Background Typically, women with higher levels of education have had fewer children and were more likely to be childless compared to those with lower levels of education. However, in recent years, there has been a trend of fertility convergence between education levels in several high-income countries, including Australia. New data are needed to determine whether this trend has continued and fertility remains educationally stratified among Australian women. Aims Using the latest available data from the 2021 Australian Census, the aim of this study is to compare the average completed fertility and number of children ever born of women born between 1952 and 1981, with a specific focus on how these metrics vary by education level. Data and methods Data on the number of children ever born are sourced from the 2021 Australian Census to compute population statistics (completed cohort fertility, proportion of women by parity, and parity progression ratios) for six educational categories (postgraduate, graduate, bachelor, diploma, year 12, year 11 and below) and six cohort groups (1952-56, 1957-61, 1962-66, 1967-71, 1972-76, 1977-81). These statistics are used to describe trends in fertility patterns over time and by education. Results Completed cohort fertility has continued to decline slowly, from 2.22 for the1952-56 birth cohorts to 1.89 for the 1977-81 birth cohorts, mostly due to an increase in childlessness and a decrease in larger families with more than two children. There has been more divergence than convergence by education level, with those with bachelor's or diploma qualifications experiencing greater declines in fertility than any other education group. Although childlessness rates by education level have converged, women with lower education have also become increasingly likely to have larger families. Conclusions While there is evidence of convergence in childlessness rates across different levels of education, the gap in fertility rates between education groups continue to increase in Australia.
This is an edited version of a speech delivered to the Population Symposium at the Australian National University School of Demography on 6th October 2023.
Background Since same-sex marriage was legalised in Australia in December 2017, thousands of same-sex couples have married. Little Australian research to date has examined same-sex marriage trends and how they are similar or different to different-sex marriages. Aims To describe trends in same-sex marriages and remarriages in Australia for the years 2018–2020, comparing and contrasting with different-sex marriages and remarriages by age and sex. Data and methods Data come from the Australian Bureau of Statistics publication Marriage and Divorces, Australia. We use available data on different-sex and same-sex marriages and remarriages for age and sex. Results The proportion of same-sex marriages declined from 5.5% of total marriages to 3.7% between 2018 and 2020. Same-sex marriages tended to be at older ages, but the age gap between same-sex and different-sex marriages for males and females reduced over time. Similar trends were observed for remarriage. For different-sex remarriages, there was a slightly higher proportion of males remarrying than females. In contrast, for same-sex remarriages, the proportion of females remarrying was double that of same-sex males. Conclusions Early trends suggest same-sex marriages and remarriages occurred at older ages than different-sex. This age gap reduced over time, suggesting that early adopters of same-sex marriage may be a different group. Interestingly, same-sex remarriage was much more common for females. Given that same-sex marriage was not legal in Australia until late 2017, it is likely that many of their first marriages were different-sex. This has received little attention in the research literature to date and requires further investigation.
Background The geographic mobility of labour has long facilitated a well-functioning labour market for Australia, being of importance in skill-matching and jobs in regional economies. Disrupting the long-distance labour commute, COVID-19 border closures and community lockdowns had an immediate and significant impact on the Australian labour market. Aims The aim is to understand Australian labour force demography and provide an empirical understanding of how regions, and their respective states and territories, faired through the pandemic. Data and methods Using Australian Bureau of Statistics SA4 level labour force participation and unemployment data, the paper highlights regional changes between 2018 and 2021 - covering periods immediately before and after the emergence of COVID-19. Its analysis is contextualised by the respective state and territory and employment conditions underpinning labour demand via proxies of gross national product and state and territory gross product, gross real income and job vacancies. Results The paper finds variations in labour force change are dependent on regional industry economic profiles between and within states and territories. This was in part due to state and territory lockdown and border closure policies as well as respective industry economic profiles. Conclusions A more comprehensive mapping and understanding of labour force shifts over time will better capture the trajectories of regional labour markets. This will enable better targeting of specific policy outcomes at various levels of government, including to encourage industry diversity, support labour reskilling and the uptake of technologies. Such policies will be better placed to assist Australian labour force transitions post-COVID and efficient labour market functioning.
This is an edited version of the W.D. Borrie lecture given by the Hon. Dr Andrew Leigh MP, Assistant Minister for Competition, Charities and Treasury, at the 20th Australian Population Association in Canberra on 23 November 2022.
Background The 2021 Census in Australia revealed that just over 1 million dwellings were ‘unoccupied’ on census night. This finding was widely reported and may have given the impression of a large number of vacant dwellings ready for households to move into, potentially offering a solution to homelessness and those struggling to find suitable or affordable accommodation. Aims The aim of the paper is to investigate whether there really were 1 million unoccupied dwellings in Australia in 2021, to shed some conceptual and empirical light on exactly what is meant by an ‘occupied’ and an ‘unoccupied’ dwelling, and also try to understand why dwellings were unoccupied. Data and methods We used a variety of census, population, and dwelling data to estimate the number of private dwellings disaggregated by occupancy on both a de facto basis (whether people were present in dwelling on census night or not) and on a usual residence basis (whether people are usually resident in a dwelling or not). A comparison with the situation at the time of the 2016 Census is made. Results The results show that there were indeed about 1 million dwellings unoccupied on a usual residence basis in Australia in 2021. But they were not the exact same 1 million unoccupied on census night, and not all of these dwellings were available to households to live in. There was a substantial increase in the number of dwellings unoccupied by usual residents between 2016 and 2021; we suggest some possible reasons for this, including Covid-related effects. Conclusions Greater clarity and more detail are needed in census dwelling data. In addition, it would be useful if there were detailed annual official statistics on dwellings and households to better inform housing policy and research.
This is an edited version of the APA Presidential address given by Dr Kim Johnstone, APA President, at the 20th Australian Population Association in Canberra on 23 November 2022.
Background There has been considerable speculation on whether the COVID-19 pandemic had an effect on childbearing behaviour. Based on the experience of other social and economic disruptions, many researchers suggested that births would decline, while others argued that there could be a positive effect. Aims This paper considers the uncertainties associated with the impacts of COVID-19, particularly the relationship between the timing of COVID-19 events and subsequent births. Data and methods Publicly available birth data from birth registers, perinatal databases, and public hospital data were compiled and analysed to document changes in numbers and patterns of recorded births during 2020 and 2021. Results Births declined in 2020 but then rebounded in 2021. Quarterly birth data from New South Wales and Western Australia suggest that the sharpest drop in conceptions occurred in the January-March 2020 quarter. This coincided with the period when the pandemic was first taking off and when uncertainty about the future was at its highest. Conclusions The uncertainty associated with the onset of the COVID-19 pandemic had a noticeable impact on births in 2020. It also shows, where data is available, that this impact was relatively short-lived, and births rebounded in 2021. We note that data is still sparse for Victoria, a state which was substantially more affected by lockdowns.
Australia’s public heath response to COVID-19 included the temporary closure of state and regional borders in an effort to significantly curb population mobility. For those who were travelling at the time, the assumption seemed to be that they could simply return home, and resume travel when it was safe to do so. While it was recognised that mobility restrictions would cause difficulties for international tourists as they did not have a permanent residence in Australia, the assumption for domestic resident travellers was that they were ‘away from home’ and could therefore simply return to their place of ‘usual residence’. Such normative framings of travellers as ‘away from home’ or away from a ‘usual residence’ present challenges for Australians who engage in practices of bi-locale and multi-locale forms of residence, for those that do not identify as having a single place of usual residence, and for the permanently nomadic. This includes a diverse range of sub-population groups: those experiencing secondary homelessness; seasonal labourers; backpackers; highly mobile Indigenous peoples; longdistance commuters; travelling show families and workers; permanent house-sitters, and; grey nomads (the focus of this paper).
Background In Australia, the Socio-Economic Indexes for Areas (SEIFA), which includes the Index of Relative Socioeconomic Disadvantage (IRSD), captures the socioeconomic characteristics of areas. Because SEIFA rankings are relative to the country or state, the decile categorisations may not reflect an area’s socioeconomic standing relative to areas nearby. Aims The aim of the research was to explore whether IRSD rankings could be re-ranked to become locally sensitive. Data and methods Using existing SEIFA data to redistribute the membership of current decile IRSD groups, we tested three methods to re-rank all SA1 areas relative to the nearest areas capped at: (1) the nearest 99 neighbours, (2) a population threshold of 50,000 (3) a distance threshold of 10 km. Results The reclassification of SEIFA IRSD deciles was largest (up to 8 decile points of change) when comparing the nearest neighbour and population threshold local methods to current state-based rankings. Moreover, compared to using current national and state SEIFA IRSD rankings, the use of local rankings resulted in more evenly distributed deciles between cities, regional, and remote areas. Conclusions Because SEIFA IRSD rankings are used to allocate resources and health services, we encourage the combined use of a state and local ranking to refine areas considered the most disadvantaged.
There is considerable literature documenting the peripatetic preferences of Australians for leisure, lifestyle and work purposes, and the paucity of reliable data that would provide insights to why people have multiple bases and the impact on local markets and service delivery (McKenzie et al. 2008 p.4; Nicholas and Welters 2017; Nicholas and Welters 2016). There have been numerous requests and submissions to the Australian Bureau of Statistics (Productivity Commission 2014; Productivity Commission 2019; ABS 2007; McKenzie et al. 2008) to systematically record population mobility, and to not limit the Place of Usual Residence to just one location in the quinquennial census. To date, these have been unsuccessful.
Background There are surprisingly few resources available which offer an introductory guide to preparing a national population projection using a cohort-component model. Many demography textbooks cover projections quite briefly, and many academic papers on projections focus on advanced technical issues. Aims The aim of this paper is to provide a short and accessible guide to producing a national-scale population projection using the cohort-component model. Data and methods The paper describes the cohort-component model from a population accounting perspective, presents all the necessary projection calculations, and covers the key steps which form part of the projections preparation process – from gathering input data to validating outputs. An accompanying Excel workbook implements the model and contains example projections for Australia. Conclusions Calculating a national population projection using a cohort-component model involves fairly simple algebra, but the broader projections preparation process is more complex, and requires careful consideration and judgement.
