Category Archives: insight

The worst insurance policy in the world

Aviva in France is still dealing with having written the worst insurance policy in the world. From the sounds of things, they weren’t alone in this foible. It’s also hard to say as an outsider what the right or reasonable resolution to their current problem is, but here is the policy that they wrote.

  • Buy a policy
  • Choose what funds you want to invest in
  • Unit prices calculated each Friday
  • Allow policyholders to switch funds on old prices until the next week
  • Hope like hell policyholders don’t switch out of poorly performing funds into well performing funds with perfect information based on backwards, stale prices.

Inconceivable – and since I don’t know more than I read on this blog post, maybe the reality and liability is really quite different.

See the post from FT Alphaville on the man who could own Aviva France.

Economic growth during and after Apartheid and the real problem with 1%

I read a letter from Pali Lehohla on news24 this weekend. Lehohla, the head of StatsSA, disagreed with a report by DaMina Advisors on economic growth in South Africa during and post the apartheid era.

To paraphrase Lehohla, he disagreed with their methodology, their data and their values and ethics:

First, I need to engage the author on methods. Second, I address the facts. Third, I focus on the morality of political systems and, finally, I question the integrity of the luminaries of DaMina and ask them to come clean.

This wasn’t data I had looked at before, but some of Lehohla’s criticisms seemed valid. Using nominal GDP growth data is close to meaningless over periods of different inflation.

Second, the methodology of interpreting economic growth should use real growth instead of nominal growth because this carries with it differing inflation rates. This is to standardise the rates across high and low inflation periods.

I haven’t confirmed the DaMina calculations, but the labels in their table do say “current USD prices” which suggests they have used nominal data. It’s little wonder any period including the 1970s looks great from a nominal growth perspective with nominal USD GDP growth in 1973 and 1974 being 34% and 23%, compared to real growth of 2.2% and 3.8%. The high inflation of the 1970s arising from oil shocks and breakdown of the gold standard distorts this analysis completely.

Lehohla’s other complaint is also important, but less straightforward to my mind –

The methods that underpin any comparison for a given country cannot be based on a currency other than that of the country concerned. The reason is that exchange-rate fluctuations exaggerate the changes beyond what they actually are.

Two problems here – one is that purchasing power adjusted GDP indices are not typically available going far back in history. The other is that if one is using real GDP, the worst of the problems of currency fluctuations are already ironed out. (The worst, certainly not all and it would still be a factor that should be analysed rather than completely overlooked.)

I was disappointed that neither piece mentioned anything at all about real GDP per capita. Does it really matter how much more we produce as a country if the income per person is declining? Income inequality aside, important as it is, more GDP per capita means more earning power per person, more income per person, more things per person. It is a far more useful measure of prosperity for a country, and particularly for comparing economic growth across countries with different population growth rates.

My own analysis, based on World Bank data (available from 1960 to 2013)

real GDP growth (annual %) real GDP per capita growth (annual %)
1961-1969 6.1% 3.5%
1970-1979 3.2% 1.0%
1980-1989 2.2% -0.3%
1990-1999 1.4% -0.8%
2000-2009 3.6% 2.0%
2010-2013 2.7% 1.1%
1961-1990 3.6% 1.2%
1971-1990 2.4% 0.1%
1991-2010 2.6% 1.3%
1991-2013 2.6% 0.8%

 

I’ve put these numbers out without much analysis. However, it’s pretty clear that on the most sensible measure (real GDP per capita) over the periods the DaMina study considered, post-apartheid growth has been better than during the 1971-1990 period of Apartheid.

The conclusion is reversed if one includes the 1960s Apartheid economy and the latest data to 2013, the picture is reversed on both measures.

This, above all else, should talk to the dangers of selecting data to suit the outcome.

This analysis doesn’t talk to the impact of the gold standard, the low cost of gold mining closer to the surface than it is now, the technological catch-up South Africa should have benefited from more in the past, the impact of international sanctions and expenditure on the old SADF and who knows what else. There are much big monsters lurking there that I am not equipped to begin to analyse.

My overall conclusion? The Apartheid days were not “economically better” even without ignoring the millions of lives damaged. Unfortunately, our economic growth has for decades been too low to progress our economy to provide a better life for all.

Here is the problem:

1961-2013 1961-2013
Real GDP growth Real per capita GDP growth
South Africa 3.2% 1.0%
Kenya 4.6% 1.3%
Brazil 4.3% 2.3%
USA 3.1% 2.0%

Despite the theory of “Convergence“, the US has had double South Africa’s per capita GDP growth for over five decades.  Real GDP per capita increased by 72% in South Africa over the entire period from 1960 to 2013, which sounds impressive until you realise that the US managed 189%. That is more than 2.5x our growth Brazil has done even better at 237%. “Even Kenya” outperformed us over this period.

1% per annum real per capita GDP growth is just not good enough.

Progress on tax free savings vehicles, but scathing words for life insurers

Read the latest (14 March 2014) document from National Treasury on tax free savings vehicles for South Africa. I think it’s a fantastic idea – both from a policy perspective with carefully designed incentives to promote long-term savings and from a personal perspective. I’m definitely going to use one for my own savings. However, one paragraph stuck out as a pretty clear message from National Treasury on their views of life insurers – and views on current product offerings rather than any historical sins:

Insurance products

Products must permit flexible contributions and may not bind individuals into any future contribution schedules. Many insurance investment policies would currently not match these criteria. Government is not open to providing a tax incentive for products that have high charges and may have an adverse impact on household welfare at the point at which the household is increasingly vulnerable. In this regard some savings products, for example endowment policies and any similar investments that include excessively high penalties in the case of early termination of the policy, pose a policy challenge from a market conduct perspective and will not be allowed in these accounts.
As discussed, National Treasury will engage with the FSB and industry in determining a reasonable approach to charges and early termination.

 

Wow. I know there are many bad insurance products around and probably some still being sold. I also know of many insurance executives who strive for value for money and are reinventing products and distribution channels to this end.
Seems to me NT isn’t yet on board.

Is credit extension in SA out of control?

Unsecured credit explosion? Sure. Concerns about abuses and sustainability in this sector? Absolutely.

But is overall domestic credit extension out of control? Are real interest rates negative? Is the global economy strong and steaming ahead?

The answer to all these questions is “no”. Here is a graph produced from public reservebank data.

Credit extension is recovering after a precipitous decline after 2007, but is still below long run averages
Total credit extension is hardly out of control.

The virtual irrelevancy of population size to required sample size

Statistics and sampling are fundamental to almost all of our understanding of the world. The world is too big to measure directly. Measuring representative samples is a way to understand the entire picture.

Popular and academic literature are both full of examples of poor sample selection resulting in flawed conclusions about the population. Some of the most famous examples relied on sampling from telephone books (in the days when phone books still mattered and only relatively wealthy people had telephones) resulting in skewed samples.

This post is not about bias in sample selection but rather the simpler matter of sample sizes.

Population size is usually irrelevant to sample size

I’ve read too often the quote: “Your sample was only 60 people from a population of 100,000.  That’s not statistically relevant.”  Which is of course plain wrong and frustratingly wide-spread.

Required Sample Size is dictated by:

  • How accurate one needs the estimate to be
  • The standard deviation of the population
  • The homogeneity of the population

Only in exceptional circumstances does population size matter at all. To demonstrate this, consider the graph of the standard error of the mean estimate as the sample size increases for a population of 1,000 with a standard deviation of the members of the population of 25.

Standard Error as Sample Size increases for population of 1,000
Standard Error as Sample Size increases for population of 1,000

The standard error drops very quickly at first, then decreases very gradually thereafter even for a large sample of 100. Let’s see how this compares to a larger population of 10,000. Continue reading The virtual irrelevancy of population size to required sample size

Fixing SA education – political will not (only) money

I blog from time to time about education in South African and its frightening link to unemployment and all the societal ills that go along with that. I also point out that as a nation we spend a fair amount of money on education with very poor results.

This story about absenteeism amongst South African teachers goes some way to explaining the problem.

Teachers in our public school system took an average of19 days of sick leave per year. I also blog about the dangers of averages. For every teacher that doesn’t take sick leave (and I’m sure there are many) there are teachers taking more than 19 days of sick leave per year.

What’s interesting here is that not only is this an astonishingly high number, it’s also clearer more than the 10 days per year on average on a rolling 3 year basis that is allowed under the Basic Conditions of Employment Act.  Let’s also not forget that while teachers should probably be paid more in an ideal world, they do also get vastly more annual leave than most already.

I’d also like a four day week every second week thank you.

How exactly are these teachers allowed to take so much sick leave? Well unfortunately the answer is the same as why our education system is in such a sorry state. Poorly trained, poorly motivated teachers without a culture of pride in their work, overly strong unions and no political will to do anything about it.

Changing attitudes and demographics

I blogged a while back about marriage and divorce rates and based on census results. I still think that’s pretty interesting stuff. Then today, I noticed a story showing how 8% fewer South Africans were married in 2010 compared to 2003 even while the population continues to grow.

The result reflects a significant decrease in the rate of marriage. Of course this still isn’t the whole story. It should be fairly obvious to everyone that the rate of marriage is not constant across age – and that was a big part of my earlier posts on marriage. So as the population pyramid of South Africa changes, we would expect a difference in the overall rate of marriage even if the rates per age themselves didn’t change.

The analysis we really need is a “hazard rate” type analysis fitting marriage rates per age (and probably by race group given the significant differences by race) and then seeing whether these rate are changing.

The linked story also points to a 42% decline in customary marriages and a much smaller 4% decrease in civil unions. This then probably reflects a separate trend fundamentally away from more traditional approaches to more “modern” (no judgement attached!) approaches. If one considers the marriage rates in Northern Europe are massively lower than in more developing markets, I’d put money on this trend continuing in South Africa for a long while and with at least as big an impact.

The Perfect Storm Part 1 – IFRS reporting under SAM

A client recently mentioned that they were concerned about the implication that the adoption of Solvency Assessment and Management (SAM) would have on insurance accounting under current IFRS4.

The apparent concern was that measurement of policyholder liabilities for IFRS reporting would change to follow SAM automatically.

Let me start out by saying this is categorically not the case. The adoption of SAM should not change IFRS measurement of insurance liabilities. In this post I’ll cover some of the technical details and common misconceptions of IFRS4 to demonstrate why this conclusion is so clear. Continue reading The Perfect Storm Part 1 – IFRS reporting under SAM