Why are young adults more likely to use public transport? (an exploration of mode shares by age – part 4)

Sat 13 January, 2024

I’ve been exploring why younger adults are more likely to use public transport, looking at data sets available for Melbourne. This fourth post in the series looks at the relationship between public transport mode share and income, socio-economic advantage/disadvantage, occupation, hours worked per week, and whether people are studying.

It concludes with a summary of the findings from the four posts in this series. For more detail about the data, see the first post in the series.

(note: I started writing this post quite a while ago – apologies I got distracted by new data releases including the 2021 census data)

Here’s an index as to which posts look at which factors (including many combinations of these factors):

  • part 1: age, sex, travelling to city centre (or not), workplace distance from CBD, education qualifications, home distance from CBD.
  • part 2: proximity to train stations, population density, job density, motor vehicle ownership, driver’s licence ownership.
  • part 3: parenthood, birth year, immigrant arrival year.
  • part 4 (this post): income, socio-economic advantage/disadvantage, occupation, hours worked per week, whether people are studying.

Income

Could income explain different levels of PT use by age, if older workers are earning more and therefore more able to afford to drive to work?

Well, do older adults actually earn more than younger adults? Here is the distribution of worker incomes by age group, split between people who work inside and outside the City of Melbourne, for the last pre-pandemic census (2016):

Apart from the few people still working in their 90s (presumably because they are making great money), income was generally highest for people in their 40s in 2016. Older working aged adults generally earnt less! This may well reflect the higher levels of educational attainment of younger adults (as we saw in part 1).

So the idea that older adults are driving to work because they are generally earning more just isn’t supported by the evidence.

The above chart also confirms people working in the City of Melbourne were much more likely to have higher incomes.

But is there a relationship between income and mode choice? The following chart shows public transport mode shares for journeys to work by both income bands and age.

Each line is for an income band, and you can see age-based variations in PT mode share for people within each income band. The biggest age-based variations were for people on lower incomes – with younger workers much more likely to use public transport than older workers.

There was less variation across age groups in public transport mode shares for people on higher incomes, particularly those working in the City of Melbourne.

Most of the higher income bands had high public transport mode shares for journeys to work in the City of Melbourne. The exception was the top band ($3000+ per week), many of whom probably have a car and/or parking space provided by their employer. Also, over 10% of people in the top income band walked or cycled to work which might be because they can afford to live close to work.

For those who worked outside the City of Melbourne, PT mode shares were generally higher for younger workers and those on lower incomes.

Here’s another view of the same data, with income on the X-axis and different colours used for different age ranges:

On this chart you can see income not having a strong relationship with PT mode share within many age groups. For those under 30, PT mode shares generally declined with increasing income. For workers over 40, mode shares slowly went up with income in the City of Melbourne, and declined slowly with increasing income for those working outside the City of Melbourne.

Overall it looks like age probably had a stronger relationship with PT mode shares than incomes, although both factors are relevant.

Here’s a chart that simply shows journey to work mode shares by personal income (regardless of age):

However, personal income is not necessarily the best measure here to measure the impact of income. A person living alone earning $2000 per week has more to spend on their transport than a person earning $2000 per week but also supporting a family. The ABS calculates a metric known as household-equivalised income, which considers total household income in the context of household size and composition. Unfortunately household equivalised income isn’t readily available for journey to work data which includes work location, hence why the above analysis uses personal income. But it is available if I’m only concerned with where people live.

Here’s a chart showing the relationship between household-equivalised income and mode shares for people who live in Greater Melbourne:

This chart is similar to the mode share chart for personal income, but there some noticeable differences at the lower incomes – with high private mode share for those on a household equivalised income between $300 and $1000 per week.

Public transport mode shares were highest at the top and bottom of the income spectrum, and lowest for those earning $400-$499 per week.

Similarly, active transport mode share was highest for the bottom and top income bands (probably out of necessity at the bottom end, and from living in walkable and cycling-friendly suburbs at the top end), while private transport mode share showed the inverse pattern, being highest for incomes between $400 and $1000 per week.

The above data was for journeys to work, but what about other travel purposes?

VISTA data shows some similar patterns for the income/age relationships, although the survey sample size doesn’t allow for a split between travel within/outside the City of Melbourne.

PT mode share was highest for those aged 10-29 for all income bands, although the relationship with income is more mixed.

For those in their 40s and 50s, PT mode share was generally higher for those in higher income bands (with the exception of the bottom income band), which may reflect home and work locations.

Younger children had very low public transport mode shares for all income ranges – which is consistent with other findings on this blog about young families.

Here’s an alternative view of the same data with income on the X-axis and a line per age group:

For those aged 30-59 PT mode share generally increased with income (possibly related to higher incomes more likely to work in the city centre), while for those aged 10-29 it generally declined with increasing income. Again, it would appear that age has a much stronger relationship with PT mode share than household income.

Here are overall travel mode shares by income:

It’s a little hard to see, but the mode share pattern is very similar to journeys to work. PT mode shares were higher for the lowest and second highest income bands and lower at middle income bands – with the exception of the highest income band which had much higher private transport mode share.

Socio-economic advantage/disadvantage

Firstly here is the distribution of Greater Melbourne population by age across the 10 deciles for ABS’s index of socio-economic advantage and disadvantage (part of SEIFA). Those deciles are actually for the state of Victoria, and because Melbourne is relatively advantaged compared to regional Victoria, there is a skew to higher deciles. 10 is for the most advantaged areas, and 1 is the most disadvantaged.

Similar to the analysis of income, people in their 40s were more likely to live in more advantaged areas.

Here is a chart of journey to work mode shares by advantage/disadvantage, split between workers aged 20-39 and 40-69:

Somewhat similar to the pattern with income, public transport mode shares were higher for both the most advantaged and most disadvantaged, bottoming out in the third (lowest) decile. This relationship held over younger and older workers, but there was still variance within age bands. When it comes to public transport use, both age and socio-economic advantage/disadvantage were relevant factors, but again it appears that age has a stronger relationship.

As an aside – because it is interesting – here are some charts showing the interaction between socio-economic advantage/disadvantage and other factors for explaining PT mode share, starting with motor vehicle ownership rates (measured at SA1 geography):

There was a relationship between PT mode share and both socio-economic disadvantage/advantage and motor vehicle ownership (except for areas with very high motor vehicle ownership), but motor vehicle ownership appears to have a much larger impact on PT mode share.

The following chart shows home distance from the CBD had a much stronger relationship with PT mode shares than socio-economic advantage/disadvantage:

The density of central city workers also was a much stronger determinant of average public transport mode share than socio-economic advantage/disadvantage:

Occupation

How do PT mode shares vary by occupation? And could variations in the occupation mix across age groups explain variations in PT mode share across age groups?

Firstly, here is the distribution of workers by occupation (using the most aggregated occupation categories defined by ABS), age, and work location (inside v outside City of Melbourne):

There is some variation in occupation distribution across age groups, with 15-19 and 20-29 the most different with many more sales workers and labourers (noting this data excludes people who did not commute to a workplace on census day). Workers aged 30-49 were more likely to be managers or professionals than most other age groups (consistent with income data).

The next chart shows public transport mode shares for journeys to work by occupation and age, disaggregated by other major factors that I have previously found to be significant: parenting status, work location, and immigrant status:

Clerical and administrative workers and professionals generally had the highest PT mode share for all categories. Labourers, machinery operators and (professional) drivers had the lowest PT mode shares, mostly followed by community and personal service workers (many of whom might do shift work – eg aged care, policing, emergency services, hospitality). Managers had significantly lower PT mode shares than professionals – perhaps due to company subsidised cars and/or parking.

You can see a clear relationship between age and public transport mode share in all “panes” of the chart. That is – even when you control for occupation and the other factors – there were still aged-related variations in public transport mode shares. Either some other factor is at work, of age itself is directly a factor influencing mode shares.

Hours worked

Does the amount of hours people worked in a week vary by age, and does it relate to PT mode shares?

Here is the distribution of hours worked by age group:

Workers aged 30-59 were most likely to be working 35+ hours per week, with those older and younger likely to be working fewer hours. So hours worked does not have a linear relationship with age for working-aged adults, and younger adults tend to work less hours.

So what was the relationship between hours worked, age, and PT mode share? Here’s a heat map table of PT mode share by hours worked and age band:

Technical note: you might be wondering why there is a “None” row. That’s for people who worked on census day, but didn’t work any hours in the previous week, for whatever reason.

This chart shows a very clear relationship between PT mode share and age for all ranges of hours worked.

You can also see public transport mode shares were generally highest for people working “full-time” (35-40 hours) and those who didn’t work in the previous week, and were generally lower for people who worked more then 40 hours (possibly working long shifts or multiple jobs – making public transport less convenient?) or less than 35 hours (juggling part-time paid work with other commitments?).

However this didn’t hold for those aged under 30, with full-time teenage workers less likely to use public transport. We’ve already seen that teenage workers generally had lower qualifications, were less likely to work in central Melbourne, less likely to work near a train station, less likely to work somewhere with high job density, less likely to be a recent immigrant, and more likely to work in occupations with lower public transport mode share.

On the bigger question, while PT mode share was generally higher for “full-time” workers, younger adults were less likely to be working full-time. So hours worked actually works against explaining why younger adults were more likely to use public transport.

Studying

Were younger adults more likely to use PT to get to work because they were more likely to also be students?

Certainly younger adults were more likely to be studying, although this dropped to only 10% for those in their 30s:

Here are average journey to work public transport modes shares by age and student-status:

So while workers who were studying certainly had much higher public transport mode shares than those not studying, there was still a strong relationship between age and PT mode share, regardless of whether workers were also students.

Which got me thinking – we’ve learnt that recent immigrants have been predominantly younger adults, and there have been many international students in Melbourne in recent years (at least up until the pandemic). Do these factors inter-play?

Firstly, census data certainly shows that more-recent immigrants were indeed much more likely to be studying, compared to the rest of the population:

In fact, over half of immigrants living in Melbourne who arrived in Australia between the start of 2016 and the census on 9 August 2016 were studying, and more than a third who arrived in the ten years before the census were studying.

So what if we control for how recently someone immigrated to Australia?

Within most arrival year bands, PT mode shares generally declined with age (except for those under 20). So again, these factors do not explain the total variations in public transport mode share by age.

For interest, here are public transport mode shares by student-status and year of arrival into Australia:

Full-time students who also worked were more likely to use public transport to get to work, although they were overtaken by part-time students for those who arrived before 1996. Also, recent immigrants who were not studying were still much more likely to use public transport.

Summary of geographic and demographic factors influencing public transport mode shares

I’ve covered a lot of material over four long posts. So here’s a summary of what I’ve learnt about demographics and public transport mode share in Melbourne in recent pre-pandemic years:

  • Public transport mode share (of all travel) was generally highest for older teenagers, and then fell away with age for those older or younger.
  • Public transport mode share of journeys to work was a little different – peaking for those aged in the mid 20s, and was much lower for teenagers and older adults.
  • Public transport mode share was generally higher in the following circumstances – all of which are generally more common for younger adults (and many of which are closely interrelated). Most of these relationships are quite strong.
    • Geographic factors:
      • living closer to the city centre (strong)
      • living closer to a train station (strong)
      • living in areas with higher residential densities
      • working closer to the city centre (strong)
      • working closer to a train station (strong)
      • working in areas with higher job density (strong)
      • generally travelling to destinations closer to the city centre (strong)
    • Demographic factors:
      • being highly educated
      • having lower rates of motor vehicle ownership (strong)
      • not owning a driver’s licence (strong)
      • not being a parent (strong), particularly a mother
      • being an immigrant, and having more recently immigrated to Australia (strong)
      • being a student (strong)
  • However, these factors don’t seem to fully explain why there are variations in public transport mode share by age (particularly for non-parents). I’ve controlled for several combinations of the stronger factors and still found variations across age bands. There’s likely to be something else about age that influences mode choice.
  • There are other factors (all demographic) that have a relationship with public transport mode shares, but these factors did not peak for young adults, unlike public transport mode share. So they actually work against explaining higher public transport use by younger adults. These saw higher public transport mode shares being associated with:
    • both very low and high incomes (but not the highest incomes)
    • both highly socio-economically advantaged areas and highly socio-economically disadvantaged areas
    • working full-time (35-40 hours per week)
    • having a professional or administrative/clerical occupation
    • not being a labourer, machinery operator, or professional driver
  • Women were more likely than men to use public transport to get to work for most age ranges (except ages 38-48), and this seems to be at least partly related to their higher levels of education, which in turn probably explains why they are more likely to work in the city centre.

For more about factors associated with higher public transport use, see What explains variations in journey to work mode shares between and within Australian cities?

How are these factors changing over time?

Elsewhere on this blog I’ve uncovered other likely explanations for increased public transport mode share, including things such as increasing population density and employment density – see What might explain journey to work mode shifts in Australia’s largest cities? (2006-2016). However that analysis didn’t look at changes in the geography and demographics of people of different ages.

In this series I’ve confirmed some “demographic” factors that are related to public transport use that have also changed in favour of public transport use over those pre-pandemic years:

But there have been other demographic shifts that probably worked against increasing public transport mode share over the pre-pandemic years:

  • The proportion of the working population who were parents rose from 22.6% to 27.1% for those working in the City of Melbourne, and from 25.3% to 27.3% for the rest of Greater Melbourne (2006 to 2016). As an aside: there was the little change in the average age of working parents – for women it went from 38.6 years in 2006 to 39.6 years in 2016 and for men it went from 40.0 to 40.3 years.
  • The proportion of people working in the City of Melbourne who were under 40 years of age declined slightly from 58.3% to 57.2% (2006 to 2016).
  • Motor vehicle ownership rates have risen significantly for adults over 60. Or put another way, for people born before around 1950, there was almost no change in their rates of motor vehicle ownership between 2011 and 2016, despite them aging 5 years. See: How has motor vehicle ownership changed in Australian cities for different age groups?

In a future post I might look at whether there has been a shift in where younger adults live and work geographically (eg proximity to the CBD, proximity to train stations, residential densities). This would be particularly interesting for the “post-pandemic” world, however it will probably need to wait for 2026 census data.

Leave a Comment » | Melbourne, Migration, Mode share | Tagged: , | Permalink
Posted by chrisloader

Update on Australian transport trends (December 2023)

Mon 1 January, 2024

[Updated 29 March 2024: Capital city per-capita charts updated using estimated residential population data for June 2023]

What’s the latest data telling us about transport trends in Australia?

The Australian Bureau of Infrastructure and Transport Research Economics (BITRE) have recently published their annual yearbook full of numbers, and this post aims to turn those (plus several other data sources) into information and insights about the latest trends in Australian transport.

This is a long and comprehensive post (67 charts) covering:

I’ve been putting out similar posts in past years, and commentary in this post will mostly be around recent year trends. See other similar posts for a little more discussion around historical trends (December 2022, January 2022, December 2020, December 2019, December 2018).

Vehicle kilometres travelled

Vehicle and passenger kilometre figures were significantly impacted by COVID lockdowns in 2020 and 2021 which has impacted financial years 2019-20, 2020-21, and 2021-22. Data is now available for 2022-23, the first post-pandemic year without lock downs.

Total vehicle kilometres for 2022-23 bounced back but were still lower than 2018-19:

The biggest pandemic-related declines in vehicle kilometres were in cars, motorcycles, and buses:

All modes showed strong growth in 2022-23.

Here’s the view on a per-capita basis:

Vehicle kilometres per capita peaked around 2004-05 and were starting to flatline in some states before the pandemic hit with obvious impacts. In 2022-23 vehicle kilometres per capita increased in all states and territories except the Northern Territory and Tasmania.

Here is the same data for capital cities:

Cities with COVID lockdowns in 2021-22 (Melbourne, Sydney, Canberra) bounced up in 2022-23, while Brisbane and Perth were relatively flat, Adelaide was slightly up, and Darwin slightly down. All large cities are still well below 2018-19 levels, consistent with an underlying long-term downwards trend.

Canberra has dramatically reduced vehicle kilometres per capita since around 2014 leaving Brisbane as the top city.

Passenger kilometres travelled

Here are passenger kilometres travelled overall (log scale):

The pandemic had the biggest impact on rail, bus, and aviation passenger kilometres. Aviation has bounced back to pre-COVID levels while train and bus are still down (probably due to working from home patterns, reduced total bus vehicle kilometres, amongst other reasons).

Here is the same on a per-capita basis which shows very similar patterns (also a log scale):

Car passenger kilometres per capita have reduced from a peak of 13,113 in 2004 to 10,152 in 2023.

Curiously aviation passenger kilometres per capita peaked in 2014, well before the pandemic. Rail passenger kilometres per capita in 2019 were at the highest level since 1975.

Here’s total car passenger kilometres for cities:

The COVID19 pandemic certainly caused some fluctuations in car passenger volumes in all cities for 2019-20 to 2021-22. In 2022-23, Sydney and Melbourne had not recovered to pre-pandemic levels, while Perth hit a new high.

Here are per capita values for cities:

Car passenger kilometres per capita bounced back in Sydney, Melbourne, and Canberra – however most cities had 2022-23 figures that were in line with a longer-term downward trend – if you disregard the COVID years.

Public transport patronage

BITRE are now reporting estimates of public transport passenger trips (as well as estimated passenger kilometres). From experience, I know that estimating and reporting public transport patronage is a minefield especially for boardings that don’t generate ticketing transactions. While there are not many explanatory notes for this data, it appears BITRE have estimated capital city passenger boardings, which will be less than some ticketing region boardings (Sydney’s Opal ticketing region extends to the Illawarra and Hunter, and South East Queensland’s Go Card network includes Brisbane plus the Sunshine and Gold Coasts). I’ll report them as-is, but bear in mind that they might not be perfectly directly comparable between cities.

Of course bigger cities tend to generate more boardings, so it’s probably worth looking at passenger trips per capita per year:

This chart produces some unexpected outliers. Hobart shows up with very high public transport trips per capita in the 1970s, which might be relate to the Tasman Bridge Disaster which severed the bridge between 1975 and 1977 and resulted in significant ferry traffic for a few years (over 7 millions trips in 1976-77). Canberra also shows up with remarkably high trips per capita in the 1980s for a relatively small, low density, car-friendly city, but has been in steady decline since.

Canberra, Sydney, and Brisbane were seeing rising patronage per capita up to June 2019, just before the pandemic hit.

Most cities (except Darwin and Hobart), showed a strong bounce back in public transport trips per capita in 2022-23, although none reached 2018-19 levels.

There are further reasons why comparing cities is still not straight forward. Smaller cities such as Darwin, Canberra, and Hobart are almost entirely served by buses, and so most public transport journeys will only require a single boarding. Larger cities have multiple modes and often grid networks that necessitate transfers between services for many journeys, so there will be a higher boardings to journeys ratio. If a city fundamentally transforms its network design there could be a sudden change in boardings that doesn’t reflect a change in mode share.

Indeed, here is the relationship between population and boardings over time. I’ve drawn a trend curve to the pre-pandemic data points only (up to 2019).

Larger cities are generally more conducive to high public transport mode share (for various reasons discussed elsewhere on this blog) but also often require transfers to facilitate even radial journeys.

So boardings per capita is not a clean objective measure of transit system performance. I would much prefer to be measuring public transport passenger journeys per capita (as opposed to boardings) which might overcome the limitations of some cities requiring transfers and others not.

The BITRE data is reported as “trips”, but comparing with other sources it appears the figures are boardings rather than journeys. Most agencies unfortunately don’t report public transport journeys at this time, however boardings to journeys ratio could be estimated from household travel survey data for some cities.

Public transport post-pandemic patronage recovery

I’ve been estimating public transport patronage recovery using the best available data for each city (as published by state governments – unfortunately the usefulness and resolution of data provided varies significantly, refer: We need to do better at reporting and analysing public transport patronage). This data provides a more detailed and recent estimate of patronage recovery compared to 2019 levels. Here’s the latest estimates at the time of preparing this post:

Perth seems to be consistently leading Australian and New Zealand cities on patronage recovery, while Melbourne appears to be the laggard in both patronage recovery and timely reporting. For more discussion and details around these trends see How is public transport patronage recovering after the pandemic in Australian and New Zealand cities?.

[refer to my twitter feed for more recent charts]

Passenger travel mode split

It’s possible to calculate “mass transit” mode share using the passenger kilometres estimates from BITRE (note: I use “mass transit” as BITRE do not differentiate between public and private bus travel):

Mass transit mode shares obviously took a dive during the pandemic, but have since risen, although not back to 2019 levels – presumably at least partly because of working from home.

The relative estimates of share of motorised passenger kilometres are quite different to the estimates of passengers trips per capita we saw just above. Canberra is much lower than the other cities, and Brisbane and Melbourne are closer together. The passenger kilometre estimates rely on data around average trip lengths (which is probably not regularly measured in detail in all cities), while the passenger boardings per capita figures are subject to varying transfer rates between cities. Neither are perfect.

So what else is there? I have been looking at household travel survey data to also calculate public transport mode share, but I am getting unexpected results that are quite different to BITRE estimates (especially Melbourne) and with unexpected trends over time (especially Brisbane), so I’m not comfortable to publish such analysis at this point.

What would be excellent is if agencies published counts of passenger journeys (that might involve multiple boardings), so we could compare cities more readily.

Rail Passenger travel

Here’s a chart showing estimates of annual train passenger kilometres and trips.

All cities are bouncing back after the pandemic.

Note there are some variances between the ranking of the cities – particularly Perth and Brisbane (BITRE have average train trip length in Brisbane at around 20.3 km while Perth is 16.3 km).

Here’s rail passenger kilometres per capita, but only up to 2021-22:

Bus passenger travel

Here’s estimates of total bus travel for capital cities:

And per capita bus travel up to 2021-22:

Note that Melbourne has the second highest volume of bus travel (being a large city), but the lowest per-capita usage of buses, primarily because – unlike most other cities – trams perform most of the busy on-street public transport task in the inner city. It probably doesn’t make sense to directly compare cities for bus patronage per capita, and indeed I won’t show such figures for the other public transport modes.

Darwin had elevated bus passenger kilometres from 2014 to 2019 due to bus services to a resources project (BITRE might not have counted these trips as urban public transport).

Ferry passenger travel

Sydney ferry patronage has almost recovered to pre-pandemic levels, while Brisbane’s ferries have not (as at 2022-23).

Light rail / tram passenger travel

Sydney light rail patronage is now growing strongly – after two new lines opened a few months before the pandemic hit.

Road deaths

In recent months there has been an uptick in road deaths in NSW and SA. Victorian road deaths dropped during the pandemic but are back to pre-pandemic levels.

It’s hard to compare total deaths between states with very different populations, so here are road deaths per capita, for financial years:

There is naturally more noise in this data for the smaller states and territories as the discrete number of trips in these geographies is small. The sparsely populated Northern Territory has the highest death rate, while the almost entirely urban ACT has the lowest death rate.

Another way of looking at the data is deaths per vehicle kilometre:

This chart is very similar – as vehicle kilometres per capita haven’t shifted dramatically.

Next is road deaths by road user type, including a close up of recent years for motorcycles, pedestrians, and cyclists. I’ve not distinguished between drivers and and passengers for both vehicles and motorcycles.

Vehicle occupant fatalities were trending down until around 2020. Motorcyclist fatalities have been relatively flat for a long time but have risen slightly since 2021.

Pedestrian fatalities were trending down until around 2014 and have been bouncing up and down since (perhaps a dip associated with COVID lock downs).

Cyclist fatalities have been relatively flat since the early 1990s (apart from a small peak in 2014).

It’s possible to distinguish between motorcycles and other vehicles for both deaths and vehicle kilometres travelled, and the following chart shows the ratio of these across time:

The death rate for motorcycle riders and passengers per motorcycle kilometre was 38 times higher than other vehicle types in 2022-23. The good news is that the death rate for other vehicles has dropped from 9.8 in 1989-90 to 2.7 in 2022-23. The death rate for motorcycles was trending down from 1991 to around 2015 but has since risen again in recent years.

Freight volumes and mode split

First up, total volumes:

This data shows a dramatic change in freight volume growth around 2019, with a lack of growth in rail volumes, a decline in coastal shipping, but ongoing growth in road volumes. Much of this volume is bulk commodities, and so the trends will likely be explained by changes in commodity markets, which I won’t try to unpack.

Non-bulk freight volumes are around a quarter of total freight volume, but are arguably more contestable between modes. They have flat-lined since 2021:

Here’s that by mode split:

In recent years road has been gaining mode share strongly at the expense of rail. This is a worrying trend if your policy objective is to reduce transport emissions as rail is inherently more energy efficient.

Air freight tonnages are tiny in the whole scheme of things so you cannot easily see them on the charts (air freight is only used for goods with very high value density).

Driver’s licence ownership

Here is motor vehicle licence ownership for people aged 15+ back to 1971 (I’d use 16+ but age by single-year data is only available at a state level back to 1982). Note this includes any form of driver’s licence including learner’s permits.

Technical note: the ownership rate is calculated as the sum of car, motorbike and truck licenses – including learner and probationary licences, divided by population. Some people have more than one driver’s licence so it’s likely to be an over-estimate of the proportion of the population with any licence.

Unfortunately data for June 2023 is only available for South Australia, Western Australia and Victoria, so we don’t know the latest trends in all states. South Australia and New South Wales regrettably appear to have recently stopped publishing useful licence holder numbers.

2023 saw a decline in licence ownership in the three states that reported. 2022 was a mixed bag with some states going up (NSW, South Australia, Tasmania), many flat, and the Northern Territory in decline.

Licence ownership rates have fluctuated in many states since the COVID19 pandemic hit, most notably in Victoria and NSW which saw a big uptick in 2021.

The data series for the ACT is unusually different in trends and values – with very high but declining rates in the 1970s, seemingly elevated rates from 2010 to around 2018, followed by a sharp drop. BITRE’s Information Sheet 84 (published in 2017) reports that ACT licences might remain active after people leave the territory (e.g. to nearby parts of NSW) because of delays in transferring their licences to another state, resulting in a mismatch between licence holder counts and population. However, New South Wales requires people to transfer their licence within 3 months of moving there, and other states likely do also. But that requirement might be new, changed, and/or differently enforced over time (please comment if you know more).

Here’s the breakdown of reported licence ownership by age band for the ACT:

Many age bands exceed 100 (more licence holders than population) and there are some odd kinks in the data around 2015-2017 for all age bands (especially 70-79). I’m not sure that it is plausible that licencing rates of teenagers might have plummeted quite so fast in recent years. I’m inclined to treat all of this ACT data as suspect, and I will therefore exclude the ACT from further charts with state/territory disaggregation.

Here’s licence ownership by age band for Australia as a whole (to June 2022):

Between 2021 and 2022 ownership rates for 16-24 year-olds fell slightly, while ownership rates continued to rise for older Australians (quite dramatically for those 80 and over, mostly due to NSW, see below).

Let’s look at the various age bands across the states:

Victoria saw a sharp decline in Victoria to June 2020, followed by a bounce back to a higher rate in 2021. The pandemic has also been associated with increased rates in South Australia, Tasmania, and New South Wales (although it dropped again in 2022). Western Australia and the Northern Territory have much lower licence rates, likely due to different eligibility ages for learner’s permits.

For 20-24 year olds the pandemic caused big increases in the rate of licence ownership in most states, however Victoria, South Australia, and Western Australian appear to have peaked. Licence ownership among 20-24 year olds was still surging in Tasmania up to June 2022.

Similar patterns are evident for 25-29 year olds:

One trend I identified a year ago was that the increasing rate of licence ownership seemed to largely reflect a decline in the population in these age bands during the pandemic period when temporary migrants were told to go home, and immigration almost ground to a halt. Most of the population decline was those without a licence, while the number of licence holders remained fairly steady.

New South Wales appears to follow this pattern, although there was strong growth in licence holders in 2021 and 2022 for teenagers.

Victoria saw a decline in licence holders in 2020 (likely teenagers unable to get a learner’s permit due to lockdowns), but the number of teenage licence holders has since grown. While for those in their 20s, the increase in the licence ownership rate is mostly explained by a loss of population without a licence:

Queensland has experienced strong growth in licence holders at the same time as a decline in population aged 20-29 in 2022. This might be the product of departing temporary immigrants partly offset by interstate migration to Queensland.

To illustrate how important migration is to the composition of young adults living in Australia, here’s a look at the age profile of net international immigration over time for Australia:

For almost all years, the age band 20-24 has had the largest net intake of migrants. This age band also saw declining rates of driver’s licence ownership – until the pandemic, when there was a big exodus and at the same time a significant increase in the drivers licence ownership rate. The younger adult age bands have seen a surge in 2022-23, and in the three states with data the licence ownership rates have dropped (as I predicted a year ago).

Curiously as an aside, 2019-20 saw a big increase in older people migrating to Australia (perhaps people who were overseas returning home during the pandemic lock downs). But then big negative numbers were seen in 2020-21, and since then there has continued to be net departures in 65+ age band.

For completeness, here are licence ownership rate charts for other age groups:

There appear to be a few dodgy outlier data points for the Northern Territory (2019) and South Australia (2016).

You might have noticed some upticks for New South Wales in 2022, particularly for those aged over 80. I’m not sure how to explain this. Here’s all the age bands for NSW:

Here’s Victoria, which includes data to 2023:

For completeness, here are motor cycle licence ownership rates:

Motorcycle licence ownership per capita has been declining in most states and territories, except Tasmania. I suspect dodgy data for New South Wales 2016, and Tasmania 2019.

Car ownership

Thankfully BITRE has picked up after the ABS terminated it’s Motor Vehicle Census, and are now producing a new annual report Motor Vehicle Australia. They’ve tried to replicate the ABS methodology, but inevitably have come up with slightly different numbers in different states for different vehicle types for 2021 (particularly Tasmania). So the following chart shows two values for January 2021 – both the ABS and BITRE figures so you can see the reset more clearly. I suggest focus on the gradient of the lines between surveys and try to ignore the step change in 2021.

Let’s zoom in on the top-right of that chart:

All except South Australia, Tasmania, and ACT showed a decline in motor vehicle ownership between January 2022 and January 2023. This might reflect the recent return of “recent immigrants” (as I predicted a year ago).

Tasmania had a large difference in 2021 estimates between ABS and BITRE that seems to be closing so who knows what might be going on there.

Several states appear to have had peaks – Tasmania in 2017, Western Australia in 2016, and ACT in 2017.

Vehicle fuel types

Petrol vehicles still dominate registered vehicles, but are slowly losing share to diesel:

Can you see that growing slither of blue at the top, being electric vehicles? Nor can I, so here’s the share of registered vehicles that are fully electric (battery or fuel cell, but not hybrids):

The almost entirely urban Australian Capital Territory is leading the country in electric vehicle adoption, while the Northern Territory is the laggard.

Motor vehicle sales

Here are motor vehicle sales by vehicle type:

The trend to larger and heavier vehicles (SUVs) might make it harder to bring down transport emissions (and perhaps reduce road deaths).

Electric vehicle sales are small but currently growing fast in volume and share:

[Updated 7 January 2024:] I’ve included calendar year 2023 sales from FCAI (their 2022 figures were very close to BITRE’s) and calculated the percentage of sales that were battery electric based on FCAI/ABS totals.

Transport Emissions

Transport now makes up 19% of Australia’s greenhouse gas emissions (excluding land use), up from 15% in 2001:

You can see that Australia’s total emissions excluding land use have actually increased since 2001. Emissions reductions in the electricity sector have been offset by increases in other sectors, including transport.

Australia’s transport rolling 12 month emissions dropped significantly with COVID lockdowns, but are bouncing back strongly:

Here are seasonally-adjusted quarterly estimates, showing September 2023 emissions back to 2018 levels:

Transport emissions are around 34% higher in September 2023 than in September 2001, the second highest growth of all sectors since that time:

Here are annual Australian transport emissions since 1975:

And in more detail since 1990:

The next chart shows the growth trends by sector since 1990:

Aviation emissions saw the biggest dip during the pandemic but are now back above 2018 levels.

Here are per capita emissions by transport sector (note: log scale used on Y-axis):

Truck and light commercial vehicle emissions per capita have continued to grow while many other modes have been declining, including a trend reduction in car emissions per capita since around 2004.

Next up, emissions intensity (per vehicle kilometre):

I suspect a blip in calculation assumptions in 2015 for bus and trucks.

Emissions per passenger kilometre can also be estimated:

Car emissions have continued a slow decline, but bus and aviation emissions per passenger km increased in 2021, presumably as the pandemic reduced average occupancy of these modes.

Aviation was reducing emissions per passenger kilometre strongly until around 2004, but has been relatively flat since, and the 2022-23 value is above 2004 levels. This seems a little odd as newer aircraft are generally more energy efficient.

Transport consumer costs

The final category for this post is the real cost of transport from a consumer perspective. Here are headline real costs (relative to CPI) for Australia, using quarterly ABS Consumer Price Index data up to September 2023:

Technical note: Private motoring is a combination of factors, including motor vehicle retail prices and automotive fuel.

The cost of motor vehicles was in decline from around 1995 to 2018 and has been stable or slightly rising since then. Automotive fuel has been volatile, which has contributed to variations in the cost of private motoring.

Urban transport fares (a category which unfortunately blends public transport and taxis/rideshare) have increased faster than CPI since the late 1970s, although they were flat in real terms between 2015 and 2020, then dropped in 2021 and 2022 in real terms – possibly as they had not yet been adjusted to reflect the recent surge in inflation. They picked up slightly in 2023.

The above chart shows a weighted average of capital cities, which washes out patterns in individual cities. Here’s a breakdown of the change in real cost of private motoring and urban transport fares since 1972 by city (note different Y-axis scales):

Technical note: The occasional dips in urban transport fares value are likely related to periods of free travel – eg May 2019 in Canberra.

The cost of private motoring moves much same across the cities.

Urban transport fares have grown the most in Brisbane, Perth, and Canberra – relative to 1972. However all cities have shown a drop in the real cost of urban transport fares in June 2022 – as discussed above.

If you choose a different base year you get a different chart:

What’s most relevant is the relative change between years – e.g. you can see Brisbane’s experiment with high urban transport fare growth between 2009 and 2017 in both charts.

Melbourne recorded a sharp drop in urban transport fares in 2015, which coincided with the capping of zone 1+2 fares at zone 1 prices.

And that’s a wrap on Australian transport trends. Hopefully you’ve found this useful and/or interesting.

2 Comments | Australian Cities, Brisbane, Car ownership, drivers license, Freight, Greenhouse Gas Emissions, Melbourne, Migration, Mode share, Mode shift, Perth, Pricing, Road safety, Road Traffic, Sydney, Vehicle sales | Tagged: , , | Permalink
Posted by chrisloader

How did Perth’s CBD end up with 19% more private transport commuters in 2021?

Sat 3 June, 2023

ABS census data tells us that Perth’s CBD experienced a massive 19% jump in the number of private transport commuter trips between 2016 and 2021. That’s over 5000 more journeys – mostly as car drivers – and is quite likely to have made traffic congestion worse.

So how did that happen? Where were these extra commuters travelling to? Were there particular changes in the modal mix in different parts of the CBD? Was this growth enabled by a big increase in car parking capacity? And what has been happening to car park pricing?

This post digs a little deeper following my last post that explored the impact of COVID on journey to mode shares in Australian cities in 2021.

A quick recap of overall changes in journey to work in the Perth CBD

Here’s the volume of Perth CBD commuters by main mode, including working at home in 2011, 2016, and 2021:

See my last post for my definition of the Perth CBD. A trip involving any public transport is classed as public, a trip that involves only walking or cycling is classed as active, and any other form of travel is classed as private.

At the 2021 census, Perth was COVID-free with relatively few restrictions on intra-state movement or activity.

Total employment in the CBD grew by a massive 26% from 82,214 in 2016 to 103,944 in 2021. Private transport trips increased by 19%, but because this was less growth than overall employment growth there was actually a commuter mode shift away from private transport of 1.6% (from 36.5% to 34.9%).

The biggest increase in CBD worker volumes was in those who worked at home.

Public transport commuting to the CBD increased by only 85 trips between 2016 and 2021, but still accounted for more trips than private transport.

LATE EDIT: It’s just come to my attention that the Fremantle train line was closed on the day of the 2021 census (10 August), which will have suppressed public transport mode share in the western suburbs.

My last post concluded there was likely a significant mode shift from public transport to remote working. There was some mode shift away from public transport and towards remote working and private transport for some middle age groups, although some of this shift is likely to be a normal trend seen as people age (and become parents). I was unable to identify occupations that saw a substantial mode shift from public transport to private transport, although some occupations saw a lot more private transport growth than public transport growth.

This post now takes that analysis a bit further by looking at spatial variations in the modal mix by workplace location.

Where were the extra private transport commuters working?

Here’s the change in private commuter trips for each destination zone around the Perth CBD:

Note: the circles aren’t always drawn in the middle of each destination zone, aren’t intended to highlight any particular location within each zone, and may not be representative of major car park locations.

There were both increases and decreases around the CBD. I’m going to focus in more detail on the following high-growth destination zones that I’ve arbitrarily named by a dominant building, precinct, or bordering streets:

Most of the zones that saw a big increase in private transport commuter trips also saw a big increase in public transport trips.

Capital Square saw jobs more than triple between 2016 and 2021 as a major new development was completed (including the new Woodside headquarters). It had the largest increase in private transport trips, but even more new trips were by public transport. The development includes five levels of car parking on a fairly large site (at least 659 car parks according to some planning documents). It also saw the largest growth in active transport commuter trips of any destination zone in the Perth CBD.

The zone I have labelled Kings Square (which includes Perth Arena and the new Shell and HBF buildings) saw only slightly more new public transport trips than new private transport trips, despite Perth train station being inside the zone.

The Royal Perth Hospital zone had almost all of its net job growth accounted for by private transport, some of which would have been shift workers. This is consistent with my last post that found a large increase in private transport commuters under the “carers and aids” and “health and welfare support” occupation groups. The hospital is directly adjacent to McIver train station, served by multiple train lines.

One mixed-use block between Terrace Road, Victoria Avenue, Adelaide Terrace, and Hill Street had an increase in private trips and a decrease in public trips. It’s difficult to speculate why this occurred due to the diverse mix of land uses.

The Elizabeth Quay zone saw more growth in private trips than public trips, despite being immediately adjacent to Elizabeth Quay train station. I’ve not been able to identify any large new car parks in the area. Car parks immediately north of the development site were offering $25 all-day car parking at the time of writing which I suspect the average employee might not consider particularly affordable.

The Brookfield Place and Central Park zones mostly saw a big increase in the number of remote workers.

Outside the CBD, the biggest decline in private trips was -1863 in a zone near West Leederville station where the Princess Margaret Hospital for Children closed in 2018 (replaced by the Perth Children’s Hospital in Nedlands).

Where was there a shift from public to private transport?

The following map shows destination zones where there was a decline in public transport trips and an increase in private transport trips (no zones showed the opposite flow):

Just under than half of the destination zones around the Perth CBD saw some sort of net shift to private transport, and most of these were very small numbers. In total these zones account for 492 trips within for my definition of the Perth CBD, about 0.5% of all workers. A net shift from public transport explains less than 10% of the total increase in private transport commuter trips.

This is consistent with analysis in my last post (which disaggregated by birth cohorts and occupations) and again suggests the growth in private trips was broadly in line with the overall growth in CBD employment. It also fits with the hypothesis that the biggest mode shift was from public transport to remote working.

Another way of analysing mode shift is to look the percentage change in private transport mode share by zone:

In the western part of the main CBD area there were many zones with a large mode shift away from private transport, and many of these zones had high employment density.

In fact, the next chart shows how employment density and private transport mode share changed between 2016 and 2021 in the Perth CBD, with the thin end of each ‘comet’ being 2016 and the thick end being 2021 (I’ve arbitrarily named several more destination zones based on major landmarks or surrounding streets).

Note: some destination zones include significant land that is not built up (eg parkland, water bodies, and/or freeway interchanges) and these will have understated employment density. This incudes Convention/Exhibition and Elizabeth Quay.

The dominant pattern is that the zones with high and increasing employment density mostly saw declining private transport mode share, although the “Terrace / Hill / Victoria” block was a standout exception having increasing employment density and increasing private mode share.

How did the CBD absorb so many more car commuters?

It’s hard to know for sure but some possible explanations include:

  • New car parking supply: I’ve already mentioned the Capital Square development that included five levels of parking. Locals might know of other new large CBD car parks, but I’ve struggled to identify any large car parks on Parkopedia or Google Maps that didn’t already exist in 2016. Many new office buildings don’t appear to include large car parks.
  • Perth was in a “mining downturn” in 2016: The Perth CBD only added 1.7k jobs between 2011 and 2016, and there was no significant increase in private commuter trips. According to a Property Council report in August 2016, Perth was experiencing very high office vacancy rates (21.8%) and had been experiencing a decline in office space demand that started around 2013. So it seems quite plausible that car parking supply grew between 2011 and 2016, but commuter parking demand only grew strongly after 2016.
  • Reduced short-term parking demand? Perhaps there has been a decline in demand for short-term parking (through the normalisation of online business meetings) enabling more all-day parking. But I’m just speculating.

Someone reading this from the parking industry might be able to share some insights (please add comments).

What’s been happening to Perth CBD car parking prices?

Like Sydney and Melbourne, Perth has a CBD parking levy – an annual fee collected by government per space. Here’s what’s been happening to the levy prices in real terms:

The parking levy increased substantially in real terms in 2010 and again between 2014-2016, but in recent years has not been keeping up with inflation. Between 2016 and 2021 there was almost no real change in the levy.

So what’s been happening to car park prices?

The City of Perth itself operates a large number of CBD car parks and in 2021/22 parking revenue accounted for 36% of its total income (source: budget 2022-23).

Thanks to the incredible resource that is the Wayback Machine, I’ve been able to dig out prices at their CBD car parks right back to 2001-02. For the sake of manageable analysis I’ve focussed on four relatively large central CBD car parks – Concert Hall (399 spaces), Convention Centre (1428 spaces), Elder Street (1052 spaces) and Pier Street (680 spaces). Here’s how those prices have changed over time, in nominal and real terms:

The 2010 and 2015 jumps in the pricing levy were clearly reflected in retail parking prices.

In real terms, parking prices peaked around 2015-2017 and have been in decline since then. Prices for several car parks were cut substantially in 2017/18 – perhaps as a belated response to a reduction in office commuter demand during the mining downturn. Then parking prices were frozen from 2019 to 2022 – presumably due to the pandemic.

So despite the massive increase in CBD parking demand, the City of Perth reduced – rather than increased – all-day parking prices, and so has probably also missed out on significant additional revenue. This has arguably helped facilitate the big increase in commuter traffic volumes, along with the likely associated urban amenity impacts of more traffic in the CBD.

The City of Perth is a democratic local government so it’s probably not going to behave in an entirely economically rational way when it comes to price setting. Prices are also locked in for each financial year so are much less dynamic. So what have commercial parking operators been doing?

Unfortunately I’ve not been able to use the Internet Archive to find historical commercial car parking prices in the Perth CBD back to 2016. What I can tell you is that “flexi” online parking at the Wilson Parking run Central Park car park has risen from $19 in October 2021 to $26 in May 2023 – suggesting commercial operators are not afraid to change their pricing. That said, the Kings Complex car park (517 Hay Street, near Pier Street) has had no increase in its online daily rate between October 2021 and May 2023 ($18).

So what is Perth’s parking policy?

The current Perth parking policy (2014) states:

“This policy recognises that vehicular access to, from and within central Perth is a critical element in ensuring its continued economic and social viability. It also continues to recognise the need to preserve and enhance the city’s environment. The policy aims to address these needs by supporting the provision of a balanced transport network in order to manage congestion and provide for the efficient operation of the transport network to, from and within the city centre.”

I suspect the term “balanced transport” is indicative of not trying to shift travel towards more sustainable, non-car modes. And I guess it would also be hard for the City of Perth to start discouraging something that generates more than one third of its annual revenue. Although an increase in prices might increase revenue, even if it reduces demand.

Furthermore, the Western Australian government is also continuing to widen Perth’s freeways, in the hope this might reduce traffic congestion. I’m not sure many cities have succeeded with such strategies, but good luck Perth!

Finally…

Wasn’t Perth public transport patronage below pre-pandemic levels in 2021?

I noted above that there were just 85 additional public transport commuters to Perth’s CBD in 2021 compared to 2016. But Perth’s overall public transport patronage in August 2021 was around 22%* below that in August 2016. If the number of CBD public transport commuters didn’t decline, the overall patronage decline must represent a mode shift away from public transport for trips to other destinations and/or for purposes other than travelling to work (and/or a decline in the number of such trips made by any mode).

*August 2016 had one more school weekday and one fewer Sunday than August 2021 which means we cannot directly compare total monthly patronage of the two months but they will be fairly close. It would be much cleaner to compare average school weekday patronage figures between months and years, but unfortunately few agencies publish such numbers (Victoria does now).

1 Comment | Employment density, Mode share, Mode shift, Perth, Pricing, Working at home | Tagged: , , , | Permalink
Posted by chrisloader

What can the 2021 census tell us about commuting to work in Australia’s big CBDs during the COVID19 pandemic?

Sun 2 April, 2023

Note: Since publishing this post, it has come to my attention that Perth’s Fremantle train line was closed on census day in 2021, which may have impacted mode shares in Perth.

The bustling Central Business Districts (CBDs) of Australia’s biggest cities were the powerhouses of the Australian economy, underpinned by public transport networks that delivered hundreds of thousands of commuters each weekday. But the COVID19 pandemic significantly disrupted CBD commuting. Working remotely from home became not just acceptable, but temporarily mandatory, and public transport patronage crashed during lockdowns.

So what might be the new normal in a post-pandemic work for commuting to our CBDs? Will people shift from public to private transport, driving up traffic congestion? How many – and what sorts of people – might work from home?

This post will try to shed some light on those questions by examining what the 2021 Australian census can tell us about how travel to our CBDs altered during the COVID19 pandemic, particularly the differences between locked-down and COVID-free cities. I’ll look at patterns and trends by age, occupation, and commuting distance. I’ll finish with a look at recent transport indications in Melbourne.

As a transport planner, I’m particularly interested in CBDs as there is a significant contest for market share between public and private transport. Before the pandemic, public transport dominated commuter mode share in the biggest CBDs, and CBDs make up a significant share of all public transport commuter trips.

Reminder: what was happening on Census day 2021

Melbourne and Sydney were in “lockdown” with workers required to work from home if possible. Brisbane was just out of lockdown, and the other cities were pretty much COVID-free, although Adelaide had experienced a short lockdown in July 2021. Here’s a summary of some key metrics (CBD office occupancy data sourced from the Property Council):

*The Property Council reported a figure of 60% for August 2021, but this would have been illegal on 10 August as there was a 50% capacity limit just after lockdown. We don’t know the exact dates when the office occupancy survey was conducted, I can only assume later in that month when restrictions were eased. 47% of CBD employees reported working remotely on census day.

What is a Central Business District?

I think of Central Business Districts as the civic, commercial, and business centre of a city, generally characterised by an area dense employment. Unfortunately the ABS’s SA2 boundaries don’t really align with these areas – especially Perth (pre 2021) and Adelaide where the SA2s covering the CBD also included areas of single-storey semi-detached housing.

So for this analysis I’ve created my own CBD boundaries for Australia’s five largest cities. I’ve selected a set of destination zones that were relatively dense in 2021. I’ve tried for reasonably smooth boundaries, and have tried to avoid under-developed areas that might have cheaper car parking. I’ve then created equivalent sets of 2011 and 2016 destination zones – as similar as possible to the 2021 boundary – with the one exception of the Melbourne CBD from which I have excluded south-western parts of Docklands in 2011 due to low employment densities in that year (much of the land was yet to be developed and instead occupied by surface car parking).

Here are maps of these CBD areas. I’ve transparently shaded the CBD for each census year in a different colour which mostly overlap to show dark green. Purple areas are where boundaries are not identical for all years.

Here are the mode splits for those CBD areas, including those who worked at home:

As you would expect, working at home dominated in locked-down Sydney and Melbourne in 2021, but was also quite common in Brisbane and Adelaide. In COVID-free Perth, working at home only accounted for 15.5% of CBD employees with the other 84.5% attending their workplaces on census day.

Public transport mode shares increased between 2011 and 2016 in all CBDs except Brisbane, but then in 2021 there was a significant shift away from all travelling modes to working at home in all cities.

The working at home share may include people who routinely work from their home in a CBD area. To get some idea about these numbers, I’ve split the worked at home share for 2021 into those who lived inside and outside the CBD:

Only a tiny share of CBD workers worked at home and also lived within the CBD. Some of these will have been working remote from their regular workplace and others will have been routinely working at home (I could try to split these apart with deeper analysis but it doesn’t seem worthwhile with such small numbers).

How did working at home vary by age of CBD workers?

A really interesting finding here is that working at home peaked for those in their early 40s in almost all cities – an age with plenty of parents with child caring responsibilities. Teenagers and those in their early 20s were the least likely to work from home, probably because they were more likely to be in jobs not amenable to working at home (eg retail and hospitality). But perhaps also some younger white collar workers may have preferred to build professional networks by being present in the CBD.

In Adelaide and Perth there was a definite trend that younger commuters were more likely to use public transport, and older commuters more likely to use private transport. This was consistent with all cities in earlier censuses (although this was not the case in Brisbane in 2021).

This got me thinking. The COVID19 pandemic and ~18 month border closure surely had some impact on the age distribution of the CBD workforce.

Indeed, here’s a look at the age composition of CBD workers over time:

Between 2011 and 2016 all cities showed a shift in the age composition towards older employees, perhaps as the cohorts of more highly educated Australians got older, people stay in the workforce until later in life, and/or other changing demographics of our cities.

But in most cities (perhaps not Adelaide) there seemed to be a larger shift towards older workers between 2016 and 2021. I suspect this will reflect fewer recent skilled migrants and international students in 2021.

We know from other analysis (see: Why are younger adults more likely to use public transport? (an exploration of mode shares by age – part 1)) that younger adults generally have higher rates of public transport use, so the shift in demographics might be favouring a mode shift away from public transport – all other things being equal (which of course they are not). There was mostly a shift towards public transport for CBD workers between 2011 and 2016, so other factors must have had an overriding impact.

How did working at home vary by CBD worker occupation?

I’ve sorted the occupations by overall worked at home share, which was similar across the cities. This list roughly sorts from blue collar to white collar and I haven’t seen any surprises in this chart. I’ll come back to occupations shortly.

How did working at home vary by distance from work?

The following chart shows working at home rates by approximate distance from home to work, for central area workers.

Technical note: For this analysis I’ve used journey to work data disaggregated by home SA2, work SA2, and whether or not workers worked at home. I’ve defined central city areas as collections of SA2s (so different boundaries to my CBD areas). Distances between home and work SA2s are calculated on SA2 centroids then aggregated to ranges.

In all cities there was a general trend to higher rates of working at home for people living further from the central city, although Sydney rates of remote working were high at all distances (the strictness of lockdown probably overriding the impact of commuting distance). This pattern in other cities likely reflects the increased incentive to work from home when you have a longer commute to avoid.

Did COVID lead to a mode shift from public to private transport?

Some transport planners have been concerned that COVID19 might lead to a permanent mode shift from public transport to private transport, probably for two reasons:

  1. A reduction in total commuter demand might make private transport slightly more competitive (eg if parking costs reduce), resulting in a different mode split equilibrium. We can only really test this aspect in Perth and Adelaide as they were COVID-free but with a small but significant share of workers working remotely.
  2. People have a fear of becoming infected by COVID19 on public transport and therefore switch to private transport (although COVID can also spread in workplaces of course). It’s a bit harder to test this as Sydney and Melbourne were in lockdown (movement restrictions no doubt had much more impact than infection fear). Perth, Canberra, and Adelaide were COVID-free, although there might have been a some fear of undetected COVID circulating – and indeed that was probably happening in Canberra which went into lockdown a few days after the census. Brisbane was just out of lockdown with some restrictions remaining so infection fear may have been higher than in Perth and Adelaide. However the level of infection fear in these “COVID-free” cities in 2021 would certainly be less than that in 2022 and 2023 where COVID is known to be circulating in the community (although there’s since been plenty of opportunity to get vaccinated).

The hypothesis I want to test for COVID-free cities is that there was a mode shift from public transport to private transport, alongside the overall mode shift to working at home.

Okay, so what can census data tell us?

Unfortunately it’s almost impossible to know the behaviour change of individuals who had the same home and work locations in 2016 and 2021 without another data source. I don’t have access to the census longitudinal dataset and that might not even have a sufficient sample of CBD workers who didn’t change home or work location between the two censuses.

But I can explore this question by looking at the changes in overall volumes and mode shares, and then drilling down into different age and occupation cohorts.

How much mode shift was there between travelling modes?

Let’s first look at the overall change in mode split of people who did commute to CBDs in the last three-four censuses (I have 2006 data for Melbourne and Sydney, but only for those who travelled):

On this split, all cities saw a significant mode shift to private transport travel in 2021. The smallest was 4% in COVID-free Perth, while the largest was 18% in locked-down Sydney.

To explore further, here are the total volumes of commuters to CBDs for each mode, across the last three-four censuses:

In the locked-down cities there was a substantial drop in both public and private transport commuters in 2021, although a larger proportional drop for public transport (in line with mode shifts seen above).

But I’m particularly interested in the then COVID-free cities of Adelaide and Perth, that exhibited COVID-free travel behaviour. Let’s start with a deep dive for Perth.

How did commuting behaviour change for Perth CBD commuters between 2016 and 2021?

The overall CBD workforce increased substantially from 83.0k to 105.7k, and this increase saw 5,164 more private transport trips, and about 85 more public transport trips. But the biggest net increase was for working at home.

If we include remote working, the overall mode share of private transport declined by 1.6% from 36.5% to 34.9%. Any mode shift from public transport to private transport was swamped by the overall shift to working remotely.

But does the overall pattern mask some mode shifts within age or occupation groups?

Did some age groups shift modes more than others? Initially for this analysis I started to look at the change in modal mix by five year age group, but of course the people within these 5 year age bands entirely change between censuses (that are held five years apart), so that wouldn’t be measuring behaviour change of a similar group of people.

Instead I’ve looked at the change in modal mix by approximate birth year cohorts (we only know people’s age in August, so the birth year groups are approximate – for example someone aged 25 at the 2021 census could have been born anytime between 11 August 1995 and 10 August 1996, but I’ve allocated them to the 1996 to 2000 cohort).

Here is the net change in volume of Perth CBD workers by birth year cohort and commuter mode (I’ve included the age of this cohort in 2021 at the bottom of the chart for reference).

As you would expect, people aged in their 20s in 2021 made up a significant share of new CBD employees, and workers aged 60+ in 2021 (55+ in 2016) had a net reduction as many went into retirement.

Public transport had the largest share of net new trips for those aged 20-24 in 2021, although a substantial share also travelled by private transport. There was a more even split of net new trips for those aged 25-29 in 2021.

There was also substantial employee growth for people aged 30+ in 2021 (unlike in 2016), and for those aged 30-54 in 2021 the biggest change was a net increase in working at home.

There were increases in private transport use and decreases in public transport use for those aged 30 to 54 in 2021. This was a net 2270* commuters – about 2.1% of the overall CBD workforce (*summing the absolute values of the smaller of the public or private transport shift). But the overall private transport mode shift was -1.6% so changes in other age groups (particularly young adults) washed out all of this shift of middle-aged workers.

Was this mode shift for middle aged workers something to do with COVID, or was it something that was destined to happen anyway? On this blog I’ve explored the relationship between age and public transport mode share in great detail, and there’s certainly a pattern of decline with age, particularly as people become parents. See: Why are younger adults more likely to use public transport? (an exploration of mode shares by age) – part 1, part 2, and part 3.

What about mode changes for different occupations? Here’s a look at commuter volume changes by mode and occupation for Perth’s CBD:

The Perth CBD put on a lot more professionals and specialist managers between 2016 and 2021, and working at home accounted for most of this net growth. The number of new public and private trips varied considerably by category but private transport growth outnumbered public transport growth for most professions.

In particular, almost all the growth in health professionals, protective service workers, and carers and aides was accounted for by private transport. These are occupations where working remotely from home is often difficult, and the high rates of private transport growth might also reflect significant rates of shift work where off-peak public transport service levels are often less competitive with private transport.

There are not many occupations that saw a net shift from public to private transport – these included office managers, program administrators, and clerical and office support workers. But again these numbers were tiny compared to the size of the Perth CBD workforce – suggesting there was very little net shift from public to private transport.

Overall there was a 1.6% shift away from private transport commuting to the Perth CBD, with most of the other mode shift being from public transport to remote working. The evidence from Perth does not support the hypothesis.

How did commuting behaviour change for Adelaide CBD commuters?

Adelaide saw only a tiny increase in the number of private transport commuters, but a significant decrease in the number of people who travelled on public transport. Overall there was a 5.3% shift away from private transport mode share (when you include remote working).

As per the analysis for Perth, here’s the change in volume of trips by mode and birth year:

For Adelaide most of the net mode shift also appears to be from public transport to working remotely. There was a net increase in private transport commuting for people aged 15 to 34 in 2021, and a small decline in private transport trips for older age groups.

There was only a tiny net shift from public to private transport of 526 people within those aged 30-39 in 2021.

Like Perth, working at home accounted for a smaller share of the employment growth for younger adults.

Here’s a look at occupations for Adelaide:

Again, the biggest mode shift here appears to have been from public transport to working at home, with the notable exception again of carers and aides, and health professionals (although small numbers). In most occupations there was also a mode shift away from private transport. Very few occupations show a net shift from public transport to private transport in Adelaide.

The evidence of Adelaide does not support the hypothesis of mode shift from public to private transport. The biggest change was a mode shift from public transport to remote working (plus some mode shift from private transport to remote working).

How did the mix of CBD car commuters change?

Yet another way of looking at potential mode shifts is whether the people driving to work in the CBD in 2021 were any different to previous censuses. For this analysis I’ve filtered for commuters to CBDs who did not use any public transport, but did travel as a vehicle driver or on motorbike/scooter (you might argue “Truck” should be included as well, but we don’t know whether there people were drivers or passengers and the numbers are tiny so I don’t think it is material).

Firstly here is the occupation split of vehicle drivers to work in the five CBDs over the last three censuses:

In most cities, there was a noticeable change in occupation share between 2016 and 2021 towards technicians and trade, labourers, machinery operators and drivers, and community and personal service workers, and away from professionals and managers. Basically a shift from white collar to blue/fluoro collar jobs, as many white collar workers shifted to working remotely. This shift was largest in the locked down cities of Melbourne and Sydney, but was also visible in Adelaide and Brisbane to a lesser extent.

It is also interesting to look at the change in volumes. Note the Y-axis on the following chart has an independent scale for each occupation group, with the biggest occupation groups at the top:

In locked-down Sydney and Melbourne, there was a massive decrease in white collar workers and an increase in machinery operators and drivers. Melbourne also saw an increase in labourers and community and personal service workers. This might reflect a reduction in car parking prices, although I cannot find evidence that prices were actually lower on census day (the City of Melbourne waived parking fees and restrictions from just after the census).

Diving deeper, there was a big increase in protective service workers in the Melbourne CBD, and about 2166 of them drove to work in 2021 (up from 1660 in 2016). This may reflect the opening of the new Victorian Police Centre in Spencer Street in 2020, complete with 600 car parks. Indeed the destination zone that includes this building (and Southern Cross Station) saw an increase of 769 private transport commuters between 2016 and 2021, the biggest increase of any CBD destination zone.

In COVID-free Perth there was an increase in professionals, clerical and administrative workers, managers, community and personal service workers, and machinery operators and drivers who drove to work, and there was only a decline in sales workers.

So what have I learnt from the latest census data?

I’ve covered a bit of ground, so here’s a summary of key findings and some discussion:

  • Locked-down Sydney and Melbourne saw a significant shift to remote working of CBD employees in 2021. COVID-free CBDs saw much less shift to remote working (Adelaide 24% and Perth 15%).
  • Remote working was most common for middle-aged CBD employees (peaking at 40-44 age bracket), and much lower for younger adults and a little less common for older employees.
  • All CBDs saw a step change in the workforce age composition between 2016 and 2021, shifting to an older workforce, probably related to the halt to immigration during the pandemic.
  • In most cities, remote working in 2021 was slightly more common for CBD employees who lived further from their CBD.
  • In all cities, the main mode shift between 2016 and 2021 seems to be from public transport to remote working.
  • No city saw a net mode shift from public transport to private transport (when you include remote working in the modal mix). The main mode shift in COVID-free cities appears to be from public transport to remote working. However it is entirely possible that some public transport commuters switched to private transport, but this was more than offset by other commuters who shifted from private transport to remote working. Few age or occupation cohorts saw a net shift from public to private transport.
  • The only CBD to see a significant increase in private transport commuter trips was Perth (with +5164). However this was still a net mode shift away from private transport mode share due to massive growth in overall CBD employment between 2016 and 2021. I’m curious about how this happened, and I will explore it further in an upcoming post.
  • Occupations likely to include many shift workers saw the biggest net private transport commuter growth in Adelaide and Perth – including health professionals, protective service workers (including police), carers, and aids.

So what can we expect in a “post-pandemic” world?

At the 2021 census all Australian cities were either in lockdown or were perceived to be COVID-free. No Australian cities were “living with COVID”, and in the cities with COVID circulating, few workers faced a choice between workplace attendance and remote working.

At the time of writing (March 2023), COVID is circulating across Australia and there are very few restrictions to restrict spread. There is an ongoing risk of COVID infection when using public transport and attending an indoor workplace (although you can choose to wear a mask of course).

Is this leading to a mode shift from public to private transport in this “post-pandemic” world? Have we even reached a new steady state? The best data to answer this will come from the 2026 census.

In the meantime I have had a quick look at some transport indicators for Melbourne.

Vehicle traffic through CBD intersections in 2022 (excluding Q1) was consistently below 2019 levels in the AM peak in most parts of the CBD. However it’s only a rough indication as much of this traffic will be for purposes other than private transport commuting to the CBD (eg deliveries, through-traffic, buses, etc) (I’ve excluded signals on Wurundjeri Way which is likely to have much through-traffic).

The next chart shows average daily patronage for metropolitan trains, trams, and buses in Melbourne based on published total monthly patronage data but not taking into account the different day type compositions of months between years (I’d much prefer to use average school weekday patronage data to avoid calendar effects, but that data series only ran as far as June 2022 at the time of writing).

This data suggests CBD private transport commuter volumes in 2022 might be a bit below 2019 levels, while there has been a substantial reduction in public transport commuting. This is consistent with what was seen in Adelaide in the 2021 census – mostly a mode shift from public transport to remote working. Furthermore, if there has been a significant increase in Melbourne CBD employment, private transport mode share (when you include remote working) is more likely to have declined below 2019 levels.

Is infection fear still influencing mode choice?

The largest COVID wave in Victoria (so far at the time of writing) occurred in January 2022 peaking at 1229 people in hospital and there was significant public transport patronage suppression (well beyond the usual summer holiday lull) as many people choose to stay home (or were sick and had to stay home). Infection fear was probably having a big impact, as I recall there were few restrictions regarding workplace attendance.

There was also a fairly large COVID wave in winter 2022 peaking at 906 hospitalisations in July, but the above chart shows no significant associated reduction in public transport patronage. This suggests infection fear was probably having a very small impact on transport behaviour in mid-2022.

Certainly in my experience few people are wearing masks on Melbourne’s public transport at the time of writing, but maybe a cautious minority have still not returned to the network.

Emerging indications are that public transport patronage is returning even more strongly in February and March 2023, which might reflect even lower levels of infection fear (hospitalisation numbers have also reached the lowest numbers since September 2021), and/or it might reflect a surge in population growth and CBD employment/student numbers. Things to keep an eye on over time!

Leave a Comment » | Australian Cities, Brisbane, Melbourne, Migration, Mode share, Mode shift, Road Traffic, Sydney, Working at home | Tagged: , | Permalink
Posted by chrisloader

« Previous Entries