long-run target Trend regional mortality age profiles from the base period converging towards (or diverging away from) a very long-run set of target mortality rates (e.g. Van Hoorn and Broekman 1999 and Lanzieri 2016)
3. Apply models developed for single national populations to every region For every region:
• Fit a parameterised model schedule and extrapolate parameters
• Use functional data models (e.g. Hyndman and Ullah 2007)
• Fit new versions of extrapolative models (e.g. Ediev 2008)
• Apply the Lee-Carter model (Lee and Carter 1992) or one its many extensions (e.g. Li et al. 2013)
4. Use multi-population models • Lee-Carter extension for multiple populations (e.g. Li and Lee 2005)
• Two-population age-period-cohort model (Cairns et al. 2011)
• Product ratio method of Hyndman et al. (2013)
• Bayesian approaches (e.g. Gongaza and Schmertmann 2016)
• Multilinear component approach of Bergeron-Boucher et al. (2018)
5. Use a national or State mortality forecasts and create regional mortality forecasts via simple relationships • Brass-type relational models (e.g. Brass 1971, Ewbank et al. 1983, and Murray et al. 2003)
• National or State mortality age schedules scaled up or down according to the SMR (e.g. Giannakouris 2010 and NRS 2016)
• TOPALS relational method using smoothed age profiles of rate ratios (de Beer 2012)
• Assume regional death rates decline by the same proportional amount as forecast national death rates (Smith et al. 2013)
• Mortality surface method (e.g. Wilson 2014, 2017)
• National or State mortality age schedules scaled up or down according to regional/national mortality rate ratios (e.g. ONS 2016)