The assumed rate of future mortality improvement has increased over three recent sets of the United Kingdom's national population projections. This optimism has not been so marked in countries which share ancestors with the U.K. population. New Zealand is one such country that provides a data-rich case example in which to investigate the portability of mortality trends.This paper compares mortality trends in New Zealand with those in England & Wales. Both countries seem to have a ‘golden cohort’ which enjoys faster improving mortality than people born before or after. The birth of the golden cohort in England & Wales coincided with cohort life expectancy there catching up with New Zealand's.We show that first generation migrants from the U.K. have better mortality than New Zealand born residents likely to have British ancestry. The advantage lasts into older ages, decades after migration. We hypothesise that migrants from the U.K.'s golden cohort brought with them an early life mortality improvement advantage, and additionally benefited from the healthier environment of New Zealand at middle to older ages. Further, given the recent strong mortality improvement in New Zealand, the U.K.'s assumptions for future mortality look relatively optimistic.

New Zealand's ageing population is at the heart of discussions around fiscal sustainability. Demographic projections, regularly produced by Statistics New Zealand, indicate future trends in the size, growth rate, and age-sex structure of the population and labour force. This paper examines those demographic projections including the key projection results, what the projections are measuring, and the methods and assumptions underlying the projections.

Statistics New Zealand is one of the few national statistical agencies to have applied a stochastic (probabilistic) approach to official demographic projections. This article discusses the experience and benefits of adopting this new approach, including the perspective of a key user of projections, the New Zealand Treasury. Our experience is that the change is less difficult to make than might be expected. Uncertainty in the different projection inputs (components) can be modelled simply or with more complexity, and progressively applied to different projection types. This means that not all the different demographic projections an agency produces need to adopt a stochastic approach simultaneously. At the same time, users of the projections are keen to better understand the relative certainty and uncertainty of projected outcomes, given the important uses of projections.

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Demographic norms are useful as a guide when specific predictive tools are unavailable.