He claims there is approximately R12bn of money outside of the formal banking system, or “under mattresses” as I believe he put it. This may be true.

Then, and this is where I have a problem, states that “It would have a massive impact if that money came into the market” with the implication that this would be a good thing. This reflects a broken understanding of monetary policy.

Putting this un-banked money into banks would allow it to be re-loaned, applying the multiplier effect and effectively expanding the money supply. Whether expansion of the money supply by R120bn (assuming effective multiplier is around 10) is a good thing or not is a question of fact, yet to be resolved.

Of course, if this were a good thing, the Reserve Bank could achieve the same thing through a combination of open market purchases of bonds (released cash into the money supply), weakening reserve requirements (allow the same money to be relent more times) or printing bank notes and dropping them from helicopters. They haven’t yet done this.

So it’s not really a good thing for the economy as a whole. It is a compelling argument for mobile banking though. Just saying.

Michael Pento from Euro Pacific capital writes about the options open Bernanke to stimulate the US economy through open market purchases given that interest rates are up against the zero bound.

He’s right about the options, but horribly misguided when it comes to wishing for deflation:

By keeping prices from falling more that they would have naturally, Fed intervention has created a burden.

The US public (and private) debt is such a significant portion of GDP, the correct answer cannot be to increase it as a percentage of GDP by deflating prices and keeping the nominal value of outstanding debt the same. Moreover, what the US needs is economic activity; encouraging everyone to leave their money in the bank because it increase in value every day and “nobody else is spending so deflation will continue” doesn’t sound like a success story to me. Downward price stickiness, particularly with wages (yes, even in the US) would add to the catastrophe.

Pent also raises the risk of hyperinflation:

…investors would be forced to once again abandon savings and chase runaway prices.

I don’t know how we went from fears of deflation to “runaway prices”. The challenge with this policy is to credibly promise moderate inflation for several years (depending on how strong your Ricardian views are).

Runaway prices are much easier to control than deflation. With inflation, we actually have a range of tools to use.

It’s unreal how many people have views on the economy that aren’t rooted in any economic theory at all.

The economics of a fund manager depends entirely on growing funds under management so that revenues (based on assets under management) grow to be larger than costs (significantly fixed and at most semi-variable). Details of performance fees and the second order impact of investment performance aside, a successful fund manager must attract positive net client cashflow, and lots of it.

Half the 960 available unit trusts have less than R100m in AUM. Some of these may be rapidly growing new funds, but many have been stagnant with slow growth for several years.

The FSB’s attention presents opportunities for consolidation between funds and should place larger funds in a stronger position competitively. Total Expense Ratios (TER) for these funds with significant scale should already be lower than smaller funds. Maybe it’s time the larger funds made more if their size and cost efficiencies. If they are going to take the heat for being too large to be nimble, they might as well reap the benefits too.

It will be interesting to see what this means for white labelled funds and whether the economics of these convince the regulator that they should survive.

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Cash has run out. The overvalued, over-geared properties cannot support the income stream that was demanded from them.

No surprises here then.

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Not least of which is what teachers actually earn. A full-page advert in newspapers last weekend gave some very respectable figures  for teacher salaries.  A teacher just starting out, with a 4 year qualification has a total cost to employer of around R229,000 per year. This includes 13th check, pension, medical aid and housing allowance, but is a surprisingly high number. It also included the then-proposed 7% increase (versus CPI at 3.7% at the moment).

The offer was increased to 7.5% since the original advert, but the numbers below are the unadjusted numbers in the advert. These are annual basic packages excluding benefits. (It’s unclear whether the before Total Cost to Employer columns include or exclude the 13th check, which is definitely included in the TCE column).

This advert prompted an immediate outcry from teachers writing to complain that they earn nothing close to that figure. This was followed up by government affirming that the figures are correct, noting that many teachers may not add up all the non-cash benefits.

IOL has an article purportedly showing that teachers are well aware of the extra benefits and aren’t paid what government claims .

The Daily Dispatch has a similar article, and includes a scan of a salary slip showing clearly (if the slip is genuine) that the government figures are bogus. From the salary slip, a teacher with 15 years of experience shows R12,885 as a monthly total cost to company translates to R167,505 as a TCE, assuming a 13th cheque equal to the entire monthly TCE (which is almost certainly an overestimate since it’s unlikely housing allowance and medical aid would be included in 13th cheque). This should be compared against the 2009 column since this doesn’t yet reflect any increases for the current year. The comparison shows that the TCE is probably slightly below what the government has as a basic salary for someone with 15 years of experience.

The figures are so different, that I can’t help wonder if it isn’t the government that is confused about the additional benefits. The total salary reflected on payslips includes the additional benefits (but probably not 13th cheque) and these benefits are deducted from the total before arriving at the cash pay for the teacher.

I can’t understand why this story hasn’t been ruthlessly followed up by the media. A few reports here and there aren’t enough. There are only a few options:

1. The government blatantly lied about the figures.
2. The government is confused about what it actually pays teachers (wow – this is problematic)
3. Teachers are not paid consistently. Perhaps some teachers do earn what the government put out in the advert, but others don’t. (How is this fair, and does the government even realise this?)
4. Teachers are misleading the press about what they earn, either inadvertently or deliberately.

Surely this is massively newsworthy no matter which of the options is correct? Doesn’t this change the bargaining positions completely?

Even if the gross figures in the table are wrong, the relative sizes might still be correct. According to the table, teachers have been getting average annual increases over the past four years of between 9.7% and 11.1%. These are not insignificant increases at all given that inflation has average well below this point. Teachers have been getting real increases every year for several years.

It’s hard to justify this based on efficiency improvements (more on this in a later blog). It’s also hard to say that education has improved over this period (although this is much debated).

The experience adjustment translate to an additional increase of between 0.4% and 1.6% per annum. So an actual teacher being according to this scale would experience an annual increase of above 10% each year, when allowing for experience adjustments.

There are so many questions of fact here. What is the point of long-running strikes and heated debates about affordability and fair wages if we can’t even agree on the current numbers?

It’s based on US research, so the parallel to South Africa isn’t perfect. On the other hand, it may prove predictive for our population.

A few snippets (it’s a long article, but well worth reading the whole thing):

1. The median age at first marriage in the early 1970s was 21 for women and 23 for men; by 2009 it had climbed to 26 for women and 28 for men
2. Definitions of adulthood vary widely – people can vote at 18, but in some states they don’t age out of foster care until 21. They can join the military at 18, but they can’t drink until 21. They can drive at 16, but they can’t rent a car until 25 without some hefty surcharges. If they are full-time students, the Internal Revenue Service considers them dependents until 24; those without health insurance will soon be able to stay on their parents’ plans even if they’re not in school until age 26, or up to 30 in some states.
3. Definitions of adulthood are clearly not just a function of age. (and so our marketing to them should consider more subtle measures than simply age ~ David Kirk)
4. As “emerging adults”, young men and women are more self-focused than at any other time of life, less certain about the future and yet also more optimistic, no matter what their economic background. This is where the “sense of possibilities” comes in, he says; they have not yet tempered their ideal­istic visions of what awaits. “The dreary, dead-end jobs, the bitter divorces, the disappointing and disrespectful children . . . none of them imagine that this is what the future holds for them”. Ask them if they agree with the statement “I am very sure that someday I will get to where I want to be in life,” and 96 percent of them will say yes.
5. But despite elements that are exciting, even exhilarating, about being this age, there is a downside, too: dread, frustration, uncertainty, a sense of not quite understanding the rules of the game. More than positive or negative feelings, what Arnett heard most often was ambivalence — beginning with his finding that 60 percent of his subjects told him they felt like both grown-ups and not-quite-grown-ups.
6. The 20s are when most people accumulate almost all of their formal education; when most people meet their future spouses and the friends they will keep; when most people start on the careers that they will stay with for many years. This is when adventures, experiments, travels, relationships are embarked on with an abandon that probably will not happen again.

This is thought-provoking stuff.

Marketing to this demographic must factor in South Africa’s demographic, social, economic and political changes over the last 40 years (and continuing development).

Further, marketers and communicators must consider how this changing pattern of early adulthood will affect these adults later in life. How it will affect their views and preferences, the goods they demand, who they listen to and what marketing works.

Their housing price index is more robust (and more independent) than those of the banks based off their own data and target markets. Rather than consider only the average price of houses sold in that particular month (which is a function of house price growth / decline but also how the type, condition, size and location of the houses sold that month differ from the prior month and year) they consider repeat sales where the same property has been bought and sold more than once.

This data is combined or “chain-linked” to provide a continuous measure of house price inflation over time.

House Price Inflation 2010 source: lightstone.co.za

The result of all of this data, best-in-class methodology and analysis? When Lightstone says “opportunities abound in local market” I actually listen. Since their business model is to sell information, I’m more likely to trust what they say.

It’s almost all unknown

I don’t disagree.  It’s just that almost every meaningful decision ever made is made without all the information.

Unknowns can be categorised a hundred different ways. One way is to think about:

1. Unknown past information
2. Uncertainty around the current situation or position
3. Unknown future outcomes

Even a game like chess, where the past history of the game is easily known by good players, the current position is clearly visible and all the possible moves are knowable, it is not possible have all the information about how your opponent will react to your move.

How to deal with decision making under uncertainty – part 1

Tyler suggests that gut-based decision making can be effective much of the time – and it can. It there genuinely is no time for anything more than an instinctive reaction, you probably are best going with your gut.

Even if you have plenty of time, listening to your guy to formulate an idea is a great idea. Insight comes partly from experience and the reinforced neural pathways of our learning brain. If you stop with the gut though, you are missing out. There is a tremendous amount of research showing how ridiculously badly our instincts perform in many areas, particularly those relating to uncertainty and complexity!

The way to use your instincts is to create hypotheses or theories to test and evaluate with real information and analysis. Prove that your instinct is right and you’re good to go. Try really hard and not disprove it, without coming up with better ideas, well maybe it’s worth giving it a shot anyway. Realising that your immediate feelings were deeply flawed? Priceless.

How to deal with decision making under uncertainty – part 2

Tyler also gives four suggestions if you don’t want to merely follow your instincts blindly.

1. Stop and Think
2. Ask for Advice
3. Give it Time
4. Relax and Have Fun

These probably aren’t the four worst ways to make decisions, but they’re certainly not the best.

Stop and Think is merely an invitation not to follow your gut. No news here.

Ask for Advice is actually pretty good. It’s just not the correct first step though (more on that in a moment).

Give it Time can also work, but on its own its just a different way of using your instincts. You’ll never know if, how or why you changed your mind. You also put yourself at extreme risk of confirmation bias.

Relax and Have Fun certainly sounds like a good idea, although whether it will give rise to good decisions depends very much on the time of industry and type of problem. In the same way that brainstorming is a good method for marketing and social appeal of ideas (it was invented by Alex Oxborn, an advertising manager) but not great for most other problems, relaxing and having fun offers no real promise of sophisticated decision making with uncertainty and complexity.

How should you make decisions with limited information?

I’m not going to say there is one correct way, but the following points are helpful:

• Work out, very specifically, what problem you’re trying to solve or what question you’re trying to answer. Sometimes framing the question clearly can provide its own insights. Further, if you are to work collaboratively with others, or seek advice, you’ll have to have a very clear idea of what you’re trying to achieve. Communication is critical to teamwork.
• Work out what information you have, what you need, what you could get, where you can get it and what the costs might be of obtaining this information. Now you can ask for advice because you know what you’re asking for.
• Use your instincts and initial thoughts and feelings to generate some avenues of investigation or hypotheses to test
• Actively work to generate new ideas and possible solutions or lines of investigation. Here, brainstorming might be useful as one method. Consider similar problems, examples or analogies from other people, other organisations, other industries, other countries and cultures, other time periods. This is where you get to be creative. Don’t worry too much about whether or not the ideas are workable – that comes later.
• Categorise and prioritise the information, questions and hypotheses. As you finish generating ideas, you need to start synthesizing the ideas into useful units.
• Critical evaluate the ideas, using logic, analysis, modelling and frameworks. Evaluation here requires both sides of the coin. What are the problems, the flaws, the risks, the reasons it can’t work. Then, what can we change, tweak, fix or improve to get around these problems or otherwise improve the scenario.

Throughout, ensure you keep the big picture in mind, that you remember what you’re trying to achieve. The dangers of under-analysis are only trumped by too much, misdirected meandering analysis.  Keep it focussed.

The steps above don’t necessarily have to be done in order, and typically each step can be revisited several times during the process. These ideas borrow heavily from Edward de Bono’s Six Hats of Thinking.

The point here is that complexity and uncertainty requires a more, not less, structured approach to use as much information as possible and to avoid many of the heuristic mistakes humans make. This is true in general, but even more so if you need to work in a team or need to convince external parties of your process to lend credibility to your decisions.

1 The Competition Commission is necessary

Monopolies serve to increase prices for consumers. In Monopoly, the “rents” charged are instantly higher as soon as a player has a monopoly on property in a certain area.

Worse than the increase in prices and decrease in supply, the additional profit for suppliers is not equal to the cost to consumers from higher prices, resulting in an overall “dead weight loss of monopoly” or an overall cost to society.

To date, the Competition Commission has focussed on cartels and price collusion. We can only hope soon they will consider issues of local loop unbundling to provide real competition to the effective monopoly Telkom has on ADSL lines.

2 The easy availability of credit is a useful and dangerous tool

An important consideration in Monopoly is to prevent competitors from owning property (so that you don’t have to pay rent on as many properties as possible) and definitely don’t get a monopoly (so they can increase rents and improve the properties, increasing rents even further).

A key way of doing this is by buying as many properties as possible, even if you mortgage many of them with a fresh injection of cash from the bank and very reasonable repayment terms. Leverage, or borrowing, can provide cost effective (especially after tax considerations) financing for profitable projects. It can be cheaper to raise than equity and increases returns to shareholders.

Leverage also creates significant risks, both in Monopoly and real life. Overextending can make you more likely to end up bankrupt. Also, by artificially increase the supply of funds for purchasing property while keeping the supply constant, the price of property will increase dramatically with distorting impacts on the allocation of resources within an economy.

3 Trading is good for those who trade

Every time two people (or organisations, or countries) trade, both parties are better off than they were before. (A hint, otherwise they wouldn’t have traded.) The trading parties are each better off, and the non-trading competitors are worse off, because a potential trade is now off the table and they are not in a better position otherwise.

There are some plausible arguments for trade restrictions in very particular circumstances. For example, I think I buy the idea of nurturing infant industries, but only if there is a reasonable chance that the industries won’t only grow as far as pimply, sulky adolescents with no drive or ambition.

Other than that, trade is good as it increases prosperity on average, which is one important way to lift more families incomes above the poverty line.

4 Liquidity risk can be the end of you

While buying as much property as possible and mortgaging some to provide additional funds will generally work in your favour and allow you greater control over the board, it also introduces liquidity risk. If you don’t have the funds to pay rent or taxes or fines when they unexpectedly fall due, you will be forced into a fire-sale of houses and hotels at way below replacement cost. You may need to mortgage even more properties, reducing your income generating ability and possibly sending you into a debt trap where your income isn’t sufficient to meet your expenses.

Always watch your liquidity. It has almost become a truism that more businesses fail because of liquidity than solvency or profitability.

5 The world is full of randomness, but it always helps to calculate the numbers

In Monopoly, the player “roles the dice and moves the mice” so to speak. There is plenty of luck around and skill can seem to disappear in an avalanche of random numbers.

Nassim Taleb (of Fooled By Randomness fame) would suggest that in everyday life we underestimate risk and overestimate skill. I tend to agree with this overall comment. It doesn’t mean that we should try to use our skill as much as possible.

Did you know that certain properties are relatively more valuable than others? The properties just after Jail are more likely to be hit than others, since several cards and one square on the board send the player to jail. Similarly, several chance cards require the player to advance a certain way, making the squares immediately after a chance square less likely to be hit. The cost to benefit of houses on certain squares are better than others, and the best bang for buck is somewhere between 2 and 3 houses per property.

It’s important to be aware that risk and uncertainty exists, but it’s more important to understand risk in a way that allows informed, risk-aware decisions to be made.

Identify, measure, mitigate and monitor risk!

Are all the lessons good?

Slightly tongue in cheek, there are a few other lessons of dubious validity:

1. Stay in jail and make more money
2. You get to keep the money if the bank makes an error in your favour
3. You can take as long as you want to repay your mortgage and only have to pay 10% interest
4. If the bank runs out of money, it can always photocopy some more
5. When the game is over, you can forget about the debt you have and walk away