In The Great Housing Hijack, Cameron Murray sets up a framework with five equilibria (asset price, rental, spatial, density, and absorption rate), which he applies to various policy issues.

I found a couple of insightful points. For example, the price-to-income ratio is a flawed measure of housing (ownership) affordability, because we really care about the cost of housing services (i.e., mortgage payments), which is a function of the interest rate. Hence, any measure of affordability needs to adjust for the interest rate. Moreover, since property taxes are priced into housing prices, we also need to adjust for different tax rates across cities. In the chapter on vacant homes, Murray distinguishes between vacant and unoccupied homes, and gives a useful analogy between vacant rental homes and unemployed workers.

Murray often makes “cui bono?” style arguments, asking about someone’s self-interest in making an argument, rather than engaging with the argument in good faith. For example, Murray points out that landowners and developers benefit from high prices, yet support upzoning.¹ But of course, many property owners are strenously opposed to new housing, giving up financial returns to protect their neighborhood character. Moreover, interest groups are diverse. A new developer entering the market wants lower prices in order to outcompete incumbents. Or take small-scale developers, who would benefit from the legalization of six-storey single-stair apartments, while big developers are happier with a discretionary system where being friends with the developer of planning is a job requirement.

In another case, Murray discusses at length how the UCLA Lewis Center is funded by a developer and landlord:

There is no way that a property owner with a balance sheet in the billions has a financial interest in policies that bring down the value of property assets […] The Lewis Group is also a landlord with 11,000 units, so it won’t support policies that reduce rents to benefit tenants. Like property lobbyists in Australia, research from UCLA’s Lewis Center is focused on deregulating town planning […] its research is always beneficial for its property-owner funders. (p.97)

This mudslinging is beneath serious researchers. In my experience, the Lewis Center does solid work, and the Housing Voice podcast is great.

On a related note, Murray points out that political incentives are very strongly in favor of incumbent homeowners, who make up a majority of voters. But I’m puzzled by this framing:

A policy that reduced home prices by 30 per cent would wipe $3 trillion of value from household balance sheets, hitting hardest the households with the highest income and the most political influence. (p.84)

In other words, if some imaginary policy could reduce housing costs by 30%, it would still be political suicide. But why are we talking about imaginary policies? Why don’t we talk about the actual policies that are on the table? There is no policy that will uniformly reduce property values. For instance, upzoning will lower housing prices but raise land values, leading to a nuanced set of winners and losers.

Murray attacks YIMBYs as self-contradictory for supporting more homes and more immigration.² But there is a tension only if you take a restrictive view of who matters (incumbent residents, not newcomers). By Murray’s logic, we can boost the number of homes per capita by deporting half of the population.

Land and housing prices

Murray claims that housing prices determine land prices:

the price of [vacant land] is the residual of dwelling value, minus the cost of developing that dwelling and a margin for the perceived risk of that arbitrage. […] The causality runs from the price of dwellings to the price of land via the cost of development. (p.48)

This picture is incomplete. In general equilibrium, land and housing prices are jointly determined; the causality runs in both directions. For example, what is the effect of doubling a city’s residential land area (upzoning from agricultural to residential)? Intuitively, this makes land more abundant, and hence cheaper for developers; competition between developers then reduces housing prices. On the residual view, this intuition is wrong. Instead, we have to say that more abundant land leads to more housing, and lower housing prices lead to lower residual land values. But in fact both channels are true; single-direction causal explanations do not work in general equilibrium models.

Murray gives a numerical example:

the price of land is $300,000 per developable lot, and the cost of developing a home is $300,000, but the price of a home is $500,000. No one will buy the land at the $300,000 price. […] The price of the vacant property must adjust back to $200,000 so that the cost of buying an existing home, or building a new one, is the same. (p.48)

But this does not necessarily follow. It could also be the case that land prices are fixed and housing prices have to adjust upwards to $600k (= 300k + 300k); that is, it’s the housing prices that are out of equilibrium. In general equilibrium, both housing and land prices will adjust, but Murray assumes a partial equilibrium view (holding housing prices fixed).

Spatial equilibrium and the location of housing

Murray takes a simplistic view of spatial equilibrium, where the location of new housing doesn’t matter, because prices will adjust as people sort geographically:

We must apparently build ‘where people want to live’. But spatial equilibrium tells us that people will live anywhere, because all locations are substitutes at the right price. Sure, higher value areas have lower travel times and better amenity; the value of this location benefit is exactly equal to the additional rent compared to other areas. (p.65)

This paragraph is very puzzling. A spatial model with congestion and agglomeration externalities delivers an unambiguous conclusion: we should build homes near jobs and amenities. Murray seems to be attached to the vanilla model without externalities.

Murray claims that planners and zoning affect the location, but not the rate, of new housing supply. This may be true: zoning restrictions in Vancouver have certainly redirected demand and caused massive growth in the suburbs (Surrey will soon overtake Vancouver in population). But there are obvious violations. If zoning causes people to double-up and form larger households to stay in the city, instead of moving to the suburbs and building a new home, then total supply is in fact lower.

I wanted to see more comparative analysis, for example using a two-city model to show how high and low levels of regulation affect the rate of new supply. Murray tends to make over-time comparisons instead of comparing against a counterfactual.

Murray claims that “one part of a region [having] no housing development doesn’t lead to higher rents in aggregate” (p.141). Clearly something has gone wrong here. By this logic, all cities could impose 100%-binding zoning constraints and there would be no effect on aggregate prices. But Murray does not present a model that could generate this result.

The rate of new supply

Murray skips over a static model and instead uses a dynamic model, where we have a rate of new supply over time (‘absorption rate’). Murray thinks it is an insightful point that developers will limit how fast they build new homes. But this seems like a mundane response to uncertainty and production lags; developers will reduce risk through a diversified portfolio of projects. And note that this behavior is encouraged by a discretionary planning regime; if developers could build apartments under apartment zoning, instead of needing permission for every project, they would have less need to smooth out risk.

Murray says:

Housing analysts who argue that we need to let the market rip to increase the number of homes always overlook the absorption rate equilibrium. Property owners will not flood the market with new homes just because the rules allow it. (p.72)

The key issue here is whether zoning is a binding constraint. If it is, then relaxing that constraint will reduce costs and increase supply. Murray seems to believe this argument: ‘developers already leave feasible sites undeveloped, so adding more feasible sites won’t make a difference’. But upzoning actually changes the feasibility threshold, by reducing land costs, which in turn increases the supply of housing (see here).

Other issues

Murray motivates his arguments using striking anecdotes, like a development of detached homes being rejected by city council for being too low density next to a proposed train station in the exurbs. This anecdote sets up the question: if lack of density is the cause of high rents, why aren’t developers building to the maximum allowed? I didn’t find this persuasive. Were there poison pills that made apartments infeasible (limits on height or floor space, setbacks, unfunded inclusionary zoning, etc.)? Meanwhile, there are plenty of examples of what the market will build when restrictions are removed. In general, I found myself wanting to see more data instead of anecdotes.

Murray repeats the common argument that developers won’t build if it causes rents to fall.³ But developers will build if costs fall; they require only that profits remain the same.

In the chapter on rent control, Murray claims that homeownership is like rent control for the homeowner, because housing costs are fixed.⁴ Variable-rate mortgages aside, this analogy is clearly inapt. (I’ve seen it argued that homeowner subsidies are analogous to rent control as a subsidy to renters; this is not Murray’s argument.)

Murray cites the Diamond et al. paper on rent control in San Francisco, but somehow claims that reducing the stock of rental housing is a “good outcome”. He neglects to mention the next sentence in the paper’s abstract: “the lost rental housing supply likely drove up market rents in the long run”.

Murray has a strange view of value capture, claiming that airspace is public property, and the public needs to be compensated when airspace is privatized by allowing landowners to build apartments.⁵ By this logic, isn’t it a giveaway to allow landowners to even build houses on their land? After all, that’s also taking airspace away from the public. The right approach here is simply optimal tax theory: we should tax inelastic factors, like land.

In Australia, Murray reports, the ratio of rent to disposable income was 20% in both 1993 and 2023. Murray claims that, since housing is a constant share of income as a nation gets richer, housing is a normal good. But he also notes that poorer households spend a larger share of income on rent, and richer households spend a smaller share. So for individuals, housing is a necessity, where the income elasticity of demand is less than 1; but for the nation, the income elasticity of demand is equal to 1, producing a constant budget share. What explains this?

Murray claims that the reason missing middle housing is rare, aside from regulations banning it, is that it is expensive to buy land with existing buildings. But then, why do we see detached houses being demolished and replaced with new detached houses, instead of townhomes or low-rise apartments? The answer is not the cost of demolition, but the fact that demand for detached houses is very high. In Vancouver, developers would rather build a detached house instead of a four-storey rental building. The four-storey would have been feasible a few decades ago, but enough mansion-buyers have moved in that now only a six-storey rental building can compete.

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