Interesting to see New Zealand so high up on that list.

There was a lot of discussion a few years ago about their relatively poor productivity. I suspect the key to lowering those hours worked, is exactly that specific issue:

http://www.productivity.govt.nz/working-paper/an-internation...

Why is it not coincidentally? I agree that it appears correlates, but why?

Presumably, people know that they will be making less after taxes per marginal hour worked, and hence choose to spend their time with family, on hobbies, etc. instead of at work. (Though I think this is reading too far into the data given.)

I don't know that I can buy that. At least in the US, many people who work that many hours are salaried, so the extra hours don't mean any extra wages, and they still work those hours. The pressures of the job force them into it, not the economics.

It's surprising to see Iceland, New Zealand and Australia that high on the list. They don't have a reputation for being workaholic nations.

I'd be interested to see a break down based on industry and location, salaried vs hourly.

I could understand if self-employed people were included, as temporary staffing shortages are often covered by business owners.

I also wonder what the hours for office workers are like. I'm sure that most public sector employees work fairly regular hours.

Perhaps some people are temporary or "zero-hour" contractors with more than one gig?

Here in Australia, I suspect mining and construction will be the biggest contributors.

Every office job I have worked has been 38 hours with no overtime save for a handful of exceptions in 8 years of tech work.

Mining on the other hand can have consecutive 12 hour shifts be the norm, and I am sure that it gets worse than that.

We have some fairly strict award rates/employment regulations that govern things like that, but mining seems to be perhaps one of a few exceptions.

My guess, based on nothing, is they've adopted a Japanese-style ethic of putting in long hours for show because of a combination of high living costs and little opportunity.

How was the data collected?