How Aus $ affects Aus votes

How Aus $ affects Aus votes

by | 11 May, 2016 | Australia, data, education, income, politics, social issues

There is no correlation between an electorate’s socio-economic standing and its preferred political party, at least not in the 2013 elections.

The simplistic view of politics suggests one party proposes policies which help poor people and the other party angles to improve the lives of those more fortunate. Yet, in Australia, the socio-economic make-up of an electorate is a very poor predictor of which party will be voted in, at least not nation-wide. It seems Labor electorates are not the working class suburbs usually portrayed, and Liberal electorates aren’t the prime real estate so often generalised.

This is clearly seen when focusing on the top 10 Liberal/National coalition seats.

Top 10 Liberal Seats

As the graph above shows, the ‘rich’ are grossly under-represented in the top 3 ‘liberal/national’ seats, and in three more of the safest Liberal seats.  On the other hand, they are hugely overrepresented in the other 4 of the top 10 seats (averaging 85% of each overrepresented electorate).  As an example, Mallee, on the NSW/Victorian border, has the highest Liberal vote, yet over 50% of the population falls in the bottom 30%, and only 6% are considered in the top 30% of Australia.

The graph below examines the link across all the electorates, by mapping the Labor 2-party preferred vote to the percentage of the electorate which falls in the bottom 30% of the socio-economic spectrum. (It’s a mess!)

Link Labour SEIFA

Similarly, there appears to be no relationship between party allegiance and private schooling.  For all the apparent willingness of the Liberal party to support private schools, areas with a high percentage of kids attending private school are just as likely to vote blue as they are red.

Liberal Private schools

While it seems there is no link between ‘class’ and politics Australia wide, a relationship does exist within capital cities.  Filtering out electorates which have less than two-thirds of its population within a capital city (using ABS’s remoteness divisions), a correlation of 0.51 appears between the Labor vote and areas with high proportions of low socio-economic households.  This means that the larger the percentage of ‘lower class’ households in an electorate, the more likely Labor is to win the seat.  Similarly, the more rich households there are in a city electorate, the more likely the Liberal Party is to win.

(Graph slightly less messy.)

Link in Cities

No such link appears to occur outside of the major cities, neither in regional cities nor in rural areas.

So, are parties not catering to one side over the other, or are constituents unable to discern how each party’s policies will affect them, or do people not vote based on what may benefit them? Or is politics a whole lot more complicated than that?

 

 

______________________________

 

Sources

Voting from Australian Electorate Commission http://results.aec.gov.au/17496/Website/HouseDownloadsMenu-17496-csv.htm

Socio-economic and School attendance from ABS, Census Statistics.

http://www.abs.gov.au/websitedbs/censushome.nsf/home/Census?opendocument&ref=topBar

De-constructing the ‘g’ gap

De-constructing the ‘g’ gap

by | 15 Mar, 2016 | Australia, data, demography, gender, income, occupation, social issues

Last week was International Women’s Day so everyone should be up to date with the latest estimate of the gender pay gap (17%), and very well versed on at least three theories behind it.

Now, then, might be the perfect time to ask why the social progress and workforce changes which occurred over the last 30 years have had no impact on the gap.

The increasing awareness, numerous policies, university attendance explosion, increasing maternity leave and participation rates, industrial and occupational distributions, and a myriad other variables have increased or decreased to varying degrees. Mostly towards gender parity. Yet the pay gap for full-time women has not deviated more than +/- 2 percentage points since Lionel Ritchie first sang “Hello…. is it me you’re looking for?!”[1].

Gender Pay gap 83 15

The gap itself is a complex issue with many moving parts. This is a look at a few of those parts, and a general wondering: how is it not improving?

 

An aging workforce

One of the biggest changes in the workforce has been workers’ age. Average full-time wages increase rapidly with age, until they begin plateauing around 30, finally peaking in the late 30s to mid 40s (depending on occupation and role).  On average, workers under 25 earn 40% less than those 25 years and over[2].

Historically, one of the reasons behind the wage gap has been that working women are dis-proportionally younger than men, and therefore lower paid (i.e. junior staff on junior wages).  But the age demographic across the sexes has become a lot more equal over the last few decades.

While the overall percentage of workers under 25 has halved since 1983, women’s compositional distribution has changed much more than men’s (as shown by the graph below)[3].

Aging workforce by Sex

This suggests junior wages, or wages from young staff who are yet to reach role maturity, should have a much smaller impact on the overall average wage than it used to. Thus, diminishing one reason why there may be a pay-gap.

On the other end of the maturity spectrum, the proportion of women over 40 has almost doubled since 1983.  This suggests a greater proportion of women are returning to full-time employment after giving birth, continuing to build on their careers, with advanced wages.

Aging workforce by catergories

The changes in women’s labour force have been so substantial that the average age gap between the sexes is less than a quarter of what it used to be: down from 4.5 years in 1983 to 1 year gap in 2015.

This said, women have not achieved age parity in the workforce, but it’s certainly a lot closer than it used to be. Yet, the pay-gap has not changed since ‘Return of the Jedi‘ hit the cinema screens.

 

Women learning it for themselves

One potential reason behind the maturing female workforce is the increasing number of women attending university.  University attendance has increased across the board, but women’s increase has doubled men’s.  While women had not achieved tertiary education parity by the early 80s, they well and truly have by 2015.  In 2013, 58% of all Australians studying at university are women. This is just as true for postgrads as it is for undergrads. In fact, women have been the majority at uni since 1987[4].

This increase in university attendance has flowed to the labour force.  Full-time working women are now 45% more likely to have graduated from university than their male counterparts.

Uni Attainment in LF by sex

However, not all graduates are created equal. Some fields of study pay more than others, and the figures above don’t provide that level of detail. But overall graduates earn substantially more than workers with no university qualifications, and women are increasingly dominating this sphere.

This further suggests a move towards pay parity.  Yet, the pay-gap has not changed since Bob Hawke first became Prime Minister of Australia.

 

From doing to managing – occupational changes

Higher paid occupations (e.g. managers and professionals) now make up much larger proportions of the workforce than they did in the mid80s. Whether it’s due to social progress, the growing number of university educated women, or any other reason, the proportion of women in these roles has increased faster than men’s over the period in question.  The proportions of full-time women in the two highest paid occupations, professional and managerial roles, have increased 12 and 6 percentage points respectively. Men, on the other hand, increased 7 and 2 percentage points.

To balance this out, the proportions of women filling admin, labouring and sales roles (the three lowest paid occupations) have decreased by 11, 4 and 3 percentage points, to men’s 2, 4 and 1.

The graph below compares the proportion of women and men by occupation in 2015 to 1986. Higher paid occupations have generally increased, and low paid decreased… and women have faired better at both ends of the spectrum.

 

Occupation can still account for some of the current disparity. Despite the move towards higher paid roles, women are still over represented in some of the lower paid occupations; e.g. 25% of women fill admin roles, as opposed to 7% of men. But the changes over the past 30 years should have had an impact on the pay disparity.

Yet, the pay gap has not changed since the average price for a Melbourne house was $52,000[5].

Changing occupations by sex2

Mining the AGEING boom

Unlike the other variables examined, women have not clearly moved to the higher paid industries over the past 30 years. In fact, women have slightly decreased proportional representation for the three highest paid industries when compared to men (i.e. mining, financial and professional services). Mining is of particular interest as it is the highest income by almost $40k, and the boom meant its growth outstripped every other industry’s growth. These two aspects combine to help stretch the pay-gap further apart.

Changes in Industry distribution, by sex, 1984 to 2015

Changing industry by sex 3

The industry experiencing the largest increase in women participation has been Health Care and Social Assistance, potentially on the back of Australia’s ageing population’s demand. While its income is only marginally below the average for all industries, the increase in Health and Social assistants means women have not migrated towards the higher paid industries in large numbers.

Having said that, as previously described, women have gained much ground in GP representation.  The proportion of women GPs has increased from 22% in 1984 to 43% in 2014*.  This means that whilst women continue to be over represented in lower paid industries, they are filling higher paid roles within these industries.

 

Ask for more

Data on workforce by “method of setting pay” (i.e. opportunity to negotiate pay, which some suggest promotes disparity) has been hard to come by. This aspect may be extended upon in future.

 

Yet, not.

Most of these changes suggest the gender pay gap should have decreased over the past 30 years. At the very least it shows the variability of many contributing aspects. To not have achieved pay parity is understandable, as there are still many obstacles to overcome, and underlying contexts/assumptions/social norms to change. And many tricky issues to figure out on how to get there.

  • Should more women work in higher paid industries, or should we (financially) value women-dominated industries more?
  • Are health and education paid less because they are women heavy industries, or are they women-dominated because they are lower paid?
  • Should we increase paternity leave to support women to stay, or support them to return after birth-giving?
  • Should women be encouraged to negotiate more or should industrial frameworks diminish the impact negotiation has on individual’s pay?

But to not have made any improvement, despite all the changes that have occurred seems odd. Changes in age  alone should have had massive impacts.

Yet, not. No change, improvement or otherwise.

This post has no answers or suggestions… just a baffled look to greater minds to tells us why…

 

 

 

[1] Based on Full-time ordinary wages, by sex from Average Wages, ABS: http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6302.0Nov%202015?OpenDocument

[2] http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6306.0May%202014?OpenDocument

[3] http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/6291.0.55.003Nov%202015?OpenDocument

[4] http://docs.education.gov.au/system/files/doc/other/time_series_data_1949_-_2000.pdf and http://highereducationstatistics.education.gov.au/

[5] http://www.econ.mq.edu.au/Econ_docs/research_papers2/2004_research_papers/Abelson_9_04.pdf

 

Burning up the runway

Burning up the runway

by | 3 Dec, 2015 | climate change, consumption, data, facebook, travel

I often think Facebook is paid by tourism companies to mock my office existence and exaggerate how often my “friends” are on overseas holidays.  But ABS figures[1]suggest Australians really are crossing customs at climate changing rates.

Australians flew overseas 9.3 million times in the 12 months to September 2015. That’s almost 800,000 departures per month. Or in Facebook terms, you can expect more than 3 out of every 100 Aussie friends to travel overseas this month: that’s a myriad mates munching at the Marrakesh markets; a bunch of selfies from Boracay’s beautiful beaches; and the occasional insightfully witticism of the commercialist culture capturing Kolkata.

Australians have long been early adopters of international flights. The first England to Australia flight took place almost a century ago, in 1919 (taking 28 days). Overseas flights, however, have really taken off in the last decades. The number of Australians flying overseas has doubled since 2006, and increased ten-fold since 1977.  Accounting for the population grow, trips per capita have doubled since 2004, and grown six-fold since 1977.

There are many ways of interpreting these figures, depending on what angle / lens / issue you care to focus on.

We could suggest that whilst Australians (according to pop media) are deeply concerned about economic instability and slowing wage rises, they have nonetheless increased their international holidays by 50% per capita since the Global Financial Crisis.

We could similarly insinuate that whilst Australians’ concern for climate change leads them to implement strategies focusing on everyday impacts, they may be undoing all their efforts by ignoring the growth of big ticket items. (The CO2 emissions from a Melbourne to London[2] return flight equate to the yearly emissions per capita for the UK[3].)

Or we could just say “look mum, I’m holding up the Tower of Pisa!” (AGAIN!)

A Culinary Atlas

A Culinary Atlas

by | 8 Sep, 2012 | data, food

Not all cuisines are created equal.  Certainly not according to the Australia voting public at least.

Following on from “Stirring the data with an urban spoon” (an analysis of urbanspoon data), this map compares popularity of different cuisines across the globe.

Culinary Atlas

Coloured by popularity
Dark Green = best, Dark Red = worst, Everything in between = everything in between
NB: Controversial borders do not reflect the views of the author, rather an attempt at standards.  Some questionable boundaries (Islas Malvinas/Falklands Islands, Cyprus) were represented in dual colours.

Some countries (Australia, China, United States) appear to have rubella. This is because their cuisines were described multiple times. Australia came under “Modern Australia” (in orange) and “Native Australia” (a slightly darker shade of orange).

Some countries’ cuisines were individually defined (Thai, French, Moroccan, Brazilian), while others came under umbrella tags, such as “Africa” or “Latin America”.

Others were missing entirely from the list (eg. New Zealand, Sri Lanka, Russia, Sweden).

Stirring the data with an urban spoon

Stirring the data with an urban spoon

by | 16 May, 2012 | data, food

One of life’s great tragedies is the limited opportunity for meal consumption, usually estimated at 3 per day.  The seriousness of such a condition is accentuated when travelling through cities at fast pace.

Having failed to find an adequate pizzeria on the first of a two-day fly by Napoli, the alleged birthplace of such fine cuisine, the pressure mounted on my second day.  Without the three-meal-per-day phenomenon I could have tried every pizzeria I walked past, but knowing I would only get one crack at it, the choice would define my soon-to-be memories of this wonderful city.  The three-meal standard was once again proving a major limitation on my savouring life.

After hours of walking, pizza napoletana.

I walked up and down the Neapolitan streets in search of this fabled slice, finally giving up as the sun was setting, mostly due to hunger, anger, and my train’s imminent departure.  In a final bout of desperation I succumbed to the type of ‘cheesy’ touristy pizzeria I would otherwise arrogantly lift my nostrils at.  Not even the world’s best table red (coca cola) could help me wash down the shame and disappointment.

Back in home territory the opportunities to try the local cuisines might not be so limited (numerically speaking), but the desire to maximise every outing still holds.  Over the years I have realised that a restaurant’s reputation is not a great predictor of satisfaction.  Neither is the size of its queue. But perhaps among the masses lie some nuggets of truth for us to take away.

Websites such as urbanspoon provide peer reviews rather than the “hat” dispersing scriptures dividing good food from evil.  Usually used to check out restaurants individually, the data held by these online voting booths can surely tell us more about our candidates.

While not including every restaurant in Australia, the 22,297 profiled in capital cities across the country appear to constitute a majority of the population.  According to a quick search in the Yellow Pages there are 31,900 “Restaurant and Cafes” across the capital cities, and an ABS publication estimates the figure at 15,423 in 2007.  While the scopes and definitions might differ slightly, the figures suggest it’s a decent sample.

When looking at restaurant reviews in bulk a few things become apparent:

  • Reviewers are generally positive creatures.
  • Cost driven expectations are not matched by experience.
  • If you love your steaks, eat at home.

Urbanspoon’s rating system is expressed as a percentage of the people who liked it vs. those who disliked it.  On average restaurants get liked 78% of the time.  This average “like score” is consistent (+/- 3%) across all capital cities*.  While almost 40% score in the 80s, less than 5% of restaurants have scores under 50%.

Surprisingly, these positive reviews are less likely for the expensive restaurants than el cheapo ones.  The elevated expectations which come with paying extra seem to lead to disappointment.Overall, cheap restaurants score 9 percentage points more than expensive ones, with the middle ranges falling in between.  This trend occurs not only across all capital cities*, but also across most cuisine types.  Cheap Thai beats expensive Thai, but then again cheap Thai beats pretty much everything!French restaurants (and to a lesser extent Japanese) seem to disturb the pattern.  Of the cuisines with large enough sample sizes, les French are one of the only cuisines not to show decreased satisfaction likelihood with increased price, keeping a steadily high level across all price ranges (80% like).

So why pay more if we’re less likely to like it?  The difference in price is not insignificant, so if these data are anything to go by: cheap is cheerful, and pricey just makes disappointment more likely.

Sometimes we don’t crave fancy or convoluted: forget the foam and the parfait, the cocktails and pate. Sometimes we just want a bit of steak (aged, of course, wagyu if possible).  In that case, do not head to a steakhouse.  Of all categories of restaurants on urbanspoon, steakhouses fare the worst with an approval rating of just 69%!How hard can it be?Perhaps it’s because it doesn’t come with the scent of closely mowed grass, but as simple as a steak is to serve (usually with a side of chips and mushroom sauce) steakhouses just don’t cut it.

On the other hand vegetarian restaurants score 80%, up there with Turkish, Korean, and Fish and Chips!

 

______________________________

* When discussing capital cities, Hobart, Darwin and Canberra are excluded due to their small sample size.

Two-speed tax decrease

Two-speed tax decrease

by | 23 Feb, 2012 | data, income, tax

Seeing as they are one of life’s two certainties, how is it that we’re so ignorant about taxes?
 
The federal government updates the income tax system roughly every second year, more often than not announcing tax cuts.  This kicks off a war of sound bites over who is prepared to deliver the deepest cuts and for whom.  What they rarely provide, however, is a clear and simple indication of what the impact of each tax plan will be on one’s paycheck.  While providing the intended tax brackets allows people to conduct the necessary analysis, I doubt most people would bother to do so, thus making assumptions on the impact of the changes.
 
Since converting the national currency to the Australian dollar in 1966, the average income has increased from just under $3,000 dollars per year to almost $55,000. Although the rate of growth has fluctuated, it has constantly been positive, with no year posting a negative growth.
*There is a break in series in 1981, as figure prior to 1981 are “Average Male Income”, and figures since 1981 are “Total Average Income”


 

Due to the combination of Australia’s progressive tax system and the continuous income growth, a government’s failure to update the tax system quickly translates into a tax increase.  For example, a person earning $50,000 this year is likely to earn around $51,500 next year due to income growth (average growth of around 4% per year since 1990).  This growth puts a larger percentage of their income in a higher tax bracket than before, therefore increasing their overall tax rate.
 

 

The graph below shows what would have happen to a person earning the average wage every year, had the tax rates been frozen in 1990-91.
 

 



Although the difference is small from one year to the next, a twenty year time-line clarifies the point.  While the average income in 1990 was $25,910 (falling within a tax bracket of 38.5%), 2011’s average income was $54,700, attracting the top tax rate of 47% back in 1990.
 




Income tax is a complex beast with many aspects including levies and rebates changing year to year.  In an attempt to simplify the history of income tax in Australia, the following graph displays the percentage of tax paid for different multiples of the average wage from the inception of the Australian dollar onwards.
*The resident Prime Minister is only indicative, as their timing doesn’t line up nicely with the financial years.



Other than a very curious bump in the late seventies*, the years since have not provided much excitement. The slow and gradual “ramp-up” through the nineties is explained by almost a decade of non-updated tax rates, similarly to a small bump in the early to mid ‘naughties’ (2001-2004).  Otherwise it has been a steady decrease of income taxes since Malcolm Fraser’s first term.  


Generally speaking, income taxes have decreased over the past few decades.  This decrease, however, is not evenly spread across the pay brackets.  While the average wage now gets taxed about 4 percentage points less than thirty years ago, people earning 3, 4 and 5 times the average wage have experienced decreases of 9, 11 and 12 percentage points.  This trend is even more pronounced if we used 1985-6 as the base year.  Since Hawke’s first term in office, income tax on the average wage has decreased 2 percentage points, while those earning over 3 times the average wage have experienced a 14 percentage point drop in their income tax!


Interestingly, people earning half the average wage are still paying roughly the same levels of tax as they did in the late 70s, hovering around the 12%.  


Of course, none of this includes the impact of tax breaks for Low Income Earners, nor does it include negative gearing or other benefits offered through our tax system.  It is purely a simple model of calculating income tax percentages, by different multiples of the average wage.  

The picture it tells appear lopsided, though mostly because there seems to be no other side in modern Australian politics.


_________________________


For references:
Tax brackets were sourced from the Australian Taxation Office’s (ATO) website:
http://www.ato.gov.au/individuals/content.aspx?doc=/content/73969.htm
Average Income from the ABS’ Average Weekly Earning’s publication:
http://www.abs.gov.au/Ausstats/abs@.nsf/0/14CDB5CD59F6A075CA2575BC001D6157?OpenDocument

Time for a road trip!

Time for a road trip!

by | 27 Dec, 2011 | data, mortality, road safety

Today is the fifth day of the 2011-12 Christmas holiday road toll period¹ and it is hard to open a newspaper or news website without being informed that so far 18 people have lost their lives on Australian roads since last Friday. According to the World Health Organisation (WHO), road traffic accidents amount to over 1.3 million deaths per year, and injure in excess of 50 million people. They are the biggest killer of people aged 15 to 39 worldwide, and ranked around 9th overall². Worst of all, these figures are expected to increase over the coming years, mostly due to the growing access to vehicles in the developing world*. These facts make road safety a worthwhile focus of media attention. What makes less sense is the misleading obsession which the media has on the holiday periods.

By focusing so overtly on the Easter³ and Christmas periods, it is assumed by the public that they claim more lives than other times. Headlines speak of the climbing toll, morbidly focusing on every death recorded during the period. They even include a state by (vs.) state tally, and each police jurisdiction either congratulates their constituents, or shows their disappointment, depending on how their stats is faring. What they rarely report, however, is that the holiday periods are nothing special. If anything, the Easter and Christmas periods claim less lives than similar periods throughout the year.

Based on data published by the Department of Infrastructure and Transport 4 (Commonwealth level), the Christmas/New Year holiday period claims an average of 67 lives per year (since 1989, which is the earliest freely available data). The average for a similar period throughout the year is 70. Similarly, the Easter period claims an average of 22 lives per year, while 24 die on similarly lengthed periods the rest of the year. Christmas day itself falls in the lowest 5% of days in terms of deaths, in the period 1989-2010.

The month of December does appear to be slightly more deadly than the rest of the year, but surprisingly it is the period before Christmas which makes it so. By the time we first hear about the Christmas road toll, the worst has passed. Similarly, March is worse than April, meaning the Easter reminder comes too late.

The calendar below shows the average number of road fatalities for each day of the year, for the period 1989-2010. The cells are colour coded, with green having the smallest number of deaths and red being the deadliest.

Unfortunately, the road toll is devastating every week, not just when the media decides to focus on it. During the last two decades, an average of 34 people died on Australian roads every week. Most of the accidents which claimed lives occurred during the weekends. Saturdays claim 63% more lives than Mondays and Tuesdays. Fridays and Sundays aren’t far behind. If the media (and law enforcement agencies) want to focus their attention on a particular period (double demerit points, increased breathalysers, etc. etc.) then perhaps every weekend is as good as the others. This would send the message that the roads are dangerous throughout the year, not just on holidays.
___________________________________________

NB: As the numbers represent the average from 1989 to 2010, the day of the week they land on changes from year to year. For presentation purposes, this calendar is based on the 2010 layout, with the 29th February added for completeness.

Dataset available upon request.


____________________________________________
* Conversely, one could argue that since the trend is due to expanding access to motorised vehicles, a growing road tally in the developing world is a horrible side effect of great progress, bringing with it increased freedom of movement, greater access to trading routes, and generally higher quality of life.

 
 _______________________________
1. Christmas/New Year holiday period begins at 00:01 on the last Friday before December 25, and ends at 23:59 on the first Friday after December 31.
2. http://whqlibdoc.who.int/publications/2009/9789241563840_eng.pdf
3. Easter holiday period begins at 00:01 on Easter Thursday and ends at 23:59 on Easter Monday. 
4. http://www.infrastructure.gov.au/roads/safety/road_fatality_statistics/index.aspx

Inflation Express

Inflation Express

by | 14 Dec, 2011 | data, Inflation, public transport

I’m not usually one to plan in advance nor buy in bulk, but with regards to Melbourne’s public transport, I might be convinced otherwise. Last week’s announcement of the upcoming 9% increase in train tickets (as well as bus and tram) has compelled me to buy my 2012 train tickets at what are still genuine 2011 prices.
Over the past two decades, Australia has kept inflation between 2 and 4% per annum. And yet, I find myself reminiscing the days when I could purchase a book of 10 bus tickets for $4.50. Being mindful of the concession price variable, and the fact that I was still wearing Brut (high school boys’ top selling deodorant!) the $4 per ticket I will be paying come January still appears a little inflated. To get a better idea of how this latest increase fares, I compared it to previous movements. With public transport data going as far back as 1972, the ABS’ CPI shows an interesting trend over the past few decades.
Throughout the 70s and 80s the increase in public transport prices mirrored that of the overall basket of goods. That is to say, the price of catching a train increased at similar rates to most other common goods. From 1990 onwards, however, the cost of buses, trams and trains has increased at a rate much higher than inflation (which includes housing costs, education, bananas, recreation and health, etc etc). While the cost of living in Melbourne increased 79% since 1990, by the time I sober up on New Year’s day, Melbourne’s public transport will have increased 190% in the same period.
Public transport’s elevated inflation is not only a Melbourne issue. Public transport has outgrown inflation by 97% across all of Australia’s capital cities. The graph below shows how Australian capital cities fare in terms of transport inflation compared to the overall Australian CPI.

(this google motion chart is not currently working… attempts will be made to reinstate it)

In the meantime… here is a temporary graph with similar data.

Public Transport Inflation

This phenomenon is made more remarkable when considering that the inflation for private motoring costs (including vehicle costs, fuel, parking, registration etc) has been lower than the total basket over the last few years. While the increase in cost of public transport is almost twice that of the overall basket, private motoring costs have increased 15% less than CPI since 1990.

I won’t speculate as to the reasons for this divergence.  Suffice to say that if we’re trying to encourage people to jump on the public transport bandwagon, a little economic incentive wouldn’t hurt.

__________