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Abstract: Old-age mortality for populations of developed countries has been improving rapidly since the 1950s. This phenomenon, which is often referred to as ‘rectangularization’ of mortality, implies an increased survival at advanced ages. With this increase comes different challenges to actuaries, economists and policy planners. A reliable estimate of old-age mortality would definitely help them develop various demographic and financial projections. Unfortunately, data quality issues have made the modeling of old-age mortality difficult and we need a method that can extrapolate a survival distribution to extreme ages without requiring accurate mortality data for the centenarian population. In this paper, we focus on a method called the threshold life table which systematically integrates extreme value theory to the parametric modeling of mortality. We apply the threshold life table to model the most recent period (static) mortality rates for the populations of Australia and New Zealand. We observe a good fit to the raw data for both populations. We then extend the model to predict the highest attained age, which is commonly referred to as ‘omega’ or in the actuarial literature, for the populations of Australia and New Zealand. On the basis of the threshold life table, the central estimates of for Australia and New Zealand are 112.20 and 109.43, respectively. Our estimates of are reasonably consistent with the validated supercentenarian in these countries. [Copyright &y& Elsevier]

Abstract: This paper aims to analyse the seasonality in New Zealand tourism demand from Australia and the USA using spectral analysis. Tourism demand is divided into four different categories depending on the tourists’ visiting purposes as registered in the customs cards upon their arrivals in New Zealand. Spectral analysis based on the sample from January 1980 to December 2007 revealed that different travel purposes share similar cyclical components but their contributions to the total variation in tourism demand differ between travel purposes and markets. More importantly, the results show that analysing aggregated data is often not sufficient to reveal the underlying seasonal patterns of tourist arrivals and policy makers would benefit greatly by analysing disaggregated data rather than relying on the analysis of aggregated data alone. [Copyright &y& Elsevier]