Last week over dinner with friends, a debate arose as to whether Australians worked harder than Americans or not. The case for the affirmative argued that many Australians were very successful overseas and indeed Australians working abroad were highly sought after by employers. The case for the negative drew on experiences working with large US firms which exhibited far more aggressive, high-pressure work-practices than Australian firms.
Since we had more wine than data, the argument did not last very long and we instead moved on to the question of whether China now more closely resembles a fascist regime than a communist one (this debate was quickly mired in definitional issues and became rather animated). Reflecting later on the first discussion, I decided to dig up some data on hours worked and attempt to determine a winner for the debate. According to the OECD, Australia and the United States drew very close in 1979 when workers in both countries put in an average of 35 hours per week. But apart from that, over the last forty years US workers have fairly consistently worked an average of 1 to 1.5 hours more each week than Australian workers.
Total Hours Worked per head of Workforce (1950-2008)
And what of the rest of the world? Among the countries covered in the 2008 OECD data, Korea* was by far the most industrious country. Employed Koreans laboured an average of 44.5 hours each week. From there, hours worked fell quickly to Greece on 40.8 hours and then down to the Czech Republic on 38.3 hours. Australia and the United States are in a tightly packed group, ranging from Iceland in seventh place overall on 34.8 hours per week down to Australia in 16th place on 33.1 hours per week. The United States is towards the top of this group, working an average of 34.5 hours and sitting in ninth place overall. The Hanseatic League is not what it once was as Germany, Norway and the Netherlands are clustered at the bottom of the league table, all putting in around 27 hours of work each week.
National Ranking of Hours Worked in 2008*
One shortcoming of these figures is that they do not give an indication of the total effort contributed to each country. This is because the averages are calculated per head of the workforce and ignores children, the unemployed, the sick and the retired. It is conceivable that in countries with fewer workers, those workers may have to work harder to support everyone else. Indeed, recalibrating the numbers based on total hours worked per head of the total population does change the rankings somewhat. Korea still puts in a good showing, but surrenders first place to Luxembourg. Australia climbs a few places to 11th place and in the process pulls one place ahead of the United States, reflecting in part the higher unemployment rate in the United States. Coming in last place is France, which puts in an average of only 13.5 hours of labour per capita.
Two Measures of Hours Worked in 2008*
But is this data enough to resolve the debate? Unfortunately not. There are too many things that this kind of broad data does not capture. For instance, underemployment is a significant concern in many countries, including Australia and the United States. If there are many people not working as many hours as they would like to, actual hours worked may not be a good indication of the relative industriousness of different countries. Segmentation is another problem. Before our dinner-table debate moved on to China, speculation arose about possible differences in work patterns in US firms based in large cities on the East and West coasts compared to workplaces around the rest of the country. Again, aggregate statistics cannot capture any such differences.
So next time this particular group of friends meets, I will have some data to bring to the table, but not enough to carry the argument.
* Only 2007 data is available for Korea. All other data is for 2008.
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excellent use of your little pointy charty thingee…nice to see you’re building on your previous posts. THought about doing something on underemployed as a follow up?
What’s the use of the chart using Total Pop again? Wouldn’t effort simply be captured by the first chart – ie. hours actually worked? The 2nd one seems like it would lose clarity based on things such as retired people and levels of of children as a proportion of total population. I imagine Iraq and Japan might be 2 good examples of young and old populations (though as the South Park Xmas special some years ago lamented, why are child eorkers discriminated against? Surely they have rights too?!)
Great stuff but I am really surprised by Greece figures. Do you know what plays into this?
Sounds like my kind of dinner party. Spirited debate is good and friends that can handle it are great.
Poland? Poland! Clearly #hours worked is defined as number of hours physically at a designated place of work not #hours spent actually working. Also those Americans spend a awful long time around the water cooler apparently.
Am I missing something?
Aren’t there 30 member countries in the OECD? There appear to be only 29 in your list here.
I’m intrigued as to why Turkey — a founding member at that — and the only predominantly Muslim country, has been omitted? Lack of data or … ?
Moreover, given Turkey’s proximity to Greece — and the country’s ongoing application to the EU — I would be interested to learn of its ‘average’ as compared with her high-performing neighbour!
Great topic of conversation though; I look forward to the next instalment!
Working hardest, not smartest. How does the ladder look when GDP is accounted for?
Hey, Stubborn Mule
By coincidence, last month there was a campaign “Go Home On Time Day”, promoted by the Australian Institute about this matter.
Do they OECD give their raw data: number of hours worked in total (not divided by labour force)?
This could be compared with the ABS data
sarahjane: Well-spotted! Turkey is missing. The reason is missing data. The most recent data for Turkey is 2004 and, while 2008 data for Korea was missing and I used 2007 data, I decided that the Turkey data from 2004 might be stretching things too far. For the record, they ranked quite well back then, at fifth place with an average of 36.9 hours per week. Here is a a 2004 chart.
apj: the idea of the by population chart is that countries with lower working populations may end up placing greater demands on their workers. At first glance, there does seem to be more uniformity in the by population numbers than in the by workforce numbers. However, this is an artifact of the fact that the by population numbers are smaller: in percentage terms the range in the numbers is similar.
Joe: I don’t really know why the numbers for Greece are so high. However, I would note, as others have, that hours worked do not necessarily translate to productivity. So, it may be that Greece has a cultural pattern of long working days, but this may not make any practical economic difference.
Matt: very good idea to look at it on a GDP basis…stay tuned!
Marco: the OECD numbers are average hours worked per head of workforce. However, since they also provide workforce numbers, these can be converted back to total work numbers (this is how I produced the per capita of population figures), which can be compared to the ABS numbers. I will have a look and see how they compare.
So the data is workforce in a country, not necessarily entirely composed of the nationals/locals? There would be different fractions of temporary/migrant workers there of other nationalities wouldn’t there? If so, it wouldn’t be representative of the question whether one nationality is more ‘industrious’ than another, I think.
penelope: You make an excellent point: there is certainly no cultural/national homogeneity imposed on the numbers. For example, any hard-working Australians abroad that one of my dinner companions may have had in mind would in principle be counted in other countries’ data rather than Australia’s (of course the data is based on sampling and so they may not be counted at all) and likewise many people would be included in Australia’s numbers who are not of Australian heritage. This is yet another example of complexities that are disguised by the broad aggregate numbers.
mule, call me pls….seriously