One of the many reasons that people choose to live in cities is that cities offer variety. As Stu Donovan has argued before, being around more people sometimes seems inconvenient, but it also exposes you to new ideas, new people, and new consumption choices.

I’ve previously written about the value that people place on choices in housing and transport markets, and how having more choices is particularly valuable for people on low incomes. This week, I want to look at how cities provide us with choice in the retail and restaurant markets.

My hypothesis is that there are economies of scale in the provision of both public and private goods. In more straightforward terms, that means that if you live closer to more people, you can have more public transport, more parks, more good restaurants, more shops, and so on and so forth. If this intuition is true, the best way to obtain variety at an affordable price is to live in a dense area of the city.

In order to test this hypothesis, I took a look at Statistics New Zealand’s Business Demography statistics, which provide information on the number of businesses (“geographic units”) and employment within particular industries. Very helpfully, Stats NZ publishes this data at a suburb level (“area units”, in Stats-speak).

I’ve focused on two particular types of businesses that serve households’ daily needs:

ANZSIC industry H45, which includes restaurants, bars, and clubs

ANZSIC industry G41, food retail, which includes supermarkets and other small-scale food retailers.

I mapped the density of these businesses throughout different Auckland suburbs. Blue colours show higher densities of restaurants/bars or food retailers; yellow colours show lower densities. A few clear patterns emerge. First, densities tend to be highest in inner city suburbs, and even more so in the city centre. Second, there are also pockets of higher density around satellite centres like Takapuna and New Lynn. Third, the density of retail and restaurants tends to be much lower on the fringe of the city.

How can we explain these patterns? Why are some areas so much better supplied with retail and dining options than others?

We can get some insights by looking at the built form retail and restaurants areas in different areas of the city.

Here’s what a retail street looks like in the city centre, where high residential and employment density sustain a lot of activity both day and night. This is O’Connell St before and after its shared space transformation. Notice how people are just walking up:

Here’s what retail looks like in an inner-city shopping and dining district, Ponsonby Road, which is surrounded by old suburbs of medium population density. It has lots of shops right on the street, plus a bit of parking tucked around the back:

And here’s what retail looks like in a newer suburb at the edge of town – Albany centre. It’s physically separated from nearby residential areas, highly car-dependent, and as a result, it requires large swathes of parking to support each shop or restaurant:

In other words, less parking is required to get shoppers to the door in densely populated areas – which should make it easier to sustain more shopping and dining options per square kilometre.

A simple econometric analysis seems to support this view. I attempted to explain the density of restaurants and food retailers in suburbs in terms of the population density and employment density of those areas. (Using Census and Business Demography data from Stats NZ.) As I hypothesised, there is a statistically significant, positive relationship between higher population and employment densities and the density of restaurants and food retailers. These two factors predict roughly 85% of the variation in restaurant and retail density in Auckland suburbs.

Regression results are reported in the table below, for anyone who’s interested. These aren’t perfect models – I suspect that it would be worth testing some spatial regression models, as retailers often attract customers from a wider catchment than a single suburb. Furthermore, we’d have to analyse changes over time in order to establish that increasing population density in an area will in turn increase retail diversity. But these results do provide a reasonable indication of the underlying relationships.

OLS regression models for restaurant and retail density Dependent variable: log(restaurant_bar_density) log(food_retail_density) (1) (2) log(pop_density) 0.464*** 0.597*** (0.031) (0.033) log(emp_density) 0.620*** 0.486*** (0.026) (0.027) Constant -5.531*** -6.290*** (0.182) (0.191) Observations 342 342 R2 0.856 0.835 Adjusted R2 0.856 0.834 Residual Std. Error (df = 339) 0.632 0.664 F Statistic (df = 2; 339) 1,011.219*** 860.694*** Note: *p<0.1; **p<0.05; ***p<0.01

What do these figures mean? The coefficients from the model – highlighted in bold – display the relationship (or “elasticity”) between population or employment density and density of restaurants or food retailers. They show that:

Areas with 10% higher population density have, on average, 4.6% more restaurants/bars and 6.0% more food retailers (including supermarkets)

Areas with 10% higher employment density have, on average, 6.2% more restaurants/bars and 4.9% more food retailers.

In short: Higher density can benefit people by giving them more choice in restaurant and retail markets. Having a mix of residential and commercial uses around is even better, as it can sustain activity throughout the entire day rather than just in the evenings or at lunchtime.

Stats NZ’s data isn’t granular enough to say, but I suspect that denser areas also have a greater diversity of dining and retail options. (This is intuitively obvious – if there are already two fish-and-chip shops in the neighbourhood, why would anyone choose to open up a third?)

What do you make of this data on density and retail choices?

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