I think there has also been a trend towards the longest-hours-worked being for wealthier people rather than poorer people.
The data bears this out, at least for the United States. The top 10% of earners generally work an average of 4.4 hours/week more than the bottom 10% of earners in the US, although worldwide it seems they work 1 hour/week less, on average.
I have to think that this is one of those hard areas to get a consistent measure of a comment thing. For example, is the 3 hour lunch meeting with a client really the same as the 3 houts a factory worker put in or the three hours recorded by a software engineer records for a specific project worked on?
I suppose we can say in each cases there is some level of “standing around” rather than real work. But I do suspect that the types of work don’t as one climbs the income ladder you start seeing more of the gray areas because the output of the effort becomes less directly measurable.
I also think that in the OP one of the factors in work was the unpleasant nature of the effort. While hardly universally true I have to speculate that at the higher income levels a larger percentage of people are doing things they find both interesting and enjoyable than hold at lower levels.
But clearly those hypothesis would likewise by challenging to evaluate as well.
at the higher income levels a larger percentage of people are doing things they find both interesting and enjoyable than hold at lower levels
How much autonomy someone has at work already makes a huge difference, even if it is a similar kind of work. I write computer programs both at work and in my free time, and the experience is incomparable, even if the programming language is the same, and the things I do at home are often more complicated.
If someone offered to pay me as much as is my current salary (or even 30% less), under the condition that I will keep working, but on projects of my own choice and at my own pace, plus I have to work 1 more hour every day, I would be quite happy to accept the deal.
The whole article is about Amazon employees being on the clock while they are using the bathroom. Spending more time in the bathroom reduces the productivity/per hour on their KPIs and thus they are incentivized against spending time in the bathroom.
Typically, a salaried white collar worker can turn up to work and use the bathroom at the start of the day, and it is counted as working hours, whereas a blue collar worker will use the bathroom before starting work (for the reasons you give about KPIs) and so it is not counted as working hours. Similarly for lunch break and end of shift. As a result the white collar worker will have a larger proportion of bathroom time counted as “working hours”, given the same time spent in the bathroom.
Maybe your point is that this is a difference of degree, not a difference in kind? True, but differences of degree matter for the working hour trends being discussed. If measured working hours stay the same but workers spend more of their bathroom hours during working hours then this is an effective increase in free time.
The relevant figure wouldn’t be the current value so much as its derivative: I don’t know how that situation has changed over time, and haven’t put in the effort to dig up information on what that data looked like in 1950.
I agree; I share your intuition that the reverse was the case in the past (the poor working longer hours than the rich), so the numbers being what they are today bears out the conclusion that the change has been towards the rich working more than the poor. Unfortunately, I just haven’t been able to find a ton of data explicitly focusing on this exact question (as opposed to a ton of related ones grouped together by Our World In Data). Best I could come up with was this Economist article from 2014 (beware paywall):
the rich have begun to work longer hours than the poor. In 1965 men with a college degree, who tend to be richer, had a bit more leisure time than men who had only completed high school. But by 2005 the college-educated had eight hours less of it a week than the high-school grads. Figures from the American Time Use Survey, released last year, show that Americans with a bachelor’s degree or above work two hours more each day than those without a high-school diploma. Other research shows that the share of college-educated American men regularly working more than 50 hours a week rose from 24% in 1979 to 28% in 2006, but fell for high-school dropouts. The rich, it seems, are no longer the class of leisure.
The data bears this out, at least for the United States. The top 10% of earners generally work an average of 4.4 hours/week more than the bottom 10% of earners in the US, although worldwide it seems they work 1 hour/week less, on average.
I have to think that this is one of those hard areas to get a consistent measure of a comment thing. For example, is the 3 hour lunch meeting with a client really the same as the 3 houts a factory worker put in or the three hours recorded by a software engineer records for a specific project worked on?
I suppose we can say in each cases there is some level of “standing around” rather than real work. But I do suspect that the types of work don’t as one climbs the income ladder you start seeing more of the gray areas because the output of the effort becomes less directly measurable.
I also think that in the OP one of the factors in work was the unpleasant nature of the effort. While hardly universally true I have to speculate that at the higher income levels a larger percentage of people are doing things they find both interesting and enjoyable than hold at lower levels.
But clearly those hypothesis would likewise by challenging to evaluate as well.
How much autonomy someone has at work already makes a huge difference, even if it is a similar kind of work. I write computer programs both at work and in my free time, and the experience is incomparable, even if the programming language is the same, and the things I do at home are often more complicated.
If someone offered to pay me as much as is my current salary (or even 30% less), under the condition that I will keep working, but on projects of my own choice and at my own pace, plus I have to work 1 more hour every day, I would be quite happy to accept the deal.
Note that there are plenty of things that count as “working hours” when white-collar workers do them but not when blue-collar workers do them.
Can you give examples?
Using the bathroom.
The whole article is about Amazon employees being on the clock while they are using the bathroom. Spending more time in the bathroom reduces the productivity/per hour on their KPIs and thus they are incentivized against spending time in the bathroom.
Typically, a salaried white collar worker can turn up to work and use the bathroom at the start of the day, and it is counted as working hours, whereas a blue collar worker will use the bathroom before starting work (for the reasons you give about KPIs) and so it is not counted as working hours. Similarly for lunch break and end of shift. As a result the white collar worker will have a larger proportion of bathroom time counted as “working hours”, given the same time spent in the bathroom.
Maybe your point is that this is a difference of degree, not a difference in kind? True, but differences of degree matter for the working hour trends being discussed. If measured working hours stay the same but workers spend more of their bathroom hours during working hours then this is an effective increase in free time.
The relevant figure wouldn’t be the current value so much as its derivative: I don’t know how that situation has changed over time, and haven’t put in the effort to dig up information on what that data looked like in 1950.
I agree; I share your intuition that the reverse was the case in the past (the poor working longer hours than the rich), so the numbers being what they are today bears out the conclusion that the change has been towards the rich working more than the poor. Unfortunately, I just haven’t been able to find a ton of data explicitly focusing on this exact question (as opposed to a ton of related ones grouped together by Our World In Data). Best I could come up with was this Economist article from 2014 (beware paywall):