This week in research #125

Here's what caught my eye in research over the past week (which was clearly another quiet week):

• Sinclair et al. (open access) compile a dataset of monthly birth rates by maternal age and parity for the Australian state of Victoria over the period from 1983 to 2020, and apply a variety of different time series models to the data, finding that Australian family policy has mainly altered the timing of births rather than reversing the long-run fertility decline, and that the Australian 'Baby Bonus' led to only a short-lived impact, concentrated among second births

The Hamilton vs. Wellington population showdown

Some of my research was profiled on the front page of the Waikato Times today (paywalled):

Forget Wellington — Hamilton is on track to overtake the capital within 14 years.

New University of Waikato projections show the city’s population could climb to 242,716 by 2040, cementing its status as New Zealand’s fastest-growing city.

Hamilton’s population projection is under the “high variant” forecasts — the growth estimates council staff are recommending, and which the Government requires councils to use when planning their Long Term Plans.

If that is compared to Stats NZ's and the Wellington Regional Growth Framework estimates for Wellington for the same year, Hamilton's population will be larger by 2716 people.

Now, this Hamilton versus Wellington head-to-head population battle seems to be attractive to the media (see this post from 2019, talking about this 2019 Waikato Times article). However, they've got things wrong this time, for a couple of reasons.

First, they are comparing Hamilton City with Wellington City, which is a valid comparison of city council areas, but may not be the comparison many people have in mind. I'll come back to that point at the end of the post.

Second, and more importantly, you shouldn't compare a projection from one source, based on one set of assumptions, with a projection from a totally different source, based on a different set of assumptions. Especially when projections from the same source are available, using consistent assumptions. Otherwise, you are not comparing apples with apples.

So, let's make some consistent comparisons. Stats NZ's projections are available on Aotearoa Data Explorer, Stats NZ’s online data tool. Search for "subnational population projections", and then scroll down to "Subnational population projections, by age and sex, 2023(base)-2053". Stats NZ offers three variants (low, medium, and high) of 2023-base population projections. The difference between the variants is that low variant projections assume low fertility, high mortality, and low international migration, while high variant projections assume high fertility, low mortality, and high international migration (and the medium variant projection is, obviously, in-between the low and high). Here are the three variant Stats NZ projections for Wellington City and Hamilton City:

The bold lines are for Hamilton City. The dotted lines are for Wellington City. The low, medium, and high variants are coloured blue, green, and brown respectively. The key thing to notice is that the lines cross over. Where the lines of the same colour cross, that is the point in time when Hamilton catches up with Wellington under that projection variant. So, with Stats NZ's projections, Hamilton is projected to be larger than Wellington by 2038 under all three projections. If we do a linear interpolation (because Stats NZ only reports their projections for five-year intervals), then Hamilton is projected to be larger than Wellington by 2034 in the low and medium variant projections, and by 2035 in the high variant projections.

Turning to the University of Waikato (UoW) projections (which I produced), there are also three variants (low, medium, and high) that can be interpreted similarly to Stats NZ's projections. The methods and assumptions differ from those used by Stats NZ. These are the projections that Hamilton City Council uses in its planning (as do several other local councils). Here are the three variant UoW projections for Wellington City and Hamilton City:

In my projections, Hamilton is projected to be larger than Wellington by 2040 in the low variant projection, by 2048 in the medium variant projection, and by 2066 in the high variant projection (which is beyond the projection horizon for Stats NZ projections as they only project for 30 years).

Why the difference? The difference between the timing using Stats NZ projections and the timing using my projections is due to differences in assumptions and the underlying models. It would take a long post to unpack all the differences in detail. The differences between the low, medium, and high variants are easier to explain. Wellington has a head start - it was much larger in 2023 than Hamilton. However, Hamilton has both higher fertility and greater net migration than Wellington. That head start makes a bigger difference in the high variant projections than in the low variant projections, because the higher fertility and international migration in the high variant projections allow Wellington to maintain that lead for longer. In the low variant projections, Hamilton's higher fertility and net migration allow it to catch up much faster. In other words, because Wellington starts from a larger population base, assumptions that lift population growth across the whole country add more people to Wellington in absolute terms, delaying Hamilton's catchup, even though Hamilton’s underlying growth rate is higher.

What is interesting is that the differential effect between low-variant and high-variant projections doesn't seem to be anywhere near as prominent in the Stats NZ projections as it is in my (UoW) projections. In part that is because the uncertainty expressed in my projections (proxied by the difference between the low and high variant projections) is much higher than the projections by Stats NZ. I'm comfortable with that, given that international migration in particular is highly uncertain. So, we should expect a fairly high degree of uncertainty when we project future population.

One final thing to note is a point I made in my 2019 post on this topic. Wellington City is only one part of a larger urban area ('Greater Wellington') that also includes Porirua City, Upper Hutt City, and Lower Hutt City. There is no projection that has the Hamilton urban zone catching up in population to the broader Wellington urban zone any time soon. I suspect that many people would be flabbergasted by the suggestion that Hamilton might become larger than Wellington. Many of those people would be thinking about Greater Wellington, and they would be right.

So, Hamilton will eventually be New Zealand's number three city council area in terms of population. However, the celebrations could easily be put on hold by a council amalgamation process that the government has started, which could conceivably merge some Wellington councils together, putting their combined population out of reach of Hamilton for the foreseeable future.

[HT: The incomparable Emeritus Professor Jacques Poot]

Read more:

• Hamilton won't be our second largest city any time soon

Kansas City rent strike rebalances relative bargaining power towards tenants

Today in my ECONS101 class, I covered search models of the labour market. In these models, a matching between a worker and an employer creates a surplus, which is then shared between the worker and employer depending on their relative bargaining power. The greater the worker's relative bargaining power, the greater the share of the surplus the worker will claim, meaning that wages will be higher. The lesser the worker's relative bargaining power, the lesser the share of the surplus the worker will receive, meaning that wages will be lower.

Search models are not just useful for thinking about labour markets though. They can be used in any situation where two (or more) parties are matched together in a way that creates a surplus, which is then shared between them. A joint venture between firms is an example. So is a marriage. In both cases the parties match together, create a surplus, and then share that surplus based on their relative bargaining power. A further example exists in the market for rental housing. Landlords and tenants are matched together. That matching creates a surplus, which is shared between them. And relative bargaining power matters, as this Yahoo!News article from the end of last year (originally published in the Washington Post) demonstrates:

In the two years she has lived at Bowen Tower, Cynthia Barlow’s apartment has flooded, been plagued by mold and been infested with cockroaches. The building’s heat stopped working. When the elevators broke over the summer, emergency workers carried a sick neighbor down 10 flights of stairs.

Meanwhile, Barlow’s rent for the two-bedroom unit increased from $993 per month to $1,213.

Growing frustrated, she hung fliers in the elevators and hosted potlucks, persuading a majority of tenants in the 90-unit building to join the Bowen Tower Tenant Union and stop paying rent until conditions improved. So far, they’ve won a meeting with the landlord, and a judge has knocked thousands of dollars off the rent debt of one resident facing eviction.

“I got tired of being treated the way I was treated,” Barlow said.

The rent strike is part of a strategy that housing activists have started to replicate in midsize cities across the country.

When tenants organise themselves into a tenant union, then ceteris paribus (holding all else equal) that increases the tenants' relative bargaining power with the landlords. If the tenants were to all leave their apartments, then the landlord has to search for new tenants, which is costly. Now, an individual tenant could threaten to move out, but filling one apartment with a new tenant is relatively easy. When an entire block of tenants makes the same threat, the landlord is facing serious disruption. More importantly, a rent strike means that, instead of losing or negotiating with one tenant at a time, the landlord faces coordinated action including withholding rent, legal disputes, repair demands, and public pressure from many tenants at once.

The tenants' increased bargaining power (due to unionising) should result in lower rents and improved maintenance of the apartments. The way this worked in practice was that tenants, feeling more powerful with the backing of other tenants, stopped paying rent. However:

Barlow is scheduled for eviction court in January, and Bowen Tower management hasn’t renewed her lease.

There is only so far that tenants can push their greater relative bargaining power, particularly where alternative affordable housing is scarce and legal protections are weak. However, the Bowen Tower case also shows why collective action may matter. Ultimately, the tenants appear to have prevailed and won substantial concessions. This later article notes that the rent strike ended after four months, when the landlord promised repairs and lower rents, and after tenants had withheld nearly US$110,000 in rent. 

Tenant unionisation does not guarantee success, and the risks to tenants can be substantial. But it does mean that tenant unions can shift the bargaining outcome, and the share of the surplus, especially when they are able to sustain coordination long enough to make the landlord’s alternative more costly than negotiation.

[HT: New Zealand Herald]

Two papers show the bad, and some good, of rent control in San Francisco

I have been talking with my ECONS101 class this week about rent controls, which is a topic that I have blogged about many times before (see the links at the end of this post). Economists really dislike rent controls, sometimes in deliberately hyperbolic terms. In one prominent case, the Swedish economist Assar Lindbeck was quoted as saying:

“Rent control appears to be the most efficient technique presently known to destroy a city—except for bombing.”

Lindbeck's statement is based on the evidence that shows the negative impacts of rent controls. One example is described in this 2025 article by Eilidh Geddes (University of Georgia) and Nicole Holz (Northwestern University), published in the Journal of Housing Economics (ungated earlier version here). They looked at the impact of a large-scale rent control expansion in San Francisco in 1994, which removed an exemption from rent control for small (less than five units) owner-occupied buildings built before 1980, on evictions.

Their data are the number of eviction notices, as well as wrongful eviction claims and 'owner move-in' eviction notices at the zip code level, from 1990 to 2010. They apply a continuous treatment difference-in-differences, which essentially compares the change in evictions (or other measure) between zip codes that were more affected by the removal of the exemption and those that were less affected. Their measure of exposure to the treatment is the number of housing units in the zip code that became exposed to rent control policies after the passage of the voter referendum in late 1994. In zip codes where more housing units were affected by the change, we would expect to see greater impacts than in zip codes where fewer housing units were affected. One limitation of this is the data source that Geddes and Holz use, which is based on building data from 1999, five years after the change was implemented. However, they show that three main sources of problems (demolition of buildings between 1994 and 1999, splitting of land parcels, and construction that changed the number of units in each building), do not have much impact on the estimated number of units affected (and so, don't have a large impact on the treatment variable).

In their main analysis, Geddes and Holz find:

...an 83% increase in eviction notices filed with the Rent Board and a 125% increase in the number of wrongful eviction claims for ZIP codes with the average level of new exposure to rent control...

These effects are large and economically significant. We find an annual effect of an increase of 20.07 eviction notices per 1000 treated units in a zip code. Over the six years in our post period (1995–2000), this translates roughly into 12% of newly rent controlled units receiving an eviction notice.

So, the expansion of rent control leads to an increase in evictions. Geddes and Holz also find that the effects:

...are concentrated in low-income areas. These areas are not necessarily those that saw the largest increases in aggregate rents during the 1990s, suggesting that landlords may be more willing to engage in eviction activity in places where there are fewer resources to fight that behavior.

Geddes and Holz caution against taking a broad interpretation of their results though, as the removal of the exemption in 1994 primarily affected small landlords, who are often 'mom and pop' landlords and are able to take advantage of 'owner move-in' eviction provisions that are not available to large corporate landlords. However, the results are consistent with the broader literature, which suggests that tenants may be negatively affected by rent controls.

But not in all ways, it appears. In a more recent article published in the Journal of Health Economics (open access), Geddes and Holz look at the impact of the same 1994 expansion of rent control in San Francisco on intimate partner violence (IPV). They first note that that the effect of rent control on IPV is theoretically ambiguous, and there are two competing models with different predictions:

In the financial strain model, lower housing costs will decrease financial stress, leading to lower levels of violence. The effect of housing policies will thus depend on whether they lower costs for couples. However, in a bargaining model, there is a crucial distinction between policies that shift housing costs overall and those that shift the relative costs of housing inside and outside of the relationship. Policies that decrease housing costs overall will change the amount of resources in the relationship to be bargained over, but will not shift the bargaining power in the relationship. However, policies that decrease housing costs inside the relationship relative to those outside of the relationship will change the attractiveness of the outside option, shifting bargaining power away from the woman.

The empirical setup in this research is the same as for their earlier research on evictions. The difference is that the outcome variable of interest is IPV, measured as:

...the number of hospitalisations resulting from assaults that comes from California’s Department of Health Care Access and Information (HCAI, formerly OSHPD) from 1990–2000.

In their main analysis, Geddes and Holz find that:

...for every one percent increase in exposure to rent control in a ZIP code, hospitalized assaults on women decline by 0.08 percent. In levels, this translates to an almost 10 percent decrease in violence against women for the average ZIP code.

They find no corresponding decrease in assaults on men, which suggests that their results are not driven by an overall decline in assaults (including non-IPV assaults). They also find no effect on reported accidents, which suggests that their results are not driven by changes in the propensity to report IPV. Interestingly, they also find:

...no evidence of changes in household size or composition, suggesting that our results are driven by changes in violence within relationships rather than changes in cohabitation or relationship dissolution.

Overall, their results are most consistent with the financial strain model of IPV. Based on that model, we interpret these results as showing that rent controls, by reducing housing costs (and it is worth noting that housing costs in San Francisco are, and have been for some time, very high), decrease conflict within intimate relationships, and decrease IPV.

So, at least there is some evidence for positive effects of rent control. These results also sit alongside earlier evidence from the same rent control expansion, which showed short-run gains for incumbent tenants, but long-run reductions in the supply of rental housing units, as well as an increase in inequality. However, few people are advocating for rent control policies in order to reduce intimate partner violence. And benefits in terms of reduced violence have to be weighed against all of the other negative consequences of rent control policies, many of which are outlined in the posts linked below.

Read more:

• Why rent controls have worse effects over longer time horizons
• The deadweight loss of rent control
• The deadly consequences of rent control in Mumbai
• Rent control and inequality in San Francisco
• Rent control and the redistribution of wealth
• Rent control and vacant properties in India
• Rent control according to Seinfeld
• There should be no debate at all about rent controls
• Rent controls make many tenants worse off in the Netherlands