Work is a central part of our lives. It is something we do almost every day, for much of the day, for decades on end. Because it is so central, looking closely at how much time we spend working can tell us a lot about our lives and the societies we live in.
How much do people around the world work? In many countries today, people work much less than in the past 150 years. Working less means being able to spend time becoming more educated, or simply enjoying leisure time. This is substantial progress, but there are still huge inequalities across and within countries, and progress still to make.
Here we present the data on working hours. We explore how it differs across countries and over time and how these differences matter for people’s lives.
Summary
- Working hours have decreased dramatically in the last 150 years for many countries.
- But there are still large differences between countries: workers in poorer countries tend to work much more than workers in richer countries.
- The primary way to measure working hours is with surveys, but the data can have limitations that are important to understand.
Interactive charts on Working Hours
Are we working more than ever?
In today’s hustle and bustle world, it’s easy to assume that we are all, by and large, working more than ever. But is that really the case?
As we explain in detail below, the research on the history of working hours shows that this is not the case.
The available data shows that in the 19th century people across the world used to work extremely long hours, but in the last 150 years working hours have decreased substantially, particularly in today’s richest countries.
The chart here shows average working hours since 1870 for a selection of countries that industrialized early. You can add or remove countries by clicking Add country on the chart.
We show annual totals, so the trends account for changes in both the length of working days as well as the number of days worked through the year. The data comes from research by the economic historians Michael Huberman and Chris Minns, who have brought together evidence from historical records, National Accounts data, and other sources.1
The chart shows that average working hours declined dramatically for workers in early-industrialized economies over the last 150 years. In 1870, workers in most of these countries worked more than 3,000 hours annually — equivalent to a grueling 60–70 hours each week for 50 weeks per year.
But we see that today those extreme working hours have been roughly cut in half. In Germany, for example, annual working hours decreased by nearly 60% — from 3,284 hours in 1870 to 1,354 hours in 2017 — and in the UK the decrease was around 40%. Before this revolution in working hours people worked as many hours between January and July as we work today in an entire year.2
For many countries in the chart we don’t have long-run series going back to the 19th century. But we do have evidence from other historical records from 1870–1900 that in many of those countries workers also used to work extremely long hours.3
For those countries with long-run data in this chart we can see three distinct periods: From 1870–1913 there was a relatively slow decline; then from 1913–1938 the decline in hours steepened in the midst of the powerful sociopolitical, technological, and economic changes that took shape with World War I, the Great Depression, and the lead-up to World War II; and then after an uptick in hours during and just after World War II, the decline in hours continued for many countries, albeit at a slower pace and with large differences between countries.4
In recent decades working hours have continued to decline in many countries, but there are large differences between countries
Zooming in to the last 70 years and looking at other countries beyond those who industrialized early, the data reveals a continued decline in working hours for many countries but also large differences between countries.
In the chart here we zoom in to the period since 1950 and we change the selection of countries to highlight some of the diversity in trends.
For some countries, such as Germany, working hours have continued their steep historical decline; while for other countries, such as the US, the decline has leveled off in recent decades.
In some countries we see an inverted U-shaped pattern. In South Korea, for example, hours rose dramatically between 1950 and 1980 before falling again since the mid 1980s. And in other countries we see no recent declines — in China, for example, hours actually rose in the 1990s and early 2000s before leveling off in recent years.
The decline in annual working hours described above has come from fewer working hours each day, as well as fewer working days each week and fewer working weeks in the year.
In a paper analyzing historical data for the US, the economist Dora Costa summarizes the evidence:5
“The length of the work day fell sharply between the 1880s, when the typical worker labored 10 hours a day, 6 days a week, and 1920, when his counterpart worked an 8-hour day, 6 days a week. By 1940 the typical work schedule was 8 hours a day, 5 days a week. Although further reductions in work time largely took the form of increases in vacations, holidays, sick days, personal leave, and earlier retirement, time diary studies suggest that the work day has continued to trend downward less than 8 hours a day.”
As Costa notes, workers had regular days off each week: one day off (usually Sunday) from at least the 1880s until around the 1940s, when two days off became more typical.
In addition to regular days off each week, workers across early-industrialized countries had days off from work for vacations and national holidays. This is shown in the chart here, which again relies on research from Huberman and Minns. The chart shows that days of vacation and holidays increased over the period from 1870–2000. The Netherlands is a stark example — workers there saw an increase from four days off for vacations and holidays in 1870 to almost 38 days off in 2000.
The declines in the length of the work day and the number of working days have been driven by several factors, including increases in productivity and the adoption of regulations that limit working hours. We discuss these and other key drivers behind working hours trends across countries and time in a series of forthcoming posts.6
The evidence presented here comes from decades of work from economic historians and other researchers. Of course, the data is not perfect — as we explain in a forthcoming post, measuring working hours with accuracy is difficult, and surveys and historical records have limitations, so estimates of working hours spanning centuries necessarily come with a margin of error. But for any given country, the changes across time are much larger than the error margins at any point in time: The average worker in a rich country today really does work many fewer hours than the average worker 150 years ago.
As the economists Diane Coyle and Leonard Nakamura explain, the study of working hours is crucial not only to measure macroeconomic productivity, but also to measure economic well-being beyond economic output. A more holistic framework for measuring ‘progress’ needs to consider changes in how people are allowed to allocate their time over multiple activities, among which paid work is only one.7
The available evidence shows that, rather than working more than ever, workers in many countries today work much less than in the past 150 years. There are huge inequalities within and across countries, but substantial progress has been made.
Do workers in richer countries work longer hours?
Economic prosperity in different places across our world today is vastly unequal. People in Switzerland, one of the richest countries in the world, have an average income that is more than 20-times higher than that of people in Cambodia.8 Life in these two countries can look starkly different.9
When considering such differences in prosperity, a natural question is: who works more, people in richer countries like Switzerland or in poorer ones like Cambodia?
Looking at the available data, the answer is clear: workers in poorer countries actually tend to work more, and sometimes much more.
We see that in the chart here, with GDP per capita on the horizontal axis and annual working hours per worker on the vertical axis.
Countries like Cambodia (which is the country in the very top-left corner) or Myanmar have some of the lowest GDP per capita but highest working hours. In Cambodia the average worker puts in 2,456 hours each year, nearly 900 more hours than in Switzerland (1,590 hours) at the bottom-right of the chart. The extra 900 hours for Cambodian workers means longer work days and many fewer days off.
There is a link between national income and average working hours, not only across countries at a given point in time — as shown in the chart above — but also for individual countries over time.
Since the Industrial Revolution people in many countries have become richer, and working hours have decreased dramatically over these last 150 years.
In the chart here we show this association between incomes and working hours over time, country by country. It is the same chart as above, except now countries’ single data points have become lines, connecting observations over time from 1950 until today.
The four highlighted countries exemplify how working hours have decreased at the same time that average incomes have increased. Germany, for example, moved far to the right as its GDP per capita increased more than 10-fold (from $5,227 to $51,191), and far to the bottom as working hours decreased by nearly half (from 2,428 hours to 1,386 hours each year).10
This makes sense: as people’s incomes rise they can afford more of the things they enjoy, including more leisure and less time spent working.
You can explore this association for other countries by clicking “Select countries” on the chart.
The key driver of rising national incomes and decreasing working hours is productivity growth.
Productivity refers to the rate at which inputs are turned into outputs. To understand working hours the key metric is labor productivity: the economic return for one hour of work.
At the most concrete level, labor productivity captures things like the number of breads that a baker bakes in an hour, or the number of cars factory workers assemble in an hour. At the most comprehensive level, it relates the total output of the economy (GDP) to the total labor input (total annual hours worked), giving us the aggregate measure of labor productivity, GDP per hour of work.
Higher labor productivity is associated with fewer working hours, as shown in the chart here with labor productivity on the horizontal axis and annual working hours on the vertical axis. The chart currently shows data for the latest available year, but you can explore this relationship over time since 1950 by using the blue time slider at the bottom of the chart.
We see that the same richer countries with lower working hours we noted before — like Germany and Switzerland — have very high labor productivity (69 and 83 $/h, respectively). If workers can produce more with each hour of work, it becomes possible for them to work less.
Though this doesn’t necessarily mean they actually do work less — workers in the US and Singapore, for instance, work many more hours than their counterparts in countries with similar productivity.11
In contrast, the countries toward the top-left of this chart have far lower labor productivity — Cambodia, for example, is at only 3$/h — and thus workers there need to work many more hours to compensate.
At the heart of the link between productivity, incomes, and working hours is technological innovation
Technological innovation — defined broadly here to include physical machines as well as ideas, knowledge, and processes — makes it possible for each worker to become much more productive. And increases in productivity in turn help drive both increases in incomes and decreases in working hours.12
A prime example of how tech innovation drives productivity growth is agriculture. As we show in detail in our entry on Crop Yields, innovations like better machinery, crop varieties, fertilizers, and land management have enabled farmers to be much more productive. In the US, for example, farm production per labor hour increased nearly 16-fold from 1948–2011.13 This increased productivity enables us to feed a rapidly growing population, even while the fraction of people working in agriculture is smaller than ever.14
The chart here shows the growth in labor productivity, not just for agriculture but for the entire economy. The technological, economic, and social structures in richer countries have enabled workers there to produce more while working less.
Besides tech innovation, there is evidence that working fewer hours can itself keep productivity higher, making the link between working hours and productivity self-reinforcing. For example, economist John Pencavel (2015) studied munitions workers in war-time Britain and found that their productivity stayed high up to a certain threshold of hours, but declined markedly above that threshold.15 We’ve probably all experienced the drop in productivity that comes at the end of a very long day of work.
The data show that it is workers in poorer countries who tend to work more, and sometimes a lot more, than those in richer countries.
This has large implications for the way we think about the economic progress made in the last two centuries and the nature of inequality between countries today.
It means that residents of today’s poorer countries like Cambodia and Myanmar — and also of today’s richer countries in the past when they were poor — are not just consumption poor, often unable to afford necessities like food and medicine. It means they are also leisure poor: because productivity is low and they must work so much just to scrape by, they can’t afford to spend much time improving their condition, becoming educated, or simply enjoying leisure time.
That people in poorer countries work so much more than in richer countries shows that differences in prosperity are not due to differences in work ethic — they are largely due to differences in circumstance and opportunity. As we ask in another post, “what would have been the chances for Steve Jobs if he was born in the Central African Republic?” No matter how hard he worked or how smart he was, it is difficult to imagine that Steve Jobs would’ve been able to realize his potential with such a steep mountain of inequality to climb.
We also see what the world misses out on when exceptionally talented people, including all the brilliant but underprivileged people in today’s poorest countries, don’t have the opportunity to realize their potential.16
Finding ways to raise productivity is therefore not just key to increasing production, but also to the reduction in working hours that is necessary for a society to flourish.
How are working hours measured and what can we learn from the data?
Work is a central part of our lives. It is something we do almost every day, for much of the day, for decades on end. Because it is so central, looking closely at how much time we spend working can tell us a lot about our lives and the societies we live in.
The data on working hours shows, for example, that rather than working more than ever — as is so commonly believed — people in many countries today work much less than in the past 150 years.
Working less means being able to spend time becoming more educated, or simply enjoying more leisure time. This is substantial progress, but there is still huge inequality across countries, and progress still to make.
To understand these changes in societies and people’s lives over time, and the substantial differences we see in the world today, it is crucial to measure and study how much time people spend working.
How are working hours actually measured? Where does the data come from, and how can researchers reconstruct long-run trends?
Here we provide an overview of the main data sources, compare the data, and explain the relevant differences and measurement limitations.
Surveys
Surveys are the primary way to collect data on working hours. They are typically conducted by national statistical agencies and come in three main types: labor force surveys, establishment surveys, and time use surveys. These surveys all provide an important perspective on working hours, but there are some key differences.
Labor force surveys collect data on employment status and time spent working by asking individual workers themselves. Of the survey types, these provide the most comprehensive perspective, covering hours actually worked in all economic sectors as part of both formal and informal employment, full-time and part-time, as well as self-employment and unpaid family work.17 But labor force surveys only cover residents of a country above a certain age (usually 15), which depending on the country might exclude a non-trivial number of workers.18
Establishment surveys collect data on employment and working hours as reported by employers.19 But because hours are reported by employers, these surveys often only cover paid or contractual hours and exclude self-employment, informal work, and some smaller firms.20 On the other hand, establishment surveys provide more detail on the industry of work than other surveys, and are more consistent with how GDP is measured, making them useful for studying labor productivity.
Time use surveys collect data on how individuals spend their time — down to the minute — across a number of activities in a typical day, including paid work.21 This level of granularity provides a useful complement to the other surveys, but as a trade-off time use surveys sample fewer people and are conducted less frequently and by fewer countries.
National accounts
To get the most comprehensive perspective on working hours possible, many countries aggregate data from these surveys with data from other sources — such as censuses, tax records, and social security registers — in an economic measurement framework called national accounts.
National accounts, and the surveys they rely on, are standardized to a degree across countries, which can facilitate international comparisons.22
But these comparisons often have limitations because many countries still implement the methods in different ways. For instance, countries might bring together different data in their national accounts, or aggregate it differently. And many countries don’t have the capacity to conduct comprehensive surveys of their labor force and produce national accounts-based statistics, giving a more limited view of work there.23
Comprehensive, cross-country data on working hours just isn’t available for the years before the mid 20th century. But researchers like Huberman and Minns (2007)24 have been able to fill some of the gap by reconstructing long-run trends for a selection of countries. How do they do it?
Through often painstaking effort, researchers have been able to find and piece together the relevant historical records that do exist. In the work of Huberman and Minns, one of the key sources for historical data on many countries is a report from the US Department of Labor published in 1900.25 The report compiled the records of many thousands of workers across numerous sectors from establishment surveys in 88 countries and territories. To reconstruct the trends in later years, Huberman and Minns pulled together data from the International Labor Organization, the work of peer researchers, and other sources.26
This was an impressive feat of reconstruction, but historical records like this do have limitations. For instance, as exhaustive as they were, the establishment-level records used by Huberman and Minns still excluded agricultural work, part-time work, and many smaller firms.
The work by Huberman and Minns is an important example of how researchers often combine and adjust underlying sources to produce one-off cross-country estimates. Another important study is the one of Bick, Brüggemann, and Fuchs-Schündeln (2019),27 who further standardized labor force surveys to enhance comparability for a selection of countries.
Besides these one-off estimates, several international organizations and research centers aggregate the working hours estimates published by national statistical agencies into cross-country datasets. The two most important datasets come from the OECD and the Penn World Table (PWT). These both draw on national accounts estimates when available, but they can differ in the other sources they use and their method of aggregation.28
In the chart you can compare annual working hours data from these four datasets. The data is shown one country at a time — with France currently selected. You can look at other countries by clicking ‘Change country’ on the chart, but note that not all sources publish data for every country.
As expected, there are differences between the sources. In 2000, for instance, Bick et al. estimates 1,642 hours of work for French workers, OECD estimates 1,558 hours, PWT estimates 1,550 hours, and Huberman and Minns estimates 1,443 hours. These differences are due to the use of different underlying sources and methods. Bick et al. use only labor force surveys; the others all rely primarily on national accounts data, but which nonetheless still have differences.
It’s also clear that these differences between sources are quite small when compared to the huge changes over the longer run. The difference between sources in 2000 is at most 200 hours, while the historical data from Huberman and Minns shows that from 1870 to 2000 annual working hours in France decreased by 1,725 hours (from 3,168 to 1,443 hours).
The analysis here shows that working hours data can have limitations — due to differences in the sources or the way the method is implemented — but that what these matter for our interpretation of the data depends on the context.
In a context where precise comparisons of similar countries is important, smaller differences between sources can really matter. This is why to compare recent working hours levels in the US and Europe, Bick et al. used only labor force surveys, which they standardized even further to maximize cross-country comparability. But as a trade-off, it was only possible to look at a small selection of richer countries.
In a context where we want to focus on a larger scale — such as the long-run historical trends we see in the chart — the limitations of the sources are not large enough to undermine our conclusions.
Large international datasets like PWT do not have the highest levels of cross-country comparability, but they allow us to look at many more countries across the world and uncover broad and important trends, such as the large differences in working hours between the richest and poorest countries.29
PWT and OECD are also useful in contexts where we want an exhaustive picture of the trends in individual countries, since they are often based on national accounts that bring together data from many sources to give a comprehensive perspective on working hours.
The data on working hours isn’t perfect, and it’s important to understand the limitations, but it can still tell us a lot about our lives and the world.
- Data: Annual hours of full-time production workers (male and female) in non-agricultural activities; Days off from work for vacations and holidays
- Geographical coverage: United States, Australia, Canada, and select countries in Europe
- Time span: 1870–2000
- Available at: Huberman, M. and Minns, C. (2007). The times they are not changin’: Days and hours of work in Old and New Worlds, 1870–2000. Explorations in Economic History.
- Data: Average annual hours worked by persons engaged; Number of persons engaged; Real and PPP-adjusted GDP in US millions of dollars
- Geographical coverage: Countries across the world
- Time span: 1950–2017 (version 9.1)
- Available at: https://www.rug.nl/ggdc/productivity/pwt/
- Feenstra, R. C., Inklaar, R., and Timmer, M.P. (2015). The Next Generation of the Penn World Table. American Economic Review.
- Data: Average annual hours worked per worker; Total annual hours worked; Persons employed
- Geographical coverage: Countries across the world
- Time span: from 1950 onwards
- Available at: https://conference-board.org/data/economydatabase
- Data: Average annual hours actually worked per worker
- Geographical coverage: OECD countries plus Costa Rica and Russia
- Time span: from 1950 onwards
- Available at: https://stats.oecd.org/Index.aspx?DataSetCode=ANHRS#
- Data: Self-reported enjoyment of various activities; Time spent on various activities (by sex and age); Days of work lost to sickness
- Geographical coverage: United States
- Time span: 1900–2005
- Available at: Ramey, V. A., and Francis, N. (2009). A century of work and leisure. American Economic Journal: Macroeconomics.
- Data: Working hours (by sex); Number of working days; Wages
- Geographical coverage: United States
- Time span: 1890–1991
- Available at: Costa, D. L. (2000). The Wage and the Length of the Work Day: From the 1890s to 1991. Journal of Labor Economics.
- Data: Weekly hours worked per employed; Weeks worked; Annual hours worked per employed; Employment rate; Annual hours worked per person; with data breakdowns by age, education level, and work sector
- Geographical coverage: United States and 18 European countries
- Time span: 1983–2015
- Available at: Bick, A., Brüggemann, B., and Fuchs-Schündeln, N. (2019). Hours Worked in Europe and the United States: New Data, New Answers. The Scandinavian Journal of Economics.
- Data: Weekly working hours per worker; Employment rate; Weekly working hours per adult; GDP per capita; Hours spent in production of home services; with data breakdowns by age, sex, education level, and country income level
- Geographical coverage: 80 countries across the world
- Time span: 1991–2012
- Available at: Bick, A., Fuchs-Schündeln, N., & Lagakos, D. (2018). How do hours worked vary with income? Cross-country evidence and implications. American Economic Review, 108(1), 170-99.