National differences in amount of paid versus unpaid work

Countries differ in many cultural ways. An important one of those ways concerns how time is managed. There are 24 hours in every day, and 7 days in every week, and the time that people spend on each of the different activities can be averaged across each year. When combined across the whole population, these averages usually differ between countries, and this is what we mean when we recognize national behaviors. There are, however, many similarities among countries that share strong cultural ties.

The Organisation for Economic Co-operation and Development (OECD) has collected data on this matter among its member countries, as it also has for many other cultural and economic characteristics. In each of the 30 member countries, the OECD conducts regular "time-use surveys, based on nationally representative samples of between 4,000 and 20,000 people." The aggregated results are available online, including data for three other countries, for comparison (China, India, South Africa).

Four main categories of time use are reported by the surveys:

• Paid Work or Study, which includes paid work time, time in school or classes, travel to and from work / study, research / homework, and job search.
• Unpaid Work, which includes child care, care for other household members, care for non household members, routine housework, shopping, volunteering, and travel related to household activities.
• Personal Care, which includes sleeping, eating & drinking, medical services, and travel related to personal care.
• Leisure Time, which includes sports, participating / attending events, visiting or entertaining friends, and TV or radio at home.

Of particular interest is that the data are aggregated separately for males and females. I will look at the gender data in a future blog post, while here I will look only at the pooled data for each country.

National differences

In order to look at the current differences between the 33 countries (30 OECD, 3 non-OECD), I have performed this blog's usual exploratory data analysis. The available data are multivariate, since there are five measured variables for each country — total paid work, total unpaid work, total personal care time, leisure time (each measured in average number of minutes per day), plus Other (to make a total of 1,440 minutes per day). One of the simplest ways to get a pictorial overview of the data patterns is to use a phylogenetic network, as a form of exploratory data analysis. For this network analysis, I calculated the similarity of the countries using the manhattan distance; and a Neighbor-net analysis was then used to display the between-country similarities.

The resulting network is shown in the first graph. Countries that are closely connected in the network are similar to each other based on their average time management, and those countries that are further apart are progressively more different from each other.

The expected cultural similarities of the countries are, in most cases, reflected in the network. For example, the country that we might expect to be the most different to the other 32 is Mexico (it is the only country from Latin America), and it is also the most isolated one in the network. It is characterized by having the greatest amount of average work time per day, particularly unpaid work, and the least leisure time.

Furthermore, the three Asian countries are clustered together: Japan, Korea, and China. They have similar high amounts of paid work, but much less unpaid work than the Mexicans.

On the other hand, it is not clear why India is shown as very similar to some of the European countries, given its very different culture. However, differences do appear in the gender patterns discussed below.

In other cases, there are occasional countries that are not where we might anticipate them to be in the network, given other known historical and cultural similarities, particularly language. For example, Sweden is not near the other Nordic countries (Denmark, Norway, Finland), as the Swedes report many more minutes of paid work per day, and correspondingly less time on each of the other activities. Portugal is not near Spain, Italy, and France, as they also report more minutes of paid work, and specifically less leisure time. On the other hand, Australia is not near Canada, the USA, New Zealand, and the UK, because the Australians report fewer minutes of paid work but correspondingly more unpaid work time. The people of Latvia and Lithuania also report many more minutes of paid work per day than do those of Poland and Estonia.

Other differences

Lest you get the impression that historical and cultural ties dominate the time-management data, we can look at one part of the data in detail.

As noted above, the Personal Care data includes separate information for sleeping versus eating & drinking. In the next graph I have plotted these two variables against each other (in average minutes per day), for all 33 countries.

As you can see, thee is no correlation whatsoever between these two variables. That is, extra eating and drinking time does not come out of the time allocated for sleeping, or vice versa.

Moreover, you will note that the denizens of the three Asian countries do not behave anything like each other, particularly as the Chinese sleep longer than everyone except the South Africans. Nor do the Swedes behave much like the Danes, in terms of eating and drinking.

Finally, the Mexicans report that they do not spend much time eating or sleeping, which follows from the work data discussed above. Instead, it is the Mediterranean peoples who like to spend their time eating and drinking. On the other hand, the Americans (and Canadians) certainly behave like they live on fast food, spending less time on eating and drinking than anyone else. They do, however, like their 8.5 hours sleep per day, which most other populations think they can do without that extra half hour.