Update on Australian transport trends (December 2022)

Sat 31 December, 2022

It’s that time of year again when BITRE release their annual yearbook chock full of numbers, and this post aims to turn them into useful information. It’s also a prompter for me to update my feeds of other transport metrics and pull together this post covering the latest trends in licence ownership, motor vehicle ownership, transport emissions, vehicle kilometres, passenger kilometres, freight volumes, and transport pricing.

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 (January 2022, December 2020, December 2019, December 2018).

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.

Overall the trend has been a flattening of licence ownership rates, and indeed Victoria was showing declining licence ownership before the pandemic. The ACT and Northern Territory had much higher rates of licence ownership in the 1970s compared to other states. But then the Northern Territory has maintained lower rates of licence ownership than most other states since the 1990s. The ACT showed very high rates of licence ownership around 2009 to 2017 – not sure if this is real or an artefact of the imperfect data (eg counting people with multiple licences).

Most states saw an uptick in 2021 with the notable exception of Western Australia – a state that was largely COVID-free until early 2022 so any COVID-avoidance incentive to get a driver’s licence might not have been very strong. Licence ownership rates in Queensland and Victoria have somewhat levelled out between 2021 and 2022, perhaps reflecting a return of international arrivals and the end of COVID lockdowns.

Here’s licence ownership by age band for Australia as a whole (to June 2021):

In 2020 and 2021 there was an uptick in ownership for people aged 16 to 29 in particular. Let’s look at the various age bands across the states:

There are some interesting recent trends for people aged 16-19. Victoria saw a big drop in 2020 but then some big increases in 2021 and 2022. South Australia and New South Wales have also seen big increases in recent years.

There were even bigger increases for 20-24 year olds following the start of the pandemic, except Western Australia and the Northern Territory (states that largely avoided COVID in 2021).

Ages 25-29 were similar:

So why have licence ownership rates increased for younger adults? Is it mode shift away from public transport to avoid the risk of COVID infection on public transport? Or is it because non-licence holders left the country?

South Australia and New South Wales publish quarterly licencing data by age band which allows us to see the impact of the pandemic more closely. I’ve combined this with ABS quarterly population data to calculate quarterly licence ownership rates:

South Australia has less historical data published:

The population aged 20-24 declined after March 2019 in both New South Wales and South Australia – a year before the pandemic hit. Then both states saw a more rapid decline after March 2020 – the onset of the pandemic.

However the number of people in this age band with a licence only increased slightly – in line with pre-pandemic trends. That is, the licence ownership rate increased sharply primarily because there was a net loss of non-licence holders.

Here’s a look at Australia’s population by age band:

There are some fairly smooth trends over time in all age bands, but then from 2020 there were some sudden shifts, particularly for age bands 16-19, 20-24, 25-59 and to lesser extent 30-39.

A plausible explanation is that international students and other non-permanent residents left Australia – many could not attend classes and were encouraged to leave Australia by the government of the day. These departures were not replaced by new arrivals as the international borders were essentially closed. Indeed once the borders reopened in early 2022, there was a sharp increase in non-licence holders in New South Wales that sent the motor vehicle licence ownership rate down sharply in March 2022 (June 2022 data has not been published at the time of writing).

Other data shows a sharp fall in the number of international students in Australia between 2019 and 2020, particularly in NSW, Victoria and Queensland (more recent student numbers unfortunately not available at the time of writing):

And there was a dramatic shift to net outbound overseas migration from the June quarter of 2020:

In previous posts (see Why are young adults more likely to use public transport? (an exploration of mode shares by age – part 3) I’ve established that recent immigrants skew to the younger adult ages as Australia generally attracts international students and skilled migrants, which also fits with the hypothesis that there was a great exodus of young adults who didn’t have a driver’s licence.

[Side note: the first quarter of 2022 represented a new record for international migration into Australia as the borders re-opened – almost 98k people.]

It’s entirely plausible that long-time residents also increased their rate of licence ownership during the pandemic, but I think the most likely major explanation is the departure of international students and temporary residents. And so I expect the return of international migration will result in lower licence ownership, car ownership, and increased public transport mode share in 2023.

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

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

To get a better understanding of recent trends, here are quarterly licence ownership rates by age band for New South Wales since mid 2018:

You can see the rise – and more recent fall – in licence ownership rates for the age bands 20-24 and 25-29. There was also a sharp fall for those aged 16-19 in September 2021, possibly due to Sydney entering a long COVID lockdown in the winter of 2021 (perhaps learners permits were not renewed or people didn’t bother applying for them if they could not take lessons). 30-34 year olds showed a small rise in licence ownership from the start of the pandemic and this seems to have been sustained, which might reflect some mode shift to avoid infection risk.

Here’s the same quarterly data for South Australia:

Licence ownership rates rose strongly for those aged 16-34, although there was an initial dip for those aged 16-19 in June-September 2020 around the start of the pandemic. Perhaps it has remained high because international students have not yet returned in great numbers to Adelaide, and/or because of a permanent mode shift towards private transport?

For completeness, here are motor cycle licence ownership rates:

Motorcycle licence ownership has been trending up slightly in New South Wales and Victoria, and slightly down in Queensland, South Australia, Norther Territory and Western Australia.

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. So the following charts will show 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.

Between January 2020 and January 2022 most states show an upwards trend in motor vehicles per population aged 18-84 (an imperfect approximation of the driving age population).

However when you look at the stock of cars per state, there was not a significant uptick in the total number of cars – indeed Victoria saw an almost flattening of total motor vehicles between January 2020 and January 2021:

Again, a highly plausible explanation is that non-driving (and non-licence holding) residents departed Australia while long-term residents largely continued their background trends in motor vehicle ownership. We might therefore see a decline in motor vehicle ownership rates in the January 2023 survey with the return of overseas immigration.

Transport Emissions

Australia’s transport emissions have been reduced by COVID lockdowns over the last couple of years but have more recently bounded back:

The above chart showing rolling 12 months emissions which washed out the lockdown period. The next chart shows seasonally-adjusted quarterly data to get around the rolling 12 month averaging – with the September 2022 quarter close to 2019 levels:

Here are Australian transport emissions since 1975:

And in more detail since 1990:

The next chart shows the more recent growth trends by sector:

Aviation emissions saw the biggest decline from the pandemic but were bouncing back in 2021-22. Car and bus emissions have declined in line with pandemic lockdowns whilst most other modes have continued to see growth in emissions.

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 continued reduction in car emissions per capita since around 2004.

Next up, emissions intensity (per vehicle kilometre):

Curiously the figures suggest a sudden drop in bus emissions per km in 2022, but I am not sure this is plausible as electric buses are still only being rolled out in small numbers. There was also an unexpected dip in emissions per km in 2015 which jumped back up in 2016. The 2015 dip in bus emissions per km is primarily a product of a dip in BITRE’s estimated bus emissions and not bus vehicle kilometres travelled, which is a hard to explain (this bus emissions dip is not seen in AGEIS estimates). I suspect this may be an artefact of BITRE methodological issues.

Emissions per passenger-km 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.

Vehicle kilometres travelled

Vehicle and passenger kilometre figures have been significantly impacted by COVID lockdowns in 2020 and 2021, and so the financial year figures are a mix of restricted and unrestricted travel periods. Accordingly we cannot readily infer new trends from this data, and it should be interpreted with caution.

Total vehicle kms for 2021-22 were lower than 2019-20 and 2020-21:

As per emissions, the biggest declines were in cars, motorcycles, and buses:

Light commercial vehicles and trucks have shown the biggest increase since 1990.

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.

Here is the same data for capital cities (capital city population data comes out only once a year with some delay, so most city data points are only up to financial year 2020-21).

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

Once again BITRE have kindly supplied me data on estimated car vehicle kilometres for capital cities that is not included in the yearbook:

Canberra is still on top for car kilometres per person but this rate has been reducing strongly over recently years.

Passenger kilometres travelled

Here are passenger kilometres travelled overall (log scale):

The pandemic had the biggest impact on rail, bus, and aviation passenger kilometres.

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

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 before the pandemic hit. Only air travel has rebounded on a financial year basis.

Here’s total car passenger kilometres for capital cities:

Melbourne, Sydney, and Canberra were impacted by extensive lockdowns in 2021-22, while the other cities were mostly lockdown free. However the then-unprecedented large wave of COVID cases in the summer of 2021-22 may have led to voluntarily suppressed travel behaviour across many cities.

Here’s car passenger kilometres per capita (again only to 2020-21 for most cities):

It’s hard to estimate any post-COVID trends based on this annual data. However, I have been processing VicRoads traffic signal count data which gives some indication about more recent traffic volumes in Melbourne. The following chart shows the change from 2019 median signalised intersection traffic count volumes per week. I’ve deliberately locked the scale as -20% to +10% as I want to focus on the difference between 2019 and 2022 traffic, and so the 2020 and 2021 lines go off the scale during lockdowns.

It’s very interesting that volumes in late 2022 were about 5% lower than 2019 levels on weekdays (a bit higher on weekends although there’s no such thing as a normal weekend).

And if you look at the time of day profile for Melbourne (below), the biggest reductions have been in the early AM peak, and evenings, while there have been increases during the AM and PM school peaks (which might be a response to COVID infection fear and/or because parents working from home can more easily drive their children to and from school):

Rail Passenger travel

The pandemic has put a large dent in rail passenger kilometres travelled, and these are likely to remain below 2019 for some time as new working-from-home behaviours stick following the pandemic:

Melbourne saw a slight increase in 2021-22, but this was probably more a product of the how long the city was in lockdown during financial years 2020-21 and 2021-22. Sydney saw a reduction in 2021-22 probably because there was little in the way of lockdowns in 2020-21.

Here’s rail passenger kms per capita (again, only up to 2020-21):

Bus passenger kilometres have reduced significantly with the pandemic:

Including on a per-capita basis:

I would expect to see these figure bounce back up as there are unlikely to be any lockdowns during 2022-23.

It would appear that the surge in Darwin bus use due to a major LNG project may have ended.

Mode split

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

Mass transit mode shares have taken a large dive during the pandemic, and I expect this to be strongly associated with COVID lockdowns where many people – especially central city workers – worked from home. It’s still difficult to know to what extent this is people switching travel modes for ongoing trips, to and what extent it is public transport trips being replaced by staying home. I hope to have more to offer on this subject in an upcoming blog post.

Transport for New South Wales conducts a rolling household travel survey, although it was suspended during COVID lockdowns in 2020 and 2021. Estimated total person trips and kilometres by mode are reported, and from this we can get an idea around mode split (including non-motorised modes):

On this data, the public transport mode share of person kilometres travelled is much higher than that derived from the BITRE data, with a peaking of around 20% before the pandemic.

Unlike Victoria, New South Wales unfortunately does not provide any detailed household travel survey data, which means it is not possible to perfectly calculate public transport mode share (ferry and light rail were bundled with “Other” pre 2020), and it’s also not possible to calculate mode share by trip purpose. All this and more is possible with Victorian published data, but unfortunately post-COVID data will not be published until late 2024.

Freight

This data shows a dramatic inflection point in freight volume growth in 2019, with a lack of growth in rail volumes and a decline in coastal shipping. 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, and are arguably more contestable between modes:

2022 saw a sudden flatlining in non-bulk freight volumes, with road increased market share to 80%, seemingly mostly at the expense of coastal shipping:

Air freight tonnages are tiny in the whole scheme of things so you cannot easily see them on the charts.

Transport Costs

The final category for this post is the real cost of transport from a individual perspective. Here are headline real costs (relative to CPI) for Australia, using Q2 ABS Consumer Price Index data up to June 2022:

Technical note: Private motoring is a combination of factors, including motor vehicle retail prices and automotive fuel. Urban transport fares include public transport as well as taxi/ride-share (which possibly move quite independently, which is a little frustrating).

The cost of private motoring mostly declined in real terms from around 2008 to 2020, followed by sharp increases in 2021 and 2022 in line with the rapidly rising cost of automotive fuel. The real cost of motor vehicles has plummeted since 1996, although it bottomed out in 2018.

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.

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 1973 by city (note different Y-axis scales):

Technical note: I suspect there is some issue with the urban transport fares figure for Canberra in June 2019. The index values for March, June, and September 2019 were 116.3, 102.0, and 118.4 respectively.

Urban transport fares have grown the most in Brisbane, Perth, and Canberra – relative to 1973. 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 – eg. 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.

What does all this mean for post-pandemic transport trends?

I also tackled this question a year ago and my thoughts haven’t changed significantly.

One thing that has become clearer is that the increase in motor vehicle licence ownership and car ownership is very likely related to the lack of recent international immigrants during the pandemic. Therefore the reopening of international borders is likely to push these rates down once more across 2022 and 2023, although they may or may not return to pre-pandemic levels. In turn, this will probably increase public transport patronage and mode share, although it is still likely to remain subdued following the wide scale acceptance and adoption of working from home, particularly for central city workers.

A key question for me is the extent to which commuter trips have shifted from public to private transport, as opposed to simply disappearing as many more people work from home. I’ll have more to say on this soon in an upcoming post about 2021 census journey to work data.


Update on Australian transport trends – January 2022

Sun 23 January, 2022

Once again, the good folks at the Bureau of Infrastructure, Transport and Regional Economics (BITRE) have published their annual yearbook chock full of data just before Christmas. This annual post aims to turn the numbers into insights about transport trends in Australia.

I’ll cover vehicle kilometres, passenger kilometres, mode shares, car ownership, driver’s licence ownership, greenhouse gas emissions, and transport costs. This year there’s also a new section of freight volumes and mode shares.

While most data series are available up until 2020-21, at the time of writing there were only June 2021 estimates of population for states and territories, not cities. So most charts for cities will end at 2019-20, the financial year in which the COVID19 pandemic had significant impacts for only the last third (i.e. from March 2020).

I will finish the post with some thoughts about what the data suggests for post-pandemic transport trends. Settle in, there are quite a few charts!

Vehicle kilometres travelled

Total vehicle kms travelled in Australia increased slightly in 2020-21, after a small but significant fall in 2019-20 due to the pandemic.

Here’s the percentage growth by vehicle type since 1971:

Light commercial vehicles have seen the largest growth overall since 1971, followed by buses (mostly in the 1980s), with motorcyles having the least growth.

In percentage terms, buses saw the largest decline in vkms with the pandemic (I’m guessing largely related to charter and tour operations), but there were also substantial declines for cars and motorcycles as people endured lockdowns and borders were closed. There was no clear impact on trucks and only a small impact on light commercial vehicles. All vehicle types except buses rose in total vehicle kms in 2020-21.

Vehicle kilometres travelled per capita

Here’s a view at the state and national level:

Vehicle kms per capita peaked in all states in 2004 or 2005 and have declined since then, with some variation between states.

Vehicle kms per capita were highest in Queensland and Western Australia, and lowest in the Northern Territory, followed by New South Wales, South Australia and the ACT – at least until the COVID19 pandemic.

All states saw a big reduction in 2019-20 with the pandemic (although less so in the NT which I understand didn’t lock down), and things bounced up in 2020-21 in all states except Victoria – no doubt due to a long lockdown in the second half of calendar 2020 due to a second wave of COVID19.

Similar patterns were seen in cities (data for most cities is only until 2019-20). Before the pandemic, Melbourne and Sydney showed the biggest declines in vehicle kms per capita.

BITRE have been kind enough to supply me with estimates of car vehicle kilometres for cities (not yet part of the yearbook data), which show similar patterns:

Passenger kilometres travelled

Firstly here are passenger kilometres travelled at the national level – and note I have used a log-scale on the Y-axis.

The COVID19 pandemic brought massive reductions in rail, bus, and air passenger kilometres travelled, and a smaller reduction in car passenger kilometres. This will likely reflect a significant proportion of the workforce shifting to working at home, an aversion to shared transport, and the closure of interstate borders during the pandemic.

Prior to the pandemic, there was a massive increase in air travel between the mid-1980s and the early 2010s, and rail saw strong growth from 2005.

Here’s passenger kms per capita:

Car passenger travel per capita peaked in 2004, and domestic air travel per capita peaked around 2014. Bus travel per capita peaked in 1990, the same year aviation was significantly disrupted by a pilot’s strike. Rail passenger travel was growing strongly until the pandemic hit.

The next sections will look at passenger kms (total and per capita) for capital cities, by mode.

Car passenger travel

After a long run of strong growth, the pandemic brought declines in car travel in all cities in 2019-20. There was a bounce back in 2020-21, except Melbourne which saw a further decline to 17% below 2019-20 levels (roughly equal to 2003 levels), no doubt due to COVID19 lockdowns. 2020-21 car passenger kms in Perth, Adelaide, and Brisbane were above 2019-20 volumes, suggesting a snap back to the growth trend.

All cities saw a significant decline in car passenger kms per capita in 2019-20, due to the pandemic.

The longer-term trend shows peaking of car use in 2004 or 2005 in all cities.

Rail passenger travel

There were massive reductions in (heavy) rail passenger kms in both 2019-20 and 2020-21 with the COVID19 pandemic, as many central city workers shifted to working from home and cities went into lockdown.

Just before the pandemic, Sydney’s rail passenger kms were rocketing up. Sydney’s rail network carries significantly larger volumes than Melbourne despite having almost the same population.

Before the pandemic, rail passenger kms per capita were increasing in Sydney, declining in Melbourne, and increased slightly in other rail cities in 2018-19. Things obviously changed with the pandemic in 2019-20.

Here is growth in rail passenger kms since 2010:

Pre-pandemic, Adelaide and Sydney has the strongest growth relative to 2010, while Brisbane had the least. However the chart would look quite different with a different base year (eg Perth would look worst on a base year of 2013). Adelaide train patronage was significantly impacted in the period 2011-2014 by electrification and other upgrade works that involved extended line closures.

Bus passenger travel

Sydney has the highest bus use of all Australian cities. It’s worth noting that Melbourne is unique in that trams dominate inner city radial street-based public transport, resulting in a lower rate of bus use compared to other cities.

All cities saw big bus patronage reductions with the pandemic, with Melbourne bus usage falling below than of Brisbane in 2020-21.

In per capita terms, Darwin has seen a massive increase in bus use due to a large staff bus network being created for a major LNG project just outside of Darwin.

Sydney overtook Brisbane for bus use per capita in 2017-18, perhaps due to some service investment, network reform, and/or reduced transfer penalties from fare reform. Brisbane saw massive increases in bus usage between 2004 and 2012, likely related to the expansion of the busway network and some service upgrades (including “BUZ” routes), which might then have been eroded by significant fare hikes.

Growth in bus passenger kms since 2010 shows these patterns in another way:

Pre-pandemic, Sydney and Canberra were showing particularly strong growth. Perth peaked in 2014 – which might be partly explained by a decentralisation of employment (see: What might explain journey to work mode shifts in Australia’s largest cities? (2006-2016)).

Again, these types of charts would look quite different if a different reference year was applied.

Light rail passenger travel

Melbourne has by far the largest light rail network, so little surprise it has the highest passenger kms. None of these light rail networks are designed to serve the entire city, so we need to be cautious comparing cities, and I won’t provide a per capita chart.

Despite the COVID19 pandemic, Sydney saw an increase in light rail use in 2019-2020, which would reflect the opening of the new south-eastern lines to Randwick and Kingsford in December 2019.

Motorcycle passenger travel

Motorcycle travel had a dip in the 1990s on these figures, then picked up strongly in the early 2000s. The patterns in 2019-2021 are similar to car passenger travel.

On this data, Melbourne bucked the trend of other cities in 2006 and started a decline in motorcycle travel. However all these figures are estimates only, and I would not be surprised if there were some “broad” assumptions behind the estimates, as motorcycle travel doesn’t usually get a lot of measurement attention, and most of the cities are estimated to have remarkably similar trends.

Mass transit mode share of passenger kilometres

It is possible to calculate the ratio of “mass” transit passenger kms (rail, light rail, ferry, and bus) against total passenger kms in cities, which essentially provides a mode share. Note however that this will include estimates of private bus travel, so it’s not exactly public transport mode share, but probably not far off.

The pandemic has led to significant falls in mass transit mode share in all cities, with perhaps the largest reduction in Melbourne (again, likely related to the second wave lockdown in 2020-21).

As I’ve shown on this blog several times, a significant portion of public transport travel is around journeys to work and education in city centres, a trip type that became a lot less frequent during the pandemic as people work and learn from home. The removal of these trips from total travel has undoubtedly shifted the overall mode share calculation.

What’s not yet clear to me is the extent to which trips not suppressed by the pandemic might have shifted from public to private transport, and whether these trips might shift back to public transport “after” the pandemic (assuming there comes a time when there is no longer heightened infection fear).

Car ownership

The following charts use vehicle count data from the ABS Motor Vehicle Census, with January 2021 unfortunately the last census taken (although hopefully Austroads take over in 2022). I’ve calculated per capita car ownership using interpolation from the most recent ABS population estimates at the time of writing.

Not everyone is of driving age, so I usually also look at motor vehicles per 100 residents aged 18-84, as an approximate representation of people of driving age:

Here’s a closer look at the last few decades:

Motor vehicle ownership has risen considerably since the survey began. However from around 2017 until the pandemic it actually decreased in most Australian states and territories (Tasmania an exception).

There has been a small but significant uptick in motor vehicle ownership in January 2021 in all states. As I mentioned in my recent blog post on motor vehicle ownership by age, I see two likely main reasons for this:

  • A lack of recent international immigrants during the pandemic – who generally have very low rates of motor vehicle ownership in the first years in Australia, and are skewed towards young adult age bands which themselves also have lower rates of motor vehicle ownership in general.
  • A mode shift from public transport, as people want to avoid the risk of catching COVID19 on public transport (whether this risk is large or small). However with working/learning from home, it’s hard to know how much of this is mode shift of continued trips, versus trips of certain modes not being made as often.

Motorcycle ownership

This chart shows a slightly different pattern to that of motorcycle passenger kilometres per capita in cities (above). Ownership and usage bottomed out around the 1990s or 2000s (depending on the state/city). However ownership has risen in most states since then, but usage apparently peaked around 2009 in most cities. This perhaps suggests motorcycles are now more a recreational – rather than everyday – vehicle choice. But I really don’t follow motorcycle trends closely so cannot be too sure.

Driver’s licence ownership

Thanks to BITRE Information Sheet 84, the BITRE Yearbook 2021, and some useful state government websites (NSWSAQld), here is motor vehicle licence ownership per 100 persons (of any age) from June 1971 to June 2020 or June 2021 (only some state agencies have published 2021 data at the time of writing):

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.

There’s been slowing growth over time, although Victoria has actually seen slow decline since 2011, and the ACT peaked in 2016.

However in both states with 2021 data (South Australia and New South Wales) there was a significant uptick in 2021 of more than 1 licence per 100 people. This is likely related to the pandemic – either more people opting for a driver’s licence to shift away from shared modes, and/or a lack of recent immigrants (many were young adults) who usually take some time to get their licence. I would not be surprised to see similar trends in other states when data is made available.

Here’s a breakdown by age bands for Australia as a whole:

Licencing rates had been increasing over time for those aged over 40 (most strongly for those aged over 70) up until 2019, but that changed for the 60-69 and 70-79 bands in 2020.

Licencing rates had been declining for those aged under 40 until 2019, although there was a notable uptick in licence ownership for 16-19 year-olds in 2018, and increases in 2020 for those aged 20-29.

However the above charts show national trends that can wash out variations at the state level. So let’s break it down for states per age band:

Licence ownership rates for teenagers has been declining significantly in Victoria, with a large fall in 2020. There were also declines in 2020 in Tasmania, South Australia and Western Australia. NSW had a significant increase in 2020, and even more so in 2021.

Note: the differences between states for this age band at least partly reflect different minimum ages for licencing.

The largest states of Victoria and New South Wales were trending downwards until 2019, but have since shot back up, quite spectacularly in NSW. This might partly reflect the absence of new immigrants who generally have low levels of driver’s licence ownership. There may also be issues with ABS’s population estimates in the unprecedented pandemic.

All states showed an increase in 2020 except the Northern Territory.

Victoria and New South Wales did have a downwards trend in this age band, but that turned around in 2020. Tasmania and the ACT have shot up since 2017.

Licence ownership for those in their 30s had been declining in NSW, SA, WA and Victoria up to 2020, with NSW again showing an uptick in 2021. Tasmania has seen strong growth in recent years.

Licence ownership for those in their 40s was declining slightly in SA, Victoria, and WA until 2020, but was still very high. NSW had a smaller uptick in this age band in 2021, compared to younger age bands.

Licence ownership for those in their 50s was declining slightly until 2020 in most states (except Queensland and Tasmania). NSW had a relatively small uptick in 2021 compared to younger age bands.

Licence ownership for those in their 60s was slowly growing in most states until 2019 but then fell in 2020 with the pandemic. The 2021 uptick in NSW did not fully recover from the drop in 2020.

Licencing rates for those in their 70s have been growing strongly in all states (except recently in WA). NSW saw a dip in 2020, but bounced back in 2021. I suspect a data error for NT in 2019.

Licencing rates for those over 80 were increasing in most states to 2020, and NSW only had a small dip in 2020.

New South Wales is the first state to give us insights into the impact of the pandemic, so here is a look at the licencing trends per age band in that state:

You can see more clearly the big growth for those aged under 30 (people who generally used public transport more often before the pandemic), whilst older age groups (60+) saw a temporary decline in licence ownership in 2020 with a bounce-back in 2021.

See also an older post on driver’s licence ownership for more detailed analysis.

For completeness, here is a chart showing motorcycle full licence ownership rates:

Queensland has two types of motorcycle licence and I suspect many people hold both, which might explain a licence ownership rate being so much higher than other states.

Freight

There has been a massive increase in domestic freight volumes since the 1970s, and according to this data, rail has accounted for most of this growth in recent decades. However keep in mind that a majority of these freight-kilometres are bulk commodities (such as iron ore, coal, and grain) which are ideally suited to energy-efficient rail and coastal shipping. Indeed in 2020-21, road transport only moved 11% of bulk goods, and 93% of rail freight movements were bulk goods.

Here are the volumes for non-bulk freight movements, which are arguably more contestable:

And non-bulk freight mode shares:

Road transport dominates non-bulk freight movements in Australia, while air freight is trivial in terms of volume (but probably non-trivial in terms of value). Coastal shipping’s mode share fell significantly in the late 1970s and early 1980s but has remained mostly around 4-6% since then.

Rail transport’s mode share of freight movements declined in the 1970s and 1980s, had a small peak of 22% in 2006, but has fallen back to 16% in 2021. That’s despite the estimated rail freight volume in 2020-21 being the highest of any year reported – it’s just that road volumes have grown even more.

Transport greenhouse gas emissions

Total emissions

According to the latest quarterly figures, Australia’s domestic non-electric transport emissions peaked in around 2018, and had been slightly declining ahead of the COVID19 pandemic.

The above chart showing rolling 12-month figures, which hides the big and sudden changes in recent quarters. So here’s a look at seasonally-adjusted transport emissions by quarter:

Data available at the time of writing was to June 2021, a quarter with fewer impacts from the pandemic (there were some lockdowns in Melbourne). As pandemic conditions eased (before the COVID19 delta wave in the second half of 2021), transport emissions shot back up to near-2019 levels. I expect we will see a decline in the September 2021 data as Victoria and NSW experienced COVID lockdowns. Reductions in Australia’s transport emissions so far appear to be only temporary.

The next chart shows a long term trend of rapid rising annual transport emissions (according to BITRE data):

A more detailed breakdown of road transport emissions is available from 1990 onwards:

To better see the trends per mode, here is net growth since 1975:

Domestic aviation emissions have seen the biggest reduction from the COVID19 pandemic, followed by road emissions. Rail and marine emissions have also shown a decline in the last two years, however I cannot be certain to what extent this is due to the pandemic.

Road emissions grew steadily until 2019, while aviation emissions took off around 1991 (pardon the pun). You can see that 1990 saw a lull in aviation emissions, probably due to the pilots strike around that time.

In the years before the pandemic, non-electric rail emissions grew strongly, mostly driven by increases in bulk freight volumes (as discussed above). I suspect the small decline in rail emissions in recent years is unlikely to be related to diesel passenger trains (most of which have continued to run to normal timetables during the pandemic).

The next chart shows growth by sector since 1990 (including a more detailed breakdown of road transport):

This data suggests the pandemic has had no impact on truck emissions, but has reduced car, bus, and light commercial vehicle emissions.

Per capita emissions

While per capita emissions aren’t directly relevant to climate change impacts, it is interested to look at whether emissions growth has decoupled from population growth for different modes. Note I’ve used a log scale on the Y-axis.

Per capita car emissions for all modes except trucks have been in decline in recent years – and more so with the pandemic. Aviation and bus emissions per capita have fallen the most with the pandemic.

Emissions intensity

We can also calculate emissions per vehicle kms travelled. I’ve labelled the value estimates for 2021 (note again a log scale on the Y axis).

There has been a slow decline in emissions per km for cars, motorcycles and buses, while light commercial vehicles remain flat, and emissions per truck km have increased (although average truck loads have also increased over time).

I’d like to be able to calculate freight emissions intensity per tonne-kilometre by mode, but it’s hard to do that sensibly with the available data (eg rail emissions are not split by freight and passenger, and many flights carry both passengers and freight).

Transport costs

The final category for this post is the real cost of transport from a individual perspective. Here are headline real costs (relative to CPI) for Australia, using ABS data:

Technical note: Private motoring is a combination of factors, including motor vehicle retail prices and automotive fuel. Urban transport fares include public transport as well as taxi/ride-share (which possibly move quite independently, which is a little frustrating).

The cost of private motoring has tracked relatively close to CPI, although it seems to be trending down since 2008, probably largely related to reductions in the price of automotive fuel (which peaked in 2008). The real cost of motor vehicles has plummeted since 1996, although it may have bottomed out in 2018.

Urban transport fares have increased faster than CPI since the late 1970s, although they have grown slower than CPI (on aggregate) since 2013.

However 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 1973 by city (note different Y-axis scales):

Technical note: I suspect there is some issue with the urban transport fares figure for Canberra in June 2019. The index values for March, June, and September 2019 were 116.3, 102.0, and 118.4 respectively.

Urban transport fares have grown the most in Brisbane, Perth and Canberra – relative to 1973.

However if you choose a different base year you get a different chart:

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

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

What do these trends suggest for post-pandemic transport?

There are some emerging trends in the data above that suggest a shift towards private transport:

  • An uptick in driver’s licence ownership in 2021 evidenced in NSW and South Australia, and likely replicated in other states (data not yet available). The increases were sharpest for young adults, normally a natural market for public transport. Motor vehicle licence ownership has a strong relationship with mode choice, and even if/when the fear of infection on public transport is gone, there may be some people who stick to habits formed during the pandemic. See also: Why are younger adults more likely to use public transport? (an exploration of mode shares by age – part 2)
  • Likewise, an uptick in motor vehicle ownership in all states in 2021 could also see some people sticking to new driving habits formed during the pandemic. Again, see Why are younger adults more likely to use public transport? (an exploration of mode shares by age – part 2)
  • The biggest reductions in transport volumes were seen in public transport, no doubt strongly associated with office workers switching to working from home during the pandemic (a large portion of whom work in CBDs). They will likely not return to working in the office as frequently as they did before the pandemic, and this may see future public transport patronage and mode share lower than pre-pandemic projections. In other analysis (not yet published here sorry) I’ve found high rates of pre-pandemic public transport use amongst occupations that are most likely amenable to working from home.

However a shift to private transport will hit headwinds if traffic congestion rises (a highly effective form of demand management) and/or car parking prices increase.

Also, the resumption of international migration will probably see an influx of people who are less likely to own and use private vehicles, at least in their early years of living in Australia (see: Why were recent immigrants to Melbourne more likely to use public transport to get to work?) – although this may depend on their perspectives of infection risk.

I think a key issue will be whether a heightened fear of infection can ultimately be removed on public transport, which would enable people to switch back to using public transport, or resume making trips where public transport is/was the “default” mode for many (eg commuting to CBDs).

A sustained mode shift to private transport following the pandemic could have significant consequences for increasing traffic congestion and transport emissions (not to mention many other issues).


What impact does paid car parking have on travel mode choice in Melbourne?

Thu 3 October, 2019

Paid parking is often used when too many people want to park their car in the same place at the same time. Does it encourage people to cycle or use public transport instead of driving? Does that depend on the type of destination and/or availability of public transport? Are places with paid parking good targets for public transport upgrades?

In this post I’m going to try to answer the above questions. I’ll look at where there is paid parking in Melbourne, how transport mode shares vary for destinations across the city, and then the relationship between the two. I’ll take a deeper look at different destination types (particularly hospitals), explore the link between paid parking and employment density, and conclude with some implications for public transport planners. There’s a bit to get through so get comfortable.

This post uses data from around 158,000 surveyed trips around Greater Melbourne collected as part of a household travel survey (VISTA) between 2012 and 2018, as well as journey to work data from the 2016 ABS census.

Unfortunately the data available doesn’t allow for perfect analysis. The VISTA’s survey sample sizes are not large, I don’t have data about how much was paid for parking, nor whether other parking restrictions might impact mode choice (e.g. time limits), and I suspect some people interpreted survey questions differently. But I think there are still some fairly clear insights from the data.

Where is there paid parking in Melbourne?

I’m not aware of an available comprehensive car park pricing data set for Melbourne. Parkopedia tells you about formal car parks (not on street options) and doesn’t share data sets for free, while the City of Melbourne provides data on the location, fees, and time restrictions of on-street bays (only). So I’ve created my own – using the VISTA household travel survey.

For every surveyed trip involving parking a car, van, or truck, we know whether a parking fee was payable. However the challenge is that VISTA is a survey, so the trip volumes are small for any particular place. For my analysis I’ve used groups of ABS Destination Zones (2016 boundaries) that together have at least 40 parking trips (excluding trips where the purpose was “go home” as residential parking is unlikely to involve a parking fee). I’ve chosen 40 as a compromise between not wanting to have too small a sample, and not wanting to have to aggregate too many destination zones. In some cases a single destination zone has enough parking trips, but in most cases I have had to create groups.

I’ve tried to avoid merging different land uses where possible, and for some parts of Melbourne there are just not enough surveyed parking trips in an area (see appendix at the end of this post for more details). Whether I combine zones or use a single zone, I’m calling these “DZ groups” for short.

For each DZ group I’ve calculated the percentage of vehicle parking trips surveyed that involved someone paying a parking fee. The value will be low if only some circumstances require parking payment (eg all-day parking on weekdays), and higher if most people need to pay at most times of the week for both short and long stays (but curiously never 100%). The sample for each DZ group will be a small random sample of trips from different times of week, survey years, and durations. For DZ groups with paid parking rates above 20%, the margin of error for paid parking percentage is typically up to +/- 13% (at a 90% confidence interval).

Imperfect as the measure is, the following map shows DZ groups with at least 10% paid parking, along with my land use categorisations (where a DZ group has a specialised land use).

There are high percentages of paid parking in the central city, as you’d expect. Paid parking is more isolated in the suburbs – and mostly occurs at university campuses, hospitals, larger activity centres, and of course Melbourne Airport.

The next chart shows the DZ groups with the highest percentages of paid parking (together with the margin of error).

Technical note: the Y-axis shows the SA2 name, rather than the (unique but meaningless) DZ code(s), so you will see multiple DZ groups with the same SA2 name.

At the top of the chart are central city areas, major hospitals, several university campuses, and Melbourne Airport.

Further down the chart are:

  • larger activity centres – many inner suburban centres plus also Dandenong, Frankston, Box Hill, and curiously Springvale (where some controversial parking meters were switched off in 2017),
  • the area around Melbourne Zoo (Parkville SA2 – classified as “other”),
  • some inner city mixed-use areas,
  • two shopping centres – the inner suburban Victoria Gardens Shopping Centre in Richmond (which includes an IKEA store), and Doncaster (Westfield) – the only large middle suburban centre to show up with significant paid parking (many others now have time restrictions), and
  • some suburban industrial employment areas (towards the bottom of the chart) – in which I’ve not found commercial car parks.

These are mostly places of high activity density, where land values don’t support the provision of sufficient free parking to meet all demand.

While the data looks quite plausible, the calculated values not perfect, for several reasons:

  • Some people almost certainly forget that they paid for parking (or misinterpreted the survey question). For example, on the Monash University Clayton campus, 45% of vehicle driver trips (n = 126) said no parking fee was payable, 2% said their employer paid, and 12% said it was paid through a salary arrangement. However there is pretty much no free parking on campus (at least on weekdays), so I suspect many people forgot to mention that they had paid for parking in the form of a year or half-year permit (I’m told that very few staff get free parking permits).
  • Many people said they parked for free in an employee provided off-street car park. In this instance the employer is actually paying for parking (real estate, infrastructure, maintenance, etc). If this parking is rationed to senior employees only then other employees may be more likely to use non-car modes. But if employer provided is plentiful then car travel would be an attractive option. 22% of surveyed trips involving driving to the Melbourne CBD reported parking in an employer provided car park, about a quarter of those said no parking fee was required (most others said their employer paid for parking).
  • As already mentioned, the sample sizes are quite small, and different parking events will be at different times of the week, for different durations, and the applicability of parking fees may have changed over the survey period between 2012 and 2018.
  • The data doesn’t tell us how much was paid for parking. I would expect price to be a significant factor influencing mode choices.
  • Paid parking is not the only disincentive to travel by private car – there might be time restrictions or availability issues, but unfortunately VISTA does not collect such data (it would be tricky to collect).

How does private transport mode share vary across Melbourne?

The other part of this analysis is around private transport mode shares for destinations. As usual I define private transport as a trip that involved some motorised transport, but not any modes of public transport.

Rich data is available for journeys to work from the ABS census, but I’m also interested in general travel, and for that I have to use the VISTA survey data.

For much of my analysis I am going to exclude walking trips, on the basis that I’m primarily interested in trips where private transport is in competition with cycling and public transport. Yes there will be cases where people choose to walk instead of drive because of parking challenges, but I’m assuming not that many (indeed, around 93% of vehicle driver trips in the VISTA survey are more than 1 km). An alternative might be to exclude trips shorter than a certain distance, but then that presents difficult decisions around an appropriate distance threshold.

Here’s a map of private transport mode share of non-walking trips by SA2 destination:

Technical note: I have set the threshold at 40 trips per SA2, but most SA2s have hundreds of surveyed trips. The grey areas of the map are SA2s with fewer than 40 trips, and/or destination zones with no surveyed trips.

For all but the inner suburbs of Melbourne, private transport is by far the dominant mode for non-walking trips. Public transport and cycling only get a significant combined share in the central and inner city areas.

Where is private transport mode share unusually low? And could paid parking explain that?

The above chart showed a pretty strong pattern where private transport mode share is lower in the central city and very high in the suburbs. But are there places where private mode share in unusually low compared to surround land uses? These might be places where public transport can win a higher mode share because of paid parking, or other reasons.

Here’s a similar mode share map, but showing only DZ groups that have a private mode share below 90%:

If you look carefully you can see DZ groups with lower than 80% mode share, including some university/health campuses.

To better illustrate the impact of distance from the city centre, here’s a chart summarising the average private transport mode share of non-walking trips for selected types of places, by distance from the city centre:

Most destination place types are above 90% private transport mode share, except within the inner 5 km. The lowest mode shares are at tertiary education places, workplaces in the central city, secondary schools and parks/recreation. Up the top of the chart are childcare centres, supermarkets and kinders/preschool. Sorry it is hard to decode all the lines – but the point is that they are mostly right up the top.

The next chart brings together the presence of paid parking, distance from the CBD, destination place type, and private transport mode shares. I’ve greyed out DZ groups with less than 20% paid parking, and you can see they are mostly more than 3 km from the CBD. I’ve coloured and labelled the DZ groups with higher rates of paid parking. Also note I’ve used a log scale on the X-axis to spread out the paid DZ groups (distance from CBD).

Most of the DZ groups follow a general curve from bottom-left to top-right, which might reflect generally declining public transport service levels as you move away from the city centre.

The outliers below the main cloud are places with paid parking where private modes shares are lower than other destinations a similar distance from the CBD. Most of these non-private trips will be by public transport. The biggest outliers are university campuses, including Parkville, Clayton, Caulfield, Burwood, and Hawthorn. Some destinations at the bottom edge of the main cloud include university campuses in Kingsbury and Footscray, and parts of the large activity centres of Box Hill and Frankston.

Arguably the presence of paid parking could be acting as a disincentive to use private transport to these destinations.

Contrast these with other paid parking destinations such as hospitals, many activity centres, and Melbourne Airport. The presence of paid parking doesn’t seem to have dissuaded people from driving to these destinations.

Which raises a critical question: is this because of the nature of travel to these destinations means people choose to drive, or is this because of lower quality public transport to those centres? Something we need to unpack.

How strongly does paid car parking correlate with low private transport mode shares?

Here’s a chart showing DZ groups with their private transport mode share of (non-walking) trips and percent of vehicle parking trips involving payment.

Technical note: A colour has been assigned to each SA2 to help associate labels to data points, although there are only 20 unique colours so they are re-used for multiple SA2s. I have endeavoured to make labels unambiguous. It’s obviously not possible to label all points on the chart.

In the top-left are many trip destinations with mostly free parking and very high private transport mode share, suggesting it is very hard for other modes to compete with free parking (although this says nothing about the level of public transport service provision or cycling infrastructure). In the bottom-right are central city DZ groups with paid parking and low private transport mode share.

There is a significant relationship between the two variables (p-value < 0.0001 on a linear regression as per line shown), and it appears that the relative use of paid parking explains a little over half of the pattern of private transport mode shares (R-squared = 0.61). But there is definitely a wide scattering of data points, suggesting many other factors are at play, which I want to understand.

In particular it’s notable that the data points close to the line in the bottom-right are in the central city, while most of the data points in the top-right are mostly in the suburbs (they are also the same land use types that were an exception in the last chart – Melbourne Airport, hospitals, some university campuses, and activity centres).

As always, it’s interesting to look at the outliers, which I am going to consider by land use category.

Melbourne Airport

The airport destination zone has around 62% paid parking and around 92% private transport mode share for general trips (noting the VISTA survey is only of travel by Melbourne and Geelong residents). The airport estimates 14% of non-transferring passengers use some form of public transport, and that 27% of weekday traffic demand is employee travel.

Some plausible explanations for high private mode share despite paid parking include:

  • shift workers travelling when public transport is infrequent or unavailable (I understand many airport workers commence at 4 am, before public transport has started for the day),
  • unreliable work finish times (for example, if planes are delayed),
  • longer travel distances making public transport journeys slower and requiring transfers for many origins,
  • travellers with luggage finding public transport less convenient,
  • highly time-sensitive air travellers who might feel more in control of a private transport trip,
  • active transport involving long travel distances with poor infrastructure, and
  • many travel costs being paid by businesses (not users).

It’s worth noting that the staff car park is remote from the terminal buildings, such that shuttle bus services operate – an added inconvenience of private transport. But by the same token, the public transport bus stops are a fairly long walk from terminals 1 and 2.

The destination zone that includes the airport terminals also includes industrial areas on the south side of the airport. If I aggregate only the surveyed trips with a destination around the airport terminals, that yields 69% paid parking, and 93% private mode share. Conversely, the industrial area south of the airport yields 6% paid parking, and 100% private mode share.

Hospitals

Almost all hospitals are above the line – i.e. high private mode share despite high rates of paid parking.

The biggest outliers are the Monash Medical Centre in Clayton, Austin/Mercy Hospitals in Heidelberg, and Sunshine Hospital in St Albans South.

The Heidelberg hospitals are adjacent to Heidelberg train station. The Monash Medical Centre at Clayton is within 10 minutes walk of Clayton train station where trains run every 10 minutes or better for much of the week, and there’s also a SmartBus route out the front. Sunshine Hospital is within 10 minutes walk of Ginifer train station (although off-peak services mostly run every 20 minutes).

It’s not like these hospitals are a long way from reasonably high quality public transport. But they are a fair way out from the CBD, and only have high quality public transport in some directions.

The DZ containing Royal Melbourne Hospital, Royal Women’s Hospital, and Victoria Comprehensive Cancer Centre in Parkville is the exception below the line. It is served by multiple high frequency public transport lines, and serves the inner suburbs of Melbourne (also well served by public transport) which might help explain its ~45% private transport mode share.

The Richmond hospital DZ group is close to the line – but this is actually a blend of the Epworth Hospital and many adjacent mixed land uses so it’s not a great data point to analyse unfortunately.

So what might explain high private transport mode shares? I think there are several plausible explanations:

  • shift workers find public transport infrequent, less safe, or unavailable at shift change times (similar to the airport),
  • visitors travel at off-peak times when public transport is less frequent,
  • longer average travel distances (hospitals serve large population catchments with patients and visitor origins widely dispersed),
  • specialist staff who work across multiple hospitals on the same day,
  • patients need travel assistance when being admitted/discharged, and
  • visitor households are time-poor when a family member is in hospital.

The Parkville hospital data point above the line is the Royal Children’s Hospital. Despite having paid parking and being on two frequent tram routes, there is around 80% private transport mode share. This result is consistent with the hypotheses around time-poor visitor households, patients needing assistance when travelling to/from hospitals, and longer average travel distances (being a specialised hospital).

We can also look at census journey to work data for hospitals (without worrying about small survey sample sizes). Here’s a map showing the relative size, mode split and location of hospitals around Melbourne (with at least 200 journeys reported with a work industry of “Hospital”):

It’s a bit congested in the central city so here is an enlargement:

The only hospitals with a minority private mode share of journeys to work are the Epworth (Richmond), St Vincent’s (Fitzroy), Eye & Ear (East Melbourne), and the Aboriginal Health Service (Fitzroy) (I’m not sure that this is a hospital but it’s the only thing resembling a hospital in the destination zone).

Here’s another chart of hospitals showing the number of journeys to work, private transport mode share, and distance from the Melbourne CBD:

Again, there’s a very strong relationship between distance from the CBD and private transport mode share.

Larger hospitals more than 10 km from the CBD (Austin/Mercy, Box Hill, Monash) seem to have slightly lower private mode shares than other hospitals at a similar distance, which might be related to higher parking prices, different employee parking arrangements, or it might be that they are slightly closer to train stations.

The (relatively small) Royal Talbot Hospital is an outlier on the curve. It is relatively close to the CBD but only served by ten bus trips per weekday (route 609).

To test the public transport quality issue, here’s a chart of journey to work private mode shares by distance from train stations:

While being close to a train station seems to enable lower private transport mode shares, it doesn’t guarantee low private transport mode shares. The hospitals with low private transport mode shares are all in the central city.

So perhaps the issue is as much to do with the public transport service quality of the trip origins. The hospitals in the suburbs largely serve people living in the suburbs which generally have lower public transport service levels, while the inner city hospitals probably more serve inner city residents who generally have higher public transport service levels and lower rates of motor vehicle ownership (see: What does the census tell us about motor vehicle ownership in Australian cities? (2006-2016)).

Indeed, here is a map showing private transport mode share of non-walking trips by origin SA2:

Technical notes: grey areas are SA1s (within SA2s) with no survey trips.

Finally for hospitals, here is private transport mode share of journeys to work (from the census) compared to paid parking % from VISTA (note: sufficient paid parking data is only available for some hospitals, and we don’t know whether staff have to pay for parking):

There doesn’t appear to be a strong relationship here, as many hospitals with high rates of paid parking also have high private transport mode shares.

In summary:

  • The distance of a hospital from the CBD seems to be the primary influence on mode share.
  • Specialised hospitals with larger catchments (eg Children’s Hospital) might have higher private transport mode shares.
  • The quality of public transport to the hospital seems to have a secondary impact on mode shares.

Activity centres

Suburban activity centres such as Frankston, Box Hill, Dandenong, and Springvale have high private mode shares, which might reflect lower public transport service levels than the inner city (particularly for off-rail origins).

Box Hill is the biggest outlier for activity centres in terms of high private mode share despite paid parking. But compared to other destinations that far from the Melbourne CBD, it has a relatively low private transport mode share. It is located on a major train line, and is served by several frequent bus routes.

In general, there are fewer reasons why increased public transport investment might not lead to higher public transport mode share compared to airports and hospitals. Travel distances are generally shorter, many people will be travelling in peak periods and during the day, there are probably few shift workers (certainly few around-the-clock shift workers).

University campuses

The biggest university outliers above the line (higher private mode shares and higher paid parking %) are Deakin University (Burwood) and La Trobe University (Kingsbury). Furthermore, private transport also has a majority mode share for Monash University Clayton, Victoria University Footscray Park, Monash University (Caulfield) and Swinburne University (Hawthorn).

As discussed earlier, I suspect the rates of paid parking may be understated for university campuses because people forget they have purchased long-term parking permits.

The following chart shows the full mode split of trips to the University DZ groups in various SA2s (this time including walking trips):

Of the campuses listed, only Hawthorn and Caulfield are adjacent to a train station. Of the off-rail campuses:

  • Parkville (Melbourne Uni, 43% public transport) is served by multiple frequent tram routes, plus a high frequency express shuttle bus to North Melbourne train station. In a few years it will also have a train station.
  • Clayton (Monash, 22% PT) is also served by a high frequency express shuttle bus service to Huntingdale train station.
  • Burwood (Deakin, 19% PT) is on a frequent tram route, but otherwise moderately frequent bus services (its express shuttle bus service to Box Hill train station – route 201 – currently runs every 20 minutes)
  • Footscray (Park) (Victoria Uni, 14% PT) has bus and tram services to Footscray train station but they operate at frequencies of around 15 minutes in peak periods, and 20 minutes inter-peak.
  • Kingsbury (La Trobe Uni, 13% PT) has an express shuttle bus service from Reservoir station operating every 10 minutes on weekdays (introduced in 2016).

The success of high frequency express shuttle bus services to Parkville and Clayton may bode well for further public transport frequency upgrades to other campuses.

University campuses are also natural targets for public transport as university students on low incomes are likely to be more sensitive to private motoring and parking costs.

However university campuses also have longer average travel distances which might impact mode shares – more on that shortly.

Central city

Most central city DZ groups are in the bottom-right of the scatter plot, but there are some notable exceptions:

  • A Southbank DZ around Crown Casino has 65% paid parking and 70% private transport mode share. This was also an exception when I analysed journey to work (see: How is the journey to work changing in Melbourne? (2006-2016)) and might be explained be relatively cheap parking, casino shift workers, and possibly more off-peak travel (eg evenings, weekends).
  • Similarly, a Southbank DZ group around the Melbourne Convention and Exhibition Centre / South Wharf retail complex has 62% paid parking and around 74% private mode share. Many parts of this area are a long walk from public transport stops, and also there are around 2,200 car parks on site (with $17 early bird parking at the time of writing).
  • Albert Park – a destination zone centred around the park – has around 54% paid parking and 87% private transport mode share. Most of the VISTA survey trips were recreation or sport related, which may include many trips to the Melbourne Sports and Aquatic Centre. The park is surrounded by tram routes on most sides, but is relatively remote from the (rapid) train network.
  • Northern Docklands shows up with around 50% paid parking and around 88% private transport mode share, despite being very close to the Melbourne CBD. While this area is served by multiple frequent tram routes, it is a relatively long walk (or even tram ride) from a nearby a train station (from Leven Avenue it is 16 minutes by tram to Southern Cross Station and around 18 minutes to Flagstaff Station, according to Google). The closest train station is actually North Melbourne, but there is currently no direct public transport or pedestrian connection (the E-gate rail site and future Westgate Tunnel road link would need to be crossed).

Inner suburbs

Some places to the bottom-left of the cloud on the chart include inner suburban areas such as South Yarra, Fitzroy, Richmond, Abbotsford, Brunswick, and Collingwood. While paid parking doesn’t seem to be as common, private transport mode shares are relatively low (even when walking trips are excluded). These areas typically have dense mixed-use activity with higher public transport service levels, which might explain the lower private transport mode shares. These areas probably also have a lot of time-restricted (but free) parking.

What is the relationship between paid parking and journey to work mode shares?

For journeys to work we thankfully have rich census data, with no issues of small survey sample sizes.

The following chart combines VISTA data on paid parking, with 2016 census data on journey to work mode shares (note: the margin of error on the paid parking percentage is still up to +/-12%).

The pattern is very similar to that for general travel, and the relationship is of a similar strength (r-squared = 0.59).

There are more DZ groups below the line on the left side of the chart, meaning that the private transport mode share of journeys to work is often lower than for general travel.

Indeed, here is a chart comparing private transport mode share of general travel (VISTA survey excluding walking and trips to go home) with journeys to work (ABS census):

Note the margin of error for private transport mode shares is around +/-10% because of the small VISTA sample sizes.

For most DZ groups of all types, private transport mode shares are lower for journeys to work compared to general travel (ie below the diagonal line). This might reflect public transport being more competitive for commuters than for visitors – all-day parking might be harder to find and/or more expensive. This suggests investment in public transport might want to target journeys to work.

The DZ groups above the line include Flemington Racecourse (census day was almost certainly not a race day so there was probably ample parking for employees, while many VISTA survey trips will be from event days), Deakin Uni (Burwood), and a few others. Some of these DZ groups are dominated by schools, where workers (teachers) drive while students are more likely to cycle or catch public transport.

What about public transport mode shares?

The following chart shows VISTA public transport mode shares (for general travel) against paid parking percentages:

There are similar patterns to the earlier private transport chart, but flipped. The outliers are very similar (eg hospitals and Melbourne Airport in the bottom-right), although the top-left outliers include some destinations in socio-economically disadvantaged areas (eg Braybrook, Broadmeadows, Dandenong).

The DZ group in Blackburn South with no paid parking but 22% public transport mode share contains several schools but otherwise mostly residential areas, and the survey data includes many education related trips.

Are shift workers less likely to use public transport?

Shift workers at hospitals, Melbourne Airport, and the casino might be less likely to use public transport because of the inconvenience of travelling at off-peak shift change times, when service levels may be lower or non-existent.

Here’s a chart showing the mode split of VISTA journeys to work by destination type categories, and also type of working hours:

For hospitals, rostered shifts had a lower public transport mode share, compared to fixed and flexible hours workers, so this seems to support (but not prove) the hypothesis.

Public transport use is actually higher for rostered shift workers at other destination types, but I suspect these are mostly not around-the-clock shifts (eg retail work), and are more likely to be lower paid jobs, where price sensitivity might contribute more to mode choice.

Unfortunately there are not enough VISTA journey to work survey responses for Melbourne Airport to get sensible estimates of mode shares for different work types.

Do longer travel distances result in lower public transport mode shares?

Another earlier hypothesis was that destinations that attract longer distance trips (such as universities, hospitals, and airports) are more likely to result in private transport mode choice, as public transport journeys are more likely to require one or more transfers.

Trip distances to specialised places such as airports, suburban employment areas, universities and hospitals are indeed longer. But the central city also rates here and that has low private transport mode shares.

Digging deeper, here are median travel distances to DZ groups around Melbourne:

The central city has higher median trip distances but low private mode shares, while many suburban destinations (particularly employment/industrial areas, universities, and hospitals) have similar median travel distances but much higher public transport mode shares.

I think a likely explanation for this is that public transport to the central city is generally faster (often involving trains), more frequent, and involves fewer/easier transfers. Central city workers are also more likely to live near radial public transport lines. On the other hand, the trip origins for suburban destinations are more likely to be in the suburbs where public transport service levels are generally lower (compared to trip origins in the inner suburbs).

Cross-suburban public transport travel will often require transfers between lower frequency services, and will generally involve at least one bus leg. Very few Melbourne bus routes are currently separated from traffic, so such trips are unlikely to be as fast as private motoring (unless parking takes a long time to find), but they might be able to compete on marginal cost (if there is more expensive paid parking).

Of course this is not to suggest that cross-suburban public transport cannot be improved. More direct routes, higher frequencies, and separation from traffic can all make public transport more time-competitive.

How does parking pricing relate to employment density?

My previous research has confirmed a strong relationship between job density and lower journey to work private transport mode shares (see: What explains variations in journey to work mode shares between and within Australian cities?). Can this be explained by more paid parking in areas with higher job density?

The following chart compares weighted job density (from census 2016) and paid parking percentages (from VISTA):

Technical notes: Weighted job density is calculated as a weighted average of the job densities of individual destination zones in a DZ group, with the weighting being the number of jobs in each zone (the same principle as population weighted density). I have used a log-scale on the X-axis, and not shown DZ groups with less than 1 job/ha as they are not really interesting

There appears to be a relationship between job density and paid parking – as you would expect. The top right quadrant contains many university campuses, hospitals, and central city areas with high job density and high paid parking percentages.

In the bottom-right are many large job-dense shopping centres that offer “free” parking. Of course in reality the cost of parking is built into the price of goods and services at the centres (here’s a thought: what if people who arrive by non-car modes got a discount?). An earlier chart showed us that employees are less likely to commute by private transport than visitors.

The outliers to the top-left of the chart are actually mostly misleading. An example is Melbourne Airport where the density calculation is based on a destination zone that includes runways, taxiways, a low density business park, and much green space. The jobs are actually very concentrated in parts of that zone (e.g. passenger terminals) so the density is vastly understated (I’ve recommended to the ABS that they create smaller destination zones around airport terminal precincts in future census years).

Inclusion of significant green space and/or adjacent residential areas is also an issue at La Trobe University (Kingsbury data point with just under 50% mode share), RMIT Bundoora campus (Mill Park South), Royal Children’s Hospital (Parkville), Sunshine Hospital (St Albans South), Victoria University (Footscray (Park)), Albert Park (the actual park), and Melbourne Polytechnic Fairfield campus / Thomas Embling Hospital (Yarra – North).

I am at a loss to explain paid parking in Mooroolbark – the only major employer seems to be the private school Billanook College.

Can you summarise the relationship between paid parking and mode shares?

I know I’ve gone down quite a few rabbit holes, so here’s a summary of insights:

  • Distance from the Melbourne CBD seems to be the strongest single predictor of private transport mode share (as origin or destination). This probably reflects public transport service levels generally being higher in the central city and lower in the suburbs. Destinations further from the central city are likely to have trip origins that are also further from the central city, for which public transport journeys are often slower.
  • Paid parking seems to be particularly effective at reducing private transport mode shares at university campuses, and the impact is probably greater if there are higher quality public transport alternatives available.
  • There’s some evidence to suggest paid parking may reduce private transport mode shares at larger activity centres such as Box Hill and Frankston.
  • Most hospitals have very high private transport mode shares, despite also having paid parking. Hospitals with better public transport access have slightly lower private transport mode shares.
  • Destinations with around-the-clock shift workers (e.g. hospitals and airports) seem generally likely to have high private transport mode shares, as public transport services at shift change times might be infrequent or unavailable.
  • Suburban destinations that have longer median travel distances (such as hospitals, airports and industrial areas) mostly have higher private transport mode shares.
  • Even if there isn’t much paid parking, destinations well served by public transport tend to have lower private transport mode shares (although this could be related to time-restricted free parking).

If you’d like more on factors influencing mode shares, I’ve also explored this more broadly elsewhere on this blog, with employment density (related to parking prices), cycling infrastructure quality, proximity to rapid public transport, and walking catchment density found to be significant factors (see: What explains variations in journey to work mode shares between and within Australian cities?).

Are places with paid parking good targets for public transport investments?

Many of my recent conversations with transport professionals around this topic have suggested an hypothesis that public transport wins mode share in places that have paid parking. While that’s clearly the case in the centre of Melbourne and at many university campuses, this research has found it’s more of a mixed story for other destinations.

While this post hasn’t directly examined the impact of public transport investments on mode shares in specific places, I think it can inform the types of destinations where public transport investments might be more likely to deliver significant mode shifts.

Here’s my assessment of different destination types (most of which have paid parking):

  • Suburban hospitals may be challenging due to the presence of shift workers, patients needing assistance, visitors from time-poor households, and long average travel distances making public transport more difficult for cross-suburban travel. There’s no doubt many people use public transport to travel to hospitals, but it might not include many travellers who have a private transport option.
  • Larger activity centres with paid parking show lower private transport mode shares. Trips to these centres involve shorter travel distances that probably don’t require public transport transfers, and don’t suffer the challenges of around-the-clock shift workers, so they are likely to be good targets for public transport investment.
  • Universities are natural targets for public transport, particularly as many students would find the cost of maintaining, operating and parking a car more challenging, or don’t have access to private transport at all (around 35% of full time university/TAFE students do not have a full or probationary licence according to the VISTA sample). Universities do attract relatively higher public transport mode shares (even in the suburbs) and recent investments in express shuttle services from nearby train stations appear to have been successful at growing public transport patronage.
  • Melbourne Airport has high rates of paid parking and private transport mode share. It is probably a challenging public transport destination for employees who work rostered shifts. However already public transport does well for travel from the CBD, and this will soon be upgraded to heavy rail. Stations along the way may attract new employees in these areas, but span of operating hours may be an issue.
  • Job dense central city areas that are not currently well connected to the rapid public transport network could be public transport growth opportunity. In a previous post I found the largest journey to work mode shifts to public transport between 2011 and 2016 were in SA2s around the CBD (see: How is the journey to work changing in Melbourne? (2006-2016)). The most obvious target to me is northern Docklands which is not (yet) conveniently connected its nearby train station. Public transport is also gaining patronage in the densifying Fishermans Bend employment area (buses now operate as often as every 8 minutes in peak periods following an upgrade in October 2018).
  • Lower density suburban employment/industrial areas tend to have free parking, longer travel distances, and very high private transport mode shares. These are very challenging places for public transport to win significant mode share, although there will be some demand from people with limited transport options.

An emerging target for public transport might be large shopping centres that are starting to introduce paid or time-restricted car parking (particularly those located adjacent to train stations, e.g. Southland). That said, Westfield Doncaster, which has some paid parking (around 19%), has achieved only 6% public transport mode share in the VISTA survey (n=365), athough this may be growing over time. Meanwhile, Dandenong Plaza has around 16% public transport mode share despite only 6% paid parking.

Upgraded public transport to shopping centres might be particularly attractive for workers who are generally on lower incomes (we’ve already seen staff having lower private transport mode shares than visitors). Also, customer parking may be time-consuming to find on busy shopping days, which might make public transport a more attractive option, particularly if buses are not delayed by congested car park traffic.

There’s a lot going on in this space, so if you have further observations or suggestions please comment below.

Appendix: About destination group zones

Here is a map showing my destination zone groups in the central city area which have 15% or higher paid parking. Each group is given a different colour (although there are only 20 unique colours used so there is some reuse). The numbers indicate the number of surveyed parking trips in each group:

Some of the DZ groups have slightly less than 40 parking trips, which means they are excluded from much of my analysis. In many cases I’ve decided that merging these with neighbouring zones would be mixing disparate land uses, or would significantly dilute paid parking rates to not be meaningful (examples include northern Abbotsford, and parts of Kew and Fairfield). Unfortunately that’s the limitation of the using survey data, but there are still plenty of qualifying DZ groups to inform the analysis.

I have created destination zone groups for most destination zones with 10%+ paid parking, and most of the inner city area to facilitate the DZ group private transport mode share chart. I haven’t gone to the effort of creating DZ groups across the entire of Melbourne, as most areas have little paid parking and are not a focus for my analysis.


What might explain journey to work mode shifts in Australia’s largest cities?

Mon 28 May, 2018

[Updated 29 June 2018 with further analysis of parking levies and their impact]

Between 2011 and 2016, journey to work public transport mode shares went up significantly in Melbourne and Sydney but dropped significantly in Perth and Brisbane. Private transport mode shifts did the opposite. Can this be explained by the changing distribution of jobs within cities, or other factors such as changes in transport costs?

In a recent post focused on Brisbane I found that stronger growth in suburban jobs relative to central city jobs could explain around half of the city’s mode shift towards private transport, with other factors (mostly the changes in relative attractiveness of modes) explaining the rest.

So how is job distribution changing in other Australian cities? How much of the mode shifts can be attributed to changing job distribution and how much could be attributed to other factors like changes in transport costs, or increasing employment density?

(for details about how I define public, private and active transport, see the appendix in this post)

How is job distribution changing in Australian cities?

Here’s a view of the changing distribution of all jobs within each city by workplaces distance from the city centre.

(Unfortunately I only have 2006 data for Sydney and Melbourne)

The changes are relatively subtle, but if look at how the bands shift between years, you’ll see increasing centralisation in Sydney but a decentralisation in all other cities between 2011 and 2016.

The strongest decentralisation was in Brisbane and Perth, which also showed the biggest increases in private transport mode share.

However Melbourne saw both a slight decentralisation of jobs and a mode shift away from private transport between 2011 and 2016.

So we need to dig deeper to find out what’s going on here.

How does private mode share vary by distance from the city centre?

The following chart shows private transport mode shares by distance from the city centre for the last two or three censuses for each city. The darkest line for each city is for 2016, with lighter lines being previous years (I only have 2006 data for Melbourne and Sydney).

There’s a clear pattern in all cities that private mode shares are lower in areas closer to the city centre, with Sydney the lowest, followed by Melbourne, Brisbane, Perth, Adelaide, and Canberra (which is also the order of their population size).

Notably Sydney private mode share averaged lower than 90% out as far as 24km from the city centre, whereas Adelaide sees 90% mode shares as close as 2km from the city centre.

If you look carefully you can see that Brisbane increased private transport mode shares in the central city between 2011 and 2016, while private mode shares dropped or were stable in all other cities at most distances.

You can also see that the central city mode shifts away from private transport were largest in Melbourne, something I’ll come back to.

Here’s the same again but for public transport:

Sydney and Melbourne saw mode shifts to public transport at most distances from the city centre, unlike all other cities.

What mode shift can we attribute to changing job distributions?

A city’s mode share (measured by place of work) will be fundamentally impacted by two types of changes between censuses:

  • Changes in the volume of jobs in each SA2 – because different SA2s generally have different mode shares due to factors like proximity to the city centre and public transport access. If there is stronger jobs growth in areas that already had lower private mode shares, you would get a mode shift away from private transport, all other things being equal.
  • Changes in the mode share in each SA2 – because different modes became more or less attractive for commuters between census years. This might be due to changes in public transport service quality, transport infrastructure provision, and relative changes in the cost of public transport, private motoring, and commuter parking. It could also be influenced by broader demographic changes.

For each city I have calculated what the city-level private transport mode share would have been in 2016, had mode shares in each workplace SA2 remained exactly the same as 2011, but the job volumes in each SA2s had still changed. The city level mode shift due to SA2 volume changes is then the difference between this hypothetical 2016 mode share and the 2011 mode share. The remainder of the city-level mode shift between 2011 and 2016 results can then be attributed to mode shifts at the SA2 level.

Here’s a chart showing the mode shift impact of both volume changes at the SA2 level, and mode shifts at the SA2 level:

As we noted above, Sydney saw a slight trend to centralisation of jobs between 2011 and 2016, and it had the largest volume change attributed reduction in private mode share (-0.4%). However other factors were responsible for a further 2.5% of the mode shift away from private transport.

The story is similar in Melbourne but to a smaller magnitude in both aspects. Both of these cities also saw increasing inner city job density – which matters – and I’ll back come to that in a moment.

In Brisbane you can see that the total mode shift towards private transport was roughly equally attributable to SA2 volume changes and SA2 mode shifts (as I discussed in my earlier post).

Perth had an overall 1.3% mode shift to private transport, and the majority of this was due to significant jobs growth in the suburbs compared to the CBD (in fact, the SA2 with the largest jobs growth was Murdoch in the southern suburbs). But there were also other factors that led to a mode shift to private transport.

In Canberra – Queanbeyan, volume changes by themselves would have seen a mode shift to private transport, but other factors were larger and led to an overall mode shift away from private transport (although it is actually complicated because the 2011 census day was in a federal parliamentary sitting week, while 2016 was not).

Nothing much changed in Adelaide.

Next I’m going to explore what could be behind the mode shifts at SA2 level, in terms of job density and real transport costs.

Can increases in workplace density impact mode shares?

As discussed in my Brisbane analysis, if the relative attractiveness of modes hadn’t changed, you might still expect a mode shift to public transport in high density employment areas with increasing jobs numbers because you would expect the cost of parking provision to increase with increasing land use density (i.e. more competition for space).

Indeed, in Sydney and Melbourne a number of inner city SA2s became significantly more job dense between 2011 and 2016, and also saw mode shifts away from private transport:

(inspect this data in Tableau)

A similar thing happened in Civic (the main centre of Canberra).

But Adelaide and Perth saw both declining job density and declining private transport mode share, which suggests something else is at play.

Job density didn’t really go down in Brisbane – see my Brisbane post for an explanation (basically, ABS redrew the SA2 boundary along the Brisbane River).

Could changes in the real cost of transport be causing mode shifts?

The following chart shows the real change in urban transport fares in Australian cities since 2000, as measured by the ABS as part of the Consumer Price Index series (which unfortunately includes public transport, taxis, and “ride share” but is for a representative sample of journeys so hopefully mostly dominated by public transport fares):

The lines are somewhat saw-toothed because public transport fares generally only rise once a year, and become better value in real terms over the course of the following 12 months.

Many cities have seen above-CPI public transport fare increases at various times, most notably Brisbane in 2010-2014. Melbourne has had above CPI fare increases, but also reduced zone 1+2 fares in 2015 which lead to a reduction on the ABS measure (the fare reduction only really applied to people travelling across zones 1 and 2 – which roughly summarised means travel between the outer and inner suburbs). Brisbane fares peaked in 2014, which was followed by a freeze and then a large reduction in 2017.

By contrast, here is the (negative) growth in the cost of “private motoring” (which includes vehicles, fuel and maintenance):

Private motoring costs have declined in real terms since 2000, although they increased a little during the second half of 2017.

The next chart shows the change in ratio between the two costs. Urban transport fares have become less competitive than private motoring over time in all cities:

But if we are looking at changes between census figures, we should probably also look at cost changes between the times of each census. Here’s how prices changed in real terms between the September quarters of 2011 and 2016 (which cover the August census dates):

The real cost of private motoring dropped in all cities, but so did the real “average” cost of urban transport fares in Sydney and Melbourne (the Melbourne drop being mostly around large fare reductions for travel across zones 1 and 2).

The biggest differences in cost changes were in Brisbane and Perth (around 18%), which I think will go a fair way to explaining why these cities had the biggest shifts to private transport attributable to SA2 mode shifts.

Brisbane saw a rapid increase in public transport fares between 2011 and 2014 which is likely to have changed many commuting habits, but those habits may or may not have changed back when fares were subsequently reduced (e.g. if someone bought a car due to fare increases, they may not have subsequently sold their car when fares reduced). Perth certainly had less mode shift at the SA2 level compared to Brisbane, which might support this hypothesis.

What about changes in car parking costs?

The ABS CPI’s private motoring cost index does not include car parking costs – which would be difficult as they vary considerably with geography.

However we do know about central city car parking levies that governments charge in a bid to reduce road congestion and fund inner city transport initiatives. Sydney, Melbourne, and Perth apply levies to central city non-residential car parking spaces, and ultimately these levies will need to be recovered through parking prices.

I’ve calculated these levies in 2017 dollars (adjusting for inflation as measured in June quarters), and here’s how they have changed since 2000:

Melbourne increased its central city parking levy by 40% per space in 2014 (category 1), and created a new lower-priced levy area in some neighbouring areas to the north and south in 2015 (category 2, see map). This is likely to have contributed to the larger mode shifts away from private transport in the central city area of Melbourne compared to most other cities (particularly considering there were similar changes in average private motoring and urban transport fares in Melbourne between 2011 and 2016).

Sydney’s category 1 fee applies in the Sydney CBD area, Milsons Points and North Sydney. It was $2390 in 2017, and has only risen with indexation since 2009 (when it was doubled). A lower category 2 levy applies in the business districts centres of Bondi Junction, Chatswood, Parramatta, and St Leonards.

Perth has an annual licence fee per bay which ranged from $1039 to $1169 in 2017.  The Perth fee was increased by around 167% in 2010, and there were also above-inflation increases from 2014. The fee increased 63% in real terms between 2011 and 2016 for “long stay” spaces, and 69% for “tenant” spaces.

I am not aware of any such fees or levies in place in Brisbane or Adelaide (a proposal for Adelaide was voted down).

So how are CBD parking prices changing?

Unfortunately good data is a little hard to find, but this Colliers Car Parking White Paper provides “average daily rates” for CBDs for 2009-2015, and early bird rates for 2015. I expect most commuters would pay early bird rates – which average between 28% and 62% of daily rates depending on the city (quite some variation!). I’ve adjusted the pre-2015 figures for inflation to be in 2015 dollars:

In real terms, “average daily” parking costs have declined in Melbourne, rocketed up in Brisbane and Canberra, and moved less in Sydney and Perth. I don’t know whether these reflect trends in early bird prices. And we don’t know how prices changed between 2015 and the census year of 2016.

So how much are parking levies contributing to parking prices?

I have to make some assumptions (guesstimates) here. Regular weekdays represent about 60% of the days of the year. If we assume say 80% of the levy is recovered from weekday commuter parking (there generally being less demand for parking on weekends), we can calculate the average weekday commuter cost of the levy to be 27% of the Sydney early bird price, 25% of the Melbourne early bird price, and 15% of the Perth early bird price. Certainly not insignificant.

Here’s a summary of the levy and “average daily” price changes and mode shifts in the central city parking levy areas:

Changes 2011 to 2016
Parking levy area or CBD SA2 Levy real increase Average daily real price change (2011 to 2015) Private mode shift New private trips Private share of new trips
Perth 63% -5% -0.8% -60 -3%
Melbourne – category 1 40% -11% -5.3% 3200 5%
Melbourne – category 2 (new) n/a -6.4% 5315 30%
Sydney CBD 0% +1% -2.6% 6204 9%
Brisbane City SA2 n/a +64% +1.7% 3135 68%
Adelaide SA2 n/a -11% -1.5% 2567 35%
Canberra Civic SA2 n/a +71% -3.2% 746 30%

Firstly, “average daily” parking prices don’t seem to be following the changes in parking levies in Perth and Melbourne (category 1 area). Other factors influencing parking prices will include supply (influenced by competition for real estate and planning rules) and demand (influenced by employment density) with the market ultimately determining prices.

Car park operators appear to be absorbing the increased cost of the levy (although we don’t know the trends in early bird prices so we cannot be entirely sure). But that’s not to say that the levy hasn’t had any impact on prices – for example, the price reductions might have been larger if the levies had not increased.

Secondly, price changes do not appear to be correlated with mode shifts as you might expect (except Canberra). Brisbane prices increased dramatically, but so did private mode share! Price reductions in Perth, Adelaide, and Melbourne did not result in increased private transport shares.

Maybe other factors are driving mode shift away from private transport in those cities. Maybe early bird prices are trending differently to “average daily” prices. Maybe increased traffic congestion persuaded people to shift modes. Maybe there were significant price changes between 2015 and 2016. Maybe most existing public transport users were not aware of reductions in parking prices.

I don’t know what happened to parking prices in the new category 2 areas of Melbourne but there was a large mode shift away from private transport (-6.4%), and they may well be linked. Indeed, Infrastructure Victoria has recently recommended the category 2 area be expanded to include the inner-eastern suburbs of Richmond, South Yarra, Windsor and Prahran. And the Grattan Institute has recommended increasing the levy to match Sydney’s rates.

Curiously, when I look at City of Melbourne Census of Land Use and Employment (CLUE) data, the category 1 area (approximated with CLUE areas) had an increase of only around 367 non-residential parking bays between 2011-12 and 2015-16 (a four year period), a lot less than the additional 3200 private trips, which might suggest increased average occupancy.

Also, it is likely that a significant portion of people who drive to city centres are not paying for their parking costs (eg employer provided car parking). Employers may simply be absorbing price increases.

For more interesting discussion and research about car parking in the City of Melbourne, see a recent discussion paper and background report prepared by Dr Elizabeth Taylor.

Did changes in population distribution impact mode shares?

While this post has been focused on changes by workplace location, it is possible to separate the overall mode shifts into the two components by home location. Here are the results:

In Sydney, Melbourne, and Canberra, stronger population growth in areas that already had low private mode shares in 2011 made a small contribution to overall mode shifts away from private transport. These cities have all seen densifying population in inner city areas better served by public transport.

The distribution of population growth in Perth and Brisbane had a small effect in the opposite direction.

And again, nothing much changed in Adelaide.

What about active transport?

Cycling-only mode share was pretty stable in most cities (except Canberra up 0.2%). Walking-only mode share declined in Sydney (-0.2%), Brisbane (-0.3%), Adelaide (-0.4%), Perth (-0.3%) but was steady in Melbourne and increased in Canberra (+0.2%). So Canberra has the biggest shift to active transport.

Can you summarise all that?

If your head is spinning with all that information, here’s a summary of what some of the major factors could be in each city between 2011 and 2016. I say “could be” because I’ve not looked at every possible factor influencing mode share.

Sydney: the 2.9% mode shift away from private transport was probably mostly to do with increasing job density in employment centres (more on that in my next post), but was also partly by a shift to more centralised jobs, and increasing population density in places well served by public transport.

Melbourne: The 1.8% mode shift away from private transport probably had a fair bit to do with increasing central city job density, the significant spatial expansion of the central city parking levy area and rates (although we don’t know if early bird prices also rose), a reduction in some public transport fares, and strong population growth in areas well served by public transport.

Brisbane: The 1.9% mode shift towards private transport appears roughly half about the decentralisation of jobs, and half the reduced attractiveness of public transport – particularly following significant fare rises between 2010 and 2014, and possibly/arguably declines in service quality.

Perth: The 1.2% mode shift towards private transport was probably mostly due to a decentralisation of jobs, and partly due to public transport becoming less cost competitive with private transport (despite an increase in the central city parking levy). Urban sprawl is probably also a factor.

Adelaide: The 0.2% mode shift to private transport is probably mostly due to public transport becoming less cost competitive with private transport. Changes in job and population distribution, and employment density do not appear to have had a significant impact.

Canberra:  The 1.0% mode shift away from private transport was probably the result of competing forces of higher jobs growth in car-dominated workplace areas with increasing job density in dense employment centres, increasing central city parking prices, higher population growth in areas better served by public transport (and possibly cycling facilities), and also the fact census 2016 was not a parliamentary sitting week while 2011 was (so really, it’s hard to be too sure!).

You might want to add your own views about changes in the service quality of public transport and cycling infrastructure in each city. I also haven’t looked at the impact of major new public transport infrastructure and service initiatives (such as the opening of new train stations), which we know does impact mode shares at a local level (maybe that’s for a future post).

I hope you found this interesting. My next post will look at suburban employment centres, and their role in changing mode shares in cities.