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SURVEY OF AVERAGE WEEKLY EARNINGS
Earnings in AWE are broadly defined as current and regular payments in cash to employees for work done. Earnings series from the AWE survey have historically excluded amounts salary sacrificed, as these were considered payments in kind. Under the conceptual framework for measures of employee remuneration, as revised in 2006 in Information Paper: Changes to ABS Measures of Employee Remuneration (cat. no. 6313.0), amounts salary sacrificed are now considered conceptually to be wages and salaries in cash, with information collected on this basis from August 2007. Time series inclusive of salary sacrifice were first published in the May 2011 issue of Average Weekly Earnings, Australia (cat. no. 6302.0), with the time series available back to May 2010. This is an additional (not replacement) series, and the ABS continues to publish the AWE series on the former basis (i.e. exclusive of amounts salary sacrificed) to maintain long term comparability of the time series.
Estimates of the annual percentage change for average earnings are published for each key series. Estimates from the survey are cross-classified by sector, state or territory, and by industry at the Australian level for males, females and persons.
Estimates are published on the following bases: original; seasonally adjusted; and trend (see Chapter 16 for further explanation of original, seasonally adjusted and trend estimates). Seasonally adjusted and trend estimates are available by Australia and State/Territory for each of the three main series listed above. Series which have no identifiable seasonal component are not seasonally adjusted.
Data collected in the survey are compiled according to concepts and definitions outlined in Chapter 4: Employment and Chapter 11: Employee Remuneration.
The scope of the survey is restricted to employing businesses. The standard scope exclusions for ABS labour-related business surveys (outlined in Chapter 23) apply to this survey.
The following persons are not regarded as employees of the sampled business for the purposes of this survey, and are excluded:
Details of numbers of employees (full-time adults and other employees), total gross weekly earnings (for full-time adults and other employees), and weekly overtime earnings of full-time adults are obtained on a biannual basis from a sample survey of employer units, using an online electronic collection methodology. Businesses which do not submit their questionnaire within a reasonable period of time after the survey reference period are followed up by mail and then phone if necessary. The target minimum response rate is 93% for the survey as a whole, and 90% for each state, sector and industry.
The survey reference period is the week ending the third Friday of the month in May and November. Due to the wide variety of pay arrangements and systems which exist, most employers are not able to report for this exact period. Therefore, employers are requested to report for the last pay period ending on or before this date, and where a pay period is greater than one week (e.g. fortnightly or monthly) the employer is requested to report only one week's proportion.
Although the historical estimates of earnings from the AWE survey (as well as current information provided on the same basis) should exclude amounts salary sacrificed, in practice there is evidence that some amounts salary sacrificed are sometimes inadvertently included. The ABS works closely with data providers to identify any instances of misreporting, and to amend their reporting practices where necessary.
A probability sample of employing business units is drawn from the ABS Business Register using the process outlined in Chapter 23. Variables used to stratify the survey frame each period are:
Strata on the survey frame that are completely enumerated include those containing business 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 employing business units. Strata which are completely enumerated because they contain a low number of business units may become sampled strata if the number of such units in those strata increases sufficiently.
In addition to constraints outlined in Chapter 23, sample selection is constrained by the need to ensure that there is minimum overlap with other labour-related business surveys, and with non-labour related business surveys.
SAMPLE SIZE AND ALLOCATION
Approximately 5,700 business units are selected in the sample, to yield a live sample of approximately 96% for the survey as a whole and 90% for each state, sector and industry.
The sample is allocated optimally across sampled strata using a technique designed to minimise the variance of AWE estimates at both the national and state/territory level.
The sample is updated each period to reflect changes in the ABS Business Register. Approximately 16% of the sample selected from the non-completely enumerated strata is replaced each period. Refer to Chapter 23 for further information.
Sample rotation is implemented for the majority of sampled strata, but is not implemented where the population of a stratum is so small that units rotating out of the sample would be rotated back in after only a short interval.
Estimates of total weekly earnings and number of employees are computed for various combinations of state or territory, sector and industry. AWE measures are the quotient of the respective earnings and employment measures. Ratio estimation is used in all sampled strata, except in small sized strata, in which case number raised estimation is used.
In both completely enumerated and sampled strata an automatic imputation procedure is used for units not responding, by applying imputed growth rates to the most recently reported employment and earnings data for these units, provided that data have been reported in a previous period. This is referred to as Beta imputation. Otherwise, the Live Respondent Mean method is used to impute for missing data items.
Significance editing was introduced in September 1992. This technique means that editing is only performed on those survey values which will significantly impact on the survey estimate if left unaltered.
Prior to May 2014, survey outliers were handled by using the 'surprise outlier' technique. From May 2014, the winsorisation methodology was introduced as the primary method to treat outliers in AWE. Winsorisation moderates the impact of an outlier business without the harsh impact of the surprise outliering approach. For more information, refer to Chapter 16.
TIME SERIES ESTIMATES
Both seasonally adjusted and trend estimates are produced for key series from this survey.
Seasonally adjusted estimates were introduced from September 1983. The change in frequency in 2012 resulted in a new seasonally adjusted series from May 2012. While seasonal factors remain present in AWE and can be calculated on a biannual basis, calculating seasonally adjusted estimates using only two points of measurement each year, rather than the four points available in a quarterly survey, resulted in a change in the level of the series. For more information, refer to Information Paper: Changes to Average Weekly Earnings, Australia, April 2012 (cat. no. 6302.0.55.002).
Trend estimates were introduced from August 1993. As a result of the change in frequency in 2012, a new trend series was produced, commencing in May 2012. For more information, refer to Information Paper: Changes to Average Weekly Earnings, Australia, April 2012 (cat. no. 6302.0.55.002).
RELIABILITY OF THE ESTIMATES
Estimates from the survey are subject to both sampling and non-sampling error (see Chapter 16 for further information). The relative standard errors of survey estimates are published in Average Weekly Earnings, Australia (cat. no. 6302.0).
The Bootstrap approach 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 AWE, the Survey of Employee Earnings and Hours (EEH), and the 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).
The AWE survey collects payroll information from employers who provide details of their employees' total gross earnings and their total number of employees. The EEH survey provides statistics on the composition and distribution of employee earnings, hours paid for and methods used to set employees' pay in Australia. The SEE is designed to measure the number of wage and salary earners and their gross earnings for the public sector. 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. The SIH provides detailed estimates of household income and wealth collected from individual households. In the SIH, the largest component of household income is employee income.
Caution should be exercised when comparing estimates of earnings between different employer based labour surveys, different household based labour surveys, or between employer based and household based surveys. There are important differences in the scope, coverage and methodology for each of these surveys, which can result in different estimates of earnings from each survey. For example, AWE and EEH exclude employees in the Agriculture, Forestry and Fishing industry, and also exclude 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, 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).
AVERAGE WEEKLY EARNINGS AND WAGE PRICE INDEX
The six monthly AWE and quarterly Wage Price Index (WPI) collections both measure the wages and salaries of employees, although they aim to measure different, albeit related, concepts. For more information on the purpose and key uses of AWE and WPI, see the feature article 'Average Weekly Earnings and Wage Price Index - What do they measure?' in Average Weekly Earnings, Australia, May 2014 (cat. no. 6302.0).
Average Weekly Earnings and Employee Earnings and Hours
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. Collecting data at the aggregate level requires fewer resources than data at the employee level, but provides less flexibility and detail in the data it provides. Data obtained on the total earnings and the total number of employees in the selected businesses are used to derive the mean, or average, earnings. As information on hours paid are not collected, AWE cannot provide hourly rates of pay. It can also only provide data for the limited number of groupings of employees (male / female, full-time adult and all employees) that are collected from businesses in the survey.
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
In order to provide a high degree of consistency and comparability over time, changes to survey methods, survey concepts, data item definitions, frequency of collection, and methods of time series analysis, are made as infrequently as possible. However, there have been some significant changes which are outlined below:
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