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6310.0 - Employee Earnings, Benefits and Trade Union Membership, Australia, August 2013 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 04/06/2014  Final
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UNDERSTANDING EARNINGS IN AUSTRALIA USING ABS STATISTICS


INTRODUCTION

Information about wages and salaries paid to employees is used for many purposes including economic analysis, social research, policy formation and evaluation, and research by employer and employee associations. The ABS publishes a variety of information on wages and salaries (generally referred to as 'earnings'), from both household and employer surveys.

KEY POINTS:
  • The ABS produces earnings statistics from a number of different sources, including both household and employer surveys, which provide a wide range of data for a variety of purposes.
  • The decision on which data to draw on depends on the purpose and type of analysis to be undertaken.
  • Estimates from a given source may differ from estimates from other sources as a result of differences in scope, coverage and methodology.
  • Many factors contribute to the level of, and changes in, earnings. These factors can be difficult to analyse independently as most are inherent in the changes in employment patterns and composition, wage rates, and hours worked.
  • Data collected at the individual level allow for compositional and distributional analysis, which makes it easier to try and account for the differences in employment patterns. The ABS encourages users to consider relevant factors when analysing data, and in general the more factors which are taken into consideration the more robust such analysis will be.

This article explores some of the earnings statistics produced by the ABS, through:
  • defining earnings statistics;
  • identifying ABS sources of earnings and related statistics;
  • highlighting relative strengths and limitations of the sources to provide guidance on the appropriate use;
  • describing the three main labour surveys that provide earnings statistics (Survey of Employee, Earnings and Hours (EEH); Survey of Average Weekly Earnings (AWE); Survey of Employee, Earnings, Benefits and Trade Union Membership (EEBTUM)); and the Wage Price Index (WPI); and highlighting the differences between them; and
  • demonstrating uses of earnings statistics through examples on distributional and compositional analysis, gender wage analysis and wage movement analysis.


WHAT DO WE MEAN BY EARNINGS?

In the broadest sense, earnings can be thought of as amounts paid by employers to employees for work done. More specifically, earnings are the pre-tax amount paid to employees for work done or time worked (including paid leave). Earnings do not include 'payments-in-kind' - i.e. the value of 'non-cash' goods or services provided to employees (fringe benefits). However in ABS collections, wages and salaries in cash conceptually include the value of goods and services obtained through salary sacrifice arrangements, where it is the choice of the employee. For more information on the conceptual framework for employee remuneration see Information paper: Changes to ABS measures of employee remuneration, 2006 (cat. no. 6313.0).

Earnings in ABS statistics are consistent with international definitions determined by the International Labour Organisation and in the System of National Accounts (2008).

For more detailed definitions and descriptions of the concept of earnings, refer to Chapter 12 of Labour Statistics: Concepts, Sources and Methods (cat. no. 6102.0.55.001).

EARNINGS and EMPLOYEE INCOME: are they the same?

Labour statistics produced by the ABS provide information on the concept of earnings, not income. Employee income statistics are conceptually broader than earnings and are generally produced under the suite of social statistics.

Earnings include:
  • wages and salaries in cash;
  • regular bonuses; and
  • salary sacrifice amounts - the value of goods and services obtained through salary sacrifice arrangements, where the employee chooses to forgo part of wages and salaries in cash in return for goods and services.
Earnings exclude (but are included in Employee Income):
  • payments in kind - the value of non-cash goods or services provided to employees (fringe benefits);
  • employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes (e.g. superannuation); and
  • severance and termination pay.
Employee Income is an employee's total remuneration, whether in cash or in kind, received as a return to labour from an employer or from a person's own incorporated business. It includes:
  • wages and salaries (in cash);
  • bonuses (irregular, one-off);
  • salary sacrificed amounts;
  • non-cash benefits (including wages and salary in-kind) - free or subsidised goods and services from an employer such as the use of motor vehicles and subsidised housing; and
  • severance and termination payments.
Total Personal Income is a broader concept which includes other monetary receipts such as government pensions and benefits, investment income, profit or loss from an unincorporated business, and private transfers (such as superannuation, child support etc).


KEY SOURCES OF EARNINGS DATA

The ABS produces earnings statistics, as well as earnings related measures, from a range of sources. The major sources of earning statistics in the ABS, and the publications in which they are released, are:

SOURCES OF EARNINGS DATA
Survey of Employee Earnings and Hours (cat. no. 6306.0)
  • composition and distribution of earnings of employees, hours paid for, and whether their pay is set by award, collective agreement or individual arrangement.
Survey of Average Weekly Earnings (cat. no. 6302.0)
  • the average weekly earnings of employees.
Survey of Employee Earnings, Benefits and Trade Union Membership (cat. no. 6310.0)
  • information on weekly earnings of employees, their employment benefits and trade union membership.
Wage Price Index, Australia (cat. no. 6345.0)
  • changes in the price of wages and salaries resulting from market pressures.
Australian System of National Accounts (cat. no. 5204.0) and Australian National Accounts: National Income, Expenditure and Product (cat. no. 5206.0)
  • compensation of employees, a very broad concept of employee remuneration.
Survey of Income and Housing (cat. no. 6523.0)
  • a breakdown of household income, including wages and salaries.
Major Labour Costs Survey (cat. no. 6348.0)
  • total earnings as well as other labour costs borne by businesses, for example payroll tax.
Survey of Employment and Earnings (cat. no. 6248.0.55.002)
  • public sector employee earnings paid by level of Government.
Quarterly Business Indicators Survey (cat. no. 5676.0)
  • private sector wages and salaries paid to employees, and other business costs e.g. investment.
Wage and Salary Earner Statistics for Small Areas, Time Series, 2005-06 to 2010-11 (cat. no. 5673.0.55.003)
  • regional estimates of wages and salaries based on postcode level aggregates of the Australian Tax Office's Individual Income Tax Return Database.

Household and employer surveys which are used by the ABS to collect earnings statistics have different strengths and limitations. It is important to be aware of these differences when analysing the data.

STRENGTHS AND LIMITATIONS OF ABS EARNINGS DATA SOURCES
Employer surveys earnings data
Household surveys earnings data
Employer surveys provide:
  • more accurately reported earnings as data are obtained from employers' payrolls;
  • components of earnings collected separately (i.e. ordinary time and overtime earnings); and
  • consistent business characteristics (such as industry and business size), as this information is maintained on the ABS Business Register.
Limitations include:
  • limited socio-demographic characteristics of employees;
  • limited information about characteristics of employment; and
  • only state/territory geographic information about place of work available.
Household surveys provide:
  • earnings by socio-demographic characteristics;
  • earnings by a range of employment characteristics, such as paid leave entitlements; and
  • greater geographic information about place of usual residence including Statistical Area level 4 under the Australian Statistical Geography Standard.
Limitations include:
  • earnings are less robust, with reliance on respondents' accurate recall of (pre-tax) earnings;
  • some respondents report on behalf of others in the household which can affect the quality of data reported;
  • fewer and less robust information about business characteristics; and
  • components of earnings estimates not available.

The rest of this article focusses on three key ABS labour surveys providing estimates of earnings and explains the purpose and key outputs of each, as well as their benefits and limitations. The surveys are:
    • the two-yearly EEH survey (cat. no. 6306.0);
    • the six-monthly AWE survey (cat. no. 6302.0); and
    • the annual EEBTUM survey (cat. no. 6310.0). The last issue of this publication is being released on 4 June 2014. In the future earnings data will be available in a new publication titled Characteristics of Employment, Australia (cat. no. 6333.0). The first release of this publication will be in respect of August 2014 and will be released in mid 2015.

In addition, the ABS WPI (cat. no. 6345.0), which provides a measure of changes in wages and salaries paid by employers for a unit of labour (i.e. hour) over time, is discussed as movements in WPI are often compared to AWE.

The first two surveys, EEH and AWE are employer surveys and measure earnings related to a 'point in time' (e.g. a pay period). They collect wages and salaries in cash that are received regularly and frequently (e.g. exclude one-off bonuses) and include payments for employees on paid leave.

EEBTUM is a household survey and also collects earnings at a 'point in time', the most recent pay period, i.e. the last total pay. It collects wages and salaries in cash, before tax or any other deductions. As the survey collects amounts of "total last pay", it may include irregular and infrequent payments or bonuses, and payments related to other periods.


SURVEY OF EMPLOYEE EARNINGS AND HOURS

The two-yearly EEH provides statistics on the composition and distribution of employee earnings, the hours paid for, and the methods used to set their pay. From 2006, estimates of earnings from EEH have included amounts salary sacrificed.

The information in EEH is collected from businesses but at the individual employee level. This makes it possible to derive measures of distribution (e.g. medians, deciles, earnings ranges) and provide some information on individual characteristics of employees. The median is a better measure of 'central tendency' than the mean when distributions are uneven or skewed, as the mean can be heavily influenced by outliers in the distribution. This is discussed in more detail later.

EEH also provides some information on individual characteristics of employees. These include: managerial/non-managerial status; occupation; sex; full-time/part-time status; adult/junior status; type of employee (permanent, fixed-term contract or casual); method of setting pay (i.e. award only, collective agreement and individual arrangement); and hours paid for. From 2014 onwards age of employee will also be collected in EEH. The EEH survey therefore complements the AWE survey by providing detailed information on the composition and distribution of employee earnings and hours, however on a less frequent basis.

A key strength of EEH is that it allows for hourly measures of earnings to be derived (currently only for non-managerial employees). Hourly earnings measures are useful for comparisons between groups who may work different weekly hours.

Non-managerial adult hourly ordinary time earnings from EEH is a widely used measure, since it allows as much of a like-for-like comparison as possible, facilitating comparison of earnings for different population groups. For example directly comparing the weekly earnings of full-time and part-time employees would not take hours paid for into account.


SURVEY OF AVERAGE WEEKLY EARNINGS

The six-monthly AWE is currently the most frequently available source of the level of earnings. It is designed to provide estimates of the level of average earnings at a point in time, and while not designed for movements in earnings, the frequency of collection supports a time series of these level estimates. Data on the average level of earnings are useful for providing a level benchmark to compare a specific amount to an average level of earnings e.g. what an individual earns compared to the average.

AWE has the longest history of the three ABS earnings sources discussed in this article. Collecting average earnings data is relatively simple and can produce estimates in a timely manner. While not designed as an index of wages, it is extensively referenced in legislation for indexation purposes.

Data are obtained from selected businesses on the total earnings (ordinary time and overtime) paid to their employees and the total number of employees in the business, which together are used to derive the mean, or average, earnings. These sample data are then weighted to provide estimates for the whole population of in scope businesses. Estimates are available by state/territory, sex, industry and sector.

The three key earnings series (excluding amounts salary sacrificed) produced from AWE are:
    • Average weekly ordinary time earnings (AWOTE) for full-time adult employees;
    • Average weekly total earnings (AWTE) for full-time adult employees; and
    • Average weekly total earnings for all employees.

The earnings series from AWE historically excluded amounts salary sacrificed. As discussed above, amounts salary sacrificed are conceptually part of wages and salaries in cash, however, the key earnings series from AWE have continued to be published on the old conceptual basis (i.e. exclusive of amounts salary sacrificed) to maintain long term comparability of the key series. Since the May 2011 AWE publication, the Average Weekly Cash Earnings (AWCE) series have also been released. These series are inclusive of salary sacrificed amounts. For more information see the Explanatory Notes of the AWE publication (cat. no. 6302.0) and Information paper: Changes to average weekly earnings, Australia (cat. no. 6302.0.55.002).

Out of the three series produced from AWE, the AWOTE for full-time adult employees series is generally considered the most stable earnings series due to the exclusion of overtime and part-time and junior employees, however it should be noted that the series does not represent all employees. AWTE for full-time employees has higher levels compared to AWOTE for full-time employees as it includes overtime. AWTE series for all employees has the lowest levels as it includes the earnings of part-time and junior employees, who receive lower pay on average than full-time adult employees.

Compositional changes in the employee population (e.g. the mix between full-time and part-time employees, or the industries and/or occupations in which they work) and the composition of the survey samples selected, can impact on the level of average earnings. For example, if there is an increase in part-time employment then, all other things being equal, the average weekly total earnings series for all employees would be expected to decrease.

EEH and AWE - some definitions

Employee refers to all civilian wage and salary earners who received pay for any part of the reference period excluding:
  • working proprietors and partners of unincorporated businesses;
  • employees paid under the Australian Government's Paid Parental Leave Scheme;
  • employees based outside Australia;
  • persons paid by commission only; and
  • non-salaried directors.
Full-time employees are permanent, temporary and casual employees who normally work the agreed or award hours for a full-time employee in their occupation and received pay for any part of the reference period. If agreed or award hours do not apply, employees are regarded as full-time if they ordinarily work 35 hours or more per week.

Adult employees are those employees 21 years of age or over, and employees under 21 years old who are paid at the full adult rate for their occupation. Junior employees are aged under 21 who are not paid at the adult rate of pay for their occupation. Junior employee earnings are included in the average weekly total earnings for all employees.

Average weekly earnings represent average gross (before tax) earnings of employees and do not relate to average award rates, or to the earnings of the 'average person'. Estimates of average weekly earnings are derived by dividing estimates of weekly total earnings by estimates of number of employees.

Weekly ordinary time earnings refers to one week's earnings of employees for the reference period attributable to award, standard or agreed hours of work. It is calculated before taxation and any other deductions (e.g. superannuation, board and lodging) have been made.

Weekly overtime earnings refers to one week’s earnings of employees for the reference period relating to payment for hours in excess of award, standard or agreed hours of work.

Weekly total earnings refers to weekly ordinary time earnings plus weekly overtime earnings of employees.

Excluded from the scope of EEH and AWE are the following:
  • members of the Australian permanent defence forces;
  • employees of enterprises primarily involved in the Agriculture, forestry and fishing industry;
  • employees of private households; and
  • employees of overseas embassies, consulates, etc.


SURVEY OF EMPLOYEE EARNINGS, BENEFITS AND TRADE UNION MEMBERSHIP

EEBTUM is a household survey, conducted annually as a supplement to the monthly Labour Force Survey (LFS). This survey collects weekly earnings data together with a range of socio-demographic information collected from individual people, such as: sex; age; marital status; relationship in household; geographic region of usual residence; school attendance; country of birth; and year of arrival in Australia.

EEBTUM also collects details about the nature of employment, including: occupation; industry; hours worked (hours paid for, hours actually worked and hours usually worked); full-time/part-time status based on hours worked; sector; size of workplace; and leave entitlements. From 2007, EEBTUM has included amounts salary sacrificed in the estimates of earnings.

As EEBTUM is collected at the individual employee level, like the EEH survey, this means that measures of earnings distribution (e.g. medians, deciles, earnings ranges) are able to be produced.

EEBTUM - some definitions

Employees refers to people who:
  • work for a public or private employer; and
  • receive remuneration in wages or a salary; or are paid a retainer fee by their employer and worked on a commission basis, or for tips, piece-rates or payment-in-kind; or
  • operate their own incorporated enterprise with or without hiring employees.
Employees who work solely for payment-in-kind are excluded.

Full-time employees are those employees who usually work 35 hours or more a week (in all jobs) and others who, although usually working fewer than 35 hours a week, worked 35 hours or more during the reference week. Full-time employees in main job are those employees who are:
  • Single job holders who usually work 35 hours or more a week, or usually work fewer than 35 hours but worked 35 hours or more during the reference week; or
  • Multiple job holders who usually work 35 hours or more in their main job and those who, although usually working fewer than 35 hours in their main job, worked 35 hours or more during the reference week.

Part-time employees are those employees who usually work fewer than 35 hours a week (in all jobs) and either did so in during the reference week, or were not at work in the reference week. Part-time employees in main job are those employees who are:
  • Single job holders who usually work fewer than 35 hours a week, and did so in the reference week; or
  • Multiple job holders who usually worked fewer than 35 hours in their main job in the reference week, or were away from their main job but usually work fewer than 35 hours a week in their main job.

Second job is a job, other than main job, in which some hours were worked during the reference week.

Weekly earnings are amount of ‘last total pay’ (i.e. before tax, salary sacrifice and other deductions had been made) from wages and salaries for jobs (all and main) held in the week prior to interview. For persons paid other than weekly, earnings are converted to a weekly equivalent. No adjustment is made for any back payment of wage increases, prepayment of leave or bonuses, etc.

Excluded from the scope of EEBTUM are the following:
  • members of the permanent defence forces;
  • certain diplomatic personnel of overseas governments, customarily excluded from the Census and estimated population;
  • overseas residents in Australia;
  • members of non-Australian defence forces (and their dependants); and
  • students at boarding schools, patients in hospitals, residents of homes (e.g. retirement homes, homes for people with disabilities), and inmates of prisons.


The three surveys discussed above have important differences in concepts, scope and methodology, which can result in different estimates of weekly earnings. Therefore, care should be taken when comparing estimates of earnings from these surveys. The main differences are described in the box below.

Differences between AWE, EEH and EEBTUM

AWE and EEH are both employer surveys, however EEH provides more detailed information from a larger sample, but is less frequent than AWE. Additionally, the two collections differ in sample design and survey methodologies. As mentioned earlier, AWE collects information relating to the total gross earnings and the total number of employees of employer units selected in the survey. The average weekly earnings measures are derived by dividing estimates of total gross earnings by the estimated number of employees. EEH collects information about weekly earnings of a sample of employees within the selected employer units. For more information see Chapter 29. Survey of Average Weekly Earnings and Chapter 30. Survey of Employee Earnings and Hours in Labour Statistics: Concepts, Sources and Methods (cat. no. 6102.0.55.001).

EEBTUM is a household survey and so differs from employer surveys in scope, sample design and survey methodologies.

The employer surveys exclude employees in the industries of Agriculture, forestry and fishing; and Private households employing staff. EEBTUM includes all civilian employees usual resident in Australia except: students at boarding school; patients in hospitals; residents of homes; inmates of prisons; Aboriginal and Torres Strait Islander communities in very remote parts of Australia; and, those who worked solely for payment-in-kind in their main job.

EEBTUM collects information from respondents who are either interviewed personally, or another adult member of their household responds on their behalf. Where earnings are not known exactly, an estimate is reported. AWE collects information from employers who complete a questionnaire with details of the total gross earnings paid to employees and the total number of employees in the business. EEH collects information about weekly earnings of a sample of employees within the selected employer unit. The business surveys are completed with information from the employers' payroll.

Industry information is collected differently for the different surveys. For employer surveys, industry is generally assigned according to the information on the ABS Business Register. In the household survey, industry is assigned based on the respondent's description of the industry activity at the place where the person works.


WAGE PRICE INDEX

The WPI measures changes in wages and salaries paid by employers for a unit (i.e. hour) of labour where the quality and quantity of labour are held constant. It is widely used as a measure of wage and salary inflation in the economy.

While AWE provides estimates of the level of earnings at a point in time, the quarterly WPI is a more relevant indicator for changes in the rates of pay. For further information on the WPI, please refer to the Explanatory Notes of Wage Price Index, Australia (cat. no. 6345.0) and Wage Price Index: Concepts, Sources and Methods (cat. no. 6351.0.55.001).

Period-to-period movements for the AWE series are not necessarily comparable with those for the WPI. It is important to recognise that the two series have different purposes and concepts, and use different sample selection, rotation, and estimation methodologies.

The WPI measures change in the price employers pay for labour that arise from market factors. Specifically, the WPI measures change in the price of wages and salaries. As a price index the quantity and quality of labour services are held constant, changes in the composition of the labour force, hours worked, or changes in characteristics of employees (e.g. work performance) are all excluded from the index. For the WPI this is achieved by ensuring that identical jobs are priced from one period to the next. This is referred to as pricing to constant quality.


USES OF EARNINGS DATA

Earnings statistics provide information on both the levels and movements in average earnings, and on the distribution of earnings for different groups of employees. Earnings statistics available from ABS sources provide key indicators to help inform policy, research and discussions of important labour market issues such as pay equity, social welfare, wage setting and income distribution. It is important to understand the relative strengths and limitations of the various earnings sources to ensure appropriate interpretation of the statistics.

As discussed above, there are a number of earning series available from ABS sources, and differences are observed when comparing these sources over time. Many factors contribute to the divergence in earnings, such as changes in wage rates, variations in hours worked, and changes in the composition of the employee work force.

The following sections provide a number of examples of the use of earnings statistics, namely: distributional and compositional analysis; gender comparisons; and wage movements.


DISTRIBUTIONAL AND COMPOSITIONAL ANALYSIS

Distributional and compositional analysis can help answer questions such as:
  • what is the distribution of earnings paid to employees, or a group of employees?
  • is the distribution different for different groups of employees? and
  • if so, what factors or characteristics of employees are driving those differences?
Mean, Median and Frequency distribution - definitions

Mean earnings: The amount obtained by dividing the total earnings of a group by the number of employees in that group.

Median earnings: The amount of earnings which divides employees into two groups containing equal numbers of employees, one half with earnings below the median and the other half with earnings above the median.

Frequency distribution: Frequency distribution of earnings show the spread of earnings within a population of interest, i.e. how much of the population have earnings at different levels, from very low to very high. This can show how earnings vary across a population.

It is useful to examine the distribution of earnings to determine whether most employees receive earnings near the average, or whether a few highly paid employees increase average earnings. When analysing earnings data, which has a skewed distribution with a long right-tail, the median is a better indicator of central tendency than the mean. However, to derive a median value, earnings for each employee in the survey are needed, i.e. the whole distribution. Both the EEH and EEBTUM collections provide distributional data as standard outputs.

Mean earnings are usually higher than the median as the mean earnings are influenced by outliers (graph 1). Relatively small numbers of highly paid employees contribute more to the numerator when deriving the mean, which results in a higher average. Generally, the larger the gap between the mean and the median for a group of employees, the more uneven is the distribution of earnings for that group of employees, indicating that a greater proportion of employees have earnings at the lower end of the distribution.

The graph below shows the distribution of non-managerial adult hourly ordinary time earnings from EEH, May 2012 survey. EEH data are more robust for analysing the distribution of earnings, as information is collected from businesses (from their payroll) but at an individual employee level. However, the EEH survey (used in graph 1) only has a limited number of characteristics of employees.

Graph 1: Total Weekly Cash Earnings, Adult full-time non-managerial employees - May 2012

Graph 1: Total Weekly Cash Earnings, Adult full-time non-managerial employees - May 2012
Source: ABS data available on request, Survey of Employee Earnings and Hours, May 2012.

Weekly earnings are affected not only by changes in the rate of pay, but also by any changes in the composition of the Australian workforce, including:
  • diversity of employment arrangements;
  • number of hours worked;
  • the extent of part-time and casual employment; and
  • mix of industries and occupations.
Many of these characteristics are not collected in employer surveys, however the household survey EEBTUM can provide insights into some of these through the availability of information about socio-demographic characteristics of employees.

EEBTUM data from August 2013 show there was a higher proportion of high earners in older age groups compared to younger age groups. The distribution of weekly earnings of employees in the age groups between 35 to 54 years were more skewed (i.e. wider gap between the mean and median), compared to those in the age groups between 15 to 24 or 25 to 34 years where the distribution is more equal (i.e. narrower gap between mean and median). The differences in the earnings distributions between younger and older groups can partly be explained by compositional differences between these two age groups.

A higher proportion of employees in the 35 to 44 and 45 to 54 year age groups work full-time in their main job. In August 2013, just over half (52%) of the employees in the 15 to 24 years age group worked full-time, whereas around three-quarters of employees in both the 35 to 44 and 45 to 54 year age groups worked full-time in their main job (73% and 72% respectively). A higher proportion of employees in the age group of 25 to 34 also work full-time (79%). This includes people who move to full-time work after completing their studies and, being a younger age group, tend to have less caring responsibilities (EEBTUM, August 2013).

The August 2013 data from EEBTUM also show that a far greater proportion of young employees were paid for few hours, 29% of employees (excluding OMIES) aged 15 to 24 years were paid for between 1 and 14 hours per week, compared with only 6% of employees (excluding OMIES) aged 25 to 54 years. This is a contributing factor towards the relatively lower weekly earnings in the 15 to 24 year age group. The middle age groups (those aged 35 to 44 and 45 to 54 years) have higher proportions of employees generally in higher skilled occupations, and are therefore higher paid. Over half of the employees in the Managers and Professionals major occupation groups are in the 35 to 54 years age group (54% and 57% respectively), resulting in higher median earnings for these age groups. Graph 2 below shows the mean and median earnings for the major occupation groups for August 2013.

Graph 2: Employees in main job (a), mean and median weekly earnings by occupation - August 2013

Graph 2: Employees in main job (a), mean and median weekly earnings by occupation - August 2013
(a) Employees excluding OMIEs
Source: ABS data available on request, Survey of Employee Earnings, Benefits and Trade Union Membership, August 2013.

However caution should be exercised, as earnings estimates from EEBTUM are not as robust because they are reliant on respondents' (or another responsible adults’) accurate recall of their (pre-tax) earnings. Also, measures provided from EEBTUM do not separate ordinary time earnings from overtime earnings.


GENDER COMPARISONS

The earnings data collected by the ABS can to some extent support comparisons of earnings by gender. However careful consideration is needed, as many factors other than gender influence the observed differences in average earnings between males and females. These factors include labour market participation, hours worked, industry and occupation. Therefore the observed differences in earnings are generally a reflection of the differences in male and female working arrangements.

It may be necessary to analyse other data sources to get a more comprehensive picture of the composition of the workforce. The LFS provides more timely and robust information about the composition of the labour force, as the data are collected every month and from a larger sample of households. Therefore latest available data from the LFS has been used for analysis of compositional differences within the employed population in this section.

Generally, when looking at ABS statistics for average earnings, male employees earn higher weekly cash earnings than female employees. Much of the difference between earnings of different groups can be explained by a variety of factors including the variation of hours worked and the types of work done, e.g. different occupations or prevalence of part-time work. For example, LFS data shows that in April 2014, 83% of male employees worked full-time, while 54% of female employees were employed full-time. Females employed full-time usually worked fewer hours per week on average (40.8 hours) than males (44.6 hours), whereas females employed part-time usually worked 19.2 hours per week on average compared to males who usually worked 18.5 hours per week on average.

The distribution of weekly earnings are heavily influenced by the proportion of people employed part-time. For example, data from the February 2014 LFS shows that the major occupation groups Sales Workers, and Community and Personal Service Workers, had the majority of people employed part-time (56% and 51% respectively). These two major occupation groups also have a relatively high proportion of females. More than half (61%) of all Sales Workers were females, and 66% of those females worked part-time. Females also counted for the majority of Community and Personal Service Workers (68%), and of those females, 58% worked part-time. The earnings data from EEH, May 2012, shows that these two groups also had the lowest median weekly total cash earnings of all occupation groups, $504 and $636 respectively.

The occupation groups Professionals and Managers have higher proportions of people employed full-time and the highest median weekly earnings. Professionals had 89% of males and 66% of females employed full-time, and Managers had 93% of males and 76% of females employed full-time (LFS, February 2014). The median weekly total cash earnings for Professionals was $1353 and for Managers it was $1642 (EEH, May 2012).

LFS data from February 2014 shows that the vast majority of people employed as Machinery Operators and Drivers and Technicians and Trade Workers were male (92% and 86% respectively), and of these relatively few were employed part-time (14% of male Machinery Operators and Drivers and 9% of male Technicians and Trade Workers). These two occupation groups also had above average median weekly total cash earnings ($1098 and $1080 respectively) (EEH, May 2012).

Graph 3: Median weekly total cash earnings for all employees, by occupation and by sex- May 2012

Graph 3: Median weekly total cash earnings for all employees, by occupation and by sex- May 2012
Source: ABS data available on request, Survey of Employee Earnings and Hours, May 2012.

The Accommodation and food services and Retail trade industries had the lowest levels of median weekly total cash earnings in May 2012 (EEH) ($455 and $590 respectively). LFS data from February 2014 shows that these two industries also have relatively high proportions of females (56% and 54% respectively) and a relatively high proportion of part-time employment. Retail trade had 48% of its workforce employed part-time, with 58% of females in this industry working part-time. Accommodation and food services had 57% of its employees working part-time with 62% of females in this industry working part-time.

The industry with the highest median earnings was Mining ($2250 - EEH, May 2012), where 84% of the workforce were males working full-time (LFS, February 2014).

Graph 4: Median weekly total cash earnings for all employees, by industry and by sex- May 2012

Graph 4: Median weekly total cash earnings for all employees, by industry and by sex- May 2012
Source: ABS data available on request, Survey of Employee Earnings and Hours, May 2012.

As described above, differences in earnings between males and females could be due to many factors, including different jobs within different occupations or industries, differences in full-time and part-time work, and also hours worked. Therefore as many factors as possible should be considered when analysing data.


WAGE MOVEMENT ANALYSIS

A key element in monitoring labour market and economic performance over time is examining changes in earnings. As earnings paid to employees represent a significant component of operating costs for businesses, changes in wages can highlight inflationary pressures facing businesses and/or impact on productivity. Changes in average earnings can also reflect the impact of the economic cycle on the labour market, or sectors within the labour market.

Up until recent times, WPI and AWE were both compiled on a quarterly basis, although AWE has recently changed to a biannual frequency with May 2012 being the last issue produced on a quarterly basis. Both WPI and AWE continue to be released in respect of May and November reference periods, and the common reference periods often lead to comparisons between the two series. Caution should be exercised when making such comparisons as differences in the purpose and design of the two collections means they will often respond differently to economic events.

Specifically, the WPI's focus on holding quality and quantity constant (to produce a measure of change in the price of a unit of labour) means it is affected solely by broad labour market influences on rates of pay. AWE will be affected by a more comprehensive set of economic factors. These include: changes in wages and salaries associated with individual performance; changes in employment that can affect the distribution of various types of employees between two periods (e.g. full-time vs part-time; higher paid vs lower paid) or changes in the pattern of hours worked (e.g. increase in total hours worked, increase in overtime hours). All these changes can influence changes in earnings between two periods to different degrees, and can result in different movements being observed for WPI and AWE. It is recommended that WPI be used to measure the change in the price of labour, or changes in wages over time, for the reasons described above.


CONCLUDING NOTE

Many factors contribute to the level and changes in earnings. These factors can be difficult to analyse independently, as most are inherent in the changes in employment patterns and composition, wage rates, hours worked and technological changes. Data gathered at the individual level, such as from the EEH and EEBTUM surveys, allow for compositional and distributional analysis, which makes it easier to try and account for the differences in employment patterns. The more factors which are taken into consideration when analysing data in general, the more robust such an analysis will be.

The various ABS sources of earnings information provide a wide range of data for a variety of purposes. Estimates from a given source may differ from estimates from other sources resulting from differences in scope, coverage and methodology. The decision on which data to draw on depends on the purpose and type of analysis to be undertaken.

The ABS encourages users to consider relevant factors in order to facilitate the most informed decision making.

More information on sources of earnings data, including conceptual or methodological differences, can be found in the Explanatory Notes of each publication, and in Labour Statistics: Concepts, Sources and Methods (cat. no. 6102.0.55.001).

For further information contact the Labour Market Statistics Section in Canberra on (02) 6252 7206 or email <labour.statistics@abs.gov.au>.


APPENDIX 1

This appendix provides a summary of the ABS data sources or publications about earnings and earnings-related data.

AWEEEHEEBTUMWPINational AccountsSurvey of Income and HousingSurvey of Major Labour CostsSurvey of Employment and EarningsQuarterly Business Indicators Survey
Designed to measureThe level of average weekly earnings.Weekly and hourly earnings and the distribution of earnings.Earnings and the distribution of earnings.Change in the price of labour.Compensation of employees.Total household income (including employment related income).Labour costs for employers, including employee earnings.Public sector employee jobs, and earnings.Revenue, profits, inventory and wages paid by private sector businesses.
Frequency/Type of data sourceBiannual business survey.Biennial business survey with payroll employee component.Annual household survey.Quarterly business survey.Quarterly compilation based primarily on quarterly business surveys.Two-yearly household survey.Irregular (currently run every 6 years) business survey.Annual business survey.Quarterly business survey.
BenefitsTime series data available (including seasonally adjusted and trend estimates).Data cross-classified by employer and some employee characteristics. Distributional data available.Detailed socio-demographic information.
Distributional data available.
Estimate of pure wage inflation removing the effect of composition.Broad measure of remuneration (includes, for example, annual bonuses and payment in kind).Distributional data on the broader context of household income and components available (including labour income) cross-classified by several employee characteristics.Earnings data in the broader context of labour costs. Data per employee also available.Public sector estimates, by level of government.Time series data available.
Primary publicationAverage Weekly Earnings, Australia (cat. no. 6302.0).Employee Earnings and Hours, Australia (cat. no. 6306.0).Employee Earnings, Benefits and Trade Union Membership, Australia (cat. no. 6310.0).Wage Price Index, Australia (cat. no. 6345.0).Australian National Accounts: National Income, Expenditure and Product (cat. no. 5206.0).Household Income and Income Distribution, Australia (cat. no. 6523.0).Labour Costs, Australia (cat.no. 6348.0).Employment and Earnings, Public Sector, Australia (cat. no. 6248.0.55.002). Business Indicators, Australia (cat. no. 5676.0).


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