6311.0 - Information Paper: Construction of Experimental Statistics on Employee Earnings and Jobs from Administrative Data, Australia, 2011-12  
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SUMMARY OF RESULTS

OVERVIEW

The LEED Foundation Projects have produced experimental statistics on employees and earnings for the 2011-12 financial year. The key findings are:

    • there were 10.3 million employees;
    • the median and mean earnings for all employees were $45,869 and $55,678 respectively;
    • there were 5.4 million male employees (52%) and 5.0 million female employees (48%);
    • the median and mean earnings for males were $55,470 and $66,994 respectively, while for females they were $37,726 and $43,489.

The LEED Foundation Projects experimental statistics provide new information on jobs and multiple job holders for the 2011-12 financial year which is not currently available from ABS statistics. The key findings are:
    • there were 13.3 million jobs;
    • the median and mean gross payments received for all jobs were $26,134 and $37,961 respectively;
    • there were 6.8 million jobs held by males (51%) and 6.5 million by females (49%);
    • the median and mean gross payments for males were $34,495 and $46,386 respectively, while for females they were $20,429 and $29,161;
    • there were 1.9 million multiple job holders (individuals with two or more concurrent jobs) whose median and mean earnings were $38,892 and $49,875 respectively, and of which 53% were female and 47% were male.

The LEED Foundation Projects experimental statistics are based on administrative data and may include non-sampling error. There are a number of data considerations that users should be aware of when interpreting or analysing the experimental statistics (see Explanatory Notes, paragraphs 31-69).

DISTRIBUTION OF EMPLOYEES & EARNINGS

In the 2011-12 financial year there were 5.4 million male employees with median and mean earnings of $55,470 and $66,994 respectively. There were a total of 5.0 million female employees with median and mean earnings of $37,726 and $43,489 respectively.

Age and sex

For both male and female employees, the median earnings in all age groups are less than the mean earnings, reflecting positively skewed earnings distributions. Employees aged between 25 and 29 years were the largest group (1.3 million) and had the lowest difference (6.6%) between their median and mean earnings ($45,215 and $48,193 respectively). This indicates that employee earnings in this age group were less skewed compared to other age groups in the distribution. In most age groups, earnings were relatively more skewed for male employees than for female employees, however in the 35 to 39 years age group, earnings were more skewed for female employees (17% difference) than for male employees (15% difference).

Median and mean earnings for the 25 to 29 years age group differ from the median and mean earnings for the 45 to 49 years age group. For males, they differ by $22,053 and $33,535 respectively, while for females they differ by $2,817 and $8,602 respectively. For male employees, median earnings begin to decrease in the 45 to 59 years age group, while mean earnings begin to decrease in the 50 to 54 years age group. For female employees, median earnings begin to decrease in both the 35 to 39 and the 55 to 59 years age groups and mean earnings begin to decrease in the 55 to 59 age group. For further information, see the Aggregate Experimental Statistics Data Cube, Table 1 in the Downloads tab.

Graph 1: Number of employees and earnings in all jobs, by age group and sex, 2011-12

Graph 1 shows the distribution of employees, their median and mean earnings, by age group and sex


State and territory

In the 2011-12 financial year, New South Wales had the highest number of employees (30.8%), followed by Victoria (24.5%) and Queensland (20.0%). The Australian Capital Territory and Western Australia had the highest mean earnings ($64,685 and $62,732 respectively). However, median earnings for Western Australia ($50,285) were 25% lower than the mean, while in the Australian Capital Territory median earnings ($59,523) were 9% lower, reflecting different skewness in the earnings distribution. For further information, see the Aggregate Experimental Statistics Data Cube, Table 1 in the Downloads tab.

Graph 2: Number of employees and earnings in all jobs, by state and territory, 2011-12

Graph 2 shows the distribution of employees, their median and mean earnings, by state and territory


Occupation

Among all major occupation categories, Professionals had the highest median earnings ($67,512) followed by Managers ($66,652). However, Managers’ mean earnings ($85,286) were 28% higher than their median, while Professionals’ mean earnings ($75,541) were 12% higher. This reflects a more skewed earnings distribution for Managers than Professionals. For further information, see the Aggregate Experimental Statistics Data Cube, Table 1 in the Downloads tab.

Graph 3: Number of employees and earnings in all jobs, by occupation in main job, 2011-12

Graph 3 shows the distribution of employees, their median and mean earnings, by occupation in main job


Industry

Health care and social assistance had the highest number of employees (11%) followed by Retail trade (8.7%) and Education and training (8.4%). Employees in Mining had the highest median and mean earnings ($114,053 and $124,589 respectively), followed by Electricity, gas, water and waste services (median $78,730 and mean $85,235). On the other hand, Accommodation and food services had the lowest median and mean earnings ($22,012 and $27,549 respectively). Employees in Finance and insurance services had the most skewed earnings data, with a 40% difference between median and mean earnings ($53,530 and $74,892 respectively). In contrast, employees in Public administration and safety had the least skewed earnings data, with a 4% difference between their median and mean earnings ($63,632 and $66,317 respectively). For further information, see the Aggregate Experimental Statistics Data Cube, Table 1 in the Downloads tab.

Graph 4: Number of employees and earnings in all jobs, by industry of main job, 2011-12

Graph 4 shows the distribution of employees, their median and mean earnings, by industry of main job


DISTRIBUTION OF JOBS & GROSS PAYMENTS

As a result of the LEED Foundation Projects, the ABS is able to produce experimental statistics on filled jobs for the first time.

In the 2011-12 financial year there were 13.3 million jobs in Australia. The median gross payment for all jobs was $26,134 and the mean was $37,961. Approximately 51% of all jobs were occupied by males, with median and mean gross payments of $34,495 and $46,386 respectively. Approximately 49% were occupied by females, with median and mean gross payments of $20,429 and $29,161 respectively.

Age and sex

Male employees had higher gross payments in all jobs across all age groups. Their highest median and mean gross payments were in the 45 to 49 years age group ($53,497 and $64,904 respectively), whereas for females they were in the 50 and 54 years age group ($30,436 and $36,357 respectively). The gross payments were relatively more skewed for female employees aged between 25 and 44 years than for male employees. For further information, see the Aggregate Experimental Statistics Data Cube, Table 2 in the Downloads tab.

Graph 5: Number of jobs and gross payment, by age group and sex, 2011-12

Graph 5 shows the distribution of jobs, median and mean gross payments, by age group and sex

State and territory

There were 4.0 million jobs in New South Wales (30%), followed by 3.2 million in Victoria (24%) and 2.7 million in Queensland (20%). As for earnings, the highest mean gross payments were in the Australian Capital Territory ($45,276) followed by Western Australia ($41,138). The median gross payment for Western Australia ($26,354) was 36% lower than the mean, while in the Australian Capital Territory the median gross payment ($34,520) was 24% lower, reflecting different skewness in the gross payments distribution. For further information, see the Aggregate Experimental Statistics Data Cube, Table 2 in the Downloads tab.


Graph 6: Number of jobs and gross payment, by state and territory, 2011-12

Graph 6 shows the distribution of jobs, median and mean gross payments, by state and territory


Industry

Health care and social assistance had the highest number of jobs (11%) followed by Retail trade (9.2%) and Education and training (9.1%), mirroring the number of employees (see Graph 4). Jobs in the Mining industry had the highest median gross payments ($73,645) followed by those in Electricity, gas, water and waste services ($66,158). For further information, see the Aggregate Experimental Statistics Data Cube, Table 2 in the Downloads tab.

Graph 7: Number of jobs and gross payment, by industry, 2011-12

Graph 7 shows the distribution of jobs, median and mean gross payments, by industry

Sector and employment size

The Private sector had 78% of all jobs, with the remaining 22% in the Public sector. Public sector employees had higher gross payments. In the 2011-12 financial year, approximately 50% of jobs were in businesses with 200 or more employees, and employees in these large businesses had the highest median and mean gross payments. For further information, see the Aggregate Experimental Statistics Data Cube, Table 2 in the Downloads tab.

Table 2: Number of jobs and gross payment, by type of legal organisation and employment size, 2011-12
Number of jobs
Median gross payment
Mean gross payment
('000)
$
$

Type of legal organisation
Private sector entities
10 434.9
23 309
36 290
Public sector entities
2 865.0
38 971
44 069
Employment size
Fewer than 5 employees
1 423.0
16 640
27 727
5-19 employees
2 008.8
18 279
28 701
20-199 employees
3 276.9
21 383
33 588
200 or more employees
6 595.1
35 066
45 192


Multiple job holders

There were 1.9 million employees who had multiple (concurrent) jobs at any point during the 2011-12 financial year. Of these, 53% were female and 47% were male. Approximately 73% of the multiple job holders had two concurrent jobs, while 24% had three to four concurrent jobs during the financial year. For further information, see the Aggregate Experimental Statistics Data Cube, Table 3 in the Downloads tab.


Graph 8: Number of multiple job holders and earnings in all jobs, by sex, 2011-12

Graph 8 shows the distribution of multiple job holders, their median and mean earnings, by number of concurrent jobs and sex



The graph below compares the distribution of industry of first job for multiple job holders (the job with highest gross payment among concurrent jobs) with industry of main job for all employees (the job with highest gross payment).

The distribution of the industry of first job for multiple job holders differs from the industry of main job for all employees. Health care and social assistance, Education and training, and Administrative and support services were the industries in which multiple job holders were most concentrated (14%, 12% and 10% respectively). However, employees were less concentrated in these same industries (11%, 8.4% and 6.5% respectively). For further information, see the Aggregate Experimental Statistics Data Cube, Table 4 in the Downloads tab.


Graph 9: Prevalence of multiple job holding by industry, 2011-12

Graph 9 compares the distribution of industry of first job for multiple job holders with industry of main job for all employees.


LIMITATIONS OF THE EXPERIMENTAL STATISTICS

The construction of the experimental statistics on employee earnings and jobs identified a number of data considerations which need to be taken into account when interpreting these statistics. These include using information as defined by and reported to the ATO; earnings being comprised only of reported amounts; multiple job holder status being determined on reported dates information; and the allocation of industry for jobs in profiled businesses being contingent on the ABN to TAU mapping.

Care should be taken when interpreting or analysing the experimental statistics For further information on data considerations see Explanatory Notes (paragraphs 31-69).


COHERENCE OF EXPERIMENTAL STATISTICS WITH ABS SURVEY COLLECTIONS

Overall, the experimental statistics were found to be broadly coherent with current ABS household and business survey estimates. However, some differences were identified between the experimental statistics and survey estimates due to differences in scope, sample design, collection methodology and processing approaches. Moreover, the Integrated Dataset used to construct the experimental statistics is based on data collected for administrative purposes, whereas ABS collections are explicitly designed to create statistical outputs.

For further information on the coherence of the experimental statistics with ABS estimates see Appendix 2 and Explanatory Notes (paragraphs 74-77).