The speed of cities, part II


Jason Collins


January 12, 2011

As I described in my last post, there is a strong relationship between the size of cities and the residents’ speed of walking. The larger the city, the quicker its residents scamper from A to B. A number of studies have confirmed this relationship and have broadened the relationship to the speed of other activities (such as betel nuts changing hands quicker in Port Moresby than in rural centres in Papua New Guinea).

As the relationship between city size and speed has been shown to be surprisingly robust, it took some time before this research was extended to other factors that may influence the speed of walking. Do people walk faster in richer cities? In colder cities? Where these other factors were examined (such as by Levine et al), the samples had tended to be limited to cities within the same country or region, limiting the variation of the explanatory factors in the sample.

This gap was addressed by Robert Levine (a guest on the Radiolab podcast that triggered this series of posts) and Ara Norenzayan in a 1999 paper in which they examined the “pace of life” in 31 countries. The pace of life measure was composed of three elements: average walking speed, the speed with which postal clerks completed a simple request (a stamp purchase) and the accuracy of public clocks. The sample included cities in North and South America, Asia and Europe, plus one African city. Generally, they took measurements in the largest city in the country.

At the top of the pace of life score rankings were Japan (4th) and the Western European countries. In fact, the nine Western European countries all placed among the top 11 for pace, split only by Japan and Hong Kong (10th). In the middle of the rankings were the Eastern European countries, the United States (New York), Canada and newly industrialised Asian countries (such as Guangzhou, China). The slowest were those from the Middle East, Latin America and Asia.

The apparently faster pace of life in the Western European countries compared to the United States and Canada is surprising and seems to go against New York stereotypes. I would suggest that one reason for the apparently faster pace of the Western European countries is that two of the three measures, postal speed and the accuracy of public clocks, may be more weakly linked with speed of life than walking speed and are heavily influenced by the nature of the public service. When we look at only walking speed, the rankings are changed. The United States jumps to 6th (from 16th overall) and Kenya is 9th (compared to 22nd overall). Conversely, Austrians have the 23rd fastest walking pace, versus their overall place of 8th. The Irish are the fastest walkers and have the second highest pace of life score.

Given the lack of earlier analysis into factors besides population size, Levine and Norenzayan sought to test a range of hypothesis about what might affect the pace of life. These were:

  1. The more economic vitality a city has, the faster its pace of life. They used the country’s GDP, purchasing power parity (PPP – a measure of economic well-being) and average calorific intake as measures of the vitality.

  2. Hotter places are slower (using the average annual maximum).

  3. Individualistic cultures are slower.

  4. Bigger cities are faster. As 23 of the 28 cities for which population size was available had more than 1 million residents, the sample did not allow them to fully test this hypothesis.

An examination of the correlation between the pace of life and the characteristics used to test the hypotheses showed that the first three hypotheses could be supported. For the overall pace of life and walking speed, there was a strong correlation with GDP (0.74 and 0.61) and PPP (0.72 and 0.59). Climate (-0.58 and -0.47) and collectivism (-0.59 and -0.60) were strongly negatively correlated. Calorific intake had a weaker but still positive correlation (0.51 and 0.39).

The correlation between walking speed and the community characteristics was generally stronger than that between the postal service or clock accuracy measures and those characteristics. Walking speed had a stronger relationship with GDP, PPP and collectivism than the other pace-of-life measures, while it had a similar relationship to the rest. This could be considered another sign that the postal and clock measures of pace-of-life have more variation due to idiosyncratic characteristics of the country than the straight measure of walking speed.

The big question that comes out of these findings is the question of causation. We have a strong correlation, but which is causing which? Does the higher value of time in rich cities result in the residents walking faster or do cities with more active residents become richer? Is there a selection effect, whereby dynamic, rich cities attract dynamic, fast walking residents? A question might also be asked about the permanence of these traits. Do residents speed up as the city gets richer? Do residents of a hot city walk faster on a cold day (or when they are in another, colder city)?

My instinct is that it is a mix of both, but that the selection effect is a significant player. However, there would be expected to be clear incentive effects of higher valued time (although which wins out - the substitution or income effect as the city gets richer?).

Unlike earlier studies, the authors found no significant link between walking speed and population size. This could be representative of the lack of variation in the sample. The authors also suggested that this could be evidence of a threshold effect in that once a city exceeds a certain size, additional population growth does not affect the pace of life. This makes some sense, in that there is a limit to the speed with which someone can realistically walk. Further, once there is a certain threshold of environmental stimulus (if we adopt the hypothesis of Milbrand and Bornstein and Bornstein discussed in my last post) or alternative forms of entertainment, it is unlikely to spur faster walking.

One interesting suggestion by the authors was the potential for reinforcement. If a large city has more economic opportunity, it may attract migrants, further increasing its size. They noted the potential for future study into which factors are mutually reinforcing. This ties back to the issue of selection effects. A city that is slightly richer may become significantly so if it can attract a certain type of resident.

As a last note,the authors also sought to look at some consequences of the pace-of-life and hypothesised that faster cities have higher rates of death from heart disease, higher smoking rates and higher subjective well-being. These were all found to be supported in the predicted directions (although the relationship was less strong than that between the other community characteristics and the pace of life). I won’t go into these findings here, but the heart disease and smoking elements make sense. The subjective well-being finding also seems reasonable if you assume that higher income and other city benefits deliver well-being. It also suggests that if there is any “over-stimulation” that residents are trying to avoid through a fast-walking speed, the cost of this is outweighed by the benefits of city life.