Improving the house price and income debate

While the RBA has warned of the risks of leveraging into the housing market on national television, they, and other analysts, have also presented a stable picture of the housing market, by estimating a house price to household income ratio of about 4x, and accompanying such analysis with statements like the ratio of housing prices to income has been reasonably flat for a number of years. 

Or, when he is at his best, Glenn Stevens can calm the nerves of recent home buyers with comments like this -

The other thing I’ll say is that it’s quite often quoted very high ratios of price to income for Australia, but if you get the broadest measures, a country-wide price and a country-wide measure of income, the ratio it about 4 ½ and it hasn’t moved much either way for 10 years.

I think I can safely say that most of Australia would disagree with this assessment of stability in the housing market or support from economic 'fundamentals'. Indeed even the RBA's own representations seem a little schizophrenic on the subject, with a recent report noting that the price-to-income ratio actually increased by 50% between 2001 and 2004.

Dwelling price growth significantly outpaced growth in household disposable income, with the nationwide dwelling price-to-income ratio rising from around 2½ in the mid 1990s to a little over 3 by 2001 and then to 4½ at its peak in early 2004.

Which is it Glenn? Did the ratio increase by 50% in that period, or hasn't it moved much either way for ten years?

One reason for the clash between public views on housing and the 'stability stance' we see out of the RBA is that the RBA grossly overestimates household incomes.

I have examined the data used by the RBA and other analysts from the National Accounts (Table 14), and tried to replicate their method and reconcile the differences with ABS household survey data, which more accurately reflects household income available for current consumption. It is possible, and I have shown my results in shown in the table below.

ABS household survey data shows that at the beginning of 2010, the average household income was $88,113 before tax and $74,360 after tax. This closely reconciles with my own household income estimates from the National Accounts data in 2010 (within 1.3%). Unfortunately due to the need to estimate the total number of households between census years, this method has quite a large margin for error.

Given the average national dwelling price at that time was $447,994 and the median about $415,000, we are definitely in an uncomfortable range of price-to-income ratios, with 5.0x in average terms using before tax income data, and around 6.0x in after tax terms. In terms of median incomes and dwelling prices, the ratio is probably closer to 5.6x before tax, and 6.8x in after tax income (as recently estimated by fellow blogger Leith van Onselen).

This happens to match the data produced by Rismark (here), after they revised their average price-to-income ratio up after noting the discrepancies in the unadjusted National Accounts data.

While I don’t believe household income and house price comparisons are the best indicator of the state of the housing market (preferring comparisons of rents to incomes and yields to other rates of return in the economy), it does seem that we can use the national accounts data to give a decent regular estimate of household incomes for those who wish to use them for analysis.  Maybe the RBA should try it sometime.

Also important to note when comparing incomes to prices is that the debt service ratio, measured as interest payment against incomes, can be misleading.  Since this measure is also published by the RBA, I assume they rely upon it in some way. 

Below is the household finances graph from the RBA chart pack (available here). We can see that, following the declines in interest rates at the end of 2008, household interest payments have settled at around 12% of disposable income. Note again that the RBA disposable income measure is probably overestimated (there is no specific note about the treatment of imputed rents), meaning the both measures are probably underestimated. But in any case the trends over time still hold.

What we need to consider here is that the interest paid graph shows what might be called a 'debt-service' ratio (although not in the true sense which would cover principle repayments). In regard to the surging household debt the RBA notes that the ...structural decline in interest rates has facilitated the increase in household debt ratios because it reduced debt-servicing costs.

That is true, but would only explain an increase in debt that accompanied flat interest payments as a proportion of income, not increasing interest payments (as I have explain in detail here).

What is also overlooked is that at lower interest rates the difference between the payment of just the interest on debt, and the repayment of interest and principle (to actually reduce the loan balance over a fixed period), greatly increases. For the same interest payment, a high debt balance with a low interest rate is more difficult to repay than a low debt balance with a high interest rate.

The table below shows the amount of debt that a household with an income of $75,000 could service with 20% of their income ($15,000pa) at different interest rates. While a halving of interest rates means the household could double the loan amount and pay the same interest payment, the loan they could actually repay over 30 years increases by far less (as shown in the right hand column).

It is also important to understand this relationship when comparing our household debt burden internationally. The RBA usually makes such comparisons without noting the importance that interest rates make to the burden of this debt on households. Given that mortgage rates vary between 7.5% in Australia to 2.5% in Switzerland and 3% in Germany and much of the EU (and noting the tax deductibility of mortgage interest in Netherlands), these differences are important. 

I will finish this analysis by presenting three graphs. 

First is a graph of the household occupancy rate. The reason to include this is that while household incomes may be still growing nicely, the number of people per dwelling has been increasing since late 2005, so in per capita terms incomes are not looking as good.

The second graph shows the contributions of insurance premiums and claims to household income (which I removed in my income estimation method). When this number is positive it means that household insurance claims were more that the premiums paid in that period. That’s why we see a massive spike in February 2011 from the claims relating to floods and cyclone Yasi (and amongst other things, the Black Saturday Bushfires in early 2009 – note the data is very cyclical with a summer peak). It seems odd to have either the insurance premiums or claims in estimates of household income (although makes up just a fraction of a percent of the total).

The third and final graph compares the growth in household incomes using each method with the ABS capital city price index. Of course, I have chosen an arbitrary baseline at June 2001, but I do note that mortgage interest rates then were the same then as they are now (indeed mortgage rates were about the same as now back in 1997 - see here), so the deviation observed could easily be interpreted as an overvaluation of housing.

What the graph mostly tells us is that there is a pretty solid reason so many people believe that house prices are historically high and are more likely to fall than rise in the near future, being supported only be our willingness to incur debt, and not our incomes. 

Using quarantine as a barrier to trade

I have been meaning to write about using quarantine as a barrier to trade since Queensland’s banana crop was destroyed by cyclone Yasi last summer and prices at the supermarket shelf hit $14/kilo and more. It seems that leading economist Saul Eslake, and economist turned politician Andrew Leigh, have done the job of deciphering genuine concerns over importing disease, and rent seeking by protected producers.

Let us start with what Andrew had to say.

In fact, just about every trade barrier can be rewritten as a quarantine rule or a consumer protection law. Suppose Californian wine producers are complaining about competition from French Bordeaux. Left unchecked, US authorities could simply raise health concerns about Phylloxera, and ban French wines on quarantine grounds. Or imagine that British carmakers are struggling to compete with Malaysian hatchbacks. Without any international guidelines, there would be nothing to stop the UK from banning Malaysian small cars for reasons of safety.

To prevent competition laws and environmental rules from being used as backdoor protectionism, the WTO has two new treaties that require health, consumer and environmental regulations to be scientifically based. National regulations cannot discriminate against particular countries, and must not impede trade any more than necessary.

If a WTO member thinks that another country is breaking the global trade rules, it can take a case to the dispute panel. Australia has complained to the WTO on seven occasions (against the European Union, Hungary, India, Korea, and the United States). We’ve won five of these cases, including decisions in favour of our beef exporters to Korea and our lamb exporters to the US.

On the flipside, we’ve had ten cases brought against us (by Canada, the EU, New Zealand, the Philippines, Switzerland, and the US). We’ve lost three of these cases, including the New Zealand apples decision (the other two losses related to imports of salmon and automotive leather).

Andrew makes the solid points that quarantine and consumer protection is ‘back-door’ protectionism, and gives a good overview of the international legal framework around trade.

Saul Eslake takes different approach by discussing the price impacts on domestic consumers from this type of protection. He also highlighted that in the wake of cyclone Yasi, high banana prices were only helping banana growers whose crops weren’t destroyed, not those who actually lost their crops from the cyclone.

On the matter of importing diseases, he makes a point I have argued to many people in the past. How would diseases go from boxed-up fruit and vegetables arriving in city ports out to farms? How high is that risk? In Eslake’s words-

If bananas and other fruit or vegetables are imported into southern ports, such as Melbourne, Adelaide or Sydney, and are subject upon arrival to appropriate inspections, they are no more likely to spread diseases damaging to Australia's banana industry than the importation of cooked and packaged Canadian salmon has done to Tasmania's salmon industry (another example of protectionism masquerading as ''biosecurity'' where, unusually, commonsense and the interests of consumers ultimately prevailed).

To me the irony of the situation is that most of the crops now requiring protection from foreign pests are imported themselves, and could arguably be classified by an environmentalist as a foreign pest.

The other irony is that the countries that do have these diseases are also exporters and can produce the crop much cheaper than us.

The logical person would ask whether the potential costs from the pest or disease are greater than the benefits derived by consumers from cheaper food? If yes, then we should keep the quarantine restrictions. If no, we should drop them.

I am not trying to say here that all quarantine rules necessarily have greater benefits than there costs. But we have lost 3 out of ten cases brought against us by other WTO member, so if 30% of the quarantine rules can be dropped because their costs outweigh the benefits, that would be good for everyone in the long run.

Anthropologist's view on debt and money

Over at Naked Capitalism is a fantastic interview with David Graeber, author of Debt: The First 5,000 years. The most intersting point for me is that economists just assumed that since money is currently primarily used to estimate exchange value, that this is the historical reason for the existence of money. While this view of money is often a workable assumption, the deeper social issues surrounding money become easily overlooked when you perceive money primarily as a means of exchange, and ignore the role of debt anf conflict as the tru origins of money.

An excerpt is below, and the full interview is worth reading, especially for those curious about Chartalism, Biblical debt jubilees and so on.

Philip Pilkington: Let’s begin. Most economists claim that money was invented to replace the barter system. But you’ve found something quite different, am I correct?

David Graeber: Yes there’s a standard story we’re all taught, a ‘once upon a time’ — it’s a fairy tale.

It really deserves no other introduction: according to this theory all transactions were by barter. “Tell you what, I’ll give you twenty chickens for that cow.” Or three arrow-heads for that beaver pelt or what-have-you. This created inconveniences, because maybe your neighbor doesn’t need chickens right now, so you have to invent money.

The story goes back at least to Adam Smith and in its own way it’s the founding myth of economics. Now, I’m an anthropologist and we anthropologists have long known this is a myth simply because if there were places where everyday transactions took the form of: “I’ll give you twenty chickens for that cow,” we’d have found one or two by now. After all people have been looking since 1776, when the Wealth of Nations first came out. But if you think about it for just a second, it’s hardly surprising that we haven’t found anything.

Think about what they’re saying here – basically: that a bunch of Neolithic farmers in a village somewhere, or Native Americans or whatever, will be engaging in transactions only through the spot trade. So, if your neighbor doesn’t have what you want right now, no big deal. Obviously what would really happen, and this is what anthropologists observe when neighbors do engage in something like exchange with each other, if you want your neighbor’s cow, you’d say, “wow, nice cow” and he’d say “you like it? Take it!” – and now you owe him one. Quite often people don’t even engage in exchange at all – if they were real Iroquois or other Native Americans, for example, all such things would probably be allocated by women’s councils.

So the real question is not how does barter generate some sort of medium of exchange, that then becomes money, but rather, how does that broad sense of ‘I owe you one’ turn into a precise system of measurement – that is: money as a unit of account?

By the time the curtain goes up on the historical record in ancient Mesopotamia, around 3200 BC, it’s already happened. There’s an elaborate system of money of account and complex credit systems. (Money as medium of exchange or as a standardized circulating units of gold, silver, bronze or whatever, only comes much later.)

So really, rather than the standard story – first there’s barter, then money, then finally credit comes out of that – if anything its precisely the other way around. Credit and debt comes first, then coinage emerges thousands of years later and then, when you do find “I’ll give you twenty chickens for that cow” type of barter systems, it’s usually when there used to be cash markets, but for some reason – as in Russia, for example, in 1998 – the currency collapses or disappears.

Econompic - negative real interest rates encourage savings

The basic premise behind stimulatory monetary policy is that lower interest rates reduce the cost of debt, and decrease the returns to savings, encouraging present spending and maintaining asset values. But recent experience (particularly in the US) has shown that in a low (or negative) real interest rate environment, savings rates are climbing.

Jake over at Econompic has put forward a reason this might be the case. He argues that if an individual needs to save a certain amount for future consumption, for example someone who wishes to fund their retirement, a low interest rate means they need to SAVE MORE NOW to reach that point.

What surprises me is that Jake’s hypothesis is fairly consistent with Milton Friedman’s permanent income hypothesis, which asserts that people will try and smooth out their earnings over their lifetime (through savings decisions) to maintain a relatively constant level of expenditure. In Friedman’s model, a transitory income, like prize money, would not be spent all at once, but mostly saved and spent over the rest of one’s lifetime. While the reduced debt burden from low interest rates may been seen as temporary by some people and not greatly affect their spending, the reduced return on savings DEFINITELY means that smoothing out income for retirement requires greater levels of saving.

For example, if interest rates are 5%, someone might want to save $1million in order to earn $50,000 per year in returns on which to live during retirement. But if interest rates are 1%, that person needs to save $5million in order to earn $50,000 in returns to fund their retirement.

One might suggest that low interest rates mean that people who need to save will save more, and people who don’t, will save less. This might translate to quite a variation in saving patterns by age, with the soon to retire boomers increasing savings, with the young workers saving less.

The low interest rates and high savings rate correlation probably also has a lot to do with household repairing their balance sheets following massive losses on equities and housing (particularly in the US and the UK).

Over to Jake for the details (original post here).

Economies of scale do not equal productivity

Only three things matter in the Australian economy - productivity (how much each person produces); employment (how many people are producing); and equality (how that output is shared). All the other random shrapnel of economic news that flies around is kind of irrelevant.

(c/o Andrew Charlton + must read article entitled The Economic Myths of Peter Costello here)

Productivity is the key to greater wealth, as an individual, a nation, and a world. Productivity is doing more with less. It is that simple. Unfortunately people often equate productivity with economies of scale and population growth, which leads to a poor understanding how economic growth really occurs.

If a farmer selectively breeds his crop so that the next generation of plants yield 5% more grain, with no further inputs required (no more water, fertiliser, harvesting time etc), then he has made a 5% productivity improvement. The output in terms of grain is 5% higher for the same inputs.

Productivity gains flow through the economy, allowing us to produce more goods over time. When other farmers follow this lead, we find that marginal land can now be used productively. We find that fewer people need to work in agriculture, because each farmer is producing more food. This frees up labour to be employed elsewhere in the economy, producing other goods to satisfy our desires.

Productivity gains normally come from two sources. The first is in the form of new inventions and innovations in the methods of production - a new engine design, a new breed of plant, a new manufacturing technique or a new material. Innovation in the methods of production is THE key driver of our prosperity.

A second way that productivity improves is through economies of scale. Even in the absence of new technology or innovation, we can produce more output with less input by specialisation of labour, and larger and more efficient capital equipment, to achieve economies of scale.

However, people often get the drivers of productivity confused. They believe economies of scale are the main driver, and innovation is some secondary consideration. But in fact, economies of scale are only sometimes productivity enhancing. Often there are diseconomies of scale, where there is a trade-off between the size of the economy, and the efficiency of the economy. This occurs when the marginal cost of production is higher than the average cost (which is bizarrely where economists believe production usually exists on the cost curve except in the case of a natural monopoly).

For example, urban water supply can initially be produced very cheaply with a network of local dams. However, once local water needs exceed this amount, another source must be found. In Brisbane and Melbourne, this source is desalinised sea water, which is far more costly than any other water. What this means is that the cost of the last batch of water from the desalination plant (the marginal cost) is far higher than the existing average cost of water to the city, which increases the average cost and makes all water more expensive. Businesses that use water will pay more, and that leaves them less able to increase production and invest in their own innovative capital. Households pay more for water, leaving them less income to spend on other goods. We are all worse off, and far less productive, due to this diseconomy of scale in water supply.

There are many other examples from roads, to electricity, to housing.

Another popular view is that there is a connection between the population of a city or country, economies of scale, and productivity - if we don’t have more people, we can’t get the economies of scale necessary to become more productive.

Yet the great problem with this view is that economies of scale do not rely on the population of the geographical area where goods are produced, but on the size of the market being satisfied by that production. This is why German car manufactures in a single Länder (state), with a population of perhaps 10 million, can achieve greater economies of scale than many other manufactures because they supply a global market with a high volume of vehicles. More people in these Länders will do nothing to make these auto firms more productive, and may likely achieve the opposite effect if the required expansion of the housing stock, roads and other infrastructure, competes for labour demand and finance with the car manufactures.

Even if population growth means that expansion of some of our capital stock occurs where economies of scale exist, there is always the need to expand the housing stock – a capital good where economies of scale do not readily exist. Duplicating any capital in this nature comes at a cost to society that can never be recovered. Read more on that here.

The below Venn diagram shows the relationship between these factors and productivity. As you can see, innovation in new production technology is the primary driver, with economies of scale sometime being beneficial for productivity, and population growth usually coming at a cost to productivity.

The implication then is for government especially to be aware of when expansion of publicly funded capital is approaching diseconomies of scale and recognise this cost to society. Why stimulate population growth when it comes at a cost to the existing population in the form of more expensive water, transport, and the diversion of resources from genuine productive investment?

'Going green'

This came by email from an unknown original source, but is appearing all over the internet now. Please keep in mind my previous comments about how we increase demand for resources when we learn to use them more efficiently – we expand our use electricity, fuel and another resources in ways we never dreamed would happen.  Also, here is some background reading on the ineffectiveness of 'green' shopping bags.

In the line at the store, the cashier told an older woman that she should bring her own grocery bags because plastic bags weren't good for the environment.

The woman apologized to him and explained, "We didn't have the green thing back in my day."

The clerk responded, "That's our problem today. Your generation did not care enough to save our environment."

He was right -- our generation didn't have the green thing in its day.

Back then, we returned milk bottles, soda bottles and beer bottles to the store. The store sent them back to the plant to be washed and sterilized and refilled, so it could use the same bottles over and over. So they really were recycled.

But we didn't have the green thing back in our day.

We walked up stairs, because we didn't have an escalator in every store and office building. We walked to the grocery store and didn't climb into a 300-horsepower machine every time we had to go two blocks.

But she was right. We didn't have the green thing in our day.

Back then, we washed the baby's diapers because we didn't have the throw-away kind. We dried clothes on a line, not in an energy gobbling machine burning up 220 volts -- wind and solar power really did dry the clothes. Kids got hand-me-down clothes from their brothers or sisters, not always brand-new clothing. But that old lady is right; we didn't have the green thing back in our day.

Back then, we had one TV, or radio, in the house -- not a TV in every room. And the TV had a small screen the size of a handkerchief (remember them?), not a screen the size of the state of Montana.

In the kitchen, we blended and stirred by hand because we didn't have electric machines to do everything for us.

When we packaged a fragile item to send in the mail, we used a wadded up old newspaper to cushion it, not Styrofoam or plastic bubble wrap.

Back then, we didn't fire up an engine and burn gasoline just to cut the lawn. We used a push mower that ran on human power. We exercised by working so we didn't need to go to a health club to run on treadmills that operate on electricity.

But she's right; we didn't have the green thing back then.

We drank from a fountain when we were thirsty instead of using a cup or a plastic bottle every time we had a drink of water.

We refilled writing pens with ink instead of buying a new pen, and we replaced the razor blades in a razor instead of throwing away the whole razor just because the blade got dull.

But we didn't have the green thing back then.

Back then, people took the streetcar or a bus and kids rode their bikes to school or walked instead of turning their moms into a 24-hour taxi service.

We had one electrical outlet in a room, not an entire bank of sockets to power a dozen appliances. And we didn't need a computerized gadget to receive a signal beamed from satellites 2,000 miles out in space in order to find the nearest pizza joint.

But isn't it sad the current generation laments how wasteful we old folks were just because we didn't have the green thing back then?

Households better of than 1994... just

Housing market data provider Chris Joye has written a great deal of analysis on Australian housing recently. However his latest graph (above), showing households have more money left over after buying the average home today than any time since 1994, is very confusing.

He explains the data and method as follows.

We decided to simply look at the "average household"--calculated by dividing the ABS's quarterly disposable national income estimate by the number of households each quarter--buying the "average dwelling" in Australia, which is defined as the average sales price in a quarter.

And he explains the findings

Like the RBA, we find that--contrary to popular myth--today's households actually have more disposable income than at any other point since we began our analysis in 1993.

One would hope that with 28 years of economic growth in the mean time household would have FAR MORE disposable income today (after housing costs). What is surprising is how little disposable income has grown because of increased housing costs.

Even Joye’s own graph shows that home buying households were worse off between 2000 and 2009, because any income growth was more than offset by the cost of homes. It also shows that home buying households in 2004 were no better off than in 1994. In fact, if this analysis was undertaken any time prior to 2009 the popular myth would be shown to be true.

I also have some other concerns:

1. The income measure in the national accounts is 57% higher than measured by the survey of Survey of Income and Housing Costs (SIHC) and does not reflect actual household income (see here)

2. The outcome does not pass the common sense test. $43,000 of disposable income left over after mortgage payments, in 1993 dollars, is actually $73,350 in 2011 dollars. This seems like a lot of disposable income for the average household to have left over considering the national median dwelling at $418,000 dollars and the associated mortgage cost of $35,000 per annum. These figures therefore assume that $113,000 after tax is the average household income. This makes no sense to me. You need to have one income of approx $170,000 or two incomes of around $75,000 to meet this income level – that is FAR above average.

3. The outcome appears inconsistent with previous data. For example, mortgage rates in 1998/99 were a little over 6% (compared with a little over 7% today), and prices were about 60% lower than today, according to Joye’s own recent published graphs.

4. The graph shows that mortgage repayments have gone from 25% to 32% of the average household income over the period (which is consistent with Steve Keen’s observations – second graph). To get back to 25% of average income, prices need to fall 20%, or mortgage interest rates drop below 5%.

5. The graph, probably unintentionally, shows that incomes grew 40% in real terms over the period, but after housing costs, they only grew 26% (with most of that growth the past 4 years).

6. Indeed, the 2008 and 2011 blips show that when prices fall home buying households are BETTER OFF. The same applies to interest rates.

I sincerely hope this type of analysis is not interpreted as a reason for house prices to rise and I hope nobody leverages into the housing market because of it without properly understanding the risk they are taking.

Peak life expectancy

Life expectancy has peaked in some US States according to recent research. This follows research published in 2005 that suggests current living children may not outlive their parents, and that peak life expectancy in the US may be reached between 2030 and 2040. Mostly, this is attributed to the massive spike in childhood obesity which typically results in lifelong obesity and associated health problems.

In coming decades, as obese children carry their elevated risks of death and disease into older age, average life spans could fall by two to five years.

The map below shows areas of the US where life expectancy fell between 1987 and 2007 (in red). At first glance it seems that rural areas are overrepresented in falling life expectancy. There is usually is typically a strong inverse correlation between obesity and income, which would appear consistent, but also one could guess that more automation of rural jobs, and greater propensity of sedentary recreation activities (the internet etc), may be a contributing factor.

Since then more evidence of decreasing life expectancy is dripping into the debate, especially in the US. One recent study suggests that based on data from 2008, the latest available, life expectancy in the U.S. fell 36.5 days from 2007 to 77.8 years.

But the overall picture still looks very good. The below graph compares the growth in life expectancy in a selection of countries.

In Australia, life expectancy continues to grow, but there appears to be no similar geographical disaggregation studies showing the divergence between urban and rural life expectancy. The data below shows that men have gained 3.1 year of life expectancy at birth in the past decade, while women have gained 2.1 years

For me, the surprising thing in these data tables is that our life expectancy at birth is rising mostly due to the prevention death earlier in life, not the extension of life after 85. If you make it that far, you have only gained six months of extra life expectancy over the decade – around a quarter of what you gained at birth (one fifth for men).

The other trend of note is that men are catching up to women in the life expectancy at birth. Again, this concurs with the observation that early preventable deaths are being reduced, as risk taking behaviour is disproportionally male.

A couple of questions spring to mind. First, will the rising trend in life expectance continue in the rest of the world? And second, the big question is whether there is a biological limit to life expectancy that developed countries are trending towards, to whether peoples lifestyles are compensating for improved medical care by being less vigilant about their health or taking more health risks?

When I watch extreme sports I often think that it could be a sign that we as a society have made life so risk free that people need to compensate by taking on risky activities. I would classify this type of risk as low probability but high impact, and it is the type of risk we seem to regulate tightly, with seatbelts, helmets, fire alarms and other safety precautions.

My interpretation is that as a society we have removed many high impact low probability risks, but compensated them to a small degree. This compensation must be small, as the data show that the prevention of death early in life the key reason for increased life expectancy at birth.

The other type of risk, high probability but low, or distant, impact is what we usually don’t address well. Smoking laws in Australia are probably the stand out success in this area. But when we do address them, they are the easiest risks to substitute for others. For example, a former smoker might find that chomping down a bit of chocolate is a good substitute for their addictive habit.

Further, we might be avoiding high impact risks by substituting for low impact risks. Parents need to be especially aware of this. For example, cycling appears to be dangerous because of the need to wear helmets, so parent might be less inclined to encourage cycling. The same goes with sports where there is a perception of high risk, such as rugby or Aussie rules football. Even the most basic of actions such as walking to school is often seen through the high risk lens (due to the low probability of abduction) and a generation used to being dropped at the gate may be less likely to walk later in life.

I have no definitive answer to either question. My gut feeling is that medical breakthroughs will stay one step ahead of any compensatory behaviour, and that life expectancy will creep up ever so slowly. I also feel that life expectancies between countries will continue to converge. But I will be on the lookout for more evidence of a peak in life expectancy elsewhere, and should we see this case arising more frequently, I believe that the theory of compensatory behaviour will need serious investigation.

RBA pragmatism and global stagflation

Since the higher than expected CPI print last Wednesday, the economic blogosphere has flooded our screens with opinions on the likely RBA decision at its board meeting tomorrow. Some have argued that the CPI was filled with ‘once-off’ movements in price (eg, the deposit and loan facilities and some fruits) and should therefore be taken with a grain of salt. Others have argued that the CPI is clear evidence that the RBA should move on interest rates to get ahead of the inflation curve.

I have a different opinion.

Raising the cash rate while Australia could be in a technical recession is a situation the RBA needs to avoid more than anything else. Think about the criticisms – “How could our central bank be so out of touch?” “Give Glenn the boot!” The very institution itself would be at risk. Forget demonstrating independence. Self preservation is the name of the game (note also that the inflation target is not a mandate of the RBA, but its own interpretation of how to fulfil is statutory role).

Therefore, the only logical decision for the RBA board tomorrow is to leave the cash rate unchanged, even if it has strong concerns about inflation. It is the same action central banks are taking in the UK and other developed countries in similar situations.

But there is more to this story. The present bout of high inflation and low growth is global, and there is little our domestic policy can do to intervene. Further, I suspect that this has much to do with physical constraints to global oil supply (at least in the short term).

As I said two years ago during the financial crisis –

...some interesting trends should occur in the next year or two. First, we should see the price of oil rise again from its current price of around $60 a barrel. Second, we should see an increase in the inflation rate on a relatively global scale. (Note that in the UK, inflation is currently at 4.4%. With the base interest rate at 4.5%, the real interest rate is now effectively zero). Third, we will see a sustained decline in global output. Taken together, a recipe for stagflation. (I also predict continued volatility on financial markets as demand and supply expectations feed back on each other).

The following three graphs show the oil production, oil price and the correlation between oil price and inflation in Australian, Asia, and other developed markets (DM). (Thanks Ricardian Ambivalence for the third graph).

The simple explanation for oil price led inflation is that a century of capital equipment, particularly in transport, is reliant on oil, has very little ability to substitute to other energy sources.  Therefore, the cost of goods is at the mercy of the oil price due to our invested capital.

Typically, there is an expectation oil production will respond to higher prices. But if there are short term physical and technological limitations, this cannot occur. In 2007 the oil price was double the price in 2005, yet total global oil production was identical. If there was not a physical limit to oil production, oil producers should have responded to this price by greatly increasing supply.

Ricardian Ambivalence has weighed in with an opinion that global inflation is not about oil. Oil price leading inflation globally in the above graph is explained away because “Oil leads CPI, in part, because variations in demand lead variations in CPI”. There may be some element of demand and oil price as co-contributors to price volatility, but my suspicion is that physical production limits to oil are the key.

Indeed, the reason these limits are having such a dramatic effect is because they were not foreseen, and investment decisions were made on the expectation of higher volumes of oil available at similar prices.

As a final statement, I want to address the ‘lunacy’ of peak oil. Many economic thinkers rule out the possibility of such an occurrence, as high prices lead to more inaccessible reserves becoming viable, as well as substitute energy sources becoming economical. Yet the recent evidence is that global oil production is back where it was in the late 1990s even though the oil price is more than 5x higher. This doesn’t seem consistent with the economic rationalism, which ignores the major prolonged adjustments necessary for these investments and subsitutions to occur.

Some may still be arguing in their mind that the reason for lower oil production currently is because of a global demand slump. But again, this fails to explain why we are willing to pay 5x the price for oil, and producers are not willing to sell any more oil at that price.

In the end, Australia is at the mercy of global forces as much as anyone, and it would be foolish for the RBA to believe that our domestic interest rate will have any significant effect on inflation without crushing our economy.

The housing market's 'once-off adjustment' meme

There is a meme floating around which has its origins in Chris Joye's numerous articles on the Australian housing market. While I often challenge Joye's economic arguments on this blog, I hope that readers realise this is simply part of a rigorous intellectual debate, and not a personal attack. Indeed, I admire his quest to provide better housing data, and agree with quite a few of his economic and political beliefs.

The meme is that the surge in debt levels and the price of Australian homes since the late 1990s was a once off adjustment to a period of low interest rates and inflation. Therefore, if these conditions hold, current prices are sustainable.

RBA Governor Glenn Stevens mentioned this 'once-off' adjustment in his recent speech 

The period from the early 1990s to the mid 2000s was characterised by a drawn-out, but one-time, adjustment to a set of powerful forces. Households started the period with relatively little leverage, in large part a legacy of the effect of very high nominal interest rates in the long period of high inflation. But then, inflation and interest rates came down to generational lows. Financial liberalisation and innovation increased the availability of credit. And reasonably stable economic conditions – part of the so-called ‘great moderation’ internationally – made a certain higher degree of leverage seem safe. The result was a lengthy period of rising household leverage, rising housing prices, high levels of confidence, a strong sense of generally rising prosperity, declining saving from current income and strong growth in consumption. (here) 

Chris Joye recently reiterated the argument here

This was a once-off "level-effect" (ie, sustainable adjustment reflecting the huge reduction in the cost of debt), not a permanent growth effect, and now these ratios are flat-lining. This is why the household debt-to-disposable income ratio, as shown below, has gone sideways since 2005, years before the GFC first materialised. That is, credit has been tracking incomes, as you would expect.

The household debt to disposable income graph is below, as is a graph demonstrating the structural adjustment of interest rates.

What makes this meme powerful is its truth. Australian interest rates did see a structural adjustment in the mid 1990s. There is also no denying that lower interest rates should lead to asset values rising relative to other prices in the economy. It also makes sense that the level of debt able to be sustainably managed, as a portion of incomes, is greater.

In the housing context, the 'once-off adjustment' argument can be demonstrated as follows.

Prior to the structural adjustment in interest rates, a buyer looking to buy a home that rents for $15,000pa, who is willing to pay a 20% over the cost of renting to buy the home, would capitalise $18,000 at the going rate of 12.8%. That's a price of $140,625. After a structural adjustment, the cost would be capitalised at 7.3%, giving a price of $246,575. A 75% real price increase should be as sustainable as the previous price (almost).

The same calculation can be made against household income, where for a fixed percentage of incomes, a 75% greater price, and level of debt, can be sustained.

Unfortunately, this logical argument only accounts for a part of the debt build up and house price growth since the mid 1990s. The RBA graphs of household finances and real house prices (below) show clearly why this is the case.

The graph of interest paid as a proportion of disposable income shows that the actual cost of debt relative to incomes has doubled (4% to 8%) since the mid 1990s. This is clear evidence that much of the debt binge, and the subsequent house price inflation, is not attributable to the 'once-off adjustment'. This adjustment would only account for the amount of debt, and home prices, that could be supported with interest costs of 4-5% of household incomes - not 8%.

The RBA also shows that real home prices have more than doubled (100% growth) since the mid 1990s to 2007, rather than seeing 75% real gains. Indeed the 2009 boom saw real home prices inch up again (with some subsequent falls in real terms).

The ABS home price figures (though not ideal for this purpose) suggest that real home prices gained approximately 150% since 1996. That's twice what is expected from interest rate conditions alone.

To get back to that 'sustainable' point, either home prices need to fall by around 30%, or interest rates need to fall by 30% (mortgage rates to 4-5%), or some combination of the two (noting also the geographical disparity any correction is likely to have). With today's CPI print surprising many on the high side, the market prediction (and mine) of rate cuts by year's end seems far less likely.  The negatively geared housing investor should take note.  

In all, the meme is powerful because it is true, but dangerous because alone it is an incomplete explanation of debt and home price trends of the past two decades. What appears clear from the data is that we have overshot the expected price and debt adjustment due to the changing interest rate environment. With this in mind, the downside risks for property values appear to far outweigh any upside potential.

The alcohol consumption J-curve

People and governments love to simplify problems to a single issue - Speed kills, Helmets save lives, Stop the boats. It helps them appear to be ‘doing something’. But real life is not so simple.

Take alcohol. While heavy drinking has long been acknowledged as being socially disruptive, more recently, the fight against alcoholism has been partly driven by arguments around health impacts.  Yet their are both positve and negative health effects from alcohol, and the positive effects are usually overlooked.  The unintended consequences of policy are also rarely considered.

The alco-pops tax was one measure aimed at curbing binge drinking, but it was a fizzer. Sales of other alcoholic beverages increased significantly, offsetting much of the claimed benefits of the tax.

Additionally, no one considered that more expensive alcohol might encourage binge drinking at the expense of casual drinking. If your preferred alcohol is more expensive, there is less incentive to drink in a casual setting where you don’t end up drunk. Why spend the extra money on alcohol unless your intention is to get drunk?

It’s a thought that has crossed my mind when considering the drinking patterns around the world. Those countries with the most expensive alcohol, usually due to alcohol taxes, usually have the most extreme binge drinking culture (that's been my personal observation, and I have no hard evidence to back up the claim).

But alas, these considerations are a little too real for the average policy maker to consider.

The Australian government’s health message about alcohol follows the single issue simplification pattern precisely (their emphasis).

Due to the different ways that alcohol can affect people, there is no amount of alcohol that can be said to be safe for everyone. People choosing to drink must realise that there will always be some risk to their health and social well-being.

But alas, the evidence seems to strongly contradict this simplified message (although the alcohol consumption guidelines are a little more generous).

The overwhelming conclusion from large scale longitudinal studies is that moderate drinking improves longevity. The graph below illustrates.

Men who never drink are just as likely to live as long as men who average 4 drinks per day, with those who drink about one drink per day (or 7 per week) likely to live longest.

The results are partly attributed to the social interactions that are associated with alcohol consumption.

One important reason is that alcohol lubricates so many social interactions, and social interactions are vital for maintaining mental and physical health. (here)

Somewhat surprisingly there are no other plausible explanations at hand that I know of. The debate appears stuck on the ‘is this relationship real’ stage, without moving on to considering why it might be real.

So here is a suggestion.

Often our body has systems that work on a use-it-or-lose-it basis. We use muscles, they grow. We don’t, they atrophy. Our bodies have a built in system (ethanol metabolism) to break down alcohol. Perhaps the very act of digesting of excess alcohol keeps the system healthy for longer.

As my good friend Wikipedia says

If the body had no mechanism for catabolizing the alcohols, they would build up in the body and become toxic.

In any case, the health impacts of alcohol consumption are another example of how common understanding and resulting policy is often detached from the more rigorous academic research. It also highlights repeated failure of policy makers to consider the unintended consequences of well meaning policy.

HT: Eric Crampton at Offsetting Behaviour

Smoking decreases health costs to society

The academic literature generally concludes that smoking reduces health costs to society. This is in stark contrast to commonly held beliefs that there are substantial health care costs borne by society from 'vices' such as smoking, alcohol consumption and fatty foods (which are the target of future regulations).

In fact I will argue (slightly tongue in cheek) that as a society we would be better off if more people would take health risks, and it would be a simple solution to the aged care burden many fear will occur when the baby boomers retire.

The following academic results are typical (my emphasis).

Health care costs for smokers at a given age are as much as 40 percent higher than those for nonsmokers, but in a population in which no one smoked the costs would be 7 percent higher among men and 4 percent higher among women than the costs in the current mixed population of smokers and nonsmokers. If all smokers quit, health care costs would be lower at first, but after 15 years they would become higher than at present. In the long term, complete smoking cessation would produce a net increase in health care costs, but it could still be seen as economically favorable under reasonable assumptions of discount rate and evaluation period.

And from here

Until age 56, annual health expenditure was highest for obese people. At older ages, smokers incurred higher costs. Because of differences in life expectancy, however, lifetime health expenditure was highest among healthy-living people and lowest for smokers. Obese individuals held an intermediate position.

As I have said repeatedly

My core argument in this field has been that increasing preventative health care, while having the benefits of a healthier and long life, often come at increased total lifetime health costs, rather than decreased costs as is often proposed. Remember, we all die some day, and any potential cause of death postponed will allow another to take its place, which of course has its own health costs. Alternatively, a more healthy existence may make us more productive for longer and lead to us contributing more in taxes over our lifetime than the potential increase in health costs which were paid through the tax system for our preventative care.

I argue that most unhealthy vices provide a net benefit to society in terms - they reduce health costs by more than the reduction in tax contributions to health care which may occur due to illness.

The reason is simple. Most of the serious health problems associated with drinking, smoking and obesity take a long time to present. A smoker whose habit had no impact on their lifetime employment, but dies as a result of lung cancer upon retirement at age 65, has still contributed all their lifetime productive efforts to society, including plenty of transfers to others via taxes on tobacco itself, but avoided ongoing health costs from ageing, and costs of the pension.

It sounds cruel, but it is true. The rest of us are better off if people die soon after they retire (unfortunately they are not). The costs of these health vices are therefore borne directly by the people who partake in them, to the benefit of those who choose not to. Perhaps an alcohol and tobacco subsidy is in order?

The only situation where relatively healthy people are worse off from the poor habits of others is if the illness resulting from some unhealthy habit or behaviour occurs early in life and is a barrier to employment and social contribution in general.  In this case the 'unhealthy choice' would result in a massive reduction in their own well-being AND incur costs on others.

The academic literature seems to suggest that this situation is relatively uncommon compared to the alternative, where apparently unhealthy habits do not radically decrease people's productive contributions during their working like.

We can see then that the aged care burden we face is a result of people living healthier and longer lives, especially in the period after retirement. This is mostly the results of better nutrition, lack of war, and importantly, far greater medical knowledge and technology. Unhealthy consumption habits, like smoking, actually have a net effect of reducing the health care burden to society.

As a final note, the amazing gap between academic understanding, public perception, and political ramblings, suggest that taxes on tobacco and alcohol are more about raising revenue than reducing society wide health care costs. The counterintuitive and technical nature these academic conclusions make them easy to keep isolated from policy discussions, allowing politicians to keep any debate at the most superficial level.

*I am not a smoker, but am an occasional drinker, and generally want to live a long time, so I selfishly choose to stay as healthy as I can.

Myth: Tight rental market boosts home prices

A common housing market myth is that low vacancy rates lead to rent increases, which lead to price increases (or at the very least, put a limit on any loss in home values). For example -

...this market imbalance will at some points cause an acceleration in rentals growth and a tightening in rental vacancies, so setting the stage for a recovery in prices through 2012.

Unfortunately, if history is anything to go by, this argument fails in real world conditions.

The two graphs below make the point clearly. In the early 1990s, vacancy rates soared and prices remained flat. But in the early 2000s, rental vacancies matched these highs during the strongest period of price growth observed in 25 years. How can these two opposing relationships been reconciled?

(Images from here and here)

I have a hypothesis.  During boom times overbuilding results in a slight glut in homes entering the rental market (eg 2000-2005). As the construction boom subsides, these homes are slowly absorbed by rental demand. When the market begins to fall (bringing much of the economy with it) potential sellers become reluctant landlords, boosting rental supply (eg 1990-1995). Additionally, nervous householders reign in spending on housing, resulting in an increased occupancy rate and lower rental demand.

There are many ways the occupancy rate increases, which don’t necessarily imply a shortage of homes. Downsizing leads to more efficient use of existing homes -

For example, the parents of a family whose adult children have moved out with friends or partners might find that the upkeep of a large house conflicts with their ‘grey nomad’ retirement plans. They can sell their 5-bedroom house and move into a new 2-bedroom unit, pocketing the price difference for their retirement.

In this scenario the construction of a 2-bedroom apartment resulted in a 5-bedroom home being available to meet the housing needs of population growth.

Other ways include university students moving home with their parents, and grandparents moving in with their children’s families.

If my hypothesis holds, then the ‘rental market cycle’ has two periods for each economic cycle, and tight markets are a signal of a price boom only if the previous trough was prior to a price fall. Therefore our next 'rental market cycle' will be one accompanied by falling prices, or flat at best.  The evidence in Brisbane seems to suggest that this pattern is beginning to occur (although prices have already fallen 10%).

(I also have a suspicion that auction results show a similar cycle - increasing in booms and busts, with low clearance rates at turning points.)

Rent seeking behaviour - scare campaigns

From the Hungry Beast

Demand shocks – the details

Many pundits claim that increasing population increases demand. In technical economic jargon it shifts the curve to the right. But what we rarely see is an exploration of the two types of demand shock and the different potential price impacts.

The first type, as mentioned above, shifts the downward sloping demand curve to the right. This means there are more people with the same willingness to pay.

The second type is a shift of the demand curve up upwards. This represents a willingness to pay more for the same goods from the same number of people.

It’s pretty clear from this distinction which of these factors is in play in Australian housing.

Let’s examine the first case. Consider an auction with 10 cars for sale and 50 bidders willing to pay $1000 for a car. You add another 50 people to the mix each also willing to pay $1000. If I’m not being clear enough, this is analogous to increasing population in the housing context.

When the auction is run with the original 50 bidders each car sells for $1,000. When the auction is run with 100 bidders, the 10 cars still sell for $1,000 each.

This is an extreme scenario but does demonstrate a very real point. Unless the new potential buyers are willing to pay more for the same items as the existing buyers, the price won’t rise. At most, a second price auction (the result of an English open auction with heterogeneous preferences) becomes closer to a first price sealed bid auction by the addition of another bidder willing to bid at a price between the second and first price (read up on some auction theory here).

As I said before, new buyers, even a small cohort of the total market, can influence the price level if they are willing to pay more than the existing buyers, since prices are set at the margins. Imagine our car auction once again, and we give 10 of our original 50 bidders and extra $500 to spend on the car. What is the new result? All cars sell for $1500 each to these 10 bidders. Even though they were just 20% of the original market of buyers, they dragged the price up 50%. In fact even if there were thousands of buyers willing and able to pay $1000 for those 10 cars, the ten people willing to pay $1500 would always win.

Prices are set at the margin by those with the highest willingness to pay.

This example, where the demand curve is shifted vertically to reflect an increased willingness to pay by the same number of buyers, is shown graphically in the right hand side graph above.

But, you say, the key problem here is that supply is being overlooked - in the simplified examples demand curves are horizontal and there is no supply response. But look at the graphs again. Not only is the demand curve a more acceptable shape, but supply does respond in both circumstances. In the first, where the demand profile of buyers shifts horizontally supply does respond enabling prices to remain at their equilibrium level.

However, when the demand curve shifts vertically, it doesn’t matter how much supply responds to price increases, it cannot be a mechanism to bring prices back down (except under extreme assumptions about the shape of demand and supply and the limits of peoples willingness to pay at the top and bottom of the market).

Of course, in the end this analysis is probably unecessary. The value of housing arises from the rents - its ability to generate revenue or provide a service. Since we haven’t seen rents outpace inflation significantly for any extended period in the past two decades, one must be quite certain that the cause of prices being much higher than a rational present value of future cash flows is pure demand side speculation.

Economics, Real Estate and the Supply of Land

As a general rule, economists relying on supply and demand curves without properly discussing the assumptions that sit underneath their graphs can be ignored.

Alan Evans' book Economics, Real Estate and the Supply of Land is an effort to refute Ricardian notions of land supply and rent, and offer an alternative neoclassical theory of land supply. The arguments in this book are taken by many who believe that reducing government involvement in town planning will decrease the price of housing. Evans’ reasoning is questionable to say the least, and supported by elaborate graphs with often biased assumptions and interpretations.

One of Evans’ aims is to refute the Ricardian proposition ‘that the price of land is high because the price of corn [read: houses] is high, and not vice versa’.

To do this he constructs a model economy with a fixed land supply where two agricultural uses compete for land – potatoes and corn. In the figure below we see his construction of this economy on the left, with demand for corn inverted so that the intersection of corn and potato demand determines the equilibrium share of land devoted to each crop, and the equilibrium rent of land at point A.

He then proceeds to add a demand shock to potatoes ‘for some reason’. The new blue line represents the new increased demand for potatoes which enables potato growers to bid up prices for land previously grown for corn and reduce the amount of land used to grow corn. He concludes with the following -

Now it is quite clear that the increase in the rent of land is not caused by the increase in the price of corn. Exactly the reverse is true. The price of corn has risen because the price of land has risen.
...
The rent for land is not solely determined by the demand for the product.

His conclusions are wrong.

First, it is still quite clear that at the new equilibrium the price of land for corn is still determined by the new higher price for corn. You could just as easily argue that every time a potato grower buys land from a corn grower he decreases the output of corn and the price of corn rises, thereby leading to an increase in the rents of land available for growing corn.

Second, he fails to notice that all he has done with the model is to demonstrate the inflation mechanism following an increase in money supply for one purpose. He increases total demand (potatoes plus corn) but shifts preferences towards potatoes so that corn demand is constant. The end result of his demand increase is to increase all prices in the model economy – potatoes, corn and rent.

Followers of Say would jump straight to this conclusion. You can’t simply increase total demand in the economy – demand is comprised of supply.

An actual demand shock, which models a change in preferences from corn to potatoes, is shown in the right hand side figure. You will notice that total demand remains constant and therefore the rents for this fixed quantity of land also remain constant.

So no, land rents do not determine prices. Prices determine rents.

Another example of poor reasoning is when Evans argues against a 100% land value tax. He argues that a tax of that nature would ‘freeze’ land development because there would be no incentive for a owner of agricultural land to sell his land to a developer for housing development, since he would not capture any of the value uplift. The rent achieved by the owner of the land will remain the same as when it is rented to the farmer – zero.

Yet in chapter 8 he argues that the value of land grows in anticipation of future higher value uses. In these cases, when the site is genuinely worth more as housing, the tax would be at a rate that reflects that higher value, and not the agricultural value. Therefore, the owner of the land will be facing a tax on the land value for housing while only receiving rents at agricultural values. As the city expands and the value of his land for housing surpasses the value for agriculture, he has a great incentive to sell or develop immediately to avoid losses.

Although I don’t support a 100% land value tax, I do support shifting the tax burden towards land and fixed rights to natural resources.

What we do learn from this book is that even the experts are prone to bias that affects their ability to apply objective logic and reason.

Faulty Reasoning

I’ve come across some fine examples of faulty reasoning lately in two key areas.

1. Analysing the economic importance of declining environmental quality, and
2. Assessing the impact of price drops in the Australian property market.

So let us take a closer look.

Pro-urban sprawl advocates (I didn’t really know there were so many until just recently) try to shrug off the claim of deterimental impacts on agricultural production from urban sprawl due to irreversibly land use changes. For example –

Suburban Development is not destroying farmland. Smart growth activists claim farmland is disappearing at dangerous rates and that government needs to protect farmland lest we lose the ability to feed ourselves. As growth expert Julian Simon wrote, this claim is "the most conclusively discredited environmental-political fraud of recent times." United States Department of Agriculture data show that from 1945 to 1992 cropland area remained constant at 24 percent of the United States. Though urban land uses increased, they now account for only 3 percent of the land area of the United States. Today, American farmers produce more food per acre than ever before. In fact, the number of acres used for crops peaked in 1930, but because of the ingenuity and innovation of American farmers, the United States continues to produce more food on less land. (here)

Why is this argument based on faulty reasoning?

Milk wars and Anti-Dumping

While there are many questionable assumptions in some economic theories, there are also many solid foundations to economic analysis. One of these was identified by Coles in its submission to the Senate inquiry into milk pricing (available in the Coles factsheet here).

The farm gate price dairy farmers receive is set by the world price because most Australian milk products are exported.


The first implication of this fact is that because prices are set by global markets, domestic buyers cannot buy at prices below the export market price - although they could perhaps be higher.

By following this logic Coles, or any other domestic dairy retailer, cannot exhibit bargaining power as a buyer from milk processors (or distributors). Dairy processors would simply sell all their products abroad, whereas the only alternative for retailers is to buy imported dairy products with associated freight costs.  Processors can then bargain the price up to the price of the retailers next best alternative of imported products. Thus, even though we are net exporters of dairy products we still pay a retail price for domestic dairy products very close to the retail price for imported dairy products.

And to provide further evidence against dairy industry claims, even if Coles did have market power, one must question why Coles would not already be getting milk for the lowest price anyone would be willing to produce for?

The sceptic in me might even go so far as to suggest that upsetting the political milk cart might have been a publicity strategy for Coles itself. News outlets have told the public that Coles is aggressively dropping prices for months now – all free of charge. You really can't buy publicity like that.

Of even greater concern than the media beat-up, and public perception of danger from falling milk prices, is that the law entrenches protection of local industries from international competitors through anti-dumping laws. As the Productivity Commission describes

Risk homeostasis, Munich Taxi-cabs and the Nanny State

There is an odd coexistence between two conflicting safety policies that may well be pursued by the same accident prevention agency. The first seeks to improve safety by alleviating the consequences of risky behaviour. It may take the form of seat belt installation and wearing, airbags, crashworthy vehicle design, or forgiving roads (collapsible lamp posts and barriers). This policy offers forgiveness for a moment of inattention or carelessness. The second policy seeks to improve safety by making the consequences of imprudent behaviour more severe and includes things such as speed bumps, narrow street passages, and fines for violations. Here, people are threatened into adopting a safe behaviour; a moment of inattention or carelessness may have a dire outcome. 

While these two policies seem logically contradictory, neither is likely to reduce the injury rate, because people adapt their behaviour to changes in environmental conditions. Both theory and data indicate that safety and lifestyle dependent health is unlikely to improve unless the amount of risk people are willing to take is reduced. (here - my emphasis) 

The above passage points out a common logical absurdity, and contains an important lesson for Australian’s with and overeager obsession of controlling personal choices through ‘nanny state’ regulations. More on the nanny state a little later. 

First, it is important to examine the hypothesis of risk homeostasis to properly understand the implication of the opening quote, since it claims that neither of the two contradictory policies aimed towards improving safety are effective. 

The essential argument of risk homeostasis is that humans have an inbuilt level or risk that they gravitate towards in response to their external environment. If we reduce the risk of an activity, people will compensate by finding other risky activities as a replacement, or undertaking the activity in a more extreme manner. For example, if we ban smoking tobacco, which doesn’t seem like such a remote possibility, do we really expect smokers to replace their habit with fruit snacks and yoga? Or might they compensate by increasing their alcohol consumption or perhaps smoking dope instead. 

Risk homeostasis is not to be confused with risk compensation, which suggests that individuals will behave less cautiously in situations where they feel "safer" or more protected, but that we don’t necessary return to a predetermined risk equilibrium point. 

Improving transport safety is an area where there is strong evidence risk compensation, and indeed of risk homeostasis.