Hours worked guide

Guide to labour statistics

Learn about our different hours worked data sources and measures and how to use them

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Released
26/03/2025

Overview

We produce a range of statistics on hours worked. These are derived from various data sources to provide different insights into the labour market. This guide will help you understand what hours worked data are available, the different features and uses of the various measures and sources, and how to choose the best data to suit your needs.

Why are hours worked important?

Measuring the level and trends in hours worked is important to monitor the performance of the labour market and understand the labour inputs contributing to economic production. Hours worked can also provide insights into people’s experiences in work and the characteristics of jobs.

Hours worked provides complementary insights to traditional measures of employment, which focus on classifying people based on their attachment to their job rather than their economic activity. For example, during the Christmas holiday period, hours worked tend to reduce as many employed people are away from their job on holiday, but employment levels do not drop accordingly, as these people remain employed.

Over the COVID period, the impacts on the labour market were generally seen in hours worked, more than in employment, as many people remained employed (for example, as they were in receipt of JobKeeper) but worked no or reduced hours.

Information on hours worked also enables a range of important analytical insights into the labour market, such as through grouping employed people according to whether they work full-time or part-time, and as the basis for measuring underemployment.

The graph below shows Labour Force Survey estimates of the number of employed people and the number of hours worked. While the trend for both is similar, hours worked exhibits a greater degree of fluctuation month to month.

Source: Labour Force, December 2024, Tables 1 and 19

Hours worked and the ‘one-hour’ rule

Hours measures and uses

We produce estimates of hours worked based on three concepts:

  • Actual hours worked – the hours that employed people work in the reference period (referred to in the remainder of this guide as ‘Hours worked’, given it is also the most commonly used of the three concepts)
  • Usual hours worked – the typical number of hours employed people work in the reference period
  • Hours paid for – the time for which payment has been received from the employer during the reference period, regardless of whether the hours were actually worked or not

Measures of hours are produced for short reference periods, such as a week, or for longer periods, such as the total hours that are worked across an entire month or quarter.

Usual hours may differ from actual hours worked at a given time if people are away from work or are at work for more hours than normal.

International standards reference additional measures of hours worked such as Contractual and Normal hours, however these are not collected by the ABS.

For more information on hours worked concepts, see Labour Statistics: Concepts, Sources and Methods.

Key sources of hours worked information

There are two key sources of hours worked:

  • Labour Force Survey
  • Labour Account

Labour Force Survey

Measures of hours actually worked and hours usually worked in the survey reference week are collected monthly in the Labour Force Survey (LFS). The headline hours worked output is ‘Monthly hours worked’ – this is the total number of hours worked across the calendar month, derived by converting the hours actually worked in the reference week to a monthly figure.

Labour Account

The quarterly Labour Account is a framework that brings together data from various sources to provide comprehensive estimates across four quadrants: people, jobs, hours and income (by industry).

The key data source for compiling hours worked estimates in the Labour Account is the LFS. The Labour Account builds on the scope of the LFS by adding estimates of hours worked by defence force personnel, short-term non-residents, and employed children aged 5-14, to provide estimates of all the hours worked in the Australian economy each quarter.

Hours worked in the LFS versus Labour Account

The Labour Account incorporates data from the Quarterly Business Indicator Survey (QBIS) and a range of other business-based data sources. Their industry distribution information is used as a basis for compiling industry estimates of employment, jobs and hours worked (see our Industry employment guide). As a result, the Labour Account provides the best measure of hours worked across each quarter, including by industry.

The Labour Account is also the recommended source for hours worked information by market and non-market sectors (the non-market sector includes the Health care and social assistance, Education and training and Public administration and safety industries). 

The LFS is the best source for hours worked data when demographic (age and sex) and geographical breakdowns are needed. As the LFS is released monthly, it can also provide more timely hours worked information. The LFS also provides information on reasons for working fewer hours than usual, underutilisation and underemployment.

The scope of the Labour Account is all people working for enterprises resident within Australia’s economic territory that are engaged in the production of goods and services within the scope of the National Accounts production boundary. It includes all people who contribute to the Australian economy irrespective of their residency status. The Labour Force Survey covers all usual residents of Australia aged 15 years and over except members of the permanent defence forces, certain diplomatic personnel of overseas governments, overseas residents in Australia and members of the non-Australian defence forces (and their dependants) stationed in Australia.

At the broadest level, hours worked are generally consistent between the LFS and the Labour Account given hours worked in the Labour Account are largely based on LFS data.

Source: Labour Force and Labour Account, December 2024

Labour Account hours worked data are also used as the labour input into the National Accounts. These replaced the LFS hours worked estimates, which were used prior to the development of the Labour Account, given the industry information is of better quality and better aligns with other industry information in the National Accounts.

Hours worked data in the National Accounts are used for estimates of labour productivity (GDP per hour), as well as other derived items such as Gross Value Added (GVA) per hour.

Topics available by data source
 Labour Force SurveyLabour AccountNational Accounts
(Total) Hours worked✔✔✔
(Average) Hours actually worked✔  
(Average) Hours usually worked✔  
Demographics (e.g. sex, age)✔  
Industry◼✔✔
Regional level✔  
Monthly change✔  
Employment characteristics✔  
Gross Domestic Product, Gross Value Added per hour  ✔

✔ Recommended for this topic in relation to hours worked data.
◼ Published for this topic in relation to hours worked data, however limitations should be noted.

Other measures related to hours worked

Average weekly hours worked

While the total hours worked across months or quarters provide important macroeconomic measures to understand the economy and the overall labour market, measurement of average weekly hours worked provides useful insights into the experiences of employed people at work.

On average, people usually work 35 hours per week. Over time this has decreased slightly (for example, it was 37 hours in April 2001). The following graph shows the difference between usual and actual hours, highlighting how hours actually worked demonstrates more volatility than hours usually worked (e.g. drops in January each year when many workers are on leave).

Source: Labour Force Detailed, Dec 2024, Tables 9-10

We classify employed people as full-time or part-time in the LFS based on a combination of hours actually worked and hours usually worked in all jobs. 

  • Full-time workers are those who usually work 35 hours or more a week (in all jobs) and those who, although usually working fewer than 35 hours a week, actually worked 35 hours or more during the reference week.
  • Part-time workers are those who usually worked less than 35 hours a week (in all jobs) and either did so during the reference week or were not at work in the reference week.

It is important to note that being employed full-time is not necessarily the same as having a full-time job. For example, a person with 2 part-time jobs will be classified as employed full-time if they work at least 35 hours a week across those two jobs.

The long-standing threshold of 35 hours provides an objective and consistent measure to classify people to full-time or part-time, and is useful for international comparisons. However, it may differ from how jobs are classified as full-time or part-time in some occupations, in employment legislation (e.g. the Fair Work Act, which notes that full-time employees usually work 38 hours a week) or in employer payroll systems.

While average weekly hours worked by full-time males and females have decreased since 2001, hours worked by part-time workers have risen slightly.

Source: Labour Force Detailed, Dec 2024, Table 10

Distribution of weekly hours worked

While 35 is the average weekly hours usually worked, around 40% of employed people usually work either 38 or 40 hours a week in 2024 (up from 35% in 2013). Other spikes in the distribution are also seen around figures ending in a zero or a five (e.g. 30, 45, 50, 60 hours).

Source: Longitudinal Labor Force microdata, December 2024

Underemployment and unemployment

In addition to the hours people work, the Labour Force Survey includes outputs on ‘hours not worked’ – that is, the hours unemployed people would like to work, and the additional hours that underemployed people would like to work. We also collect information on people who, in the LFS reference week, worked fewer hours than usual, including the reasons.

Working time arrangement and working patterns

A variety of working time arrangements are collected in the annual Characteristics of Employment survey, including: 

  • Whether has minimum guaranteed hours
  • Whether usually works the same hours each week
  • Whether has agreement to work flexible hours
  • Whether usually works extra hours or overtime
  • Whether works shift work
  • Days of the week worked
  • Whether usually works from home

Data and resources available

This section summarises the hours worked data available according to their key features. It also lists other information available to help you understand hours worked data. 

 

ABS hours worked data sources
ReleasePillarFrequencyDescription
Labour Force SurveyHousehold surveyMonthlyHeadline estimates of employment and unemployment. Includes estimates of (total) monthly hours worked, hours actually worked and hours usually worked.
Labour AccountAccountsQuarterlyAggregate labour market statistics, derived from a variety of data sources. Composed of four quadrants: jobs, people, hours and payments. This data, which is the best for industry analysis, is an input into the National Accounts.
National AccountsAccountsQuarterlyUses estimates of hours worked from the Labour Account. Hours worked is the labour input used in the production of goods and services, and is important in understanding labour productivity.
Characteristics of EmploymentHousehold surveyAnnualPresents data on employee earnings, working arrangements, trade union membership and labour hire workers. Working arrangements includes information on hours worked in relation to working patterns, job flexibility, working from home, casual work and job security.
Employee Earnings and HoursBusiness surveyTwo-yearlyIncludes weekly hours paid for (and hourly earnings) by sector, method of setting pay, industry and occupation.
Census of Population and HousingHousehold survey5 yearlyCollects data on a range of topics, including income, labour force status and number of hours worked in the week prior to Census night.

Other information

For further information see: