## Monday, December 30, 2019

### The puzzle of high home prices and vacant homes

One pattern that stands out in the property market is that although homes prices are at all-time highs, so too is the proportion of vacant dwellings. This is a puzzle. How can it be the case that when housing is in high demand it is also rational to keep more housing vacant?

Australian data shows that the number of residential dwellings has grown faster than the number of households for the past decade, indicating a substantial rise in the proportion of empty homes. This phenomenon has been a broad one, experienced in cities such as SydneyVancouver, and Toronto. Here are some of my previous thoughts on the topic.

The resolution to this puzzle is as follows. Housing is an asset, and in asset markets there is a trade-off between liquidity and returns. A vacant home is a more liquid asset than an occupied home. Timing a sale is easier, the sale is faster, and it is likely to result in a higher price when vacant. When capital gains are a large proportion of the total return, and capturing this return requires timing the market because of price variability, the value to liquidity from vacancy can be high.

In short, when yields are low and prices high and variable, the benefits to vacancy are high.

Here’s an example. In Scenarios A and B the total asset return to housing is 10%. But in Scenario A the price is high and yields are low. Here, leaving the property vacant forgoes only a quarter of the total return from the asset. If prices are variable in this Scenario, then timing a sale becomes an important factor for earning the capital gains. Hence, the liquidity from vacancy has a large benefit.

 Return Cap. gains Rent Scenario A 10% 7.5% 2.5% Scenario B 10% 2.5% 7.5%

In Scenario B the price is low, as the rental yield is 7.5% of the price. Capital gains are also low at 2.5%. In this low price, low capital gain, scenario, keeping the property vacant requires giving up three-quarters of the total return. The benefits from doing so are limited since capital gains are low, and hence less variable.

So there is an economic logic behind the puzzle of high prices and high vacancy, and it stems from the fact that housing is an asset as well as a consumption good. But there is also a criminal logic. Much of the vacant housing in Australia (and probably Canada and a few other locations) is due to money laundering. There are no checks on the source of finance for home purchases and no checks on who the ultimate beneficiaries are in the ownership structure. You can buy a home in a trust or company name, and the identity of the trustees and the company owners need not be disclosed. If you then also do not earn rental income, the corporate structure is protected from scrutiny by tax authorities. Housing is a great way to hide ill-gotten gains.

The criminal logic and economic logic are closely aligned. When most of the return to housing comes from capital gains it makes housing a more attractive place to hide money as three-quarters of the total return can still be had. But when most of the return comes from rent it is much less attractive — and it may require corporate disclosure due to local incomes warranting taxation.

Finally, some new data
On another note, new data from the Australian Bureau of Statistics came out recently, filling one of the holes in the housing data landscape — the share of lending to investors that is directed towards purchasing or building new homes.

This data helps to answer questions about the economic value of new credit in the economy, the real economic effects of monetary policy, and more. In standard economic thinking, low interest rates make borrowing to invest in new buildings and equipment more viable. Because standard economic models do not include secondary markets, the effect on the trade of existing assets is mostly ignored. Yet we can see that the majority of home purchases are simply trades of existing housing, and hence are a key mechanism through which low interest rates mostly cause higher prices without having much effect on new construction.
As you can see in those few months of investor data,  investor lending is not substantially more biased toward new housing than lending for owner-occupiers. For investors, 24% of loans have been for new housing in the past few months, just as 24% of loans to owner-occupiers have been.

The main difference seems to be that the typical existing home bought by owner-occupiers is more expensive than the typical new home, whereas for investors the mean value of lending to both is the same.

## Monday, September 16, 2019

### Rent control is totally normal price-cap regulation

Bernie Sanders has smashed the Overton window. Rent control is going global.

Unfortunately, this means that the economics 101 brigade has come out in force to smugly Vox-splain their incorrect model of rent control and housing market dynamics.
Regulating housing rents makes economic sense because homes are attached to land monopolies. Monopolies are inefficient, and regulations can improve outcomes. The two classic regulations are 1) a tax on monopoly super-profits, which is common for mineral and energy resources, and 2) a price cap, which is usually applied to network infrastructure, like rail, electricity, and water. If price caps sound to you a bit like rent control, then you would be spot on. They are rent control.

Rent control is not weird or unusual for regulating monopolies. The weird thing is that land is no longer considered a form of monopoly.

Let me explain how these two classic regulations would work in housing markets to socialise monopoly profits from housing locations.

A super-profits tax would work like this. When a new home is constructed, the owner would be able to seek the market rent. That first year’s market rent would become the regulated price that would attach to that home in a rental database. The home would still be allocated in the rental market using open market prices. But any gap between the market price and the regulated price would be 100% taxed. This is shown in the figure below.

If the market price fell below the regulated price for some reason, that loss would accumulate as a credit against future tax obligations when the market price increased again.

With a super-profits tax system housing resources, including new construction, are always allocated by market prices.

Since the financial crisis, rents have increased by roughly 25% in the United States. A quick guess-timate suggests that around a trillion dollars of rents are paid in the US each year. Had such a tax been implemented ten years ago it would now raise about $250 billion a year with no efficiency loss. In Australia, total housing rents have increased from around$30 billion to $45 billion in that period, meaning a housing super-profits tax would now raise around$10 billion per year (after adjusting for the increased housing stock).

The second way to regulate the land monopoly in the housing market is with price caps (rent controls). Here, the sitting tenant is protected from price increases that are not the result of additional housing investment or renovation but arise due to the favourable location-monopoly of the owner.

As before, market prices match tenants to housing and provide incentives for new construction. However, a sitting tenant is protected from price increases that arise from the location-monopoly. This only works if their tenure is secure, and they cannot be evicted as a way to change the rental price back to the market price.

The image below shows how the gap between market price and rent-controlled prices is a transfer to sitting tenants. If market prices fall below the regulated price, the tenant can have the option to renegotiate or move to pay the lower market price. Again letting markets decide resource allocations. It is only in periods of rapid price growth that sitting tenants are protected.

On balance, this type of regulation transfers some monopoly super-profits to tenants in the short-term but gives them back to owners as tenants relocate and homes are again allocated by market prices.

Either system of regulations will socialise some of the monopoly rents in housing markets. In fact, it is widely acknowledged that a reduction in volatility of returns can accelerate new housing investment. Recent studies also show that owners of older housing choose to accelerate redevelopment into more dense housing if their rents are regulated.

Both regulations are common in other monopolistic sectors of the economy. The main issue is that these regulations will transfer billions of dollars of value away from landlords, and landlords won’t like it. And the economic 101 brigade will always find a way to argue that policies to help the poor are bad for them.

## Sunday, September 8, 2019

### Housing subsidy and UBI confusion

When the Australia government introduced a cash grant for first home buyers, the aggregate effect was to increase home prices by roughly the amount of the grant, quickly negating its effect on affordability.

This observation has led many people to mistakenly believe that giving cash grants in any form will pass through one-to-one into higher home prices (or rents). In discussions of all types of welfare—from UBI, to traditional welfare payments—this error comes up.

The error comes about because people fail to see that when given a choice, people spread their extra buying power across all the different types of goods they consume. An income subsidy is not the same as a subsidy for a particular type of expenditure.

Economists have been studying the way spending patterns vary with income for over 150 years. Ernst Engel noticed in 1857 that as incomes rise, households spend a lower proportion of their income on necessities like food. This observation became known as Engel’s Law, and the income-spending relationships for different goods became known as Engel Curves.

Housing, like food, is a necessity. As such, the share of income spent on housing usually falls as incomes grow. The Australian data shows that even for private renters—where one would expect competition from higher-income renters to bid up housing rents—the share of income spent on rent falls from nearly 50% of gross income for the lowest income quintile households to just 13% for the highest-income households.

This data might seem to imply that it is possible for up to 50% of a cash welfare payment to “pass through” to landlords for low-income households. But remember, this is not the marginal amount that would come out of extra income. Because the share of spending on housing falls as income rises, the spending on housing out of the extra income must be far lower than the average. In fact, across income quintiles in Australia, the marginal additional spending on housing per dollar of additional income sits tightly in the 5-7c range. It may be possible that long-run adjustments mean that more than this marginal amount is spent on housing out of extra income, but it will always be less than the average amount.

The story is rather different, however, if welfare payments are tied to a particular type of spending. This even more important in the case of housing, where the total stock changes extremely slowly and where landowners have monopolistic incentives to prefer price gains over investing in additional supply.

In this example, as long as the smaller lots exceed $262,500 each, the total return to land exceeds the home price growth of six lots. If we take the case where the price of the eight smaller lots is$280,000 each, then the return from price growth alone for the previously optimal six lots is $300,000, and the additional return from the option premium is$140,000 (280,000 x 8 — 350,000 x 6) to give a total return from capital gains to this undeveloped land of $440,000. Here ω=0.47. In the notation, the return to land is RL = Ṗ + ωṖ + rL. ### The housing supply problem We can now express the gains from supplying housing in terms of the effect of on returns from shifting land and cash into housing, or RH− (RL + RC). After substituting our returns for each component we get “return profits”, π, of π = Ṗ + rH −􏰀Ṗ + ωṖ + rL +ci􏰁 = rH −􏰀 ωṖ + rL + ci􏰁. Therefore, supplying new homes at any point in time increases “return profits” if rH > ωṖ + rL + ci. This is a more difficult hurdle than the one under SPT, where price growth did not enter the housing supply problem at all. But this also tells us that high home price growth reduces the willingness of landowners to convert their land into new housing. Not building now is valuable because it keeps the option open to build a more dense subdivision in the future (either a vertical subdivision in the form of apartments or horizontal in the form of housing lots). If you feel the urge to imagine a supply curve of sorts, then put the rate of price growth on the y-axis and the supply curve (willingness to supply) is downward sloping. Many property researchers are now adopting this type of model. For example, in the model of Alvin Murphy shows that “rising prices make building today more attractive, but also make waiting more attractive, thus reducing the responsiveness to price.” But if rising prices cause less willingness to supply, why are home price booms associated with massive construction booms? The answer to this is quite simple. Not only are landowners and potential housing developers return-maximising, so are all agents in the economy. A little house price growth will attract everyone in the economy to shift away from cash and into housing, new or existing, as this increases their “return profit”. Since the current owners of the stock of housing have the same incentives to buy and not sell, new housing becomes a the main available investment option for all those willing buyers. But there will always appear to be a shortage of new (or existing) housing for sale. The weight of money that shifts into housing markets both increases home prices and the volume of new home sales. but also decreases the willingness of landowners to sell enough new or existing housing to significantly reduce this price growth. This BSDT also shows the effect of binding density constraints, which fix ω at zero. This increases the willingness of landowners to supply homes now rather than delay. Instead of planning constraints reducing the total supply of housing as assumed in SPT, they can instead increase the rate of new housing supply. In the economic literature housing supply has been a mystery for a long time because of the attachment to a model that is conceptually misapplied. Putting returns and balance sheets front and centre is going to be a far more productive way to improve our understanding of housing supply in the future. ## Monday, April 22, 2019 ### Three Economic Myths about Ageing: Participation, Immigration and Infrastructure Leith van Onselen and I were commissioned by the Sustainable Australia Party’s Victorian branch to examine the causes and implications of population ageing in Australia, and whether maintaining a high immigration program is a worthwhile policy response. Below is a summary of our report: ## Overview Population ageing due to longevity is one of the greatest successes of the modern era. However, it is widely thought to dramatically reduce workforce participation and overall output resulting in significant economic costs. This widely held view is wrong. Ageing countries have higher economic growth and the improved health and longevity of older people increases their economic contribution. High immigration is also thought to combat population ageing and be a remedy for these non-existent costs of ageing. This is wrong. Low immigration can affect the age structure by helping to stabilise the population, but high immigration has almost no long-run effect besides increasing the total population level. This creates bigger problems in the future. It is also widely thought that simply investing in infrastructure will accommodate high immigration and population growth at little cost. This too is wrong. Diseconomies of scale are a feature of rapid infrastructure expansion due to (1) the need to retrofit built-up cities, (2) the dilution of irreplaceable natural resources, and (3) the scale of investment relative to the stock of infrastructure. This ageing-immigration-infrastructure story is wrong on all three of its major points. Population ageing should be seen as the successful result of improvements in medical and health practices that have improved longevity and fostered a long-lived and economically productive society. ## Key Research Findings • Population ageing is a successful result of efforts to improve longevity. • Countries with older populations maintain high workforce participation, are more productive, and grow faster economically. • Ageing does not lower workforce participation in general. Since 2012 there have been more full-time workers aged over 65 than under 20. • Low net immigration of between 50-80,000 permanent migrants per year can alter the age structure over the long-term by stabilising the population. • Low net immigration increases GDP per capita and wage growth. • High net immigration above this 50-80,000 amount has almost no additional effect on changing the age structure and simply increases the total population. • Most of the increase in permanent migration since the early 2000s has been through the skilled migration program. • This program primarily benefits the migrants themselves and increases wage competition for other workers. • A focus on skilled immigration fosters a “brain drain” from developing countries, reducing human welfare. • There is a real economic cost to high population growth due to the diseconomies of scale inherent in rapid infrastructure expansion. • There is a real cost from environmental degradation due to development to accommodate much higher populations. • The high costs of population growth are often ignored, as immigration policy is a federal matter, while infrastructure provision is predominantly a state and council matter. • Population growth in general dilutes ownership of our environmental endowments, mineral wealth, fisheries, wildlife, and national parks. • The political capital and resource devoted to managing high growth have an opportunity cost in terms of solving other social problems such as homelessness, indigenous disadvantage, mental health, and other social services. ## Policy Recommendations: • Reframe ageing as the economic success story that it is. • Reframe immigration as an environmental and ethical choice, not an economic necessity. • Lower overall net immigration to the 50-80,000 range by mainly targeting skilled visas. This can largely be achieved by increasing the minimum salary for skilled migrants to 150% of the average full-time salary, or$129,900. This desirable net immigration range can be achieved while having a slightly higher permanent intake of around 80-90,000 per year, as permanent departures will reduce the net effect while still maintaining the optimal target range.
• Adopt systems for infrastructure planning and provision that clarify the expected cost of new public and essential services, and ensure upgrades keep pace with city growth for the benefit of existing and new residents.

## Sunday, March 24, 2019

### High home prices jack up rents

In traditional economic thinking, the interaction an independently determined supply and demand for rental housing set the market rental price.

But that simplification ignores an important part of the story—where does demand, or the willingness to pay for rent, come from?

It might help to start thinking about a different product to clarify my point. Consider that you need some fruit and the prices per kilogram are as follows:
Apples - $5 Pears -$4
Bananas - $3 The demand for apples will be quite low since the close substitute goods have a lower price. Now consider this situation: Apples -$5
Pears - $7 Bananas -$6

What does the demand for apples look like now? The demand for apples will be higher since the price of substitutes has risen.

This is basic microeconomics, right? The demand for a good rises if the price of substitute goods rise, and vice-versa. High priced substitutes mean that each buyer will have a higher willingness to pay.

So now let’s talk about housing. There are roughly three goods in this market—buying, private renting, and social/public renting. If the price of one of these substitutes rises (or their accessibility diminishes due to queueing) so should the demand for the others.

What this means is that even though rental prices are a better indicator of the supply and demand interaction in the housing market than home prices, the demand curve that determines the rental price itself shifts with home prices. The demand curve in the rental market is not independent of the price (or cost) of home-buying.

We can see a pattern in some markets, like the chart of Seattle below, where rising prices led to rising rents, then falling prices led to falling rents.

While there are many other important interactions in housing markets, the substitute goods price effect is going to be part of the story.

To dampen housing demand (and therefore rental price) it pays to create a housing system with many substitute ways to access secure housing. A huge investment in social (below-market-priced) housing, for example, will provide a substitute option for many private renters.

The effect of this investment will be larger than the number of people who take up the option. Many households who don’t end up in social housing will keep their bids for private rentals below the price of the social housing option, reducing prices in the private rental market as well.

I don't know how big this effect is. But even a 5% effect on the willingness to pay for private rental housing still equates to \$2.5 billion in annual total rents paid by the 30% of households who rent.

In general, therefore, the more housing alternatives that exist, the more stable and low-priced the total housing system should be. Any substitution effect on demand from price changes in one housing market will have a lower effect on each other market.

## Monday, February 4, 2019

### Using economics to justify our fears: The case of ageing and holidays

One of the great myths in economics is that there are substantial negative impacts from population ageing. But there is no economic basis for this fear. In fact, it is a good example of how economic reasoning is often used to provide a back-story for our instinct and emotion, rather than as a basis upon which to form a considered view.

For example, in the economic story we tell to justify our fear of ageing we use outdated assumptions about work patterns (over 15 years old is in the workforce, over 65 is not) and often ignore the counterbalancing effect of fewer young children needing care and schooling.

But when it comes to other discussions about policy, such as more public holidays, a shorter working week, or robots taking jobs, we pick a different economic story to make sense of our insecurities about losing our job.

In reality, the economics behind these two views are contradictory, as I will now show.

When it comes to ageing the economic story involves the calamity that might arise if the ratio of working to non-working people in the economy falls (the age dependency ratio). But imagine shifting your focus from this ratio to another ratio, which is the number of working to non-working days in the economy each year (the workday dependency ratio). Both are equivalent ways to conceptually carve up the total work done in the economy—either by people or by time— since Yearly Output = Working People (WP) x Working Days (WD).

In the absence of changing work norms, ageing may reduce output by reducing the first term in this equation as a share of total people. But so too will any policy change that reduces someone's working years of life, such as introducing additional years of schooling.

The number of working days (or even hours) per year is a function of many things, like norms about overtime, limits on weekly hours, weekends, statutory holidays, and more. Changes in these variables can also reduce output if they reduce yearly work time.

According to the Australian Bureau of Statistics, expected ageing in Australia over the next 15 years is likely to increase the age dependency ratio by 18%. This is the ratio that justifies fears about population ageing.

But where is the fear about shorter working years? We can, for example, look at what would happen if Australia had the same number of annual vacation days at the UK of 37 compared the current 28. Some sources say that leading the charge of fewer work days are countries such as Austria with 38 vacation days, and out in the lead are Brazil and Sweden with 41 days!

If Australia merely adopted the yearly workdays of the UK then we would increase the workday dependency ratio by 11%. If we went crazy and had six-weeks annual leave and hit the world-leading 41 days paid annual leave, then our workday dependency ratio would increase 16%, or nearly the same as the increase in the dependency ratio that is so feared when it comes to ageing.

If a higher age dependency ratio is a major economic problem, then so too is a higher workday dependency ratio. One cannot be an economic problem if the other is not. I'm not the first to say this. Dean Baker has said it all before.

This is just one example to show how our policy debates are not shaped by raw economic reasoning, but are instead shaped emotions, instinct, and more often than not, by interest groups. Economic reasoning is then used to justify opinions already held, and the economic reasoning used to justify one view need not be consistent with the reasoning used to justify any others. That's just the way human minds work.