Merry Christmas!

This Christmas greeting from the atheist penguin household comes to you courtesy of Hungry Boy, Chatterboy, and Grandma Penguin, who assisted with the architecture.

Book Review: Nudge

Today’s book review is Nudge: Improving Decisions about Health, Wealth and Happiness, by Richard H Thaler, and Prof Cass R Sunstein.

I’ve missed the zeitgeist with this one – this book was apparently very popular with Barack Obama’s policy team well before he won the election. And Sunstein is now head of the White House’s Office of Information and Regulatory Affairs. Nevertheless, it is still a great read, even two years late.

This book does a superb job of translating the themes of behavioural economics:

• Heuristics: People often make decisions based on approximate rules of thumb, not strictly rational analysis. See also cognitive biases and bounded rationality.
• Framing: The way a problem or decision is presented to the decision maker will affect their action.
• Market inefficiencies: There are explanations for observed market outcomes that are contrary to rational expectations and market efficiency. These include mis-pricings, non-rational decision making, and return anomalies. Richard Thaler, in particular, has described specific market anomalies from a behavioral perspective.

into policy choices – mainly for governments, but also for anyone who is trying to help people towards good decisions, without taking away their choices.

So the authors talk about various ways in which public policy can be improved by understanding the real behaviour of real people, rather than always assuming that they behave “rationally” (or in ways that would see them make economically rational decisions, at least).

The key chapter of the book, for me, was the chapter about Choice Architecture. As part of their introductory section explaining that humans do not always behave as “homo economicus”, Thaler and Cass describe what they call “Choice Architecture”. Choice architecture consists of all the different ways in which people’s choices are influenced within a given decision making framework:

• Defaults – depending on the significance of the decision to the person making it, many people will take the option that involves the least effort. So, for example, when installing new software, most people will take the default option. So the person who decides the default has huge power in that decision. In many cases, doing nothing is the default option. But that doesn’t always have to be the case. Organ donation is a good example where different cultures have different defaults – in some cases the default assumption is that organs will be donated. And in other cases that they won’t. And organ donation rates are mammothly different as a consequence.
• Expect error – many people make errors. A good choice architecture is forgiving of that. Good examples come from medicine – where drug regimes are designed to help patients remember to take them (for example, there are rarely pills that need to be taken every second day, because they are most likely to be forgotten).
• Give Feedback – people make better choices when there is immediate feedback about what they have chosen – for this reason many digital cameras make better photographers. So the more frequently people make choices, with feedback, the better their subsequent choices will be
• Understanding mappings from choice to welfare – how do people figure out which choice is going to work for them? In medicine, where the choice is often between different types of undesirable side effects with different probabilities – this can be very difficult. So helping someone going through this choice do the translation between the choices and what the outcome will be like is an important part of setting up a good choice architecture. For example, for big medical decisions, talking to someone else who has made one of the choices can be extremely helpful – particularly if they have worked out how to live with a particular side effect.
• Structuring complex choices into simpler ones – If you are offered a flat choice between 30 different options – for example for ice cream – it’s quite hard to decide quickly.  But if similar choices are grouped together (fruit sorbets with each other, various chocolate options together, and then the weird and wacky bubble gum flavours in a third spot) – you will probably choose one group, and then choose within the group, and be able to come up with a good choice. But the choice could be changed by the groupings you are given.
• Incentives – (most often price) – this is the part of choice architecture which always gets a mention in economics textbooks. But it is often not that important, particularly in situations where the price paid isn’t particularly obvious (situations that many companies try hard to engineer – for example exactly how different credit card charges work isn’t all that obvious until well after the payment decision has been made) There are many situations where price is a long way from being the main consideration  - an just calling those situations “price inelastic” doesn’t necessarily capture the right policy information about what incentive might work. And of course, incentives are not just about the consumer price. They are also about understanding the incentives for all the suppliers in the chain – the home builder who has no incentive to put insulation into a house before it is sold, to the hairdresser, who gets a commission if she can convince me to start colouring my hair to hide the grey.

Fundamentally, offering a choice to someone (with or without a price signal), and especially offering a default choice (which is often unavoidable) will be making decisions on behalf of the chooser. It is important to be aware of that – so that the default or the framing is as constructive as possible. And it can be stronger than that. By being aware of the choice architecture of many aspects of our society, public policy decisions can be improved. It’s not an example in the book, but I think Sydney’s experience with water policy shows that. This paper from IPART shows that ”if price increases were used to replicate the demand reduction achieved by level 3 water restrictions, residential water (usage) prices would need to rise by between 62 per cent and 143 per cent. If the water (usage) price increase applied to both residential and non-residential consumption, prices would need to rise by between 57 per cent and 121 per cent. ” Sometimes price isn’t the most effective way for a government to achieve a given outcome – it can be achieved with nudges in other ways that may have smaller negative effects than the price alternatives. One chapter of the book (grandly titled Saving the Planet) suggests that making an effort to provide feedback to people about the environmental consequences of their decisions would significantly improve behaviour.

The book is less successful in extending the analysis to the case for privatizing marriage – or, less radically, making the “default” partnership (currently marriage) a more logical structure. Although they make some good points, here they start to tread into the area many micro-economists find themselves in – pontificating on a subject that has been written about extensively without making the effort to read the the previous literature more than superficially. A minor cavil, though, for what is an excellent and thought provoking book. It should be read by policy wonks everywhere.

Liberal party Sex symbols

After this column from Janet Albrechtson, arguing that, really, women will vote for Tony Abbott because he’s sexy (blog commentary here and here):

And for completeness sake and because we are all human, there is no point avoiding the other thing that differentiates Abbott. Fit and50-something, the runner, cyclist and former boxer in a pair of Speedos with a “love rug” is also a rarity in politics. On that note, I’m counting on more than a few women agreeing with Nigella Lawson, the curvy kitchen guru, who said: “I like an animal. Hairy back, hair everywhere. I don’t understand why a woman would want a hairless man. If I was to go for smooth, I may as well be lesbian.” Be honest, girls. Abbott has caught your attention in a way that Rudd never did. Or will. Whether that translates into votes for Abbott is another matter. But watch that space too.

I was amused to read this in my Sun Herald “the hot list of 2009″ (from the very fluffy Sunday Life magazine):

Malcolm Turnbull

Oh, how the mighty are fallen! The former leader of the Opposition has made more enemies in the past 15 months than Gordon Ramsay has in a lifetime. Was it because he was smug? Out of touch? Could it possibly have been that booming baritone voice? Probably. But let’s pause for a second and consider the man. Admit it, he’s handsome. And he gave up the leadership for a …principle. And before you curl your lip and turn the page, consider the alternative: the reptilian Tony Abbott. He may have slithered his way into the hot seat, but it’s Mal who has our loins.

I think that settles it. The only people who actually think Tony Abbott’s election has raised the sexiness of the liberal party are those who have a political stake in doing so.

Fertility rates update

The annual fertility statistics were released last month. There wasn’t as much of the traditional story about how Peter Costello had single handedly forced up the fertility rate by introducing the baby bonus (here’s a story here – reasonably staid), which was so prevalent a few years ago, but I thought was worth updating a  fertility post I wrote a few years ago, in which I tell you why it’s all to do with Gen Xers finally having children.

The births per woman* this year jumped from 1.92 per woman to 1.97 per woman – the highest since 1977. Here’s a graph showing the variability of this statistic.


But this statistic is misleading. The main reason there are more babies this year is about the age of the women having babies. A very strong trend in the past 10 years (at least) has been a delay in women having babies. If current age specific rates continue, women born in 1972 will be the first generation to have more babies in their 30s than in their 20s.

The graph below shows this effect.

And if we then look at the total births per woman, by the year of birth of the woman, we can see that this fertility rate is much smoother, and is gradually falling towards 2.0.**

Interestingly, the total births per woman is not that far away from where it was for women born at the beginning of this century – a woman born in 1906 could expect to have 2.33 babies in her lifetime, and a woman born in 1972 can expect to have 2.0 babies in her lifetime. The rate peaked for women born in 1933, who could expect to have 3.11 babies in their lifetimes. You can also see that those women didn’t have nearly as many babies in their 30s as their mothers did – they had had two babies already in their 20s, so the fertility rate of women in their 30s dipped substantially.

So  the baby bonus has had very little if anything to do with the number of babies born in Australia recently – it is just all those thirty something women finally having the second baby they always intended to have.

And here’s a couple of bonus interesting statistics that really jumped out at me when I was playing with these statistics – first teenage fertility rates:

The teenage fertility rate for women born in the 20s is pretty similar to the teenage  rate for women born in the 70s – it continues to drop now, but had an enormous jump in between. I had expected that precipitous drop in teenage birth rates that happened (the peak was for women born in the 50s), but I hadn’t realised it had gone up first.

And the fertility rates for women in their 40s still haven’t caught up to where they were for women born a century ago:

______________________________________________________________________________________________________________

* the population births per woman is calculated by adding up the total births in a given year, and dividing them by the total number women of childbearing (15-49) age that year

** note that at the older ages, for babies born after 2008, I have projected by assuming that age specific fertility rates stay as they were in 2008. This probably understates the babies born to women born after the mid 60s slightly, as age specific fertility rates continue to increase, particularly in the late 30s and through the 40s.

This (sartorial) life

On Friday, one of our major suppliers treated a few of us to a Boardroom lunch. It was very stylishly done, with good conversation about a mix of business and personal topics.  Amusingly, as we were leaving, our host commented that it was a shame it was on a Friday. “We usually wear casual clothes on a Friday, so it was a bit of a nuisance to put the tie on.” Amusingly, our office has dress down Friday also, so we had all dressed up just for each other.

Next time, maybe we’ll know each other well enough to go casual.

Warning: Actuarial post ahead – mortality statistics

This week, the ABS released the annual mortality statistics – the analysis of all the people who died in Australia in 2008.. Overall, at a population level, the “standardised death rate” (deaths per 1,000 population, adjusting for a standard age structure) was 6.0 per 1,000 people – the same as 2007. But splitting it down to males and females, the standardised death rate for both males and females went up slightly (from 7.2 to 7.3 for males and from 4.9 to 5.0 for females).

The ABS only releases statistics to 1 decimal place, so its hard to tell exactly where the increases were. But they appear to be largely in the older ages for women (all ages above 70 have a slightly higher death rate) and in the middle to older ages for men (40-44 year olds have gone up slightly, as have the over 80s, the early 70s and the early 50s).

It’s particularly interesting that the older age death rates have gone up, because that goes against a trend where mortality rates at older ages have been improving very significantly (much more than at younger ages) for many years.  Looking at the last 10 years, it is the first time that any mortality rate has gone up over the age of 70.

So I had a look at the preliminary cause of death analysis. I was half expecting to see a big increase in pneumonia and flu type deaths (perhaps the swine flu was widespread before our current flu season?) But diseases of the respiratory system dropped from 7.9% of the total to 7.3% (and the number of deaths from that cause actually dropped by 4% during the year). Lots of other causes took their place. But one increase interested me: Deaths from Endocrine, nutritional and metabolic diseases (mainly diabetes) increased by 10% during the year.  The numbers are small, but doctors have been warning for some time that current mortality improvements will come to an end as the proportion of the population that is obese increases. It’s too early to tell, but I’ll be watching the final analysis for this year (due out in March) with interest.

 

Why is Australia doing so well?

By world standards, the Australian economy is doing very very well. Our unemployment rate was 5.8% in October, up from 4.3% a year ago. No banks have been bailed out.  In May 2009, two Australian banks were in the world’s top 20 by market capitalisation (where Australia has around 1% of world GDP).  While the government has provided a guarantee on deposits, there have been no equity investments from the taxpayer into banks (or any other financial institution). And According to the Reserve Bank (page 72 of their semi annual review), fewer than 1% of households with mortgages have negative equity, compared with 23% in the US, according to this report. So is it just Australia being the lucky country, or is there more to it? I’ve got a few ideas of what we’ve done well, and a few more about our luck.

First, what have we done right?

Loan to valuation ratios – conservative lending

Australian mortgage holders, and mortgage providers have always been pretty conservative on loan to valuation ratios. A normal mortgage has a maximum of 80% of the home valuation. More than that, and you must take out mortgage insurance – which only benefits the bank if you default. That’s a statutory requirement. So while there were people borrowing more than 100% of the valuation, they weren’t that common. So our banks were not as aggressive as banks world wide. They tended to stick to lower risk lending and securitization.

Quite a lot of pundits give credit to for this conservative lending to the four pillars policy – the top four banks cannot be taken over by each other so banks knew they were relatively safe from takeover, so could afford to rest on their laurels and not take enormous risks.

On corporate lending, there was some poor lending. But none that has taken the banks down.

Regulation

The Australian Prudential Regulatory Authority (APRA) has a few things going for it. First, it regulates all retail deposit taking entities (as well as all insurance companies). So it catches, in a single institution, a large proportion of the financial services sector. Second, it had a near death experience in 2001, with the collapse of HIH. HIH was one of Australia’s biggest general insurers, and in Australia’s biggest corporate collapse (at least at the time) it fell apart with a $5 billion shortfall. That was on APRA’s watch.

APRA had been following a path of fairly light touch regulation – setting principles based rules, and enforcing them at a fairly high level. This is what the HIH Royal Commission had to say about their performance:

By 20 September 2000 APRA was on notice that HIH was potentially overstating its statutory solvency position by including pledged assets in the solvency calculation of its licensed insurers. Within weeks APRA had realised that HIH was also overstating its statutory solvency by means of a netting‑off process and incorrect reporting of its related body assets. At around this time APRA also learnt of the serious deterioration in HIH’s UK and US businesses. But, in spite of the mounting evidence of HIH’s problems, APRA did comparatively little in response. It grappled poorly with the information in its possession, either failing to recognise its significance or failing to analyse it thoroughly. It lacked commitment in enforcing in its requests for further information and explanations from HIH. It did not recognise the seriousness of the situation until it was too late for effective intervention.

Early in December 2000 APRA received a copy of the Ernst & Young report that was mentioned earlier. Later in December the officer to whom the report was delivered perused it. He passed it to his superior. That officer did not read it until late February 2001. He immediately recognised its significance but by then it was too late.

APRA paid attention to that report. Not only did they introduce a new supervisory regime for general insurance, but in a move that wasn’t particularly obvious outside APRA and regulated financial institutions, they changed their style of regulation. John Trowbridge, one of the three Members of APRA, has given a number of speeches in which he outlines the APRA approach to supervision, and why it has been very effective. Here is one:

Our prudential standards are built around capital adequacy, effective risk management and good governance. A fundamental plank of our approach is that we hold the boards of regulated institutions accountable for meeting the standards. We normally work through management but we reserve the right to deal directly with the board and we do so whenever we think we need to.

As I see it, our system does work effectively because APRA is a vigilant and effective supervisor. It was not always so, but APRA now has the resources comprising the experience, culture, competence and strategy to operate effectively.

The quality of active supervision of individual institutions is a critical success factor. Prevention is not only better than cure, it is also better than punishment after a failure. Active supervision is a pre-requisite and a sine qua non of an effective prudential regulatory system.

As someone who has been supervised by APRA, there is a lot to that. Their sticks don’t seem that large from a distance, but they can come in to a company at any time and demand any set of documents. If they think that you aren’t doing things properly, they can demand a lot of documents and management time. And if they don’t understand something, they are unlikely to let you do it, if they have any part of their regulatory armoury they can invoke to stop you. Each “visit” will result in a letter with some requirements, recommendations, and suggestions. The Board is expected to see that, and follow up on them. And if you are laggardly, they will keep visiting.

If you’d asked me two years ago, I’d have said they were excessively intrusive. There is definitely a cost to being regulated so intensively. But it does seem that that cost is a reasonable one to pay, given the place of financial institutions in our economy.

Stimulus

In common with everyone else, the government stimulated the economy heavily 9 and 6 months ago with various one-off handouts. In the Australian economy, we had the advantage that the budget wasn’t already in deficit, which means that the stimulus hasn’t damaged government finances to the extent it has in other economies. So while the government could have chosen that approach regardless,  Australia will not have to slash the budget too far in future.

Exports to Asia

Economic success isn’t just about financial institutions, of course. It’s also about the real economy. And Australia has the huge advantage of being the natural resources supplier to the Asian economy, particularly China. While the WA (the resources heavy state) economy took a sharper tumble than the rest of the country six months ago, it’s pretty much back to boom times now. So the real economy is in good shape.

On imagining flexible work

I’m not necessarily the best person to write about this. I have a very full time job. Both maternity leaves, I came back part time, and ended up full time quicker than I intended, as it just seemed easier to go in for that meeting every single day…

But I feel I do a reasonable job as a boss, in a large corporate, of making it work for my team. Usually I think that what I do is just sensible – it’s not that easy to get good staff these days. But then I run into people who tell me that flexible work is impossible in their teams (monthly deadlines, etc, etc) and I think that maybe I have some insights.

I have a team of nearly 40 people. In that team, I have various flexible arrangements:

• most actuarial students are studying some pretty tough exams. They have a day off a week study leave, during their peak exam season (2 months or so before the twice yearly exams). So all actuaries are used to organising who gets which day off (Wednesday is always the most popular – usually the senior students get that one).
• a uni student who comes in a day and a half a week. She does the mundane data crunching that everyone else turns their noses up at
• a guy with irreplaceable corporate knowledge, who was keen to take serious paternity leave when his wife went back to work. He is working a day and a half a week, one full day, and the rest what he can fit in, while we try and make sure we take advantage of his substantial experience
• Someone who works from home three days a week, two in the office – a completely full time load. I thought I had her forever, with that set up, but unfortunately a 50% pay increase was enough  that she was prepared to go into the office five days a week again for another company (the extra pay was enough so her husband could stay home with the kids).
• My deputy is four days a week (but five days for three months a year during year end). He started doing that when his youngest child was three – five years later, he would go full time again for the right job, but hasn’t found it yet. His wife is now working three days a week, so he values his day at home more than ever
• Two more people work 60% jobs, one of them two days in the office and one at home, and the other 9 – 2 every day.

And the one that cause me the most soul searching. I replaced one of my senior managers recently. The best candidate, by far, was someone who wanted to work three days a week. She had been doing that for the last 8 years. I really didn’t think the role was doable three days a week, but talked to her anyway. She convinced me that she was good at managing it. Three months later, it is working out much better than I expected. If she was working full time, she probably wouldn’t have taken the role – she would have had a bigger choice, and taken something more senior, with more challenge. But with the savings from her working only three days, I’ve hired an extra junior person in her team.  She is giving space to her team to grow and develop, but at the same time adding much needed experience to the team.

Part of the reason I took the risk on my new hire was that I passionately believe that the workplace has to change to give opportunities to people to work less than a five day week. I have the opportunity to make that happen, in a small way, in my team. So I went for it. But next, I realise, if I really believe in this stuff, I need to show my colleagues how well it works – to help them realise how much wider your talent pool can be with a bit of imagination.

In this current depressed environment, there are opportunities – many companies are actively asking people to go part time. But many more should be taking the opportunity to get a bit of experience at a cheap price, by going for someone who is keen to do a part time role.

Snobbery

I’ve been noticing, at work, in the last few years, my propensity to form instant judgements about people. And the things that cause me to judge the quickest? If someone catches public transport to work, I instantly conclude that I am going to like them and get on well with them (and the converse, of course).

Ironically, my actual experience suggests that this is not a particularly good test. I can think of plenty of people who catch public transport to work with whom I have civil relationships, but absolutely nothing in common with. And even a few that I can’t stand.

Really, I think all this says is that I am a complete snob. But a very ideologically sound one, of course.

In the meantime, I have discovered that the North Shore train line is a fabulous place for professional networking, if you aim to get into town between 7.30 and 8.

IQ Testing

I found an interesting old post and conversation a while ago about a sad article in the New Yorker. The New Yorker article was about a young gifted child who committed suicide. The brief facts are that a young 14 year old boy committed suicide with the gun at his parents’ farm. He had been homeschooled because he was gifted, and his parents had had advice that school would do nothing for him, because he was too smart for school.

One of the commenters, Jason Smith, said:

“Unfortunately my conclusion is that much of the popular writing, including advocacy groups and programs, on the gifted is distorted to emphasize their exceptionality as much or more than the mainstream education movement distorts the facts to justify the cookie cutter educational model. “

This over identification of extremely gifted children is, in my inexpert view, largely for technical reasons around the IQ test.

The original IQ tests were fairly approximate. They started out being approximations of the idea that your IQ is the ratio of your “mental age” and your “actual age”, particularly if you were a child. So if you were 10 years old, but could largely do school work of a 15 year old, your IQ was 150. Then that got conflated into IQ tests being statistical measures, with a mean of 100 and a standard deviation of 16, and a normal distribution. The trouble is that those two things don’t actually go together. The ratio thing was only a way of helping to understand the concept, it was never particularly scientifically based; and it would be a miracle if the human population neatly fitted those two concepts together with such nice round numbers.

I’m cribbing from this article, which is mainly about the new SB V test.

So until two or three years ago, there was one test for testing IQs for gifted children (the others tended to have too low a ceiling – if they were too gifted, they got full marks, which didn’t help work out just how gifted they were) – the SB LM. It was old, and had a number of other issues (like cultural biases), but had discriminatory power (that is even when you got to the very smart kids, you could tell which one was more likely to be a genius). That could give results up to 200, neatly fitting the mental age ratio idea (a 10 year old with a mental age of 20 is almost conceivable – see Terence Tao as an example). But nearly everyone who wrote studied gifted children commented that there were more of them than you would expect. But instead of concluding that the test wasn’t calibrated in the way you would expect - either the distribution of the population wasn’t normal, or  the standard deviation of the population was bigger than everyone thought on that particular test – testers still categorised children tested with IQs of (say) 160 as 1 in 10,000. But actually, it was probably more like 1 in 500 to 1,000.

The most likely explanation for this (in my non expert view) is the Flynn effect. The Flynn effect essentially says that the IQ of the population has increased by 3 IQ per year per decade for the last 30 years or so.The SB LM was introduced in 1972, so it is 30 years old. So the mean IQ of the population has gone up from 100 to 109 in that time. Doesn’t sound like much. But that alone, assuming that the distribution changes uniformly, would increase the proportion of children scoring above 160 from 1 in 11,000 to 1 in 1,300. Put that together with the commonly held view that the distribution of IQs has fatter tails than a normal distribution (ie there are more people at both extremes than suggested by the standard measures), suggests that there are a lot more children with IQ’s above 160 than the statistics suggest.

So Stanford Binet introduced a new test – the SB 5. It was designed to fix a whole lot of problems around IQ testing, among them, the ceiling effects on previous IQ tests, and the weird distributions that seemed to suggest we had “an epidemic of geniuses”.

So the new SB 5 really has a standard deviation of 15. I’ve been trying to find a sensible comparison for that child with an IQ of 160 on the old tests. The answer appears to be an IQ of somewhere around 135 – 145. (also see Table 7 here). But many people don’t like that, as our previous genius now appears to be merely smart. And if you are a parent with a gifted child, it’s easier to get your school to pay attention if you’ve got a very big IQ number to wave at them, as this kind of subtlety, particularly something involving standard deviations, is not what your average primary school teacher is trained to understand.

So anybody who has been tested on the old SB LM tends to rubbish the new SB V as incorrect – sometimes because it doesn’t give the old ratio IQ answer, and sometimes because it implies that the high IQ they have been tested with isn’t as rare as you might think.

Miraca Gross, studies 15 exceptionally gifted children in her book Exceptionally Gifted Children. They have been identified as children with IQs (on the SB LM test) of 160 or over. And they certainly seem to do a lot better with radical intervention than they do if teachers try to teach them pretending that they are no different to other children. So even if the old IQ tests overstate the rarity of gifted children at this level, they still identify children who will do better with radical intervention (such as skipping several years of school) that feeds their hungry brain at a faster rate than your average child.

Do I have any conclusions? Not yet. The main one is that just writing this out has made me even more uncomfortable with pushing myself down a path of caring about the result on an IQ test of either of my children. But yet; if it helps me advocate for them to get a more fulfilling and interesting education than they might otherwise get; is that worth while? Or will it just turn me into that nightmare pushy parent who I have rarely come across, but seems to exist just out of reach in all the stories about gifted children?