This dataset, presented as a scatter plot in Figure 3.2, illustrates the wide disparities in free time and income across various countries for the year 2020. Free time is calculated by subtracting the average annual working hours from the total hours in a year. While the data suggests a general trend where higher-income countries tend to have more free time, it also highlights striking differences. For instance, France has much more free time than South Korea despite similar income levels, and the US has a significantly higher income than Poland despite workers in both countries having similar amounts of free time.

Annual Hours of Free Time and Income per Worker (2020) [Figure 3.2]

Figure 3.25 applies the work-leisure choice model to the data from Figure 3.24. It plots the daily consumption and free time for a representative worker in each country. For each country, a budget constraint is constructed as a line passing through the point of maximum free time (24 hours, \$0 consumption) with a slope equal to the wage rate. A crucial step in this analysis is the assumption that the observed data points represent the workers' actual optimal choices. Based on this assumption, the model allows for the inference of worker preferences by drawing hypothetical indifference curves tangent to the budget constraint at each country's observed consumption-leisure bundle.

Indifference Curves of Workers Across Countries (Figure 3.25)

This metric is calculated by dividing the total number of hours worked annually by the average number of people employed. It encompasses regular hours for all types of workers (full-time, part-time, part-year), both paid and unpaid overtime, and hours from secondary jobs. It specifically excludes any time not worked, such as public holidays, paid leave (annual, sick, parental), and time lost to industrial actions like strikes.

Average Annual Hours Actually Worked per Worker

Directly comparing working hours across countries using statistical data is challenging due to methodological inconsistencies. Key limitations include variations in how self-employed individuals are counted, the degree to which the informal economy is captured, and different methods for estimating unpaid overtime. These discrepancies can distort the analysis of international labor patterns if not properly considered.

Limitations of Cross-Country Working Hour Data

Figure 3.16 presents a graphical analysis of the historical trade-off between free time and consumption in the US for the years 1900 and 2020. The diagram's horizontal axis represents daily free time in hours, ranging from 14 to 24, while the vertical axis shows daily consumption in dollars, ranging from 0 to 200. The 1900 data is represented by a budget constraint connecting (0 hours, \$40) and (24 hours, \$0), with the average choice at Point A (16, 38). The 2020 data features a steeper budget constraint connecting (0 hours, \$250) and (24 hours, \$0), with the average choice at Point D (19.5, 105). The slope of each budget line signifies the real wage for that year.

Figure 3.16: Modeling US Work-Leisure Choices (1900 & 2020)

The Organisation for Economic Co-operation and Development (OECD) compiles and publishes the 'Average annual hours actually worked per worker' dataset, a crucial resource for comparative analysis of labor trends across different countries and time periods. To maintain data integrity and version control, economic studies that utilize this dataset, such as the cross-country work-leisure analysis in Figure 3.25, are careful to specify the date the data was accessed (e.g., June 2022).

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The Organisation for Economic Co-operation and Development (OECD) is an international organization that provides key economic statistics, such as data on average annual hours worked per worker and household disposable income, which are used to analyze economic trends.

Organisation for Economic Co-operation and Development (OECD)

A comprehensive analysis of historical trends in work and leisure, especially regarding the income-substitution effects of wage changes, draws upon a specific group of key sources. This group includes macroeconomic datasets from the OECD on average work hours and household income, alongside detailed historical data from academic studies like Huberman and Minns (2007).

Key Sources for Historical Analysis of Work-Leisure Choices

To cite the ebook, use The CORE Econ Team 2023 The Economy 2.0: Microeconomics Open access e-text https://core-econ.org/the-economy/.

To cite a unit, use The CORE Econ Team 2023 The Economy 2.0: Microeconomics Open access e-text https://core-econ.org/the-economy/ Unit [unit number] (url).

CORE Econ - The Economy 2.0: Microeconomics

The Organisation for Economic Co-operation and Development (OECD) provides a comprehensive dataset on household disposable income, a key indicator of economic well-being and purchasing power. This dataset is frequently used as a source for economic models and analyses, such as the cross-country comparison of work-leisure choices in Figure 3.25 and the historical analysis of US labor supply in Figure 3.16. Researchers typically cite the access date to specify the version of the data used.

OECD - Household Disposable Income

This dataset from the Organisation for Economic Co-operation and Development (OECD) compiles data on how individuals allocate their time. It is a key source for analyzing labor trends and is used to create visualizations like Figure 3.19 (on gender gaps in paid work) and Figure 3.20 (on average paid and unpaid work by gender). The dataset was noted as accessed in June 2022.

OECD - Time Use

The Organisation for Economic Co-operation and Development (OECD) provides a dataset on the gender wage gap, accessed in June 2022. It is a primary source for creating visualizations that compare wage and work disparities across countries, such as Figure 3.19 (on gender gaps in paid work and wages) and Figure 3.20 (on average paid and unpaid work by gender).

OECD - Gender Wage Gap (Source Data)

The manufacturing industry in higher-income economies exhibits a distinct structure regarding firm size and its contribution to employment. Based on OECD data from 32 countries, the sector is numerically dominated by small businesses; 83% of manufacturing firms have fewer than ten employees. However, large firms with 250 or more employees, while representing a small fraction of all firms (8%), are disproportionately important for employment, as they provide jobs for over half of the entire manufacturing workforce.

Structure of the Manufacturing Industry: Firm Size and Employment

OECD Dataset: Average Annual Hours Actually Worked per Worker

Figure 2.11 is a scatter plot that visualizes the relationship between unemployment benefit generosity and unemployment rates across OECD countries from 2001 to 2020. The horizontal axis represents the gross unemployment benefit replacement rate, which is the average portion of a worker's pre-tax earnings replaced by benefits. The vertical axis displays the average unemployment rate. The plot is used to demonstrate that there is no simple positive correlation between these two variables.

Figure 2.11: Unemployment Benefit Generosity and Unemployment Rates across the OECD (2001–2020)

Data from surveys of unemployed individuals in 2021, presented in Figure 6.7, shows substantial variation in the average time spent jobless across different countries. For instance, durations ranged from 5-6 months in the US and Canada to over a year in other nations. This evidence highlights that job loss is a significant event for many, as the associated loss of income and benefits can persist for an extended period, making the experience very costly.

Average Unemployment Duration Across Countries (Figure 6.7, 2021)

A 2007 academic paper by M. Huberman and C. Minns, titled 'The times they are not changin’: Days and hours of work in Old and New Worlds, 1870–2000', was published in the journal *Explorations in Economic History* (Volume 44, Issue 4, pages 538-567). This study serves as a significant source of historical data regarding working hours in various countries.

Huberman and Minns (2007) Study on Historical Work Hours

The Penn World Table (PWT) is a comprehensive database that provides national accounts economic data for a large number of countries over an extended period. Its primary contribution is to offer internationally comparable measures of Gross Domestic Product (GDP) and its components. To achieve this comparability, the data is adjusted using Purchasing Power Parity (PPP) exchange rates, which account for price level differences across countries. This makes PWT a crucial resource for research in macroeconomics and economic growth. Version 10.0, released in 2021, is a recent iteration of this dataset.

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