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How low-density housing is making us poorer

Economist Matt Williamson takes a look at the economic benefits of dense cities

Enabling a higher density of businesses and houses can bring many benefits to cities. It makes us as individuals, and as a society, richer – and not only in monetary terms. More choices of where to live, and less land per home, means lower house prices. A denser urban form means less time spent in traffic, lower carbon emissions and lower infrastructure costs.

Retail, hospitality and entertainment precincts thrive when their customers don’t have to travel as far to reach them, and the location of so many people near each other enables greater specialisation in the workforce and greater economies of scale.

We can do things more efficiently and at lower cost when we co-locate. Businesses involved in a production chain will create more goods more cheaply when they’re clustered together than if each step in the chain requires transportation over a large geographic distance.

That is what economists refer to as “economies of agglomeration” – the benefits that occur when things and people are located closer to each other. When more people cluster together, it means there is more formal and informal networking, more innovation, higher specialisation, and therefore higher GDP and wages. Larger and denser cities tend to have more efficient labour markets. When you have a bigger pool of candidates, it’s easier for a company to find an employee who’s an exact right fit, and it’s easier for an employee to find a company that’s right for them too.

In 1890, economist Sir Alfred Marshall remarked that cities have “ideas in the air”. He developed the theory of “knowledge spillovers”, that closely clustered businesses in the same industry will quickly adopt innovative new production techniques and technological advancements.

Principles of Economics, 1890

Some great examples include the semiconductor industry in Silicon Valley, or the film industry in Los Angeles. Knowledge spillovers also apply to related industries. A classic example is Detroit’s shipbuilding industry in the 1830s, which later accelerated the growth of an automobile industry in the 20th century, because companies could apply similar technology and processes.

When you have more customers clustered together, businesses can specialise their product offerings to more closely match what people truly want. If you live in a small town you may have to settle for a restaurant serving food described no more precisely than “Chinese”, but in a larger centre, you’ll find restaurants specialising in Sichuan, Cantonese, Shandong or Jiangsu cuisine. It could even specialise in producing dumplings or noodle dishes, a more niche offering than would be sustainable in a smaller market.

This is what’s known as agglomeration in consumption, or to non-economists, a better selection of restaurants. Larger centres also enable economies of scale in consumption. If you want to go to a lot of rugby games, or see a lot of international live music acts, your preferences will be better met if you choose to live in Auckland than Alexandra.

This is what’s known as agglomeration in consumption, or to non-economists, a better selection of restaurants.

Exactly how much richer can locating closer together make us?

Well, it turns out, potentially quite a lot. Prior to Auckland’s upzoning in 2016, Waka Kotahi estimated doubling the density of employment in Auckland could increase productivity by 5-10%.[1]

One US study found that if New York, San Francisco and San Jose had kept restrictions on new housing to the same level as the median US state between 1964 and 2009, US GDP would be 14% higher today. This translates to a “total wage bill” across the entire US economy that is $1.32 trillion higher, or an additional $9,174 in wages for the average worker.[2]

Another study found that if the average US state had housing rules that were even half as permissive as Texas over the 1940-2014 period, labour productivity would be 12.4% higher, and consumption spending would be 11.9% higher.[3] It would mean more productive businesses, higher wages and more spending on the things we want and need.

Unfortunately, one key theme linking many highly productive urban centres around the world is expensive housing. High house prices restrict many people from living and working in these highly productive centres, so people instead choose to live somewhere more affordable and less productive. Research out of the Netherlands shows the key driver of where people choose to live is how plentiful the supply of new housing is, rather than the supply of high-paying jobs.[4]

Escaping the rat race and moving to a small town may sound like a nice idea when you’re stuck in traffic on your morning commute, but when thousands of people make this decision, the productivity impact can lead to a significantly lower GDP than if we just enabled more apartments and townhouses to be built in high-demand areas, and let people move to where they were most productive.

By failing to enable enough housing in our most productive centres, we risk failing to capture these productivity gains, because people are forced to locate not where they are most productive, but where they can afford to live. That means a less productive society, fewer of the things we enjoy, lower living standards and a larger gap in wages with Australia.


[1] Graham, D. J. & Mare, David C. (2009). Agglomeration elasticities in New Zealand (Research Report 376). NZ Transport Agency
[2] Hsieh, C.-T., & Moretti, E. (2019). Housing Constraints and Spatial Misallocation. American Economic Journal: Macroeconomics, 11(2), 1–39.
[3] Herkenhoff, K. F., Ohanian, L. E., & Prescott, E. C. (2018). Tarnishing the golden and empire states: Land-use restrictions and the U.S. economic slowdown. Journal of Monetary Economics, 93, 89–109.
[4] Vermeulen, W., & van Ommeren, J. (2009). Does land use planning shape regional economies? A simultaneous analysis of housing supply, internal migration and local employment growth in the Netherlands. Journal of Housing Economics, 18(4), 294–310.

Authors who contributed to this article

Matthew Williamson