Vision 28

How would you measure the safety of private motor vehicle travel?

Let’s agree to focus on fatalities. Serious injuries are also important, but all the points I am going to make hold equally as well for injuries as for fatalities. Continue reading “Vision 28”

Population: will we just disappear?

Last week on ABC insiders, the discussion briefly turned to population policy and its role in the previous election. Kerry-Ann Walsh (former Herald-Sun journalist, now semi-retired and occasional opinion writer for Fairfax) chimed in with

Given what Australia’s needs are going into the future…and the fact that the fertility rate is so low, we will just disappear if we don’t have a healthy immigration level.

  And the fact that both sides were blathering during the election campaign and trying to hoodwink the Australian people is a disgrace.

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The suggestion that the Australian population is about to disappear is fanciful. It is about as wrong as anything can be in politics – it is arithmetically wrong. I have run a few projections to illustrate the point. Others might get slightly different answers depending on various assumptions, such as the exact age distribution of mothers and how mortality will progress in the future.

TFR is the total fertility rate – meaning the number of children on average a woman will have (supposing she does not die before having them). A value slightly above 2 (in our case about 2.07) corresponds to replacement i.e. zero population growth. The history of the TFR in Australia is HERE. The TFR in Australia right now is about 1.97. The lowest it ever reached was 1.73 in 2001. Other countries have much lower TFRs. For instance, in Hong Kong the TFR is about 0.9, despite there being no 1-child policy as there is in the rest of China. A comparison of the rates in different countries is HERE.

The projections below all assume zero net overseas migration (i.e. about 220,000 migrants to balance the 220,000 permanent departures each year), starting from a population of about 22.1 million at the beginning of 2010.

TFR 2130 2050
ZPG 2.07 24.5 25.4
Now 1.97 24.2 24.6
Lowest ever 1.73 23.5 22.9
Hong Kong 0.9 20.9 17.4

It doesn’t really look like we are going to “disappear” does it?! Even under the worst case 1.73 scenario, the population will still be higher in 2050 than it is now! I am afraid that it is journalists who are hoodwinking the Australian people on this issue, not the politicians.

Here is another scenario to consider. Suppose that we drop the baby bonus and that the TFR falls back to about 1.80 in response. Suppose that we also reduced net overseas migration to 100,000 per year (instead of 200,000 which is now talked about as a compromise figure). Remember, this means 320,000 migrants per year. It is not a closed door policy. Under these two policies – which represent the absolute extreme of what would be politically possible in terms of reducing population pressure – does the population stagnate? No. It increases to 28.7 million in 2050 and continues to grow into the future.

There are reasons for running an immigration policy, but saving us from a seriously declining total population is not one of them. Neither is it any sort of solution to the ageing population problem, but that is for another post.

Cross posted from Fishing in the Bay.


The SPT shouldn’t be such a tough sell

The government have made some solid major decisions during their first term. In my opinion, the size and delivery vehicles for the stimulus were appropriate. I think the Super Profits Tax (SPT) is sound, though you can argue over the details and which minerals it should apply to. Unfortunately, the government are not only incompetent administrators but positively autistic communicators. The SPT was well received in the days immediately after the budget. What happened? The SPT should sell itself. Especially because it feeds well into what should be the government’s two strand narrative.

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The first strand should be that they saved us from the GFC. Never mind whether you agree with this or not. It is a strong positive for them and they will win a landslide if the election is fought on this issue. The SPT is the flip side of the stimulus and an excuse to keep the stimulus front and centre of political debate.

The government put us into a big fiscal hole with the stimulus package. They have taken some criticism for the implementation (i.e. pink bats and school canteens) but the voters are mostly glad of the fact of the stimulus, while having misgivings about the debt going forward. The government have always claimed the country should get back into surplus over the business cycle. The money has to come from somewhere. Where else are we going to get the huge sums required?

Yet Wayne Swan denies that this is the main reason for the SPT. He wants to claim credit for getting us back into surplus by 2012-13 but is coy about how he is doing it. He should openly acknowledge his strategy. Yes, we need the money to balance the budget in 3 years.

This not only moves the focus back to on the consequent early surplus, but it feeds beautifully into what should be the second strand of the government’s narrative, namely investment in infrastructure and long term management of inter-generational wealth. Back when they were able to communicate, the ALP ran very hard with the idea that Howard had squandered the resources boom, pointing to slow trains and under-resourced schools. Regardless of whether you accept this view, it gained a great deal of traction. They should be positioning the revenue gained from the SPT as the avoidance of losing revenue the way we did in the last boom. People hate to lose revenue. If they position it this way, every time the punter hears the SPT mentioned, they think of all the money that would be lost if we did not have it.

But Rudd lives in Canberra and doesn’t know how ordinary people think. How else to explain calling it a Super Profits Tax? This is the greatest own goal of all time – a minor variation on the opposition’s “Great Big New Tax” mantra. They could have called it the 10% Excess Profits Premium, which carries the message that (a) it is only on high profits, (b) it is only a marginal change from 30% to 40% and (c) the country receives a premium on their resources. Premium is such a nice positive word compared to tax. Does the government have anyone who knows how to sell a product?

Apparently not. Instead, their shifting message is drowned out by mining industry propaganda which does not bear the slightest critical scrutiny. Journalists apparently think that they must not point out nonsense in the interest of appearing balanced. The mining lobby’s campaign has the following elements.

The SPT tax is excessive. It is only a change from 30% to 40% on profits over 6%. I am sure that most punters think that mining companies are being taxed an extra 40% on all their profits, if not on all their revenues. Rudd should have called it a 10% premium, not a 40% tax. The fact that this is worth $9 billion per year tells you how much profit is being made.

The SPT will harm investment. Since it is only a marginal charge on excess profits, it could not cause any existing profitable projects to close. It could certainly affect the economics of future ventures, since the rewards on the denominator of the risk/reward ratio will be smaller. So we might see less projects in future. This is not such a problem though. First, it will roll out slowly over time so there is a chance to react. If necessary, we can encourage new projects in the future by allowing more of the exploration costs to be deductible. Second, the resources are still in the ground so nothing (or little) is actually lost.

The marginal rate of 40% is internationally uncompetitive. It is suggested that the 40% rate being higher than say 25% in Chile is somehow relevant. This is nonsense. A decision to invest in country A or B will depend on the relative profit margin, not the tax rate itself. If Australia had diamond fields where you could just walk around and pick them up then we would be well advised to tax profits at 99%. I reckon mining companies would still fall over themselves to pick the diamonds up. No journalist has called the marginal tax rate argument for the nonsense it is.

The SPT tax is retrospective. It applies to future profits only. The mining companies complain that they made the decision to pursue these projects under a different tax regime. That’s true but in that case every time a landlord puts up rent on a commerical property it is retrospective. As the unfortunate holder of Tabcorp shares I know first hand that the value can decrease when government removes a monopoly right. Retrospective? This is just abuse of language.

The SPT increases sovereign risk. If they mean sovereign risk of the country then Kyran Curry from S&P disagrees. He says the mining tax would have no effect on our credit rating, which is an indicator of sovereign risk. In fact, he says the tax raised over the first two years could strengthen the rating.

The SPT will harm the whole economy. It is only a change from 30% to 40% on profits over 6% for one industry sector that is currently thriving. Moreover, most of the big mining company dividends go to foreign based shareholders. If you had to find $9 billion per year to take out of the economy to get us into surplus, you would be hard-pressed to find a less damaging way to do it.

None of this means that I support every aspect of the SPT. Many economists prefer a purer Resources Rent Tax. Nor do I think that the SPT would necessarily be an easy sell even if Rudd was at the top of his game. Nick Gruen thinks that the political landscape has fundamentally changed from when the RRT on petrol was introduced, and he may be right.

So what has been the effect of the SPT on the fortunes of the big miners and the country? I downloaded the share prices of RIO, BHP and the ASX for this year and looked at the month prior to the budget announcement and the month after. I calculated the movements of $1 equally invested in RIO and BHP on January 1 and subtracted off value of the same $1 invested in the ASX. The graph is below. The zero does not mean anything in particular. It is changes in the graph that tell you how mining is faring compared to the general market. I also downloaded the DJI for the same period so I could compare Australian and US shares.

The budget was May 11, about the middle of the graph. I guess you can tell two stories here. The mines drop compared to the ASX on May 11 and 12 and the ASX drops compared the DJI over the next week. Or you can look at the previous month which suggests that the market already knew the SPT was coming. If the drop from April 12 to May 12 is all due to the SPT then it is around a 10% loss for the mines. If you only count post announcment it is about 4%. Either way, mining share prices have been moving up compared to the market over the last month – as has the ASX compared to the DJI – recovering perhaps half the lost ground. This might represent the market perception of the likelihood of the SPT actually ever being implemented.

I wish I had the time to do a similar graph for “small miners” but I do not know enough of their names and there are too many of them. If the SPT designers are to be believed, small mining shares should show the opposite pattern to that of the large miners.


Hot tip: bet one Aussie dollar each way.

At the one extreme we have exotic financial derivatives that no-one knows how to value as well as opaque bundles of high risk loans and low risk bonds that no-one knew how to value either. At the other extreme, we have the simplistic nonsense known as technical analysis that anyone can understand, but happens to be bollocks. No wonder the world financial system is such a ferrel beast.

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Age write Lucy Battersby has produce this gem of an article, that spruiks the sage thoughts of Paul Ash, president of the Victorian chapter of the Australian Technical Analysts Association. It is all about the much-buffeted AUD.

It turns out that the Aussie went down for a while, then up, then down, then up a little bit, then down a tiny bit. This is clearly big news. But not one to take things at face value, Ms. Battersby notes that the Aussie is

at a moment of indecision that could see it continue downwards or climb and break though resistance.

Let’s rush straight out and put some money on it to……go up?… go down..? Hell, let’s just buy a Tatts ticket.

But it gets more specific (and consequently more wrong) as the article progresses. Mr. Ash claims that for the next day “it is critical if the AUD can spend 24 hours above 90 cents.” Like Uri Geller and John Edwards though, he never actually completes the prediction of what might happen after that. But he is clearly saying that Tuesday Feb 23 is critical. Forget any notion of EMH or martingales. The claim is that the value Vt of the aussie dollar satisfies the condition

if inf{Vt:t ε Feb 23} > 0.90

then ∂EVt/∂t>0 ….. or perhaps ∂EVt/∂t<0. Take your pick.

Ms. Battersby then chimes in to describe technical analysis as

a search for patterns which not only “provides a theoretical basis” for traders but “removes sentiment and gut feeling” from trading.

The straw man strikes again. The only possible trading strategies apparently are pattern searching or gut feeling. Forget any research on the company you want to own. Someone tell Warren Buffet and his acolytes.

But I have been a little unfair to Mr. Ash in claiming that he never makes a prediction. He does actually come out with one towards the end. He says that if the AUD gets above the “non-confirmed resistance line” of 91.7 cents “then we would say with confidence that the AUD is on an upward trend.”

Anyone heard of a tautology? Since it is below 91.7 now, if it gets to 91.7 it will be on an upward trend. Gentlemen. Place your bets!

Hat tip to Mike Smith for slipping this article under my door.


Survival science – just run like hell

You know the story of the two guys who are being chased by a lion. One says to the other “We are going to die. We can never outrun this lion.” His friend replies: “I don’t have to outrun the lion. I only have to outrun you.”

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A recent paper* turns the modern spotlight of statistics onto that pressing issue of how best to survive a big cat attack. The authors analysed data from 185 puma attacks on humans in North America over more than 100 years. The response was severity of injury, ranging from no injury to death. The predictors were age, group composition and behaviour. I am not sure about age but I am guessing that you shouldn’t go walking by yourself in puma country for a start. The modern data crunch used to reveal the elusive truth was multinomial regression.

It turns out that age had no effect on injury severity. Once the puma gets his claws into you, you are pretty well fu…d, well in serious trouble however old you are.

There is confirmation that if you are in a group you have less chance of injury – just as the guys in the humourous story reasoned from first principles. But the severity of injury is not reduced by larger group numbers. Your mates are obviously too busy climbing up the nearest tree to distract the puma from snacking on your wobbly bits.

It also appears that your behaviour influences the chance of serious injury. Specifically, it is found that if you stand still and wait for the puma to attack you then you have a higher chance of injury (74%) then if you run like hell (50%). And it doesn’t really matter how fast you run – presumably because the puma can run faster than you or Usain Bolt.

So, if you see a puma attacking then you should run. Who would have thought! ** This is science and modern number crunching at its best – pushing the frontiers of human knowledge and saving human lives.

*Anthrozoos: A Multidisciplinary Journal of the Interactions of People and Animals, 22, 77-87.

** OK, I am being a bit hard on the authors. Actually, conventional wisdom and some wildlife agencies advise against running. The California Department of Fish and Game says on its Web site, in part: “Do not run from a lion. Running may stimulate a mountain lion’s instinct to chase. Instead, stand and face the animal.”


Doubleplus Good Financespeak

Has anyone noticed how the vocablary of the finance industry is heavily laden with moral overtones?

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Consider the following list of financial terms and the images they conjure: `assurance’, `bond’, `credit’, `consolidation’, `equity’, `interest’, ‘mutual’, ‘obligation’, `redemption’, `reconciliation’, ‘security’, `trust’, ‘venture’. I wonder how many of these terms have their origins in the Protestant business philisophy of the nineteenth century – that wealthiness is next to godliness.

Even the trashy housing loans that got us into this mess are called “sub-prime”, which to me sounds like a cut of beef only slightly more chewy than eye fillet. “Lambs to the slaughter” might have been a more honest marketing strategy.

And my favourite bit of financial jargon is ‘efficient market hypothesis’ as Doublespeak for complete bloody randomness. ?


Iran Election Statistics

How do you detect election fraud? A recent article in the Washington Post describes a novel statistical idea. It is the kind of twist on viewing the data that any freakonomics fan should have thought of.

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Most people believe the election results in Iran were rigged. They base this on a couple of arguments. The most obvious is that Ahmadinejad did unreasonably well, including especially in areas where you would expect him to poll poorly – for instance in the home seat of his main opponent Mousavi. This argument would sway most people but it is not scientific. Ahmadinejad could still say that he ran a great campaign and that the people decided he was a safer pair of hands.

Another more statistical argument is that the variability in Ahmadinejad’s vote is too small. By too small, I think they mean less than one would expect from the regional variation that one normally sees. So this does intersect with the first argument and Ahmadinejad’s high vote in some unlikely seats. But it is a distinct statistical view in that we focus on variation across seats rather than overall mean level. Certainly, if one could actually show that the variability of Ahmadinejad’s vote was less than binomial variation this would be pretty damning and suggestive that someone had just made the figures up.

Well, it turns out that the variability of the vote is about 100 times higher than binomial – there is plenty of regional variation overall. I suppose we could compare the variability with a different benchmark – such as the variability of the vote for winners of previous elections – but the argument starts to lose force as there are other explanation of why variability might decline.

So, if we are interested in revealing whether the election count data has been concoted, let’s focus more on the process of human beings making figures up. Humans are pretty bad at making figures up. Human generated data typically looks too good to be true and follows theory too well. It is well known, for instance, that Mendel’s famous pea data was probably concocted, perhaps by his assistants. Forged signatures can often be recognised by experts as being too consistent. Real signatures are not perfect and vary from day to day.

Humans are especially terrible at generating random numbers. And for a large voting count, for instance 325911 which was Ahmadinejad’s count in the region of Ardabil, the last few digits should be essentially random. On the other hand, if someone were making the numbers up and not concentrating too hard on the unimportant final digits, you might expect to see some tell-tale signs of non-randomness in the those final digits.

This idea is due to Alexandra Scacco and Bernd Baber who have suggested that there is indeed such evidence in the data. They claim that human generated random numbers tend to have too many 7’s and not enough 5’s. And looking at pairs of digits, they claim that human generated digits will have too many adjacent sequences such as 23 and 76.

The data for the 2009 Iranian presidential election are HERE and a graphic of the marginal distribution of the last digit is below. There are indeed too many 7s and not enough 5s. The overall goodness-of-fit of a uniform distribution has a P-value around 8% but this may underestimate the evidence. If we concentrate on the a priori hypothesis of too many 7s and not enough 5s then the chi-square statistic is much, much stronger.

But is the hypothesis of too many 7s and not enough 5s really a priori? I could not find any evidence on the web for the assertion of not enough 5s but there is some prior reason to look too many 7’s. If we just look at the excess of 7s the P-value is around 0.4%. The excess of 20/116=17.2% sevens over the expected 10% is very suspicious indeed.

One might obtain even stronger results if we concentrate only on those electorates where Ahmadinejad’s vote was likely to be poor. One assumes that the fraudsters would not alter the counts in the electorates where he won. So the random digits in these true counts might dilute the non-randomness in the fraudulent counts.

I also had a look at the last pairs of digits hoping to find something even stronger but I could not recover the results quoted in the Washington post article. Moreover, I could not find any evidence for their claims about adjacent sequences, though I have heard that two digit primes tend to get preferentially chosen. Anyway, I challenge readers to look at the digits and find some really damning evidence of non-randomness (which we would have to correct for the effort you put into the search!)

If I were going to fudge some numbers, I would start multiplying the real counts by some scaling factor, or leave the last digits alone, or even use a random number generator on my mobile phone! I guess criminals and fraudsters are not always very smart.


Management versus Economics

I recently became aware* of a paper by Benito Arruñada and Xosé H. Vázquez that attempts to link the outcome of MBA degrees to the different subjects offered – specifically the proportions of subjects that are based on standard assumptions of rationality and self-interest (called economics subjects in the paper) and those that rely on “human assumptions” (called management subjects in the paper).

In a nutshell they are interested in the proposition that “managers are more successful than business analysts.”

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The analysis is based on FT ranking data and done at the level of the school. The authors do make an attempt to account for he problem of endogeneity of GMAT scores. They conclude that

Controlling for the average quality of their students and some other schools’ characteristics, average salaries are significantly greater for those schools whose core MBA courses contain a higher proportion of management courses as opposed to courses based on economics or technical disciplines.

However, there is a major problem with the findings it seems to me. They measure the success of the course by average salaries (3 years after graduation). There is no measure of management ability. It seems to me that the authors have fallen into the very mindset that they decry. Measuring manager performance by the salary that the graduate manages to negotiate for themselves is precisely how a (rather poor) economist student might think!

I am not at all surprised that those students who major in management subjects (such as human resource management, negotiations and leadership) are better able to find a high paying job than those who major in Finance and Econometrics, poor tongue-tied geeks that they are.

*via Nick gruen at Clubtroppo


Mind the gap

Several years ago I posted a graphic plotting country’s GDP per head against mean lifetime and drawing attention to the tragic loss of life in southern Africa, mainly due to AIDS. There is a fantastic data visualisation tool called GapMinder that tells this story – and other stories- much more clearly. And it is really fun to play with.

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Click HERE to open the tool in another window at a much sexier version of the original graphic (for the year 2007). You need Flash 7 and it may take 30 seconds to load but it is worth the wait.

A quick explanation. Each point is a country and upper right means high GDP and high life expectancy. GDP is on a log-scale partly because the distribution is so skew, but also because the relationship is almost linear that way. Colours are different continents – with Africa in blue. Size of the blob is population size – probably not of primary interest here. But the really cool thing here is the last dimension – time. Move the slider back to 1800 and hit the play button to see the data displayed in sequence for the past 200 years.

My original interest in these data was the AID epidemic in Africa. Focusing on the blue swarm of African nations, you will see that there was virtually no improvement in life expectancy until after WW2. Over the past 30 years however, you will also see the blue swarm stagnate to the bottom left. Then, during the past decade about 10 middle income countries just drop through the floor. Pretty stark it is.

You can follow individual countries just by clicking on them (or on their name in the list at the left). Below is the trajectory for Iraq. What do you think happened in 1979?

Other countries whose trajectory has a story to tell – Rwanda but ther civil war was devastating it pre-genocide (1994), Chile which did well after Pinochet (1974) but was doing extremely well in terms of life expectancy before 1974. Check out Russia…it hardly looks like the wall coming down was a resounding success.

Let’s get parochial. Apart from minor glitches after the great depression and WW2, Australia has enjoyed an uninteresting march towards wealth and health. Give me a boring trajectory any old time. For those who ever doubted that NZ was the eighth state, look at their trajectory at the same time as ours. Peas in a pod.

China watchers might like to focus on the middle kingdom around the late 1950’s. I was actually impressed that they managed to get data on life expectancy from a nation that does not like its dirty linen aired. But this thought process led me to a more obvious question – what does life expectancy mean for 2007? This has to be a model projection – it is not really data at all. So I checked the documentation and it is defined as “the number of years a newborn child would live if current mortality patterns were to stay the same.” In China’s case then this would mean that the drop we see is an extrapolation of what would have happened if the great leap forward continued indefinitely. Ditto Rwanda. It is certainly not the case that the babies who were born in Rwanda in 1991 will have a mean life of 24 years.

I look forward to the inclusion of 2008 and 2009 data so we can see the ffect of the GFC and how it is differentially felt in different countries. Look out for the Icelandic bubble to bounce faster than Novak Jokivich’s service routine. You can waste hours playing with this site. There is a huge range of economic, environmental, health, education and demographic measured to select from.

If you want to use this tool for your own data.. .. you can’t. But GapMinder suggest using Motion Chart, which is a free gadget in Google Spreadsheet (an online spreadsheet similar to excel).

Cross Posted at ClubTroppo and Fishing in the Bay


Rooned. We’ll all be rooned.

There is something about the way real estate trends are reported that borders on the irresponsible. OK. Real estate is the single biggest exposure that Joe and Jill Average have to the economic cycle and people are naturally interested. I get it. But bearing in mind the level of herd behaviour involved in any market, media exaggeration of any figure that can be converted into a sensational headline can only fuel irrational exuberance and despair.

Continue reading “Rooned. We’ll all be rooned.”