Working Hours

How much time do people across the world spend working? How have working hours changed over time, and what do these changes matter for people’s lives? Explore data and research on working hours.

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.

See all interactive charts on working hours ↓

Working hours throughout history

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.

Working hours per worker have declined after the Industrial Revolution

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.

Shorter work days, but also more holidays and vacations

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

Why should we care?

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.

Working hours and prosperity

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.

Working hours tend to decrease as countries become richer

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.

People are able to work less when they work in more productive economies

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 topic page 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.

What we learn from this

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.

Measuring working hours

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.

How are working hours measured?


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

How do researchers reconstruct long-run historical trends?

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.

How does the data from different sources compare?

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).

What does this tell us about the study of working 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 Sources

Huberman and Minns (2007)

Penn World Table

Total Economy Database


Ramey and Francis (2009)

Costa (2000)

Bick, Brüggemann, and Fuchs-Schündeln (2019)

Bick, Fuchs-Schündeln, and Lagakos (2018)

Interactive charts on working hours


  1. In this chart we have taken the original data published by Huberman & Minns (2007) and extended coverage using an updated vintage of the Penn World Table (PWT), which is in turn based on the same underlying source that Huberman and Minns used for all data since 1950, the Total Economy Database. You can find more details and links to our sources in the ‘Sources’ tab of the chart.

  2. A key point to keep in mind when interpreting these trends is that they refer to working hours per worker, which is different from working hours per person. The per person measure corresponds to working hours per worker multiplied by the employment rate. Hence, changes in employment patterns — such as the historical rise of female participation in paid employment in these countries — mean that changes in hours per worker do not translate directly into changes in hours per person.

  3. A study by Michael Huberman and Frank Lewis reconstructed estimates of working hours in 1870 and 1900 for 48 countries across six continents using data from worker records kept by individual business establishments. They drew from a collection of records published by the US Department of Labor in 1900, and found substantial variation, but very high working hours for many non-industrialized countries. They found for example that in 1870, Colombia, Uruguay and Brazil had similar average working hours per worker as the US. The full reference of the paper is Huberman, M., & Lewis, F. D. (2007). Bend it like Beckham: Hours and wages across forty-eight countries in 1900 (No. 1229). Queen's Economics Department Working Paper.

  4. The increase in hours between 1938 and 1950 in the chart for some countries is due in part to the uptick during and just after World War II, but also plausibly due in part to differences in the source data and methodology.

  5. Costa, D. L. (2000). The Wage and the Length of the Work Day: From the 1890s to 1991.Journal of Labor Economics, 18(1).

  6. In our first post in the series, we discuss how increases in labor productivity have driven a rise in incomes and a decrease in working hours.

  7. Coyle, D. and Nakamura, L. I. (2019). Toward a Framework for Time Use, Welfare, and Household Centric Economic Measurement. Federal Reserve Bank of Philadelphia Working Paper No. 19-11.

  8. We chose Cambodia and Switzerland here because they both also have working hours data available, but the difference in average income can be even more extreme. For instance, people in Qatar have an average income that is 117-times higher than that of people in the Central African Republic.

    These differences refer to GDP per capita measured in international-$ and account for price differences between countries to enable comparisons. You can read more about this here.

  9. But life can also look similar, as you see in the pictures of the homes, computers, and phones of people on similar income levels in the two countries.

  10. These trends in GDP per capita are measured in constant international-$ and account for inflation to enable comparisons over time and between countries. You can read more about this here.

  11. We explore the differences in working hours between similar, highly productive countries — and also the differences within those countries — in forthcoming posts.

  12. For a discussion of how technology drives productivity growth and a rise in incomes (economic growth), see Romer, P. (1990) Endogenous Technological Change. Journal of Political Economy. For a discussion of the relationship between productivity growth, economic growth, and working hours, see Boppart, T. and P. Krusell (2020) Labor Supply in the Past, Present, and Future: A Balanced-Growth Perspective. Journal of Political Economy.

  13. See Figure 18 on p. 28 of Wang et al (2015) Agricultural Productivity Growth in the United States: Measurement, Trends, and Drivers. USDA Economic Research Report 189.

  14. The transition of employment out of agriculture to other economic sectors as countries become richer is known as ‘structural transformation’. You can read more about this in our post Structural transformation: how did today’s rich countries become ‘deindustrialized’?

  15. Pencavel, J. (2015) The productivity of working hours. The Economic Journal.

  16. Agarwal, R. and Gaule, P. (2020) Invisible Geniuses: Could the Knowledge Frontier Advance Faster? American Economic Review: Insights.

  17. Hours actually worked means hours spent directly on work and excludes things like annual leave, sick leave, public holidays, meal breaks, and commuting time. Unpaid family work in this case generally includes market-oriented work, such as for the family business, but not other unpaid work at home such as childcare, cooking, and cleaning. Since the latter type of unpaid work is typically performed by women, this has large implications for understanding gender differences in labor. We discuss these issues as part of our topic page on Women’s Employment.

  18. Only covering resident workers means that any cross-border workers are excluded. Only covering workers above a certain age means that any child laborers are excluded. While the incidence of child labor has been going down over time, especially in high-income countries, there are still an estimated 265 million working children in the world (almost 17% of the worldwide child population).

  19. Employers include businesses, non-profits, some government agencies, and other organizations that pay a wage.

  20. Unlike hours actually worked, paid or contractual hours typically include some time not spent working, such as during sick leave, and fail to include time spent working that wasn't paid or planned, such as overtime.

  21. Activities also include unpaid household work, school, leisure time, eating, and sleeping.

  22. By organizations such as the United Nations, International Labor Organization (ILO), OECD, and Eurostat.

  23. For further discussion of different sources and their comparability, see the methods guides of the OECD and the Total Economy Database and the work of Bick, Brüggemann, and Fuchs-Schündeln (2019).

  24. 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.

  25. U.S. Department of Labor (1900) Fifteenth Annual Report of the Commissioner of Labor: Wages in Commercial Countries. 2 vols. Washington, DC.

  26. The original sources are: 1870–1913: Huberman (2004) [in turn relying on the US Department of Labor Fifteenth Annual Report, 1900]; 1929–1938: International Labor Organization (1934–39), except for Canada (Ostry and Zaidi, 1972), U.S. (Jones, 1963; Owen, 1988), and Australia (Butlin, 1977); 1950–2000: University of Groningen and the Conference Board GGDC Total Economy Database (2005).

  27. 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.

  28. PWT sources its working hours data from The Conference Board’s Total Economy Database (TED). For more details on the underlying sources, see the TED guide and the OECD database.

  29. We gain further confidence in these conclusions when they are echoed by research that focuses only on more standardized, comparable sources for a necessarily smaller set of countries, as in the work by Bick, Fuchs-Schündeln, and Lagakos (2018).

Cite this work

Our articles and data visualizations rely on work from many different people and organizations. When citing this topic page, please also cite the underlying data sources. This topic page can be cited as:

Charlie Giattino, Esteban Ortiz-Ospina and Max Roser (2020) - “Working Hours” Published online at Retrieved from: '' [Online Resource]

BibTeX citation

    author = {Charlie Giattino and Esteban Ortiz-Ospina and Max Roser},
    title = {Working Hours},
    journal = {Our World in Data},
    year = {2020},
    note = {}
Our World in Data logo

Reuse this work freely

All visualizations, data, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

The data produced by third parties and made available by Our World in Data is subject to the license terms from the original third-party authors. We will always indicate the original source of the data in our documentation, so you should always check the license of any such third-party data before use and redistribution.

All of our charts can be embedded in any site.