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SURVEY OF EMPLOYEE EARNINGS AND HOURS
Hours paid for:
How employees' pay is set (collected for the first time in 2000):
Data can also be cross-classified by: state/territory; sector (public, private); rate of pay (adult, junior, apprentice/trainee or disability); full-time/part-time status; sex; managerial/non-managerial status; type of employee (permanent or fixed-term, or casual); occupation; industry; and employer size.
Data are compiled according to the concepts and definitions outlined in Chapter 4: Employment, Chapter 11: Employee Remuneration and Chapter 12: Workplace Relations.
For the first-stage sample of employing organisations, the standard scope exclusions for ABS labour-related business surveys (outlined in Chapter 23) apply to this survey.
The scope of the second-stage sample is restricted to civilian employees based in Australia, who received payments for the survey reference period. Self-employed persons (such as proprietors/partners of unincorporated businesses), employees who did not receive pay for the reference period (such as persons on unpaid leave), employees based outside Australia, and members of the Australian permanent defence forces are not in scope of the survey.
Detailed information is obtained about a sample of employees from each selected business, using online electronic collection. Prior to the May 2012 survey, information was obtained using a mail-out/mail-back collection methodology.
The survey reference period is the last pay period ending on or before the third Friday in May of the survey year.
Businesses that do not submit their data within a reasonable period of time after the survey reference date are followed up by mail and/or phone.
The survey uses a two-stage sample selection approach. The first stage involves selecting a probability sample of employer units from the ABS Business Register. The statistical unit for the first stage comprises all activities of an employer in a particular state or territory, based on the Australian Business Number (ABN) unit or Type of Activity Unit (TAU). Each statistical unit is classified to an industry which reflects the predominant activity of the business. The collection and reporting units used in the survey usually correspond to the statistical unit. However, where the ABN/TAU unit is unable to provide information required for the survey, it may be split into a number of 'reporting units'. For further information on statistical units used in ABS business surveys, refer to Chapter 23.
In the second stage, businesses selected in the first stage are asked to select a random sample of employees from their payrolls using instructions provided by the ABS.
First stage sample selection
A probability sample of employing businesses (ABN/TAU units) is drawn from the ABS Business Register using the process outlined in Chapter 23. Variables used to stratify the survey frame at stage one of the sample selection are:
Strata on the survey frame that are completely enumerated include those containing selection units with benchmark employment greater than a set cut off (this cut off will vary for different states/territories), and strata with a very small number of selection units in the population.
In addition to constraints outlined in Chapter 23, sample selection is constrained by the need to minimise overlap with the quarterly Survey of Average Weekly Earnings (AWE), for businesses with less than 20 employees.
Second stage sample selection
Second-stage sampling units (employees) are selected using systematic sampling within selected first-stage units. A random start and a skip are provided to each selected business for use in selecting the second-stage sample from its payroll(s). Businesses are not required to order their payroll in any particular way when selecting the sample.
Sample size and allocation
For the first-stage sample, approximately 8,200 employer (selection) units are selected to yield a live sample of approximately 7,500 units.
For the second-stage sample, approximately 53,000 employees contribute to the estimates. The maximum number of employees for any reporting unit is 40.
The ABS reselects the sample for the EEH each time it is conducted. At the same time, the overall design of the sample is examined to ensure that it remains efficient.
The estimation process occurs in two stages. In the first stage, number raised estimation is used to estimate the number of employees in each business. In the second stage, number raised estimation is again used to estimate the total number of businesses, and therefore employees, in the target population.
In the sampled strata, the Live Respondent Mean method is used to impute for non-responding businesses. In the completely enumerated strata, a ratio imputation model is used.
Survey outliers are handled using the 'surprise outlier' technique.
Business Provisions were introduced in the 2000 survey, whereby adjustments are made to survey estimates to allow for births and deaths of businesses that have occurred up to the end of the survey reference period, but which are not reflected on the survey frame.
For further information on estimation methods used in ABS business surveys, refer to Chapter 23.
TIME SERIES ESTIMATES
Seasonally adjusted and trend estimates are not produced for this survey.
RELIABILITY OF THE ESTIMATES
Estimates from the survey are subject to both sampling and non-sampling errors. The standard errors of survey estimates are published in Employee Earnings and Hours, Australia (cat. no. 6306.0).
The Bootstrap method is used to calculate estimates of variance for this survey. The Bootstrap is a variance estimation method which relies on the use of replicate samples, essentially sampling from within the main sample. Each of these replicate samples is then used to calculate a replicate estimate and the variation in these replicate estimates is used to calculate the variance of a particular estimate.
COMPARABILITY WITH OTHER SURVEYS
The ABS produces earnings statistics from a number of different sources, including both household and employer surveys. The three main employer-based surveys that provide earnings statistics are the EEH survey, the AWE survey and Survey of Employment and Earnings (SEE). The main household-based surveys providing earnings statistics are the Characteristics of Employment Survey (COE) and the Survey of Income and Housing (SIH).
Caution should be exercised when comparing estimates of earnings in the EEH release with estimates of earnings included in the biannual Average Weekly Earnings, Australia (cat. no. 6302.0) and the annual Characteristics of Employment (cat. no. 6333.0) publications. There are important differences in the scope, coverage and methodology of these surveys, which can result in different estimates of earnings from each survey.
The EEH survey collects payroll information about weekly earnings and hours paid for, and the individual characteristics of a sample of employees within each selected employer unit. The AWE survey collects payroll information from employers who provide details of their employees' total gross earnings and their total number of employees. In contrast, COE compiles data from a household-based survey where respondents are either the employed person or another adult member of their household who responds on their behalf. Where earnings are not known exactly, an estimate is reported.
In the EEH, salary sacrificed amounts have been included in the estimates of mean and median weekly earnings from 2006 onwards, whereas the earnings series from AWE historically excluded amounts salary sacrificed. However, since the May 2011 AWE publication the Average Weekly Cash Earnings (AWCE) series has also been released. This series is inclusive of salary sacrificed amounts. 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. From 2007, COE (and its predecessor) have included amounts salary sacrificed in the estimates of mean and median weekly earnings.
There are also scope differences between both household and employer surveys. For example, AWE and EEH exclude employees in the Agriculture, Forestry and Fishing industry, and also employees of private households, whereas these employees are included in the COE survey.
For further information on a number of earnings series available from ABS sources, and the differences between source surveys, please refer to the feature article 'Understanding Earnings in Australia Using ABS Statistics' published in Australian Labour Market Statistics, July 2014 (cat. no. 6105.0).
Employee Earnings and Hours and Average Weekly Earnings
The AWE survey provides estimates of the level of average earnings at a point in time. The six-monthly estimates are used to provide a level benchmark against which a specific amount can be compared, e.g. what an individual earns compared to the average. Average earnings estimates are available by state/territory, sex, industry and sector.
Compared with the EEH survey, the AWE survey provides more frequent but less detailed information on the composition and distribution of employee earnings. Unlike EEH, AWE data are collected at the business level: the AWE survey collects total/aggregate payroll data, while the EEH survey collects detailed information about a sample of employees within the business.
Although there are differences in concepts, survey design and methodology between the surveys, there is sufficient overlap such that EEH survey data can be considered a complement to AWE survey estimates (AWE is released earlier). When comparing EEH data with AWE data, ensure the Average Weekly Cash Earnings series is used as these series are most closely aligned.
For more information on understanding EEH statistics, see the feature article in 'A Guide to Understanding Employee Earning and Hours Statistics' in Employee Earnings and Hours, Australia, May 2016 (cat. no. 6306.0).
DATA COMPARABILITY OVER TIME
Caution should be exercised when comparing data between different years as EEH is not designed as a time series. Changes to survey methods, survey concepts, data item definitions, frequency of collection, and methods of time series analysis, are made as infrequently as possible. Key changes have included:
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