The forecast accuracy of Australian Bureau of Statistics national population projections

Wilson, Tom

doi:10.1007/bf03031880

Cited by 32 publications

(47 citation statements)

References 17 publications

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“…Mortality forecasts based on subjective expert opinion are often biased by opinions about biological upper limits on human life span, and as a result, future improvements in mortality are capped (Olshansky, 1988). Mortality levels projected in this way have often turned out to be overstated, and population numbers underestimated, because mortality improved more than was foreseen or believed possible, particularly at older ages (Keilman, 1997;Lee & Carter, 1992;Murphy, 1995;Olshansky, 1988;Wilson, 2007). The existence of a fixed biological limit on the human life span, and its likely level, continues to be a subject of debate and disagreement among biologists, demographers and actuaries (Fries, 1980;Oeppen & Vaupel, 2002;Olshansky, 1988;Vaupel, 2001).…”

Section: Expectation Methodsmentioning

confidence: 99%

“…Wilson (2007) found that mean absolute errors of age-sex population projections for Australia were largest at the youngest and oldest ages, with high errors at older ages attributed to both inaccurate mortality rate forecasts and numbers by cohort moving into these age groups. Furthermore, official national and state projections are only provided for single ages to 99 and 84 and in aggregate for ages 100+ and 85+ respectively.…”

Section: Projected Very Elderly Population Numbersmentioning

confidence: 99%

“…Appropriate projections of Australia's very elderly population at national and state levels are vital for national and regional planning, policy making and budgeting of social welfare, health and aged care services and housing. Retrospective tests have revealed that very elderly population projections produced by the ABS have turned out to be too low, due to underestimated mortality improvements (Wilson, 2007(Wilson, , 2012a. In order to create more reliable projections, appropriate projection approaches need to be identified.…”

Section: Mortality Forecastingmentioning

confidence: 99%

“…Furthermore, the ABS' 1992 very elderly population projections to 2011 turned out to be too low by 18% for males and 10% for females. Various local and international studies suggested that the tendency for official projections of very elderly populations to be too low was due to the use of expectation methods in forecasting mortality, and in particular overly conservative targets (Lee & Carter, 1992;Murphy, 1995;Olshansky, 1988;Wilson, 2007Wilson, , 2012. In addition, in earlier chapters, large errors in official census-based estimates for populations aged 90+ were identified.…”

Section: Decomposition Of Growthmentioning

confidence: 99%

“…According to Wilson (2007), high errors at older ages could largely be attributed to inaccurate mortality rate forecasts. The historical under-projection of very elderly populations stems from the over-projection of death rates, or, more specifically, under-projecting the extent to which death rates would decline in future.…”

Section: Introductionmentioning

confidence: 99%

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Population estimates and projections for Australia’s very elderly population at state and national level

Terblanche¹

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As in many developed countries, the very elderly population (ages 85+) is the fastest growing age group in Australia, with far-reaching economic and social consequences. To effectively plan and budget for the income, aged care and health care needs of the very elderly, accurate estimates and projections are required. There are, however, several obstacles relating to the availability and accuracy of very elderly data. Official population estimates at very high ages in Australia have been found to be too high and fluctuate implausibly over time. International and local studies have found large errors in projected very elderly populations, stemming from inaccurate mortality rate forecasts.This thesis aims to create accurate estimates and projections for Australia's very elderly population at a state and national level. Various methods for estimating very elderly populations from death counts were assessed for accuracy at both a national and state level.While the Human Mortality Database uses such methods to create estimates for many countries, their accuracy has never been assessed for Australia. Furthermore, little is known, locally or internationally, about their performance at a sub-national scale. In this study, the accuracy of various nearly-extinct-cohort methods were assessed at the Australian national and state level by retrospectively applying them to extinct cohorts and comparing the results against those obtained from applying the Extinct Cohort method. Suitable methods were applied to create very elderly population estimates and death rates for Australia from 1972-2012 by sex, state and at single ages 85-110+. The growth, changes in the age-sex composition and the demographic drivers of growth of Australia's very elderly population were analysed. Based on these estimates, more reliable death rates were calculated, allowing a detailed study of the changing patterns and trends in Australian adult mortality. Finally, a number of mortality forecasting methods were retrospectively evaluated for their accuracy in projecting adult death rates for Australia over 10 and 20 years ending in 2012. An appropriate method was applied to create projections for the next three decades.It was found that, compared to the official census-based estimates, more plausible and accurate estimates, especially for ages 95+, could be derived from death counts. The Survivor Ratio (SR) method with results constrained to official estimates for ages 85+ produced accurate very elderly population estimates for Australia across the sexes and ages at both a national and state level. Internal migration is sufficiently minor to be ignored. Very accurate state-level estimates could also be derived using a simpler method of apportioning national single-age estimates between the states. Adult death rates in Australia were found to show consistent and regular patterns of decline since the 1970s, with rates of decline decreasing with age. These patterns support the use of simple direct extrapolation methods for forecasting. The Geometric,...

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Section: Expectation Methodsmentioning

confidence: 99%

Section: Projected Very Elderly Population Numbersmentioning

confidence: 99%

Section: Mortality Forecastingmentioning

confidence: 99%

Section: Decomposition Of Growthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Population estimates and projections for Australia’s very elderly population at state and national level

Terblanche¹

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Numerical simulations of snowfall events: Sensitivity analysis of physical parameterizations

et al. 2015

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Accurate estimation of snowfall episodes several hours or even days in advance is essential to minimize risks to transport and other human activities. Every year, these episodes cause severe traffic problems on the northwestern Iberian Peninsula. In order to analyze the influence of different parameterization schemes, 15 snowfall days were analyzed with the Weather Research and Forecasting (WRF) model, defining three nested domains with resolutions of 27, 9, and 3 km. We implemented four microphysical parameterizations (WRF Single‐Moment 6‐class scheme, Goddard, Thompson, and Morrison) and two planetary boundary layer schemes (Yonsei University and Mellor‐Yamada‐Janjic), yielding eight distinct combinations. To validate model estimates, a network of 97 precipitation gauges was used, together with dichotomous data of snowfall presence/absence from snowplow requests to the emergency service of Spain and observatories of the Spanish Meteorological Agency. The results indicate that the most accurate setting of WRF for the study area was that using the Thompson microphysical parameterization and Mellor‐Yamada‐Janjic scheme, although the Thompson and Yonsei University combination had greater accuracy in determining the temporal distribution of precipitation over 1 day. Combining the eight deterministic members in an ensemble average improved results considerably. Further, the root mean square difference decreased markedly using a multiple linear regression as postprocessing. In addition, our method was able to provide mean ensemble precipitation and maximum expected precipitation,which can be very useful in the management of water resources. Finally, we developed an application that allows determination of the risk of snowfall above a certain threshold.

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Discussion and Conclusions

Wilson¹,

Temple²,

McDonald³

et al. 2021

The Changing Migrant Composition of Australia’s Population

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The forecast accuracy of Australian Bureau of Statistics national population projections

Cited by 32 publications

References 17 publications

Population estimates and projections for Australia’s very elderly population at state and national level

Population estimates and projections for Australia’s very elderly population at state and national level

Numerical simulations of snowfall events: Sensitivity analysis of physical parameterizations

Discussion and Conclusions

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