Australia through the demographic lens
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How has Australia's population changed over the years? Learn more about the shift in population growth through understanding migration, fertility and mortality rates.
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Australia through the demographic lens
- 1. 1 Australia through the demographic lens Presentation to GPT - March 2014
- 2. 2 Significant demographic changes in Australia • Historic levels of population growth • Large increases in overseas migration gain • A reversal in fertility rate trends with decreases becoming minor increases (more babies) • Continued declining mortality rates (people living longer) • Different patterns of migration between the states
- 3. 3 the historical view: 1971-2001
- 4. 4 Population by age Australia 1971-2001 Source: ABS Australian Demographic Statistics, 2013
- 5. 5 Population growth by age Australia 1971-2001 Source: ABS Australian Demographic Statistics, 2013
- 6. 6 a turning tide: 2001-2013
- 7. 7 Net overseas migration Australia, 1976-2013 Source: ABS, Australian Demographic Statistics
- 8. 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Recent arrivals (2006-2011) Total population Source: 2011 Census of Population and Housing, ABS Age structure of migrants Australia,2006-2011
- 9. 9 Fertility and number of births Australia, 1976-2013 Source: ABS, Australian Historical Population Statistics, 2008 ABS, Australian Demographic Statistics
- 10. 10 Fertility rates Selected countries, 1975-2010 Source: United Nations, Population Division, World Population Prospects
- 11. 11 Population growth by age Australia, 2001-2011 Source: ABS, Australian Demographic Statistics 2013
- 12. 12 three growth markets: 2011-2031
- 13. 13 Population growth by age Australia, 2011-2031 Source: .id Small Area Forecast Information (SAFI), 2013
- 14. 14 Population change Australia 1971-2051 Source: ABS, Australian Demographic Statistics, .id SAFi 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000
- 15. 15 Population by age Australia, 2011-2031 Source: .id Small Area Forecast Information (SAFI), 2013
- 16. 16 the state of the states
- 17. 17 Net overseas migration by state Australia, 1976-2013 Source: ABS, Australian Demographic Statistics
- 18. 18 Net interstate migration Australia 1976-2013 Source: ABS, Australian Demographic Statistics
- 19. 19 Total growth States, 2006-2011 0 50000 100000 150000 200000 250000 300000 350000 400000 450000 NSW Vic Qld SA WA Tas NT ACT Absolute growth 2006-2011
- 20. 20 Comparative growth States, 2006-2011 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% NSW Vic Qld SA WA Tas NT ACT State % growth 2011 5 year growth %
Editor's Notes
- There has been a major shift in population growth patterns in Australia. This leads to opportunities for businesses who have access to this knowledge and plan to take advantage of the changes – many of which are not well understood.
- A quick look at history gives us an insight into how dramatic the population shifts we are seeing are. The dominant view – Australia has an aging population
- The black bars are a snap-shot of the Australian population in 1970. At that time, with high birth rates and a relatively lower life expectancy, the Australian population was weighted towards the younger generations. However, moving through the dark grey, light grey and then the orange bars, we can see the baby boomers (who were in their mid-twenties in 1971) moving through the population profile, and the population becoming centred around a higher average age. Interestingly, the number of children in the population remained relatively static. Figure 3 presents the total change in each age group between 1971 and 2001. While there was strong growth in the ‘middle-aged’ group, the number of children barely moved, primarily reflecting a trend decline in fertility rates through this period.
- At the same time, there was a solid increase in the older generation as life expectancy increased substantially. As a result, the centre of gravity shifted, and the Australian population aged. a turning tide: 2001 to 2013
- However, between 2001 and 2013 we saw major shifts in population growth patterns emerging. Fertility reversed a long run decline, and migration rose to record levels. There were even considerable changes in the make up of interstate migration in this period.
- Through the thirty-year period between 1976 and 2006, migration has moved in cycles broadly correlated with the business cycle. That is, there were periods of very low migration coinciding with the early 80s and early 90s recessions. However, through that period, even in the biggest years net migration never exceeded 150,000 persons a year. From 1995 onwards, coinciding with Australia’s strong economic run, net migration has barely fallen below 100,000 persons a year, resulting in a sustained contribution to population growth over this period. However, what really stands out in this chart is the spike in migration that coincided with the GFC. In 2008 migration surged, topping out at 300,000 persons in 2009 – a figure double the previous peaks. With the Australian economy the ‘envy of the world’ throughout the GFC, Australia became an attractive destination for foreigners, and many Australians living overseas repatriated. What’s more, there appears to have been a level shift increase in migration, which has held around the 200,000 mark for several years now. This means that migration is having a big impact on Australian population growth. We had a sustained period of high migration prior to the GFC, and post GFC we’ve had a sustained period of very high migration. It is likely that in the short-term, the fertility rate does not benefit from this mass wave of migration, as a large share of the migrant population is not interested in becoming parents because they are here to study and get a foothold in the Australian labour force. However, in the medium to long term, they boost the pool of potential parents significantly.
- The age structure of these migrants is one thing keeping the population of NSW young. It is highly concentrated between the ages of 15 and 35, more so than in any other state, probably due to the student population
- Figure 4 tracks the Australian fertility rate and total number of births between 1976 and 2013. What it shows is that there was a sustained trend decline in fertility in the years leading up to 2001. Greater freedom for women in their family choices, changing preferences and the introduction of the pill caused a sharp fall in fertility in the 1960s and 70s, which persisted into the early years of the new millennium. As a result the actual number of births per year plateaued out around 1985, and remained practically unchanged over the next 20 years. Population projections made around the turn of the millennium were built on the expectation that the fertility rate in Australia would continue to decline (the dotted line), following the lead of mature countries like Italy, Germany and Japan. However, around 2004/5 the fertility rate actually picked up, and picked up substantially to just under 2 children per woman. This is relatively close to so-called ‘replacement levels’ of about 2.1 children per woman. As a result, the number of children born each year in Australia has increased to a level about 50,000 children over and above long-term averages. So in just 6 years, we’ve added an extra 300,000 children to the population, over and above our “business as usual” numbers. This has created a major disruption in this market segment, and has major implications for education, childcare, children’s consumables and so on. It is interesting to theorise about what caused this sudden reversal in Australian fertility.
- Australia is not alone. Figure 5 tracks fertility rates in a number of Western countries. In countries like Canada (orange line) and in Northern Europe (blue line), the recovery in fertility rates has been even more pronounced. Even in Japan (green line) fertility rates seem to have found a floor, and are tentatively moving upwards again. At any rate, it is too early to tell in Australia if fertility rates will sustain the recent upward trend, or will find a new level somewhere around the replacement rate. However, what is known is that there has been a substantial increase in the number of children born over the past six or so years. It has created a minor population bulge that will work its way through the system over time.
- The trend reversal in fertility rates, together with sustained strength in migration has changed the trajectory and shape of the Australian population over the past decade or so. The baby boomer bulge is evident in the growth of 55-70 year olds, but it is not the only story. There has also been strong growth in the number of people in their early and mid twenties, largely on the back of stronger migration, as well as strong growth in the number of infants, reflecting the pick-up in fertility rates as well as growth in the parent age groups, notably 25-29 year olds. And so in terms of population, it’s a three horse race. There is a baby boomer generation, a young adult generation, and an infant generation moving through the system. As a result, for business the Australian future holds three significant growth sectors.
- With something like 200 councils using profile.id® over the past 15 years or so, a frequently asked question at council briefing and training sessions has been, “Can you extend profile.id® to include economic data?” These requests grew in number as Local Government’s role in economic development has grown. Quite simply, this was the inspiration to develop economy.id® – and now to extend it with an Impact Assessment model. However, getting reliable economic data for sub-State economies is a significant challenge and this blog discusses how we discovered a solution by partnering with economic brains trust, NIEIR. The challenges We started by evaluating what economic data was available in the Census. Having used Census Journey to Work data many (many) years ago for my Geography honours thesis, I was aware that Census Journey to Work destination data provided a good basis for profiling an economy at the local area level. The data provides in aggregate, a rough the number of jobs by industry sector for any local government area. However, while providing a reasonably accurate ‘shape’ of the economy (dominant and emerging industry sectors), it does not provide an adequate measure of economic activity at the local area level. For example, we know that Census counts of employment are notoriously inaccurate, with up to a 20% undercount due to the automatic exclusion of those persons who are employed but fail to state a location, or who can’t be coded to their exact workplace address. While Census data is an excellent resource for detailed worker characteristics (and is used in economy.id®), using it as the main source of broad employment numbers is problematic. Reliable primary economic data sets exist only at the national, state and regional level at best. Therefore the only way to get a realistic measure of jobs, output, turnover etc. at the local area level is to undertake economic modelling. The most significant challenge with local area economic modelling is to ensure that the process reflects the unique economic characteristics of the local area. For example, one of the traps is to apply national and state-level productivity propensities at the local level, which we now know is simply not accurate because it assumes a that the economic characteristics of all local areas are the same. The need for local nuance At .id we have been looking for a solution to this problem for quite some time. Enter Peter Brain from the National Institute for Economic and Industry Research (NIEIR). While Peter is famous for predicting major economic crises – namely the Asian Economic Crisis of 1997 and more recently the Global Financial Crisis – even more importantly, NIEIR’s reputation among the council officers familiar with their work preceded them and attracted .id’s interest in a partnership in developing economy.id®. NIEIR are recognised as industry leaders in the development and provision of robust economic modelling at the smallest credible geographic unit (Local Government Area). For over 10 years NIEIR have been producing the annual benchmark State of Regions Report commissioned by the Australian Local Government Association (ALGA). NIEIR modelling draws on many data sources to offer the most nuanced data possible at the local level. The NIEIR dataset is the result of a process of economic micro-simulation modelling – it is an amalgam of many different existing data sources (between 6 and 10 depending on the region and time period) which are synthesised to produce a series of estimates of the size and value of each industry. All the modelled data uses a breakdown of 19 ANZSIC industry divisions (e.g. Manufacturing) into 49 sub-groupings (e.g. Food Product Manufacturing) providing a highly detailed picture of which industries are contributing to the local economy. Importantly, the NIEIR model is updated on an annual basis (with quarterly breakdown for some characteristics). This means the impact of global, national and local economic changes can be clearly seen on each industry sector at the local level. We established that this modelling was superior to any other models we evaluated for the following reasons: Uses micro-simulation modelling (bringing together multiple data sources to simulate a realistic view of the local economy) Modelled annually ensuring the model is regularly updated to reflect global, national and local factors. Does not rely purely on Census counts of employment (Census data is a fantastic resource but is known to undercount employment by 20% because it excludes anyone who does not state their workplace address). Uses Centrelink, DEEWR labour market statistics, ATO data to provide a more accurate estimate of CURRENT employment. Estimates Hours Worked and converts this into a measure of Full-Time Equivalent Employment to ensure that underemployment cannot be hidden. Does not assume that the productivity of an industry sector is the same across all LGAs in the State, but uses ATO data to ensure local differences are taken into account. Uses locally derived inputs such as commercial building approvals by floor space, and Dun and Bradstreet datasets on business start-ups and exits to capture local industrial growth and decline. Makes manual adjustments are made to refine the model based on local knowledge such as arrival of new employers, closing industries, large building construction etc (clients can input into this process) Mining areas are treated differently to take into account fly-in-fly-out and other considerations. To benchmark we need a national dataset so we can see the relative position of every LGA. Problem - Economic data is not generally available for local areas such as sub-State regions or Local Government Areas. Economic modelers have the challenging task of taking national and state figures and modeling them down to these smaller geographic areas. Their task is to create an economic model that is the most accurate representation of economic reality that we can have. Criteria - I’m sure you will thank me if I don’t go into the intracacies of economic modelling here – but there are a couple of points I need to get across.In simple models, State wide data is taken and divided across LGAs as if they are all the same. For example the value of a mining job in Brisbane is treated in the same way as on in Mount Isa – even though they are patently not the same thing at all and can lead to all sorts of strange anomolies in the data. National Economics (NIEIR) are .id’s economic modelers of choice. We believe that their model is the most sophisticated and nuanced for local areas. Together we have built a set of economic indicators for every LGA in Australia as a starting point to understanding their areas’ contribution to the State and National economies. Today we present the National Economic Indicators Series for the first time. It will be publically available from .id’s website and updated annually. There are xx data series in the indicators, and I stress that this is only a starting point for analysis – but it does provide a very quick way of benchmarking one area to another and answering questions like? Which areas are similar Which areas are performing well Which areas area struggling economically So without further ado, here is the inaugural set of National Economic Indicators. What it won’t tell you is why … that’s where you need to build a more comprehensive story of your local economy –
- If we take the current population profile, we can see these three population spikes moving through the generations and defining the shape of the Australian population in 2031
- These projections have been produced using a number of key assumptions. In particular, we expect overseas migration to remain strong, with a net gain of approximately 200,000 per year. We also expect the fertility rate to steady, rather than continue its upward trend, which will temper growth in infant and child age groups somewhat. Currently 23m. 36.5 million in 2051 - 36m in 2050 - K Rudd “Big Australia”. 51m in 2101.
- Nevertheless, recent trends mean that as the baby boomers enter their declining years, there will be strong growth in the two generations behind them. This is a healthy thing for Australia. Indeed, compared to the demographic challenges mounting in Japan, China, Italy and a number of countries around the world, Australia’s demographic profile is relatively robust. The projections presented here are obviously the big picture macro forecasts for Australia. However, at .id we build our forecasts from both the top-down and the ground up, and develop micro level forecasts for our clients, right down to individual blocks and neighbourhoods. So while these three growth sectors will define the coming twenty years, cities, suburbs and neighbourhoods could have radically different experiences. Our research and the suite of tools available to .id clients help them factor in these specific, market level forecasts into their business planning.
- While there has been a solid and sustained increase in migration, there has also been a change in the destinations those migrants are choosing to call home. Figure 7 shows that traditionally, the large majority of immigrants headed for NSW (sky blue) and Victoria (navy blue). However, over the past decade or so, we’ve seen a process of convergence in migration shares. Around the turn of the millennium there was a pick up in migration to Queensland, taking share from NSW in particular and Victoria to some degree, and in recent years, there’s been a strong pick up in migration to WA, reflecting the influence of the mining boom. As a result, in 2013, migration levels into these four states have become broadly similar. The change in destination preferences will have a major impact on state economies. There have also been significant changes in the flows of interstate migration. Typically, Victoria and NSW experienced net population outflows, often as new migrants decided to establish themselves elsewhere
- (Figure 8). To a large extent Queensland was the beneficiary of these population outflows, and has typically enjoyed strong population growth through interstate migration. However, over the last decade or so, this has been largely unwound. Interstate migration into Queensland has eased considerably, as have population losses in NSW. However the real news here is Victoria, which for the first time in a long time has enjoyed positive (if small) net interstate migration. There has also been a fillip in interstate migration into Western Australia in recent years, again reflecting the influence of the mining boom.
- Queensland historically the fastest growing State. Been replaced by WA as the fastest growing State. In 06-11 only 4th fastest behind WA, ACT and NT Talk of two-speed economy – the mining states – assumed Queensland is on the positive side of the ledger .... BUT Percentage of persons employed in mining is lower than WA – has less effect on GDP and consumption More trade exposed industries (tourism, manufacturing) Queensland does not do well with a high Oz dollar It’s all about relativities...which create push and pull factors