Wednesday, December 15, 2021

Ignoring age and COVID risk is unscientific

I listened to a frustrating Sam Harris podcast about COVID policy yesterday. What struck me about these "expert" commentators was that they

  1. kept finding reasons to link COVID policy back to Trump, which was weird, and
  2. all but ignored the enormous age variation in COVID risk. 

Both these seem like popular ways of thinking, unfortunately. 

I want to comment briefly on the second issue. This should help explain why I support vaccinations for the elderly but feel strongly against vaccinating children, vaccine targets and mandates. 

The risk of serious illness or death with COVID is far more age-skewed than most viruses. In the below figure I show this skew. COVID is a serious disease for the elderly.

I also plot vaccine risks in the dashed orange. You might not be able to see it because it is so close to the axis. For age 70, the benefit-to-cost ratio of the vaccine is about 250x (i.e. the blue line is 250 times higher than the dashed orange line). A great outcome and something anyone would be foolish not to recommend. 

But exponential curves are deceiving. Let's zoom in on this curve for young age cohorts. I do this below (curve equation is 10^(-3.27 + 0.0524xage)). Notice now that we are way down near the vaccine risk. It's close. I show a broad range of risks and call this COVID curve the risk of serious illness. I do this because reality doesn't follow the neat equation I used to plot the curve and children are likely even lower risk than shown. 

In short, because the age skew of COVID risk is so severe, these huge many-hundred-times benefit-to-cost ratios can reverse at low ages so that the costs are many times the benefits. This is why so many doctors are calling for a halt to mandates for vaccinating children. 

We should let this well-known information about COVID guide us rather than politics and panic. 

Saturday, December 4, 2021

Did Germany and Tokyo really get affordable housing through planning?

Not that long ago Germany as a whole featured heavily in this debate over planning rules and house prices. With Frankfurt topping the latest UBS real estate bubble index, and Munich at number four, we don’t hear much about that anymore. 

Tokyo is another city where planning rules are argued to have led to cheap housing.

Have we all forgotten that Tokyo was the world’s most expensive city not that long ago and is famous for how small its dwellings are? It also has less than 50% homeownership. 

Across the central 23 wards of Tokyo, there are only 19sqm of dwelling space per person. Only 22% of Tokyo households have more than 29sqm of space per person. Across the prefecture as a whole, there are about 30sqm per person of residential space. 

Australia has about 90sqm of internal residential space per person—roughly three times as much as Tokyo. Australia would need to nearly triple its population without building a single extra dwelling to have the same "housing abundance" as greater Tokyo, and would still have way more private garden space.[1]

Yes, there is an overall trend in Japan towards more dwelling space per person. But this is driven mostly by the rise in elderly households, especially elderly singles. When an elderly couple remains in their home after their children leave they increase the floor space per person even if that young adult child moves to an apartment with less space than their share of space at their parent’s home. When one person from an elderly couple dies, they leave behind an elderly single-person household, boosting the floor space per person metric. Many countries whose ageing populations are not as advanced as Japan’s will also see this same trend automatically.

Another issue is Japan’s long period of deflation. CPI is up 10% in Japan in the past three decades, while it’s up 300% in the US, for example. Average wages have also been flat for decades. It is not a good idea to compare rents or prices in Japan without factoring in their unique wage and consumer price conditions.

Overall I’m not persuaded that a housing market more like Tokyo’s is desirable. On the more substantial point that relaxing town planning rules got that outcome, I find little evidence.

fn [1] I’m wary of charts like the one below since the only statistics I know about dwelling sizes rely on self-reported estimates by various ad hoc surveys by statistical agencies.

There are also reporting differences of the floor area of new homes. For example, enclosed garages attached to a home are included in floor area in Australian new homes, but not US homes

Monday, November 22, 2021

Alice in housing economics wonderland

“When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to mean — neither more nor less.”
’The question is,” said Alice, “whether you can make words mean so many different things.”
― Lewis Carroll, Through the Looking Glass

An increasing academic and policy focus on housing supply has unfortunately not brought with it an increase in clarity over the meaning of words. Words like housing supply, demand, zoning, price and affordability, have come to mean whatever the authors want them to mean. 

This is unhelpful. 

I've put together in the below table various potential meanings of these catch-all economic terms, and the words I think we should use instead to increase clarity. 

For example, economists should be crystal clear that the economic price of housing is the market rental price (i.e. the price that  measures the amount of good and services given up to get that good). The sale price of  a dwelling is merely the market’s judgement of the asset value of buying a rental income stream in perpetuity and is heavily affected by prevailing interest rates (capitalisation rates), land and property taxes, and expectations of changes to the asset value (capital gains expectations).

With such a variety of definitions, what can the phrase “an increase in the supply of dwellings relative to demand will reduce dwelling prices” actually mean?

The obvious and strictly true definition is when the terms mean

supply → market willingness to sell housing in this period,
demand → market willingness to pay for housing in this period, and
price → the sale price of a dwelling in this period.

This merely describes asset market bid and offer schedules. When there is a "supply shift" in these schedules that massively reduces prices, we call that a market crash (a topic that is also poorly understood). But the economics of housing stock change is more sophisticated than this.

Supply and demand might also mean number of dwellings and total population—completely different ideas from bid and offer schedules in asset markets, instead focussed on material quantities that are expected to move together. 

Sometimes supply is used to mean zoned capacity (how much can build built within current zoning rules) and is often assumed to be synonymous with the absorption rate (how quickly the market will develop new housing subject to asset market conditions). Changing zoned capacity does not necessary change the absorption rate, yet they are often described as one and the same thing.

Perhaps if we could describe what we mean more specifically we can start to allow the evidence to support or disprove theories about how the housing and property market operate. 

I'm open to improving and expanding the table with better, or more widely used, terminology and will update and refine it over time. 

Tuesday, November 16, 2021

Opening remarks to housing inquiry

A video of my testimony to the inquiry is here (from 11:00:00)

My full written submission is here and my follow-up response to questions raised is here.

I believe I am one of the few witnesses who has worked for residential and industrial property developers, in government departments dealing with infrastructure charges and regulation, and now as a housing researcher. 

To be clear, Australia has more, bigger, better dwellings per capita than any point in history. We are also building new dwellings at a near record pace in a period where population growth is the lowest in decades.

More housing is better than less housing. Absolutely. I agree.

The argument I disagree with is that private landowners want to build faster, but only pesky council and state government red tape is slowing things down.

While I certainly have many ideas for improving and simplifying the planning system I see this as a separate topic to housing affordability.

We’ve heard from previous witnesses that housing developers have a lot of trouble building on unzoned land. No doubt. The whole point of unzoned land is to not have development at that location and get it located in the zoned land. It’s hardly evidence of anything except that these developers are bad at their jobs, always buying the wrong land for what they want to build.

Indeed, they certainly appear to be terrible lobbyists. If what they claim is true about zoning keeping prices up, then lobbying for mass rezoning is financial suicide. It would vastly increase the number of competitors in their market and reduce prices, wiping billions in value from their balance sheets. What sort of industry lobbies for that?

Perhaps this story is a lie.

In 2003, the AFR ran the headline “Brisbane running out of land for housing”, with land for housing expected to run out by 2015 according to the same expert lobbyists who have attended this inquiry. Yet detached housing lot production was 30% higher in the 6 years since 2015 than in the 6 years prior.

Are they terrible at their jobs? Or just telling stories that conceal the true nature of property markets?

Remember, only landowners can choose to make planning applications. Only landowners can choose when to build homes. Councils don’t do this. There is no speed limit to building new housing in the planning system. Planning regulates the location of different uses and densities, like road lanes regulate locations on the road. Density (dwellings per unit of land) and supply (new dwellings per period of time) are completely different concepts. More density does not equal faster supply.

The key issue at stake in this debate is that land is an asset. It is therefore priced like one. This is why when it is a good time to buy it is also a good time not to sell.

This is true for developed and undeveloped land. Stocks of undeveloped land sit on the balance sheet of developers, earning a return by growing in value while undeveloped.

The trade-off between the return from delaying developing land, versus developing now, creates a built-in market speed limit on the rate at which private landowners develop. As a previous witness mentioned, “… if you are a property owner or developer that had land that was consented and you hadn’t sold it a year ago then you are in a very strong position.” Builders might like to build faster, but landowners prefer to maximise returns on their assets. 

We can see how this pays off with a case study of Jordan Springs, a Lendlease subdivision of around 2,000 housing lots in Sydney that took a decade to sell. I looked at the sales rates over time and saw that the average rate was only 45% of the peak rate (3-month average), though some periods had sales just 12% of the peak rate. The speed of developing new housing lots was far below the capability of developers and the capacity of zoned land. By selling at this slower rate, and capturing overall market gains in the form of higher prices, they made an additional $137 million on the project. Prices were 31% higher at the end than the start for land lots on a per sqm basis.

It would have been financially irresponsible of them to develop faster than they did.

I’m not saying that this behaviour is wrong, or a conspiracy, or even that it has major price effects. The stock of housing only changes a couple of percent a year at the best and small changes to those small changes make tiny price differences. This is just normal market behaviour. This is why for the century prior to the existence of zoning we had the same issues of unequal access to land and housing ownership, only much worse.

The current housing asset price boom is a global one. Average prices are up 20% in the last year in the US, the same as Australia, and many places that were previously lauded as having flexible zoning, like Germany and cities in Texas, have had the highest price growth. What we are seeing is a period of global asset re-pricing, as intended by monetary policy.

If you really want more homes build them. Flood the market with a public housing developer—you know, just in case the private developers don’t do what they said they would. It might be a sensible insurance policy. No doubt the property lobbyists will find something wrong with this, even though it is exactly the outcome they pretend to be lobbying for—more competitors and lower prices.

Wednesday, November 3, 2021

Public housing is way cheaper than rental subsidies

A discussion about the best way to provide below-market-priced housing popped up on Twitter recently. Peter Tulip noted many of the limitations of such systems—queuing, quotas, qualifying criteria, etc—concluding that a cash payment to help pay market rents is an economically-efficient way to get the policy outcome of reducing housing costs to low-income households.
I am not against providing such cash payments. They are clearly better than nothing. But the reason I believe governments should build and own some housing is that it provides a better bang for your housing subsidy buck.

Consider the two alternatives over a “tenant life” of say 30 years.

With cash rental assistance, the government pays, say for the sake of argument, $13,000 per year the first year. But to have a meaningful effect this must grow over time to reflect growth in rents and incomes. At a 2% growth rate, by year 30, the subsidy is $23,000 and over 30 years the total subsidy paid is $527,000. The present value of this 30-year flow of subsidy payments at a 2% discount rate is $374,000.

With public housing ownership, the government builds or buys a dwelling worth $500,000 today to supply that dwelling at a rent that is currently $13,000 below market rent per year (i.e. the same rental subsidy to the resident). The remaining rent paid by the tenant covers ongoing costs only. Like the cash rental subsidy, the gap grows over time to be $23,000 in the 30th year. Instead of $374,000 in present value terms, this option costs $500,000 today to build or buy the dwelling (much less if built on under-utilised publicly-owned land).

However, with public housing ownership, a government agency owns the property at the end of the 30 years. Over this period, the asset value grows. Even if it grows in line with the 2% growth of local incomes it means that the property is worth $890,000. In reality, because incomes at a location rise faster than the average (because cities expand), it is likely to be more. For reference, this is only a 76% rise in three decades; a conservative figure when compared to the 143% price rise seen in Australia’s capital cities in the past 18 years. 

The table below shows a comparison of the two alternative ways of providing the same value of housing subsidy to a resident over 30 years. Although the public housing ownership option costs $500,000 upfront, today's value of the final sale price is $490,000, leaving a net economic cost of just $10,000. This approach gets 40x better value for the budgetary spend. If capital growth is closer to historical norms then public housing can more than pay for itself.

What we learn from this is that 
  • The cost of rental assistance over the long term is not much different than simply buying a dwelling and giving it to the household ($374k vs $500k). 
  • The cost of rental assistance over the long term is much more than providing the same rental subsidy via owning the property ($374k vs $10k) 
  • Getting out of the housing ownership game over the past three decades and shifting towards rental subsidies has cost government budgets billions.
[UPDATE] I've updated the figures to reflect 2% growth of incomes and rents and 2% interest and made the spreadsheet available here. Play around with the numbers. 

[UPDATE] People seem to think that interest payments need to be taken into account somewhere. They do not. Prevailing interest rates are incorporated via discounting. 

[UPDATE] Thanks to Jago Dodson for letting me know that a 1993 review by the Industry Commission (now Productivity Commission) ranked public housing first in terms of efficiency and cost-effectiveness out of a variety of alternative housing subsidy approaches they assessed. 

[UPDATE] Thanks to Vivienne Milligen for letting me know that the 1989 National Housing Policy Review found similarly—that public ownership of housing is the lowest-cost strategy for housing poverty relief. 

Tuesday, September 7, 2021

Housing supply… another inquiry

Dwelling assets are being repriced globally, as expected by central banks who have sought to achieve this with their interest rate policies.

Part of political theatre that comes with rising dwelling asset prices is to fake concern for the non-homeowners. In the past two decades, this has taken the form of blaming supply and town planning for the fact that investors arbitrage returns and leverage into housing when interest rates fall.

It is nonsense from top to bottom.

We know this because the most recent of many UK reviews into housing supply concluded that it was not desirable to implement any new incentives for housing developers to build faster if that meant they had to accept lower prices.

We know this because a 2004 Australian review concluded that the stock of housing changes by such a small amount each year that even very large changes to the rate of new supply will have small price effects.

We know that it suits vested interests in the property market to focus the debate on non-solutions that provide them windfall gains in the form of rezoning.

Housing markets are quite easy to understand. The difficult part is first unlearning all the nonsense that fills the newscasts and journals.

Australia’s latest inquiry into housing supply has begun. I took the chance to make a submission outlining my views on the housing market and writing a document that I hope provides some lessons about how to understand housing.

Please enjoy it here.

The following summarises
  • There are more, bigger, better, dwellings per capita in Australia in 2021 compared to any point in history.
  • Multiple government inquiries at all levels over the past two decades have ostensibly sought to find the cause of house prices hidden in the pages of local zoning laws.
  • Dwellings are assets and are priced based on financial market conditions.
  • Density (dwellings per unit of land) and the rate of supply (new dwellings per period of time) are conceptually different but often confused in housing supply discussions.
  • This submission argues that market housing supply has exceeded household demand. State planning systems have flexibly accommodated new supply while regulating the location of different types of dwellings.
  • Compared to household incomes and rents, the cost of buying a home (measured by mortgage payments) in 2021 is historically cheap. This is due to lower interest rates and is why intercensal homeownership is expected to rise in 2021. However, asset price adjustments will mean that this situation will not persist.
  • Taxes on property are efficient and fair and do not add to housing costs but rather subtract from property values.
  • Affordable housing is cheap housing. Cheaper housing means lower rents and prices. Any “affordability” policy that reduces market prices will remove billions in landlord revenues each year, transferring that value to tenants, and trillions in housing asset values, with that value transferred to future buyers. 
  • Fostering parallel non-market housing systems, just as public healthcare provides a non-market medical system, can be an effective way to improve housing affordability. 
  • There are no local, international, or historical examples of planning reforms leading to cheaper housing. Indeed, a Productivity Commission review concluded “given the small size of net additions to housing in any year relative to the size of the stock, improvements to land release or planning approval procedures, while desirable, could not have greatly alleviated the price pressures of the past few years.” (p154)

Monday, August 16, 2021

Do medical school entrance tests constrain supply?

The GAMSAT is an entrance test that all prospective students to medical schools in Australia must take.

I want to use a hypothetical scenario about this test to understand how it might be possible to determine whether it constrains the rate at which new doctors are trained. 

The hypothetical

Some people say that this test affects the total stock of doctors and hence the price of medical services.

You have the following information and are asked whether this is a potentially important concern.

In addition, you know that 

  1. Only those with a bachelors degree are eligible to take the test.
  2. The number of people graduating with bachelors degrees each year is nearly a consistent 20,000 per year, adding to a large pool of candidate test takers.
  3. Those who do not pass the GAMSAT can re-sit the test as many times as they like in subsequent years. 
  4. Those who pass have the option, but no obligation, to attend medical school. 
  5. You must re-sit the test if you do not go on to medical school within three years.
  6. 100% of those that decide to attend medical school complete it and become practising doctors. 

You are asked to advise whether the pass rate contains information about the degree to which the entrance test determines the stock of practising doctors. Some say the high pass rate and ability to re-sit the test shows that the GAMSAT test is not a constraint on the supply of doctors.

Let us think this through.

The system perspective

The first thing to do is get a good understanding of the system with the numbers involved. The below diagram shows how the stock of potential candidates flows through the testing system to become doctors. There are three decision points.

  1. The choice to take the GAMSAT test
  2. The pass/fail choice
  3. The choice to proceed to study after a pass

I draw these choices as taps that control the flow of “water” into the “buckets” (stocks of people at each stage). Notice that two of the choices return the people back to the pool of candidates—the pass/fail, and the study/delay choices. 

Quite clearly the most important choice in getting water from the stock of potentials to the stock of doctors is the choice to sit the GAMSAT test in the first place. 

This choice has by far the biggest effect on the outcome, with its variability accounting for the variation of flows through the system by a magnitude of 16x. One year 50 people took the test. One year it was 800.

None of this variation appears due to the GAMSAT test as the pass rate is unchanged and the choice to proceed is unchanged (we will return to this assumption).

By looking at the system in this way we can see that the maximum amount of additional doctors getting through the process by removing the GAMSAT test is 6%. It is likely to be less than this because those who fail often repeat the test.

You conclude that the GAMSAT test is at most an extremely minor factor influencing the rate of supply of new doctors.

A new argument

However, some argue that there is no evidence in the 94% pass rate that the GAMSAT is not a major constraint. 

The argument is that the existence of the test reduces the number of applicants. Those who are likely to fail will know in advance and choose not to take the test. Therefore, even if the pass rate was 100% the GAMSAT could still be a major restriction on the flow of new doctors. It might be a plausible assumption that the variation in the choice to sit the test is explained by the number of people who believe they will pass it. 

So we have two potential mechanisms of actions of the GAMSAT test.

  1. A direct effect due to the pass rate
  2. An indirect effect due to reducing the number who choose to take the test 

How could we tell if the second mechanism was important?

We could look further up the system and see if the variability of the choice to take the test is related to factors regarding the test stringency, or other factors. But how would you measure test stringency if not for the pass rate?

You would need a third variable that measures test stringency that is unrelated to the pass rate, and that correlates closely with the number of test-takers. Possible? I’m not sure. 

The problem is that if the second indirect effect dominates, then what are we to make of variation in the pass rate? What if a 10% pass rate is the norm, and that falls to 5% when the number of test-takers is high? This would surely indicate that the indirect effect is minimal and that people do not have a good idea of whether they will pass in advance. Or that they are willing to take the chance even if they have a good idea in advances. 

Whichever way you cut it, the presence of an indirect effect surely must show up in the pass rate to some degree.

What have we learned?

It seems logical that there is information in the pass rate about the degree to which the GAMSAT test can reduce the flow of new doctors compared to if the test did not exist.

In the real world, and not the hypothetical I described, the pass rate for the GAMSAT is about 20-25%. In fact, the pass rate is itself determined by a quota on new university places. The test doesn’t constrain new doctors because the university quotas do it, and that quota determines the passing grade and hence the pass rate. 

The reason for explaining this is because this post is not about medical school. It is about town planning. The “entrance test” in the planning system is a planning application, which is required to (re)develop a property. 

Many argue (e.g. point 4 here) that just because 90%+ of the planning applications are approved that this doesn’t indicate there is at most a small effect on the rate of new housing supply. They argue that the indirect effect dominates and that’s why the approval rate is high. 

But this leaves us with a conundrum. We know that a property with a planning approval is worth a lot more than one without. Therefore there is a large payoff to getting an approval. Just like there is a large payoff to becoming a doctor. 

Yet candidate medical students are willing to sit a test with a near 80% failure rate, often repeatedly, to get that payoff. However, property owners are not, even though the payoffs can be worth tens of millions of dollars or more.  

While an indirect effect surely exists in both medical school entrance tests and town planning applications, the pass rate also contains information about the existence of this effect.  

Monday, August 9, 2021

COVID logic vs the public health army

“There are two schools of thought… Science stands for healthy scepticism… asking for better evidence… Then you have a second school of thought that is public health… it has the stance that we have a crisis, we are like an army, the platoon must do this or that. Anyone who leaves the platoon must be shot down.”
I like the way John Ioannidis has characterised the COVID public health response. The science and scepticism approach has been overridden by the public health army approach, which has little need for evidence. I recommend his presentation in this video, which is the source of the above quote.

The two schools of thought might explain the “you are better than this” responses I sometimes get on Twitter when I raise concerns that the public health policy seems detached from the scientific and logical reality. I hope it’s because they want me in their army. I hope it’s not because they have given up seeking the truth. 

For some reason, I have a brain that can’t stop trying to seek out contradictions and the underlying logic that makes sense of the world. Scientific scepticism seems hard-wired. For example, when I look at Australia’s superannuation system, logic forces me to conclude that the system as a whole makes funding retirement harder, not easier. So I say we should dismantle it altogether.

I predicted that house prices in Australia would rise in May last year and people scoffed. Someone told me I should hand back my degrees. But the underlying logic I saw was correct (or at least useful for prediction).

Being right when the mob is wrong is, unfortunately, never popular.

In fact, a good rule of thumb is that there is no new information when someone says something popular. There is a huge amount of information when someone risks their reputation to say something. This is why John Ioannidis remains one of the few experts whose words contain actual information. He risks his reputation to say them.

This blog post is about the scientific and sceptical school of thought on COVID policy. It provides a glimpse of the contradictions and the underlying logic I see at play. Some of my previous thoughts and comments on COVID policy can be found here.

Seeking logic and evidence

Vaccines are the path

The current marching song is that vaccines are the path to freedom. Recently promoted by the Grattan Institute, an 80% vaccination target gets discussed as the key to returning to normal life.

There are two problems with this. First, getting 80% of adults vaccinated is quite difficult and has only been achieved in a small number of places.

Second, highly vaccinated places are getting COVID, some more than at any time before (e.g., Iceland, Israel, San Francisco, with surely more to come). While vaccines appear to be reducing mortality rates from COVID, differentiating the effect of the vaccination from the effect of previous population exposure is quite a challenge.

It seems to only make sense to vaccinate the elderly given the risk relativities and the limited effect on transmission.

Blaming one side of politics or the other for the “botched vaccine rollout” looks like nonsense to me when the experience elsewhere is that the level of vaccination is not having a major effect on subsequent virus waves.

Masks work

The only problem with this idea is that you cannot see it in the population-level data. In fact, you cannot even see much evidence that masks work in surgical theatres. Here is a thread containing many studies showing they don't. 

Masks have become political symbols. And people love it.

The seasonal resurgence of COVID across the US despite vaccination and masking is quickly turning into a political problem to be manoeuvred around, not a health issue. Yet more signs that COVID policy is not health-driven.

Vaccine passports

Another chant I hear is that vaccine passports are necessary. But if vaccines work, we do not need a vaccine passport. The vaccinated are not at risk and their presence in the population reduces virus spread regardless. If vaccines do not work, then a vaccine passport is not stopping the virus from circulating and spreading amongst the vaccinated.

Notably, the recent data shows that vaccines wear off and vaccinated people get COVID at quite a high rate compared to unvaccinated (perhaps as much as 80% after six months) and are likely to transmit at a similar rate. This is why vaccine boosters are being planned. 

I cannot see how the current crop of vaccines gets anywhere near a reasonable benchmark for restricting movement. Most people when pushed seem happy that vaccine passports would be used as an incentive to get vaccinated rather than as a direct health measure. 

R0 talk and “exponential” threats

Despite a high reproduction rate and infectiousness, many COVID Delta waves have fallen off dramatically with relatively low infections (e.g. India). R0 does not seem to give any indication of the final size of an outbreak. 

Another big unknown in the modelling is the degree of prior immunity in terms of the variation in COVID waves over time and between regions (such as if previous local viruses conferred some protection in the population), and in terms of potential for reinfection.

Lockdown cost-benefit

The lack of discussion about costs and benefits from masks and lockdowns is mass willful blindness. When an attempt is made, or some concession is made that the approach of evaluating costs and benefits is sound, usually another panicked argument is substituted instead.

Way back in the early days of COVID we saw some appalling attempts at cost-benefit analysis. One was out by a factor of 1,000! You could not be more wrong if you tried. Despite this, these same people are pretending to have been right all along and are still being taken seriously by the media.

That basket case Sweden

Sweden had a roughly 5% increase in total deaths in 2020 with no vaccine and no lockdowns (98,000 against ~93,000 expected deaths). For context, total deaths increased 5% in Australia from 2015 to 2017 (144,000 compared to 137,000 due to a 1.5% increase followed by a 3.5% increase). 

Sweden saw no increase in deaths in any age group under 50 years.

When faced with these facts some say Sweden did reduce mobility voluntarily and that made the difference. But this merely implies that compulsory masks and mass lockdowns are not necessary and do not make a difference. You cannot have it both ways.

Kids and vaccines

Plenty of medical experts and ethicists warn about the risks of vaccinating children. They are rightly cautious. If one death per million from the AZ vaccine applied to Australian children that would kill 7 kids if they were all vaccinated. How many would it save? Given the low risk of COVID in children that number seems to be roughly 14 to 20. Are you happy with that trade-off?

This paper estimates the likely range of vaccine-related deaths if 80% of 18-59 year olds are vaccinated at 17 to 153. Given how little vaccines seem to stop virus transmission these risks need to be carefully assessed. 


A concern of mine has been that lockdowns would result in a rise in suicides. Thankfully that has not happened, but that does not mean there is no harm from lockdowns. U.S. data is showing a 50% rise in emergency department visits by teenage girls involving suspected suicide attempts.

The material prepared for quarantining households is predicated on the fact that forcing people to stay in their homes for weeks on end will lead to people bashing each other. Recent surveys of domestic violence care agencies suggest this has been the case. 

Surveys show huge increases in depressive symptoms during lockdowns. These human well-being costs are real. 

Media reporting for the army

I want to also demonstrate how easily the media falls into line with the public health army.

You may have seen the below chart showing that death from the AZ vaccine is less likely than being killed by a lightning strike in any year. Did you ever question it?

I did not at first either. But once your logical mind is brought into action you have to ask some questions. This is a classic example of the media picking and choosing “facts” and repeating them until they become the truth. Here’s the AMA President repeating it. Expect to hear it in casual conversation.

But there are two problems with this “fact”. First, the AZ vaccine has seen 7 deaths in Australia from roughly 7 million doses, so that risk is closer to double the 0.5 per million presented. Much more for all side-effects. Second, a risk of 0.4 per million for lightning strikes implies about 10 lightning strike deaths in Australia per year. But in reality, it is usually less than 2 (average of 1.9 for the past decade). So this is overestimated by a factor of five. 

These two corrections mean that the AZ vaccine is ten times more likely to kill you than lightning. This “fact” is off by a factor of ten. The vaccine risk is still low. But this is hugely misleading and certainly is not going to promote trust in authorities when the error becomes more widely known. 

Do you think the author of the original article presenting this “fact”, or the editors at The Conversation, actually care? Nope. 

I have been reliably informed that someone with a keen eye for statistics approached the author to request they update the chart with more accurate statistics (their original lightning strike stats were simply lifted from here). But no. No action. The editors prefer to keep the wrong statistic on this hugely important topic rather than issue a small correction. Off by a factor of ten is totally acceptable as long as you are marching with the public health army. 

And what of the risk of people dying with COVID? Why not put that on the chart and make a decent comparison. There has been almost no attempt at putting COVID risk in context in the media. 

Perhaps the reason is that the data doesn’t sing to the public health army marching song. Take the Swedish data again. For ages 0-19 the risk of dying from COVID after 18 months of community transmission including two waves of infections, mostly with no vaccine, masks or lockdown, was 3.7 per million (9 deaths out of 2.4 million population). On an annual basis that is 2.5 per million. If we partition the data to account for co-morbidities, a healthy young person’s risk of COVID death gets much lower. Lower than the one in a million risk from the AZ vaccine? Probably not. But not a big difference, and certainly not enough difference to warrant the calls for rushing to vaccinate children. 

Another place the media seems to be wrong is the story that vaccines produce better immunity than recovering from COVID. You might have heard this or seen a tweet like this.

So let us check the source of this claim. Nope. The study has no comparison between recovery-induced immunity and vaccine-induced immunity. It does show that some well-known immune responses do wane over time after infection. But this natural immune response may still be more persistent than the response from vaccines. However different evidence would be needed to establish the relativities. That doesn't stop the authors from making this claim, which is strange considering that one of the findings is that there is a subpopulation of people with a super strong and persistent immune response. Could they be simply chanting the public health army marching song?


All of this has been a long-winded way of saying that a lot of what you hear about COVID and vaccines and the effect of our policy choices is incomplete, misleading, or plain old wrong. The one part that does make sense is quickly getting vaccines to the elderly—the overwhelming evidence for this conclusion is why every place is doing it regardless of differing views on masks, lockdowns, vaccine passports or border controls. In my view, vaccinating the elderly is one of the few policy actions the evidence favours. 

The rest of the actions only make sense if you are in the business of marching a public health army and don’t care where that army is going or how many of its own it loses along the way. Lockdowns cost a huge amount of lives, masks don't do anything at a population level, and vaccine passports make no sense given the type of vaccinations available. 

If the underlying logic of COVID I have identified is roughly true, then I should be able to make some predictions. Here are some. 
  1. There will be a time in the next two years when Australia has a much bigger COVID outbreak than any yet despite being hugely vaccinated.

 Depending on the political fallout from 2021 we may even collectively take no action. No masks. No lockdowns. No border closures. 

  2. Australia will see a year with a 7% increase in all-cause deaths (about 10,000) in the next decade and no one will notice. 

Given the ageing population and the normal variation in deaths each year, this makes sense. I’m actually being intentionally bold on this prediction. Realistically a 5% increase (7,000 extra deaths), or 134 extra deaths per week, is more likely to be observed. 

  3. Vaccine passports of some sort will be enacted against all evidence. 

They will be cheered by the mainstream media as they justify all the terrible policies the public health army has forced onto us so far. No one will care that the vaccines wear off or that the vaccinated transmit the virus to a similar extent after six months or so. The public health army will march on from the vaccine race song to the vaccine passport song, to whatever else keeps the marching going. 

How the analysis looks to me

There is a spoof viking show called Norsemen on Netflix. In it, the characters talk about customs of life and death in a hilarious matter-of-fact way. I feel like I am living in a spoof Netflix show. The wonks are arguing the finer points of how to skin a virgin alive to please the gods while I stand by looking at the evidence that suggests rejecting the premise altogether. If only our policy choices today were a laughing matter.

Tuesday, August 3, 2021

An Australian homeownership prediction

I have a good track record of making “mad” predictions about Australia’s housing market that turn out to be correct. 

In May 2013 I wrote that "if you have been holding off purchasing a home because of the risk of capital losses, then these risks are probably lower now than at any time in the past decade."
In May 2016 I said it was a good time to sell.

In May 2020 I argued that prices were more likely to rise than fall.

Here is another prediction. In the next fortnight, all Australian households will complete the census, as they do every five years. When the data comes out, it will show a slight uptick in the homeownership rate compared to the 65.4% from the 2016 census.

Why am I predicting this?

First, I want to look at the long term trends. Australia’s homeownership rate (share of households who own the home they live in, including if they have a mortgage) peaked in 1966 at 71.3%, having risen from 52.6% just two decades prior. 

That boom in homeownership was brought about by heavy-handed government intervention in the housing market, including
  • rent controls that persisted post-war and incentivised landlords to sell,
  • public finance for first home buyers building new homes,
  • large scale public housing with tenant purchase programs,
along with many other interventions.

The market era from the 1980s onwards has seen homeownership rates fall from 70.4 % in 1986 to 65.4% in 2016.

However, there are ups and downs within the slight downwards trend over the last 30 years.

In a housing market, an imbalance of home buying between landlords and first home buyers leads to changes in overall homeownership. More landlords selling and more first home buyers buying is the only mechanism that changes the overall distribution.

Let’s look at those two elements of the market.

Since there are no available direct records of whether a property buyer is a landlord or first home buyer in any transaction, we can look at the patterns of mortgage finance.

The plot below shows the share of housing finance going to first home buyers and investors (sorry for no pre-2002 investor data).

The green shading shows the census periods with rising homeownership, and the red shading is falling homeownership, with the percentage point change in homeownership marked. 

Since the last census in 2016, first home buyers have been large a proportion of all new mortgage lending, consistent with the 1991-2006 period of slightly rising homeownership (up from 68.8% to 69.8%).

But the stark change recently is the decline in investor lending in the market since 2016. In the 2011-16 period, investor lending was 39.4%, but since 2016 it has been 30.8% on average. Not buying and selling are somewhat equivalent asset investment options for investors. They both reduce the allocation to housing (just like not selling and buying keep more of an investment portfolio in property). We can then infer that the decline in investor buying is likely related to more investors selling. 

This might not be the case. A confounding factor is the change in risk-weighting by banks for investor lending due to the fallout of the 2017-18 royal commission. Perhaps this means relatively fewer investors are selling compared to buying, but the overall level of activity fell substantially. 

Another factor worth keeping in mind is the make-up of total households. The recent period of declining homeownership coincided with a period of rapid migration. These new households were more likely to be renters, at least for a short period. Most of this sub-set of renting households, including foreign students and temporary workers, have left Australia since COVID. 

This combination of factors is why I am predicting a bounce in homeownership in the 2021 census.

Tuesday, July 20, 2021

Saving us from COVID-19 will cost lives after the pandemic

First published at AFR here.

Missing from the debate about the human cost of COVID lockdowns is an understanding of how societies produce health and longevity in the first place. 

What are the economic and social ingredients of an historically unprecedented 83-year life expectancy in Australia, and are these at risk from our COVID response?

Over the past decade, Australian life expectancy grew one and a half years. That is 35 million life-years gained for a population of the current size. 

The sum of all our economic and social life interactions can be thought of as a longevity machine. It produces economic wealth but it also produces health in the form of longer and happier years of life on average. 

Economic and health outcomes are tightly related. A functioning economy pays for hospitals and clean affordable food and the roads and ports to ship food, medicine and other goods. Constructing sewage and energy systems, houses that keep us warm and safe, and schools that educate the next generation, are all parts of a functioning economy.

Sure, the economy is imperfect. Some components of the machine are a net negative for longevity, but the overall system does the job. 

Delaying and disrupting the operation of the longevity machine costs lives. A day of delay to the machine in Australia costs 9,600 additional life years by pushing back longevity gains. By this metric, lockdowns reduce expected life-years by far more than might be gained from reducing COVID transmission.

In developing countries like India and Nigeria, where life expectancy is much lower (55 and 70 years respectively) but growing faster, each day of delay to their progress costs 1.4 million life-years. This is an astronomically high human cost that must be accounted for and compared to plausible COVID health scenarios. 

This big picture longevity machine view of how social and economic processes create longevity might seem strange to some people. But it is a useful approach when looking at large-scale disruptions from lockdowns because it is surprisingly difficult to break out exactly what elements of social and economic life produce health outcomes. Is it diet? Friendship and social support? Education? Work quality? Family stability? Healthcare services? All have individual and coordinated effects, and all get disrupted by lockdowns in a variety of ways.

We can, however, look at some of the disruptions to different parts of the longevity machine to get a feel for how they cause irreversible reductions to health. 

For example, prioritising COVID medical research above other diseases is likely to slow the longevity machine. The delay of other medical diagnoses, treatments and routine vaccinations will generate huge irreversible health costs for years. Due to border closures and supply issues from lockdowns, delays to global childhood vaccination programs are estimated to have already cost over a million lives of children under age five. Converting into life-years remaining at death, this cost alone would constitute more harm to human health than COVID.

We know that average population immunity to other circulating viruses has diminished due to declines in human interaction, creating new outbreaks in children of other deadly viruses such as respiratory syncytial virus (RSV). Global poverty has taken off, as has inequality within countries. Both are factors that reduce longevity. 

Mental health is on the decline, binge drinking is up, teenage suicide attempts are up, and demand for counselling services is up. Surveys of well-being show unprecedented falls. 

The freedom to travel and take memorable vacations are on the decline, reducing well-being. The kindness that happens in chance human interactions in daily life is down. 

Childbearing has been delayed globally, meaning many women will now have fewer children than they desire because of this delay, a blow to their well-being. 

Important life events such as high school formals, weddings and funerals, family reunions, birthday celebrations, and milestone sports and cultural events for budding young athletes, musicians and performers are all off the cards, with no chance of catching up for these losses in the future.

Australian governments have been extremely proactive with economic stimulus policies, providing fuel for the longevity machine to recover. But time cannot be recovered. Many lockdown losses, such as those described above, are locked in and will be felt for decades to come. 

A public health mantra is that when combatting a single cause of death, one must avoid unintended health costs elsewhere, lest you inadvertently worsen overall health outcomes by your response. This is why pandemic plans prior to 2020 did not support large-scale lockdowns, and indeed, cited risks that behavioural changes might worsen virus propagation as well as health due to other factors. 

But these diverse and often hidden health outcomes do not attract much media attention. Thinking about how the sum of social and economic activities as a longevity machine can show just how big a health risk even small disruptions make.