FET (old posts)

Latest writings are now on substack

noreply@blogger.com (Cameron Murray) — Mon, 16 May 2022 04:56:00 +0000

All my writing is now being posted on my new substack page.

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Here's a preview of some of the latest articles.

The content of this site will ultimately be merged with the content on substack when I launch a better Fresh Economic Thinking experience in 2023.

A social housing fund is bad policy

noreply@blogger.com (Cameron Murray) — Sun, 24 Apr 2022 23:27:00 +0000

A social housing fund is a policy idea gaining traction. The ALP has proposed a $10 billion one in their election platform. The Grattan Institute has proposed a $20 billion one.

The basic idea is to sell bonds to the market and use the cash from that sale to buy a range of higher-yielding assets. Because there will be a differential return between the low cost of borrowing and the higher return on assets, this creates a net return from the fund to pay for building new public housing.

It sounds so bland and innocuous that it is easy to miss how economically backwards the policy really is.

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Housing stock per capita mostly measures demographics

noreply@blogger.com (Cameron Murray) — Sun, 10 Apr 2022 10:47:00 +0000

I don’t like this chart.

Not only is there an unjustified implication of direct causality (X causes Y, and planning regulations cause X), the pattern in the chart rests on choices about

countries,
time periods,
measures of the housing stock, and
measures of the price of housing.

I want to focus here on how comparing countries with different demographic trends, particularly ageing, has implications for interpreting housing stock per person measures.

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Why politicians must pretend to want cheap housing

noreply@blogger.com (Cameron Murray) — Wed, 16 Mar 2022 22:28:00 +0000

UQPPES Statecraft Autumn Lecture, March 2022

Let me start with my thesis.

Much of the contemporary debate about housing affordability is a distraction; promoted by vested interests and reinforced by political incentives. The proposed solutions are usually policies that favour property owners, not renters and buyers.

The first way we know something is off is the language. Affordability is a beautifully vague word. It’s a word that works nicely as a covert signal—that is, a word that means something different to your target audience compared to others.

Aspiring homeowners can be led to believe that the word implies cheaper prices to buy homes. Maybe also cheaper rents. They feel their concerns are acknowledged. It appears like something is being done for them.

For homelessness and public housing advocates, the word affordability can imply a boost to public housing investment to provide non-market housing options to the neediest. The word makes it appear that something is being done for them too.

But the beauty of a covert signal is that the true meaning is known only to the target audience. In this case, large property owners and developers. They know that affordability means that absolutely nothing will be done that puts the value of their property assets at risk. To them, the word is an invitation to participate in the next great property scam.

They know that to appear to be doing something about affordability, their political mates will simply ask them what policies they want. Whatever tax break, rezoning, or subsidy they come up with will then become the nation’s new “affordable housing” policy.

It is no leap to say that these outcomes are in fact the real objective of pretending to care about cheap housing by distracting us with the word affordability.

In his 1946 essay on Politics and the English Language, George Orwell wrote:

When there is a gap between one's real and one's declared aims, one turns as it were instinctively to long words and exhausted idioms, like a cuttlefish spurting out ink.

Affordability is a long word that hides the real aim of boosting the asset portfolios of major property owners behind the declared aim of making housing cheaper for residents.

So why must politicians play this Orwellian game of pretend at all? There are three political economy issues at play.

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Falinski's housing inquiry report will be peppered with lobbyist catch phrases...

noreply@blogger.com (Cameron Murray) — Mon, 14 Mar 2022 01:13:00 +0000

...and many journalists will lap it up uncritically.

Like the dozens of previous housing inquiries before it, Falinski’s inquiry into housing supply will find that giving valuable rezoning development rights to well-connected property owners and developers is the housing policy we need.

The puzzling part is that the housing developers interviewed under oath during the inquiry said that they wouldn’t flood the market to decrease prices even if they could.

Falinksi: Is it not your view that, if we increase the amount of supply, prices will go down?
Mr Helmers: I don't think that's the case…
Mr Long: My view is consistent with Richard's: rezonings won't necessarily lead to lower housing prices… … Falinksi: …[d]o you think if state local governments rezoned more land to allow greater supply, that you could see dwelling prices drop by 20 per cent?
Mr Warner: No. Straight out, I concur with some of the comments before. It's not going to create that much of a difference.

For perspective, Australian capital city housing prices increased 21.7% in the year to September 2021. No housing developer thought it plausible that mass upzoning could get close to reversing one year’s price growth.

Instead, they all latched on to the phrase that mass rezoning will “will moderate price growth”. I have no idea what this means. If price growth is zero in the counterfactual, will it mean prices start falling? If it moderates price growth, why can’t rezoning moderate price growth down to a negative?

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My COVID story - Part 2

noreply@blogger.com (Cameron Murray) — Sun, 06 Mar 2022 10:59:00 +0000

Read My COVID Story - Part 1 here.

January 2021 - Sticking with the crowd

I was approached to write a short piece for The Mint magazine. I sent a rough draft of the type of article I would write. When it dawned on them that I was going to challenge the COVID mantra they decided that they must stick with the crowd and not publish anything.

I later put that draft piece on my blog. The predictions in it have been quite accurate. Take a look.

Back then, zero COVID was still a thing that people thought was possible, despite all evidence. The vaccines were going to be the way to achieve that dream.

June 2021 — Vaccinate the kids becomes a thing people want to do

I was invited on ABC’s Q+A television program to be a panelist sharing opinions about COVID policy. You might be wondering how someone gets invited. My experience was that Stan Grant and the producers wanted to be able to say that our reaction to COVID was overblown but didn’t want to have to say it themselves and cop the flak.

Here’s a write-up about that appearance from ABC News.

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If planning constrains housing supply, how does it do it?

noreply@blogger.com (Cameron Murray) — Tue, 01 Mar 2022 01:01:00 +0000

I’ve long puzzled over the exact mechanism by which planning regulations are supposed to constrain the rate of new housing supply. Sure, they constrain the locations at which different types and densities of uses can occur. That’s their purpose.

But density (dwellings per land area) and the rate of supply (new dwellings per period across all sites in a region) are very different.

It seems logical to me that landowners maximise their economic returns from two choosing

a density of development that maximises the residual (i.e. their revenue minus the cost of development), and
a rate of sales (and hence development) per period of time.

It is not at all clear that if more dwellings can be built on one site that this changes the optimal rate of sales per period for that site.

It is also the case that only landowners can choose to make planning applications, and that a huge majority of approvals are for projects that exceed coded density limits. We have a property market after all.

What I am puzzled about is that when someone claims that planning reduces housing supply, what sort of counterfactual pattern of supply do they have in mind?

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My COVID story - Part 1

noreply@blogger.com (Cameron Murray) — Tue, 22 Feb 2022 01:59:00 +0000

March 2020 — People lose their minds

My first ever public comment about COVID was this. I was both prescient and wrong.

Everyone has lost their shit about coronavirus as if lives lost this way are worth orders of magnitude more than lives lost any other way. In two to three weeks time the reality will set in that there are real costs of locking down society that can be measured both in value of resources wasted and in blood. All perspective has been lost at present.

If only I’d written years instead of weeks, then it would have been spot on.

As someone who has thought about health policy, well-being, and trade-offs for many years, my first reaction to the media coverage of COVID and the mystery China virus was to ask the following question: What is the normal number of deaths in a city the size of Wuhan? Without this context, all the media coverage made no sense. A city with 12 million people can expect about 96,000 deaths a year. That’s 264 a day.

So when I read headlines like “Death toll rises to 600” and that smoke from crematoriums working overtime was filling the city, I had a reasonable baseline from which to sniff out nonsense. The numbers mattered then and they still matter now.

If you search online for news articles of COVID or coronavirus deaths from February 2020 you will see just how small the death numbers are and how crazed and fearful the reporting was. Some of the reporting just had made-up figures, with orders of magnitude differences from one article to the next. No one really cared.

Even at this early stage, the lack of deadliness of the virus was becoming clear for those who wanted to find out. The case fatality rate was likely to be sub 0.7%, even with relatively limited testing (i.e. 0.7% of known cases, not all cases). Clearly, this implied that early estimates were hugely biased because infections were far more widespread than initially assumed.

The Diamond Princess cruise ship had 3,711 people on board and had 14 deaths. On this cruise, 0.37% of people died over a two month period. Is that good or bad?

We know that background mortality is about 0.8%. So every two months you can expect 0.13% of people to die. But this is across the whole age distribution. Even a small skew towards the elderly massively increases this number. For example, in your 80s you have a one in twenty chance of dying each year on average. In your 90s, a one in five chance.

The age distribution of the Diamond Princess was super high, so 0.37% of people dying within two months is totally within the normal range.

We knew this in March 2020.

Image source: https://wattsupwiththat.com/2020/03/16/diamond-princess-mysteries/

We already knew then from the Italian outbreak that the average age of COVID deaths was higher than deaths from all other causes combined.

Taking all this information together was pretty encouraging. This is why herd immunity was thought to be simply a matter of months away. Flatten the curve for two weeks, then a month or two later the whole thing would be over. No one expected to be having masks, border closures, vaccine mandates and passports for two years.

With markets crashing I took the opportunity to put forward some ideas about macro-stabilisation policy, such as having a public agency take equity stakes in companies that wanted bail-out money and buying up housing developments in distress to smooth construction cycles and add to public housing stocks.

Of course, none were taken up. But looking back, they were much more sensible than what we got with a JobKeeper giveaway, a Cashflow Boost, that cost hundreds of millions and resulted in a net upwards redistribution of wealth.

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New metrics to show the value of delaying housing supply

noreply@blogger.com (Cameron Murray) — Thu, 03 Feb 2022 05:21:00 +0000

*This article is based on a submission to the Housing Supply Inquiry that I contributed to for Prosper Australia.

This neglected economic puzzle has become a heated policy debate. Rapidly rising dwelling prices globally have grabbed the attention of policy makers. Many have subsequently targeted planning and zoning as areas for housing reform. Australia, New Zealand, the United Kingdom and various states in the United States, are conducting new reviews into planning, housing supply, and prices.

Unfortunately, most analysis of housing supply conflates density (dwellings per unit of land) and the rate of new housing supply (new dwellings per period of time across all sites). This is because the time dimension of the investment decision facing a landowner is typically ignored in the economic analysis of housing supply.

But the optimal inter-temporal choice of landowners is hugely important for understanding the rate of new housing investment in property markets. Just as there is an optimal density of development that maximises the value of the site, there is also an optimal rate of sales of new dwellings per period that maximises the value of the site.

Across all candidate development sites in a region, the rate of new housing development (new dwellings per period of time) is known as the market absorption rate or build-out rate. Regardless of planning or zoning, this rate is the result of many landowners making individually-optimal choices about when and how fast to develop.

The economic logic behind the market absorption rate is described in Murray (2021). Some key elements of it are important to clarify. Owners of the property where a new home can be built already possess an asset on their balance sheet worth exactly the market value of the land. Developing that land with a new dwelling is a balance sheet reallocation. If developed for immediate sale, the property owner is swapping an undeveloped site asset for a cash asset. If developed for rental, the owner has swapped an undeveloped land and cash asset (to fund construction) for a dwelling asset.

Whether these asset swaps are economically viable depends on the relative returns to each. Only in a market where demand is rising does it make sense to increase the rate at which undeveloped land assets are swapped for cash assets. When market demand is falling and very “thin” (few buyers at current prices), it makes sense to slow the rate of new housing development. Other factors like interest rates (the return on cash after sale), taxes on land ownership (that reduce the return to retaining ownership of undeveloped land), and the ability to vary the density of development in the future (a flexible planning system can make delay more profitable by allowing higher density in the future, increase the return to delay), all have effects on this rate.

One interesting problem for this new type of analysis is demonstrating how economically important the payoff to delaying new housing development is for property owners. To address this, I am proposing here some new metrics that can be applied to housing developments to demonstrate the degree to which varying the rate of sales in response to market conditions increases the total economic returns from developing a site. These metrics demonstrate that independent of any planning controls on density, there is a “speed limit” on the supply of new housing in the form of the market absorption rate.

Development Rate Ratio (DRR)

How fast did the subdivision develop compared to how fast it could have if the maximum observed rate of sales was sustained?

Housing developers often argue that new housing is being built as fast as the planning system allows. Indeed, quite a deal of economic analysis also makes this assumption. However, once a subdivision or apartment building is approved by the planning system, the private choices of the developer determine how fast the approved new housing is developed. This includes how fast they sell, which is the key limiting factor of the build-to-order model of new housing production.

To demonstrate the degree to which these private choices limit the potential rate of new housing supply I proposed looking at the Development Rate Ratio (DRR).

The DRR shows the average speed of development as a ratio of the maximum speed, using the average monthly rate in the fastest three-month window. A lower number indicates that the new housing development proceeded more slowly than was demonstrated to be possible.

Development Rate Variability (DRV)

A second metric is Development Rate Variability (DRV). DRV is the ratio of the fastest speed of monthly sales to the slowest monthly sales during a development. This shows how sensitive to market conditions the choice of sales can be. A higher DRV shows how much the private choices of housing developers change the rate of new housing supply.

It may be argued that it is impossible to sell fast in a depressed market. But this is only true if prices are held constant. The very heart of the housing supply debate is whether planning changes create conditions for private housing developers to build faster at lower prices.

These two new metrics can help paint a picture of the variation in the market absorption rate due to the private choices of landowners. To complement these metrics, we also create new metrics of the economic returns available in housing development from varying the rate of supply in response to market conditions.

Delay Premium (DP)

What is the economic gain from varying the rate of supply of new housing to “meet the market”?

To answer this question a sensible counterfactual must be established. The counterfactual implied in most economic analyses of housing is that housing is supplied once the market price gets above the feasible price for development. In other words, housing developers fix the price of all housing (or land lots) at the beginning of the project (a fixed point in time) then vary only the speed of sales to match market demand at that initial feasible price.

The dynamic approach recognises an economic return to varying both the rate of supply and the price. This is then the difference in revenue between the following two approaches.

Setting a price at the beginning of the project and selling all dwellings or housing lots at that price until the project is completed
Varying both the rate of supply and price to maximise profits from the project.

A metric that identifies the economic gains to delay is the Delay Premium (DP). The DP is the share of total revenue that was made by varying price as well as quantity (ignoring discounting) and is calculated as follows.

Two parts of this equation need some explanation. First, when applied to detached housing subdivisions the total revenue is for land only, not for homes. This is because the additional gain from building the home comes with added construction costs leaving the land value as the net income. Second, the reason for including the minimum land price rather than the initial price is because the lowest price in the sequence of sales indicates the minimum willingness to sell.

A higher DP means that a larger share of the total revenue came from actively varying both price and quantity during the selling period.

Available Delay Premium (ADP)

Another metric that shows the economic gains to delay is the Available Delay Premium (ADP). It measures the maximum difference in sales price over the life of a project (the peak price per sqm that often occurs at the end of a project and the lowest sale price that usually occurs near at the beginning) multiplied by the total sold land area as a proportion of actual revenue. This metric indicates a theoretical maximum degree to which revenue could have varied (as a proportion of actual revenue) if all sales were made at the highest price compared to all sales being made at the lowest price.

The interpretation of the ADP is to show how important choosing the timing of sales can be to the final returns of a project. A higher ADP indicates that varying sales rates due to changes in demand, and hence price, will have a higher economic payoff.

Applying these metrics

Jordan Springs is a 900-hectare residential subdivision located in Penrith (53km west of Sydney’s CBD) and was approved for development in 2009 with the first residents moving in during 2011.

By 2012 the development was owned by Lendlease, which published in its annual report that year that the area would ultimately provide over 2,000 detached dwellings and 200 apartment dwellings, with an expected 10-year development timeline. The subdivision masterplan is below.

Unfortunately, data on land and house sales in this subdivision is only available to me at the moment from 1st October 2015 to 8th October 2021, a period over which there were an estimated 2,131 new land lot or dwelling sales.

Summary of absorption rate metrics

The four absorption rate metrics for the available data on this large subdivision project are summarised in the table below.

In this data, total revenue was around $1 billion. The 0.13 DP represents about $137 million of value that was gained by varying prices during the project rather than setting the minimum profitable price and selling all lots at that price. The difference in revenue between selling all lots at the lowest per square metre price and the highest price was $310 million. These figures also provide insight into the variability and risk involved in land and housing development.

Further analysis and detail

It is also worth looking at the variation in sales and prices over the available data for the Jordan Springs project.

The chart below shows the smoothed monthly rate of land and house sales for new dwellings (orange), alongside the repeat sales (dashed black) over time. Minimum, maximum and mean sales rates are marked (which are used to generate the DRR and DRV metrics). Notice that in the quiet housing market of 2019 that sales were much slower than in the busy 2016-17 market period.

The next chart below shows the land price per square metre observed in the sales data over the same time period, with maximum, minimum and mean prices market (which inform the DP and ADP metrics). During this five year window, land prices varied by around 30% (the ADP metric) but had noticeable peaks and troughs that coincided with macroeconomic conditions.

Finally, we can look at the relationship between price growth and the rate of supply in the final chart below. Although these data points do not generate a statistically significant relationship, visual inspection shows clearly that periods observing price growth also saw faster new supply, especially in earlier development stages during 2016-18, as expected if the developer is optimising sales rates and price to maximise their revenue (as predicted by the logic of the market absorption rate).

The enormous variation in the rate of supply in large projects such as Jordan Springs, with thousands of approved dwellings, is a clear indication of macroeconomic and market conditions being the main determinant of the rate of new housing supply.

Ignoring age and COVID risk is unscientific

noreply@blogger.com (Cameron Murray) — Thu, 16 Dec 2021 00:30:00 +0000

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

kept finding reasons to link COVID policy back to Trump, which was weird, and
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.

Did Germany and Tokyo really get affordable housing through planning?

noreply@blogger.com (Cameron Murray) — Sun, 05 Dec 2021 05:30:00 +0000

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.

Alice in housing economics wonderland

noreply@blogger.com (Cameron Murray) — Tue, 23 Nov 2021 04:12:00 +0000

“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.

Opening remarks to housing inquiry

noreply@blogger.com (Cameron Murray) — Wed, 17 Nov 2021 00:47:00 +0000

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.

Public housing is way cheaper than rental subsidies

noreply@blogger.com (Cameron Murray) — Thu, 04 Nov 2021 05:52:00 +0000

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.

Many submissions to the Falinski inquiry call for “inclusive zoning”, “affordable housing”, “social housing” and similar programs.
A central feature of these policies is rent control, with housing being allocated by a mix of queueing, bureaucratic formula and randomness. 1/6
— Peter Tulip (@peter_tulip) October 28, 2021

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.

Housing supply… another inquiry

noreply@blogger.com (Cameron Murray) — Wed, 08 Sep 2021 05:48:00 +0000

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

There is no mystery to rising house prices.

Central banks are trying to make them rise, as they repeatedly explain. That's how we manage the macroeconomy these days.

BoE:https://t.co/ia7YkkAzwj

RBA:https://t.co/Xr21vQjKzB pic.twitter.com/dwTTNM4IAn
— Cameron Murray (@DrCameronMurray) September 7, 2021

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.

The Letwin review of housing build-out rates was weird.

After learning that private landowners don't voluntarily flood the market to depress prices, they then decide that any policy to change that would be bad.

Like, what was the point of the review?https://t.co/WuMJvs09Pa pic.twitter.com/hT0kAfegd7
— Cameron Murray (@DrCameronMurray) July 17, 2020

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.

From way back in 2004 when the Productivity Commission looked at the evidence and concluded that higher rates of new housing supply can't change prices much. https://t.co/yAD7CZSNVQ pic.twitter.com/qPtpuLC7K1
— Cameron Murray (@DrCameronMurray) September 7, 2021

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)

Do medical school entrance tests constrain supply?

noreply@blogger.com (Cameron Murray) — Tue, 17 Aug 2021 04:52:00 +0000

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

Only those with a bachelors degree are eligible to take the test.
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.
Those who do not pass the GAMSAT can re-sit the test as many times as they like in subsequent years.
Those who pass have the option, but no obligation, to attend medical school.
You must re-sit the test if you do not go on to medical school within three years.
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.

The choice to take the GAMSAT test
The pass/fail choice
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.

A direct effect due to the pass rate
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.

COVID logic vs the public health army

noreply@blogger.com (Cameron Murray) — Mon, 09 Aug 2021 13:12:00 +0000

“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.

Suicides

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?

Predictions

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.

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.  
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.  
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.

An Australian homeownership prediction

noreply@blogger.com (Cameron Murray) — Wed, 04 Aug 2021 02:57:00 +0000

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.

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

noreply@blogger.com (Cameron Murray) — Tue, 20 Jul 2021 22:45:00 +0000

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.

COVID, Q+A, tough questions and sense-checking

noreply@blogger.com (Cameron Murray) — Tue, 15 Jun 2021 03:09:00 +0000

Q+A is not real life. Nor is Twitter for that matter.

In the days since my appearance I have received more than one hundred emails and messages from people from all walks of life across the country. These are not cranks. There are academics, scientists, and doctors, who are unable to speak up in their own organisations.

“l feel silenced by my occupation.”
“I am a … working on vaccines…”
“Please keep this confidential. I am a ... professor…”

I’ve had letters from young people pleading for some sense about the human cost of lockdowns, especially from Victoria.

The theatre of television is not where truth can be found. What people will say in public and what they privately believe are rarely the same. This is true even for Q+A panellists and hosts. Very few people have the luxury I do of following the data and evidence no matter where it leads. Most have reputations to protect, for themselves and their organisations.

Such people need someone else to speak up first. That is fine. Over the past decade or so I have become the guy that says the obvious before it is popular.

In doing so I’ve been called left-wing nutter, a right-wing nutter (make up your mind trolls), and many variations of “he’s an idiot”. Very witty. Often my views are later accepted more widely as being correct. But no one cares.

We don’t live in a world where truth matters. Making good predictions provides little credibility.

We live in a society of humans who are “group-ish” and loyal. One where people form their views socially, facilitated by story-telling. Being wrong with the group is better than being right but going against the crowd.

Here are a few things that have been on my mind regarding the state of COVID policy and analysis in the past few days. Before you dive in, you can read my earlier thoughts on COVID policy here.

People are self-censoring

Self-censoring at present makes sense for many people.

If you don’t, the power of big tech will do it for you. Bret Weinstein is no science slouch, nor are his guests, which include doctors and scientists (including the inventor of mRNA vaccines). Yet he has repeatedly been demonetised and censored on YouTube.

In this tweet YouTube is spreading deadly misinformation. It is creating the false impression that Ivermectin is ineffective against COVID. The evidence is discussed in the video. If there is disagreement on the evidence discussion is required. #FollowTheSilence #CensorshipKills https://t.co/uF7BjZ3tRP
— Bret Weinstein (@BretWeinstein) June 12, 2021

Totally normal words and arguments by world-leading experts have become taboo. Herd immunity? Taboo. Great Barrington Declaration? Taboo. Our public health response has devolved into a social media political team sport, with no regard for facts and evidence.

In this social climate, who would stick their neck out in public?

Our new “health experts” are anything but

Eliminating COVID is a preposterous policy objective. Not only is it unlikely it is impossible to do nationally. The only public health objective that matters is maximising overall health and wellbeing.

Yet zero COVID is trumping all other considerations. The experts are not even trying to consider the cost. Lockdowns are free of health and wellbeing costs in their fantasy world. This is astonishing.

Here’s a clip with a variety of experts, including Sunetra Gupta explaining that although they are not as attention-grabbing as COVID deaths, the human toll of lockdown is very real.

No one cares about solving the problem. There is no plan.

Take a look at Ivermectin and the censoring of anyone who suggests that existing safe drugs should be used as COVID treatments. One might even suggest that there are financial incentives at play for pharmaceutical companies to make sure only their expensive new drugs are approved for COVID treatment.

Take a look at the logic being used to promote vaccines. The “experts” on Q+A simultaneously had the view that vaccines should not be compulsory and we should not open the borders until we are nearly totally vaccinated.

What if only 50% of people want to be vaccinated? What then?

Also, why should we vaccinate children when we know their COVID risks are minimal? Nearly 25% of the population are children, and COVID vaccines are not recommended for them.

We are told we must learn to live with COVID and future variants, but we are unable to accept that this means people will die from the disease. You cannot have it both ways. Have a logical plan, please.

No one cares about acquired immunity from disease

Experts worry that a perverse idea has spread widely—that people don’t get immunity from their body’s own response to contracting a virus. Yet saying the sensible reality that recovering from infection provides immunity gets you censored, no matter what your scientific credentials.

I said vaccinating children for COVID was crazy on national television. This provoked a response from the President of the AMA who wanted to imply something very different, but who ended up saying that the medical advice is that vaccines are not recommended for children. My views are totally in line with much of the medical profession. So why the need to put on a show to make it seem otherwise and give a distorted picture of the evidence to the public?

Even Harvard professors are not safe from censorship around sensible medical advice.

When making unscientific claims, media often refer to "health officials" or "experts" without citing anyone. I challenge @Twitter to name vaccine experts believing that everyone, including children and those with prior immunity from natural infection, MUST be Covid vaccinated. pic.twitter.com/tYhCjdKzgf
— Martin Kulldorff (@MartinKulldorff) March 28, 2021

No one cares about killing poor children elsewhere

We know that the rollout of childhood vaccination programs has been delayed and disrupted, especially in the poorest countries. There is a huge cost to this in the form of avoidable child deaths. One estimate suggests that the disruptions due to border closures, logistics, and prioritising other vaccines and health supplies will cost the lives of over a million children aged under five. The longer lockdowns go on, and the more we devote health and science resources to COVID above other health issues, the higher this toll.

Are the figures in this study correct? I do not know. Their value is in providing a sense of balance. COVID is just one disease amongst many. Attempting to estimate the potential scale of other health issues that have been neglected is something that should have been front and centre of the policy response in Australia and globally.

Economic development makes people live longer

The investments that make people live longer are not usually direct healthcare investments. They are instead things like clean water, dealing with city waste, functional sewerage systems, reducing urban and local pollution, and clean food supplies. These have been proven time and time again to be what makes people living longer.

Now consider the cost of locking down India. Each year investments in these types of basic services create enormous health improvements of around 0.25yrs of additional life expectancy across the population (i.e. every four years life expectancy increases one year). Delaying this process with lockdowns is hugely costly there. A one year delay costs 0.25 life-years x 1.37 billion population = 342 million years of life—an astronomically high figure compared to even the worst-case COVID death toll.

The commentary on Australia’s economic performance is also amiss. The fact that economic activity recovered to its previous level does not mean lockdowns and border closures were economically costless. The counterfactual is where we would be today with no lockdown but with the stimulus actions we have seen, as the policy option to stimulate economic activity has always been available.

The stylised chart below shows what I mean. Comparing point A and B to show there is no economic cost is silly. Comparing point C and B is the only sensible approach.

The coming debate about COVID deaths vs lockdown deaths

Soon we will have a heated debate about how many lives were saved because of lockdowns. We will only have the debate about how many lives lockdowns actually cost in private, as those discussions will continue to be censored for a while yet.

Here is a quick overview of some of the mistakes of logic we can expect to see.

If recorded deaths by COVID are below excess deaths over the 2020-21 period, then that gap will be typically attributed to “missed COVID deaths”. This attribution is a wrong assumption. There will certainly be missed COVID deaths, and over-counted COVID deaths, but the gap can arise for multiple reasons, including lockdown deaths.

The Economist has already been implying these are all uncounted COVID deaths (see image below). They all seem to come from Asia and Africa (puzzling). I will be very interested to check back on their modelling exercise in 12 months time when we have more accurate records of what happened. Looking at how past predictions turned out is a great way to sense check claims, but something that the media rarely does.

Taxing rezoning windfalls (betterment)

noreply@blogger.com (Cameron Murray) — Tue, 01 Jun 2021 22:28:00 +0000

This is an excerpt from a new paper of mine available here.

What is the source of rezoning gains?

The answer to this question relies on understanding the nature and extent of property rights. A core right of a property owner is to exclude others. A right holder of this type usually also has a residual claim to income generated in the space over which they have exclusionary rights (“pay to use this space or I’ll exclude you from it”).

But these rights are limited. They evolve as the law evolves, including zoning and planning law. Rights to access and sell minerals within a property’s exclusive space, for example, are not part of the private property rights bundle in Australia. They are instead owned collectively by States.

The value of private property rights is primarily determined by how much revenue can be generated above costs (excluding property rights costs) on a site at a particular location. The value of property rights is a residual, just as other assets like shares in company ownership represent residual claims on income. Whichever use of a site generates the largest residual income is its highest value use.

The revenue potential of private property rights is affected by market conditions, location-specific features, fixed improvements, and the nature and extent of the property rights bundle itself. Investing in new fixed improvements, like buildings and earthworks, can add to property value because they remove a cost to gaining revenue (remember, property value is revenue minus costs needed to earn that revenue at that location). The value of fixed improvements becomes “attached” to the property as they cannot be separated physically or legally from the property right to a location.

However, the value of private property rights can also increase due to external factors that are not due to investments made by the property rights owner. When this occurs, it is known as betterment. For example, new public works that improve the accessibility of a location will increase the value of those sites because they reduce the transport costs of using those sites to generate revenue. Similarly, when the law changes the nature or extent of property rights in a way that increases the revenue-generating potential of that site, such as with rezoning, the resulting increase in value of the property rights bundle is betterment.

Planning rules coordinate property uses across locations by defining property rights bundles. For this coordination role to affect property uses it must legally restrict some uses so that the highest value legal use is different to what might occur with a “no zoning” property rights bundle. Hence, there is an inherent conflict between maximising the value of any individual property and coordinating the location of property uses across a region.

The diagram in Figure 1 shows how betterment arises conceptually and how a tax on betterment transfers value to the public that would otherwise accrue to private property owners.

Figure 1: Betterment in the residual model of property value

The left column shows the value of the property rights at a site, such as agricultural or industrial land. That value is determined by the revenue that can be made from exclusively using that site, minus the necessary costs. The site’s property rights value is the residual.

Suppose the market value of the output being produced increases, such as the value of crops on an agricultural property, but all input costs remain the same. In that case, the site value rises to reflect the higher residual value of production on that site. The new site value and its betterment component from these external factors is shown in the second column of Figure 1. Another example is if the rent of a residential dwelling rises, but the costs of operating that dwelling remain constant. This increases the property value. Where a property tax system exists, some of the value gains accruing to property rights from higher market prices of production are shared with the public.

The third column of Figure 1 shows what happens if there is a change in the nature or extent of the property rights through rezoning. For example, if the previous highest value use of a site was industrial only because zoning laws prevented other higher value uses such as residential, then rezoning will change the highest value legal use of the site and hence its value. The difference between the “before” site value (V1) and the new “after” site value (V2) is betterment.

A flexible planning system presents opportunities to increase revenue from development by exceeding codified density limits and hence offers another way to generate betterment for a landowner. The betterment gained from exceeding codified planning density limits is just as real as the betterment gained from rezoning. It is why, despite cost, risk, and time involved, many property owners seek planning dispensation instead of complying with codes and gaining fast approvals.

Here is a useful way to conceptualist betterment. Rezoning adds an additional private property right to the previously owned bundle. The value of this new right is betterment, and it reflects what the market would pay if these new property rights were instead auctioned for sale to existing property owners.

The effect of a tax on betterment arising from rezoning is illustrated in the fourth column of Figure 1 using the 50% tax rate proposed in Victoria. A share of the betterment value is transferred from the private property owner to the public, reducing the private payoff from rezoning decisions and increasing the public’s share.

The size of betterment from rezoning can be extraordinarily large, often many multiples of the previous site value. For example, a well-situated industrial site in Sydney’s inner west was bought for $8.5 million, rezoned high-density residential, then sold again just a few years later for $48.5 million.

Rezoning at Fishermans Bend in Melbourne led to numerous sites trading at values many multiples of their previous industrial use values. At 320 Plummer Street, Port Melbourne, the 7,468m2 site formerly used as the Rootes (Chrysler) factory transacted in 2009 for $1.7 million with industrial zoning rights. After rezoning to high-density residential, an application was made and approved for the development of three towers containing 443 dwellings and 908m2 of commercial floor area. The property was subsequently purchased for over $11 million. Even after inflating the 2009 sale price to $3 million to reflect sale prices in 2015 for similar industrial properties, the windfall rezoning betterment is roughly $8 million, with the site trading for nearly four times its previous value.

Notably, betterment is not an additional cost to housing development. The value of property rights is a residual; after all, there are no input costs to these rights. Betterment merely reflects the change in the market value of the residual claim on income of the property rights owner, and taxing betterment merely transfers this value from the property rights owner to the community.

Harvesting housing supply

noreply@blogger.com (Cameron Murray) — Fri, 21 May 2021 12:22:00 +0000

There is a common thread between the boom in lumber prices in the U.S. and dynamic models of housing supply.

That common element is that lower interest rates make it optimal to both harvest trees slower and to build new homes slower. Let me explain.

Take a look at the diagram below representing a forest with trees at different stages of growth.

The stock of potential timber from trees at different stages of growth is marked as Q. So 10 tonnes of large trees, 7 tonnes or medium trees, and 3 tonnes of small young trees. A total of 20 tonnes of timber there.

But each stand of trees with a different maturity has a different rate it grows per year. Young trees accumulate timber faster (proportionally) than older trees. The growth rates for the trees in each stand are marked—the oldest grow at near enough to 0%, the next at 5%, and the youngest at 10% per year.

Given this forest with a stock of 20 tonnes of timber, how much is optimal to harvest each year?

The trick to thinking about this question is to realise that the trees are assets, quite literally growing in value each year. When you harvest a tree you are swapping a "tree asset" for a "cash asset". The way to tell what is optimal is to compare the return from the tree asset that you give up to get the return from the cash asset. For example, if you can earn a 7% return from cash, you won't harvest a tree that is growing in size, and hence value, by 10% per year. It's a losing trade to give up 10% to get 7%.

In this forest, we harvest 10 tonnes this year if the interest rate is below 5%, and 17 tonnes if it is above 5%.

When it comes to forest management, lower interest rates mean slower harvesting of timber. If interest rates fall from 7% to 3%, then all the trees growing at a rate between 3% and 7% per year should be left to grow rather than be harvested and replaced with saplings. This is well understood when it comes to harvesting forests.

But it is not well understood when it comes to "harvesting housing development opportunities".

Undeveloped urban land is a lot like a tree—it grows in value without being developed (harvested). Like our forest, we don't just develop all land as soon as the revenue exceeds the cost. We optimise the rate per period to maximise value from the site (or set of sites). This is why developers stage housing subdivisions as much as possible.

A lower interest rate changes the trade-off between owning undeveloped land and getting cash from development. It makes a slower pace of housing development optimal, all else equal.

Not all else is equal, obviously. The price adjustment to lower interest rates generates demand that new housing supply responds to—interest rates are not the only factor. In the last 20 years we have relied on this temporary demand-boosting effect of interest rate reductions to generate supply, but this has led to structural low-interest-rate conditions that will not encourage supply when demand falls.

In housing, optimal harvesting is called the "housing supply absorption rate". I explain it here.

Stamp duty for land value tax

noreply@blogger.com (Cameron Murray) — Mon, 10 May 2021 23:03:00 +0000

The NSW government is proposing to give homebuyers the option to not pay stamp duty on their housing purchase and instead opt to pay an ongoing land value tax. I have labelled such policies SD4LVT.

SD4LVT seems to be motivated by "bad economics". All the efficiency gains that economic analysts claim will occur are merely assumptions and not very realistic ones at that.

A major consideration for SD4LVT is its effect on housing prices. While SD4LVT is often marketed as "saving buyers" thousands on their purchase, this ignores the well-known issue that stamp duty is economically incident on the seller.

What that means is that buyers have a willingness to pay for a home that includes the cost of stamp duty. If the market price of a home is $500,000 and stamp duty is 3%, then the purchaser must have been willing to pay $515,000 to buy the home. If stamp duty is removed, then this purchaser who was willing to pay $515,000 to buy the house can spend that $15,000 saved on stamp duty bidding up the market price. Instead of the government getting $15,000, the seller gets it.

This is why a stamp duty holiday on housing purchases was enacted in the UK last year to "kickstart the stalled housing market".

So we know that reducing stamp duty alone will increase prices. But won't a land value tax decrease prices because it adds an additional cost for the buyer?

Yes.

And we are now at the crux of the issue. Neither tax will, in the short run, reduce the cost of housing. Homebuyers are paying the maximum they are willing. Whether that payment is directed to home sellers, or the government via stamp duty or land value taxes, has no effect on the underlying property market dynamics of rationing via prices and the costs buyers will need to pay.

In a presentation I made to Victorian Treasury a few years back, I explained this point with reference to the ACT's ten-year SD4LVT transition. I showed the below graph which makes the point that if the present value of the flow of future land value tax liabilities equals the stamp duty, the same willingness to pay for housing is just distributed differently under a land tax regime.

I also explained how to calculate the likely market price effect for a government replacing the same average stamp duty revenue stream with a land tax revenue stream.

The rule is

If turnover rate < capitalisation rate, price increases
If turnover rate > capitalisation rate, price decreases

Let's work through an example with some round numbers to demonstrate. The average housing sale is priced at $700,000 with a $37,000 stamp duty (5.3%). Without stamp duty, the price would be $737,000.

Assume that turnover is 100,000, or 4% of stock per year. This provides $3.7 billion in stamp duty revenue.

For a land value tax to raise $3.7 billion, it would need to raise $1,480 per dwelling, since in this example there are 2.5 million total dwellings. A land value tax rate in the dollar can be worked out in order to raise this amount based on the land value share of the average home. Say land value is 60% of the average home value, or $420,000, then the land value tax rate on the dollar is 0.35% per year.

Whether the market price rises or falls depends on whether the present value of a perpetual stream of $1,480 annual payments is worth less or more than $37,000 upfront stamp duty.

If the capitalisation rate is 5% (the rate at which a flow of income is converted to a present value), then the present value of the land value tax is only $29,600. In this scenario, the market price would rise to $707,400 because a $37,000 stamp duty liability has been replaced with a $29,600 land value tax liability. Notice that the capitalisation rate here is above the housing turnover rate (5%>4%).

If the capitalisation rate is 3%, then the present value of the $1,480 land value tax payment stream is $49,300. In this scenario, a $37,000 stamp duty liability is replaced with a $49,300 land value tax liability, and hence the house market price will fall by $12,300 to $687,700.

The question of whether SD4LVT is a good policy change depends not on the price effects—it merely redistributes who gets what payment and when—but on efficiency effects from making housing turnover cheaper. On that note, I refer you to my previous analysis showing that these claims are overblown and that the revenue volatility of stamp duty is a good thing because it stabilises the economy.

In general, if you want to reallocate the economic rents that have accumulated to landowners, then a land value tax is a good way to go. But you do not need to remove another tax that achieves the same thing. Both taxes can work well together to divert economic rents from landowner to the public.

Why I am anti-anti-zoning

noreply@blogger.com (Cameron Murray) — Mon, 19 Apr 2021 05:27:00 +0000

I have fairly unique views on zoning, housing supply and prices. Here they are. Presentation slides covering similar issues can be downloaded from here. A video of the presentation is here.

Is zoning good?

The principle of zoning and land use regulation is very good and something I support. In practice, a lot of zoning and planning controls generally are designed poorly. I'm a big fan of simple rules.

For example, in Queensland, Australia, the developer charge (impact fee) on new housing was required to be set using a complex forecast of future population growth and infrastructure needs, with the fee per dwelling calculated in a big spreadsheet and published alongside various maps. I know it well. It was my job to help councils follow the required procedure and approve these modelled fees.

Then in 2011, the government announced a fixed cap on developer charges across the State. All councils quickly adopted this maximum charge. This system has been in place now for a decade, and it functions well enough. Its simplicity is a huge advantage, and across the planning system, there are similar gains from simplicity. (This surprise policy change also allowed me to demonstrate that these charges do not add to the price of housing)

I am a fan of the following process for managing land use.

Periodic reviews (each decade) of local planning schemes.
Extensive community input into these schemes, perhaps with a citizen jury having the final say.
Reviews to require some minimum zoned capacity unless there are strong reasons not to (not every area needs to accommodate housing growth).
Strict adherence to the scheme between reviews.
Few zones with simple controls (e.g. height, floor area ratio, setbacks, and use types).
A simple, fast and cheap way for applications that meet the code.
A longer assessment for applications that do not meet the code, which allows for community input into the decision.
A mechanism for capturing value from changes of use (adopt the ACT betterment tax).

Across most of Australia, planning schemes generally follow this basic structure, though with limited value capture. Debates happen because buying land already zoned for what you want to build requires you to compete with other buyers and pay a higher price, reducing your potential profits. The big economic gains come from buying unzoned land then arguing about the planning scheme to get your site rezoned. Many developers choose to make planning applications with designs that do not meet zoning codes. By doing so, they choose the longer, slower, more expensive path. Doing so usually pays off for them if it results in more saleable building space on the site.

There is bad zoning and planning. I do not like systems where applications that comply with the zoning codes can be stopped. Yes, some bad designs will get through. But the whole point of creating the code is to "set and forget" the rules and not argue on a case-by-case basis.

I have no issues with detached house (single-family) zoning. I have no issues with car park requirements. Whether these are desirable should be debated during the review of the local planning scheme. In general, removing car park requirements should be accompanied by local transit investment and on-street parking management to address any issues. I'm not anti-car. I think cars are a good, flexible, way to move about in low-density areas. But they can be troublesome in high-density areas.

Generally, the transformation of detached housing into "missing middle" housing faces economic constraints. The rezoning jump should probably be to 4-5 storey buildings. Alternatively, allowing townhouse/ancillary dwellings that can fit in yard spaces will work to slowly increase density. New suburbs, even on the city fringe, should be allowed to have townhouse density housing, and the zoning decisions of these areas should fit with transport plans. I am not anti-suburbia. There is no problem with even large areas being zoned for low-density housing, especially if they are not planned to get transport upgrades.

Nothing is going to be perfect. While I think the planning profession overthinks things and tries to micro-manage more than it should, some coordination is necessary. Whichever way cities evolve, there are going to be arguments and conflicts. Planning can improve these non-planned outcomes and avoid conflicts if the system is kept simple and done well.

To summarise, I like good, simple zoning that includes plenty of zoned capacity and complements transport plans. I dislike complex micro-managed zoning systems. Unfortunately, most of the economic analysis of zoning never actually assesses planning rules, nor the zoned capacity in the system. Planning rules are usually just assumed to be a binding constraint on the total stock of housing. This type of detailed analysis is hard to do on a large scale because local rules vary. My recent study is one of the few that do.

I also do not think that shifting a city from a "bad" planning system to a "good" planning system has much of an effect on either the rate of new housing supply overall or on housing prices.

I like more new housing supply. But the property market does not. To supply more than the market we need a non-market supplier. More on that later.

Housing is an asset. It is priced like one.

Rent is the consumer price of housing. Only the rent is affected by the number of dwellings relative to the demand to occupy them. Rents rise with wages, not other consumer prices.

For the economists out there, think of consumers with Cobb-Douglas preferences in the utility function. This utility function generates fixed budget share results, where consumers spend the same share of their budget on each consumption alternative (on average across the distribution). This means that households will optimally spend roughly 20% of their income on housing, regardless of supply, and that the market gets to this equilibrium mostly through price adjustments, with higher-income households outbidding for relatively superior locations.

Here is what the private rental cost share of income is in Australia over a 20 year period. Yes, there are cycles, but in 2017-18 it was the same 20% income share that it was in 1997-98.

Most of the housing price adjustment over the past two decades has been yield compression—prices have risen while rents have been flat relative to household incomes. The housing asset, rather than earning a 5%+ yield when purchased at the old price, now earns a 2.5% yield. Prices double relative to incomes, but the consumer price of housing remains as expected, tracking wages.

There is no mechanism by which planning or zoning can affect housing asset pricing except via rents. This is why I do not take seriously the claims that Houston and Tokyo are good examples of how planning has constrained housing prices. Rents in those places reflect incomes, just like elsewhere, and both have had historically enormous price bubbles. In fact, Houston home prices increased the exact same 65% that Sydney prices did from 2010 to 2020.

Density and supply are different concepts

A major confusion in the housing supply and zoning debate is that density, or dwellings per area of land, is assumed to be equivalent to supply, or new dwellings per period of time. This is wrong.

Developers choose the housing density at a site to maximise the site's residual land value. They also choose the rate at which they sell, developing to meet market demand in a "build to order" type of approach. This rate is known as the absorption rate. They also choose this rate of sales, and hence their rate of supply, to maximise the site's residual land value.

Many people seem to assume a contradictory idea that housing developers choose the density that maximises their land value but a rate of sales that minimises their land value.

I don't.

I've outlined how the optimal density and rate of sales work together in my paper entitled A Housing Supply Absorption Rate Equation. I take the logic of optimal density but include time in the model (yes, time is usually absent from models of new housing supply) to show how the two decisions relate. Here's a free version of the paper. Here's the published version. Notably, the main result is that the optimal rate of supply is independent of the density of dwellings. If it is optimal to make five sales per month when you are building 100 dwellings on a site, it is also optimal to sell five per month are building 1,000 dwellings on a site.

Rules on density do determine the location of different types of new dwellings. But the overall market rate of supply is determined by demand. There is no independent supply curve.

Undeveloped land is an asset

Undeveloped and zoned land is an asset that earns a return via capital growth. Owners of undeveloped land do not have to develop to earn an economic return. They manage ownership of these sites like any other capital asset that sits on their balance sheet.

The image below is from the annual report of one of Australia's largest housing developers. They own sites that can produce 56,000 apartments and 47,000 detached housing lots. But they aim only to produce 4,000-6,000 per year because that's what they expect the market will absorb.

I have a paper showing how undeveloped land is managed as an asset by housing developers rather than treated as inventory.

In fact, flexible zoning makes the value of undeveloped land grow faster before it is developed, incentivising development delay. This has been known since the 1980s when Sheridan Titman published a real options model of housing in a little journal called the American Economic Review. Titman's model relies on the idea that development timing choice will be delayed if density can be adjusted. If the optimal density increases with price, then sites with density limits will be developed first because the return to delay is lower. In density-constrained areas, the payoff to delay comes from higher prices, but in density-unconstrained areas, the payoff to delay includes both higher prices and higher density. A higher payoff to delay means a longer delay.

He writes

It is shown that the initiation of height restrictions, perhaps for the purpose of limiting growth in an area, may lead to an increase in building activity in the area because of the consequent decrease in uncertainty regarding the optimal height of the buildings, and thus has the immediate affect of increase in the number of building units in an area.

Vacant housing is also an asset—a more liquid but lower-return version of an occupied home. We can look to China for a good example of vacant housing stored as a balance sheet asset. Over 22% of dwellings there are vacant and housing supply has been astronomically high for decades, yet prices are still extremely high. Those high prices are due to the asset portfolio decisions of the Chinese people, which has compressed gross rental yields down to about 1.6%. Rents, as they do everywhere, reflect household incomes.

I recommend this video on Chinese housing.

This is why I ask https://t.co/VY7C11iFbb pic.twitter.com/vHrBn38Sr8
— Cameron Murray (@DrCameronMurray) April 3, 2021

A problem with the standard economic approach to housing is that by disregarding the time dimension, the picture of the housing stock and its geographical distribution leaves no room for undeveloped land. All land is always developed to its highest and best use, and the only way the housing stock changes is via a complete demolition and rebuilding of the city at the new optimum. It is a model of the optimal density (economic frontier) not the actual stock or rate of supply of housing.

The political economy

The political economy implied by anti-zoning advocates implies that well-connected property owners and developers are the weak ones, whereas the un-resourced Grandma who complains about development is the politically powerful one. Maybe that is true in some places. Not in Australia.

I did a study on rezoning and found that politically connected landowners are very likely to get their land rezoned and capture millions in windfall gains. Even our Prime Minister is a former property lobbyist. In these circumstances, are we really pretending that developers cannot build housing because of political barriers?

People also argue that when one site gets rezoned, the effect is mostly to increase the value of their land. But if a whole city got rezoned, then the value of all land decreases. Developers are playing a risky game by lobbying for city-wide rezoning when they actually want only their site rezoned. It is puzzling then that development lobby groups that call for large scale rezoning are so powerful. They should not exist in a world where large scale rezoning decreases land values, because no individual developer would be incentivised to support that collective lobbying effort.

If a whole city adopted a no-zoning rule, with no restriction on the density of housing or uses, what would happen? There would be quite a few sales as the asset market adjusted. Some landowners would sell up, others would buy in. Development in new areas where it was previously not allowed would happen. But after a short adjustment period, there would not be a noticeable change in the rate of new housing being built.

Auckland, New Zealand, a city of around 1.5 million people (about 600,000 dwellings) adopted a new plan that increased zoned capacity for dwellings by one million. There was no effect on the rate of supply. Can you spot when this happened in the below chart?

My view

Zoning is a useful tool for ensuring that different types of land uses happen in different areas. That's what it does. Just like lane markings on the road regulate where vehicles can go if they travel in different directions, zoning regulates where different types of stationary objects can go.

Zoning is not a good tool for slowing down, or speeding up, the rate of development. It is private landowners who make decisions about when and how quickly to develop.

If we want to build faster than the market absorption rate, we need a non-market housing supplier to do that. It is simply not optimal—either individually or jointly—for private landowners to sell new dwellings faster.

In fact, the recent low-interest-rate environment has made it optimal for private landowners to develop slower than otherwise. The logic is that developing housing is swapping a land asset for a cash asset. Since cash has such a low relative return, landowners are less in a hurry to do that. Higher interest rates would increase the equilibrium market absorption rate, but only after a short-term downwards price adjustment that will reduce the rate of new housing supply.

Lastly, I am suspicious of a political movement (e.g. YIMBYs) that argues that the market is not supplying enough housing but does not suggest any public intervention to build more housing. All the post-war success of boosting homeownership and housing supply was the result of heavy-handed government involvement in the housing market—rent controls, public finance of new construction, public land subdivisions, public housing, and more. All the problems we now face in a fully private housing market existed for centuries prior to the invention of zoning.

As I like to say, the private property system is the original exclusionary zoning. All the problems I have seen blamed on zoning are merely problems of the private property system and will only be resolved by providing access to land and housing through non-market means.

I would like to know what the people arguing for zoning reform as the secret to cheap housing and high homeownership think about how we historically achieved these outcomes?

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— Cameron Murray (@DrCameronMurray) March 17, 2021

Making sense of property as a monopoly

noreply@blogger.com (Cameron Murray) — Wed, 31 Mar 2021 03:11:00 +0000

Let us start by assuming that the property system is competitive and see how far that gets us in making sense of property pricing. After all, there are many different owners of different locations. That seems like what the textbooks describe.

The competitive market of economic theory has a few quirks. At the firm level, the demand curve is flat. Varying your own supply has no price effect. Yet, at the market level, varying supply does have a price effect. The problem of adding up a bunch of zero effects from firm quantity variation to a positive effect at the market level is an issue. It is resolved by assuming free entry at the market price; if a firm decreases its output while all others retain the same output, a new firm will enter the market and sell exactly that amount necessary to get back to the market equilibrium.

Neat, huh?

So let’s get back to it. We have a bunch of property-owning firms that can redevelop their space into housing. Each property owner sees a flat demand curve at the market price (because of our neat assumption) and has a cost curve that looks like...

Well, what does it look like exactly?

In strictly economic terms, the only input to the property right over a location is the existence of a property system. There are no input costs. To develop housing there are of course costs involved, such as fees, construction, and selling costs. But you can net these costs out of both demand and supply to look at the market for “empty” locations, or property rights to locations. After all, new housing supply is merely the subdivision of space—the subdivision of property rights into smaller pieces. The demand curve is still downward-sloping for that property rights market, but the supply curve must sit at zero.

Here we hit our first problem. If we assume perfect competition, we can only have land (location) prices of zero.

This “zero cost of location” view is what Ed Glaeser argues is the right way to think about housing.

…housing is expensive because of artificial limits on construction created by the regulation of new housing. It argues that there is plenty of land in high-cost areas, and in principle, new construction might be able to push the cost of houses down to physical construction costs.

In other words, land prices should be zero everywhere. Any deviation from this is due to regulatory intrusions in the market. Indeed, this implies that the very existence of a land market with trades at non-zero prices indicates it is not competitive. This is a bizarre conclusion in my view.

Maybe we will have more luck making sense of the property system by assuming it is a monopoly despite the many different owners. This has some intuitive appeal. First, you can’t choose to have your locations supplied by a competing property titles system. You can’t run more than one property system in parallel. Can you imagine the conflicts over who owns what space with multiple property systems? Second, the ownership of monopolies is often carved up (subdivided) and owned by many different people who each own constituent parts. Though we usually call these company shares or stocks.

So what then of the economic theory of monopoly?

As a starting point, a monopoly model avoids the assumption of free entry as the reason individual firms cannot observe their own-supply effect on price. This matches the reality of the private property system as it does not allow free entry. You can only compete in the property market by first buying property from the property market. This seems sensible.

The property market for any use, like housing, therefore looks this at a point in time.

Since costs are all sunk, we can simplify a bit by ignoring the stock of existing housing and look forward in time only. Think about redrawing the axes with the origin at the equilibrium current price and stock.

A change in the housing stock is the supply of new housing. The question of interest is how the stock of housing evolves over time in a property monopoly to determine an equilibrium rate of new supply?

In this model, if demand stays fixed and existing housing does not depreciate, then no new housing is built.

As demand shifts, new supply is added at a rate that maximises the revenue gain from selling those new properties rather than keeping them undeveloped in your balance sheet. It is the same monopoly maximisation principle applied at the margin. In other words, you sell new housing lots at a rate that maximises the present value of that flow of sales.

This logic is shown below. From the t=0 equilibrium, demand shift upwards. The green line shows the marginal revenue from the new supply (i.e. the change in the housing stock, Q, over that period). The new equilibrium is where the revenue from that flow of new property put to housing uses is maximised (i.e. where marginal revenue from that flow is zero).

This equates to a rate of supply that I explain in my absorption rate theory of housing supply (assuming a zero interest rate to simplify the inter-temporal trade-off).

The steeper (more price sensitive) the demand, the less supply responds to the same vertical demand shift. That’s because each property owner is sensitive to their bigger own-supply effect on the market price. Thin markets mean less supply.

Under this monopoly logic, the supply curve for property is not an independently-determined cost curve, but a derived curve based on the slope of the market demand curve.

But how do you get to the monopoly outcome? Is a conspiracy needed?

Not at all. All that is needed is trial and error. Remember, unlike the competitive market assumption of free entry, in the monopoly model, changes in firm output affect market output. If firms start near the competitive rate of supply per period in the face of a sloping (and rising) market demand curve, they will quickly learn to get to the monopoly rate of supply independently.

All that is needed is a learning rule of “win-stay, lose-shift”. This rule says that if the increasing the rate of supply last period increased your marginal revenue, then increase next period, otherwise decrease the rate of supply. If decreasing the rate of supply last period increased your marginal revenue, continue to decrease, otherwise increase.

When I simulate this learning rule with three firms, they quickly converge to the monopoly rate of supply, and hence the monopoly price. This convergence will occur even with 1,000 firms in the market. Property markets have been around for a while now. It seems likely that the current set of property owners has learnt this maximising equilibrium.

It seems logical to conclude that the monopoly model of property makes more sense than a competitive model. Indeed, monopoly was the traditional economic way of understanding property markets. In terms of understanding housing markets and effective policies to reduce prices, I think the following points are key.

That the property system is a monopoly shows that the rate of new housing development is mostly a product of demand. Property owners don’t want to build faster. This is because supply is not independent of demand. Supply is merely a reflection of demand.
Rezoning and changing planning rules might change where development happens (as it should—they are location regulations after all) but probably won’t change the rate of new supply. The rate is the one the market wants. Developers don’t want to flood the housing market.
Making housing cheaper should be understood the same way we understand other monopolies. We regulate prices. We create public options. Pretending that we can somehow capitalise on competitive market forces that don’t exist won’t change things.