The Labour Force Outlook in the
Minerals Resources Sector:
2005 to 2015
Rep ort pr ep a r ed f or t he Miner als Industry
National Skills Sho rt a g e St rat eg y
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CONTENTS
1.
EXECUTIVE SUMMARY....................................................................................................................................4
1.1.
2.
PURPOSE OF THE REPORT .............................................................................................................................6
PROJECTING THE DEMAND FOR LABOUR: DATA SOURCES & METHOD...................................8
2.1.
OUTLINE OF THE DATA SOURCES AND METHOD USED ...........................................................................8
3.
OVERVIEW OF LABOUR DEMAND 2015 ...................................................................................................11
4.
OCCUPATIONS AND SKILLS REQUIRED IN 2015 ..................................................................................16
4.1.
4.2.
5.
OCCUPATIONAL STRUCTURE IN THE RESOURCES SECTOR .................................................................16
BROAD OCCUPATIONS REQUIRED IN EACH OF THE COMMODITIES ....................................................20
CAPACITY OF THE ECONOMY TO RESPOND TO GROWING DEMAND FOR LABOUR..........35
5.1.
5.2.
5.3.
5.4.
5.5.
6.
INTRODUCTION .............................................................................................................................................35
LIMITATIONS OF THE ANALYSIS ................................................................................................................35
AUSTRALIAN LABOUR FORCE TRENDS ....................................................................................................36
PROJECTIONS OF EMPLOYEES IN OCCUPATIONAL CATEGORIES .........................................................39
DEMAND-SUPPLY RATIOS ...........................................................................................................................44
CONCLUSIONS AND RECOMMENDATIONS ...........................................................................................53
6.1.
6.2.
SKILLS SHORTAGE OR PEOPLE SHORTAGE? ...........................................................................................54
RECOMMENDATIONS ...................................................................................................................................54
7.
APPENDIX A ........................................................................................................................................................56
8.
APPENDIX B ........................................................................................................................................................59
8.1
8.2
8.3
9.
CALCULATING THE BASE EMPLOYMENT DATA SET ...............................................................................59
CALCULATING PROJECTED EMPLOYMENT DEMAND ..............................................................................61
DISTRIBUTING PROJECTED DEMAND BY OCCUPATIONAL CLASSIFICATIONS AND MINE ACTIVITY
...........................................................................................................................................................................61
APPENDIX C ........................................................................................................................................................62
9.1.
9.2.
10.
EMPLOYMENT SHARE PROJECTION: GROWTH CURVE MODELS ..........................................................62
DATA AND SOURCES ....................................................................................................................................63
REFERENCES....................................................................................................................................................64
LIST OF TABLES
TABLE 1:
TABLE 2:
TABLE 3:
TABLE 4:
OUTPUT AND EMPLOYMENT, DATA USED FOR EMPLOYMENT PROJECTIONS .............................14
PERCENTAGE OF EMPLOYMENT CHANGE IN 2015 .............................................................................15
OCCUPATIONAL STRUCTURE BY COMMODITY COMPARED TO ARGUS MODEL ..........................17
PROJECTED ECONOMY-WIDE EMPLOYMENT IN OCCUPATIONAL CATEGORIES (NO. OF
PERSONS)....................................................................................................................................................40
TABLE 5: PROJECTED EMPLOYMENT AND DEMAND IN OCCUPATIONAL CATEGORIES: GROWTH RATES 43
TABLE 6: ECONOMY-WIDE CAPACITY TO RESPOND TO DEMAND FOR LABOUR FROM THE RESOURCE
SECTOR .......................................................................................................................................................52
2
LIST OF FIGURES
FIGURE 1: ESTIMATED EMPLOYED PERSONS IN MINING INDUSTRY (TO 2010) .............................................11
FIGURE 2: ACTUAL AND PROJECTED VACANCIES IN MINING (2000 – 2010) ...................................................12
FIGURE 3: TRENDS OF ANNUAL PERCENTAGE CHANGES ..................................................................................13
FIGURE 4: STATE LABOUR DEMAND IN 2005 - 2015.............................................................................................15
FIGURE 5: OCCUPATIONAL STRUCTURE BY SIX COMMODITIES FOR 2015 .....................................................18
FIGURE 6: OCCUPATIONAL STRUCTURE BY THREE COMMODITIES FOR 2015 ...............................................19
FIGURE 7A : COAL - PROJECTED EMPLOYMENT GROWTH AND OCCUPATIONAL STRUCTURE ...................20
FIGURE 7B : COAL - OCCUPATIONAL DISTRIBUTION BY OPERATIONAL ACTIVITY .......................................21
FIGURE 8A : IRON ORE - PROJECTED EMPLOYMENT GROWTH AND O CCUPATIONAL STRUCTURE IN 2015
..................................................................................................................................................................22
FIGURE 8B : IRON - OCCUPATIONAL DISTRIBUTION BY OPERATIONAL ACTIVITY ........................................23
FIGURE 9A : GOLD - PROJECTED EMPLOYMENT ...................................................................................................24
FIGURE 9B : GOLD - OCCUPATIONAL DISTRIBUTION BY OPERATIONAL ACTIVITY ......................................24
FIGURE 10A: BAUXITE - PROJECTED EMPLOYMENT ...........................................................................................25
FIGURE 10B: BAUXITE - OCCUPATIONAL D ISTRIBUTION BY OPERATIONAL ACTIVITY ..............................26
FIGURE 11A: COPPER - PROJECTED EMPLOYMENT ..............................................................................................27
FIGURE 11B: COPPER - OCCUPATIONAL D ISTRIBUTION BY OPERATIONAL ACTIVITY .................................27
FIGURE 12A: NICKEL - PROJECTED EMPLOYMENT ..............................................................................................28
FIGURE 12B: NICKEL - OCCUPATIONAL D ISTRIBUTION BY OPERATIONAL ACTIVITY .................................29
FIGURE 13A: ZINC - PROJECTED EMPLOYMENT ...................................................................................................29
FIGURE 13B: ZINC - OCCUPATIONAL DISTRIBUTION BY OPERATIONAL ACTIVITY ......................................30
FIGURE 14A: LEAD - PROJECTED EMPLOYMENT ..................................................................................................31
FIGURE 14B: LEAD - OCCUPATIONAL D ISTRIBUTION BY OPERATIONAL ACTIVITY .....................................32
FIGURE 15A: URANIUM - PROJECTED EMPLOYMENT ..........................................................................................33
FIGURE 15B: URANIUM - OCCUPATIONAL DISTRIBUTION BY OPERATIONAL ACTIVITY .............................34
FIGURE 16: TOTAL WORKING AGE POPULATION AND A NNUAL PERCENTAGE CHANGE , AUSTRALIA 1990
TO 2015....................................................................................................................................................36
FIGURE 17: SHARES OF POPULATION , BY AGE GROUP , AUSTRALIA 1990 TO 2020.......................................37
FIGURE 18: LABOUR FORCE PARTICIPATION RATES IN AUSTRALIA , BY SEX (JANUARY 2005). .................38
FIGURE 19: GROWTH OF THE LABOUR FORCE, AUSTRALIA 2002-2020. ..........................................................39
FIGURE 20: PROJECTED EMPLOYMENT IN OCCUPATIONAL CATEGORIES: GROWTH RATES .......................40
FIGURE 21: PROJECTED ANNUAL GROWTH RATES ..............................................................................................41
FIGURE 22: GAP BETWEEN DEMAND AND SUPPLY : NUMBER OF PERSONS.....................................................42
FIGURE 23: GAP BETWEEN DEMAND AND SUPPLY : NUMBER OF PERSONS.....................................................43
FIGURE 23: GAP BETWEEN DEMAND AND SUPPLY : NUMBER OF PERSONS.....................................................43
FIGURE 24: GROWTH RATES BY OCCUPATIONAL CLASSIFICATION. ................................................................44
FIGURE 25: DEMAND SUPPLY RATIO, BY OCCUPATIONAL CATEGORIES: ALL COMMODITIES..................45
FIGURE 26: DSR, BY OCCUPATIONAL CATEGORIES: COAL. ...............................................................................46
FIGURE 27: DSR, BY OCCUPATIONAL CATEGORIES: IRON ORE.........................................................................47
FIGURE 28: DSR, BY OCCUPATIONAL CATEGORIES: BAUXITE ..........................................................................47
FIGURE 29: DSR, BY OCCUPATIONAL CATEGORIES: COPPER. ...........................................................................48
FIGURE 30: DSR, BY OCCUPATIONAL CATEGORIES: NICKEL. ...........................................................................48
FIGURE 31: DSR, BY OCCUPATIONAL CATEGORIES: GOLD ................................................................................49
FIGURE 32: DSR, BY OCCUPATIONAL CATEGORIES: URANIUM ........................................................................50
FIGURE 33: DSR, BY OCCUPATIONAL CATEGORIES: LEAD ................................................................................51
FIGURE 34: DSR, BY OCCUPATIONAL CATEGORIES: ZINC .................................................................................51
3
1.
EXECUTIVE SUMMARY
This study projected the demand for labour in key occupational groups required by
the mineral resources sector for nine major commodities in Australia from 2006 to
2015. The labour demand projections are based on mineral output projections for the
major commodities to 2015, supplied by BIS Shrapnel (2005). In addition to projecting
labour demand in the resources sector, the project examined the capacity of the
economy to respond to increases in demand.
Our projections indicate a significantly increased demand for labour in the resources
sector leading up to 2015. Key findings include the following:
•
To achieve currently predicted increases in output, the resources sector will
need to employ 70,000 more workers than it currently employs, by 2015;
•
The largest shortages are projected to be in the non-professional occupational
classifications with the greatest absolute increases being in tradespersons
(26,983 additional workers required) and semi-skilled workers (22,058
additional workers required);
•
Our projections of economy-wide employment (our indicator of the potential
for supply response) in these non-professional occupational categories
indicate that they are likely to be the slowest growing, indicating that the
minerals industry will need to attract a greater share of people in these
occupational categories;
•
The fastest growing demand for workers will be in copper, nickel, bauxite and
potentially uranium mining;
•
Of the 70,000 additional employees required, almost 42,000 will be required in
Western Australia, almost 15,000 in Queensland, and approximately 5,000 in
both New South Wales and South Australia;
•
The output projections we have used indicate the fastest growth between
2006 and 2010. There is therefore the potential for a rapid onset of significant
labour shortages. Further, these shortages will continue to worsen as the
growth rate of projected labour demand remains above the capacity of the
labour market to respond.
Our findings indicate that labour shortages are likely to be a major constraint on the
growth of the mineral sector over the next decade. The resources sector clearly needs
a continuing and vigorous program to attract and retain labour in the identified areas
of skill shortages. Given that the projected demand supply gaps are largest in
occupational classifications with low skill levels, the labour shortage problem
identified here in the resources sector is not one that training policy can necessarily
4
address. It is more a matter of attracting people to the industry, in other words, what
the sector is facing is a people shortage, not necessarily a skills shortage per se.
Against this backdrop, we make the following recommendations:
•
It is common knowledge that the resources sector faces labour supply
shortages, however, the extent and composition of the shortages have been
less widely understood. The industry needs to promote a broader
understanding of these aspects of the labour shortage in order to encourage
broader support for policies to deal with the problem;
•
The identified demand gaps suggest that there may be pressure on
compression of wage differentials especially between professional and nonprofessional employees, and that the sector investigate ways it can
accommodate such changes in income differentials;
•
The finding that the projected shortages will be most acute in the area of
semi-skilled employees suggests that a heightened focus on the development
of appropriate training systems is required, with a particular emphasis on
designing systems for quality on-the-job training provision. This means
ensuring the identification and cultivation of appropriate in-house trainers as
well as the design of appropriate on-the-job training evaluation systems;
•
The shortfall of workers is so large that all alternative labour reservoirs need
to be identified and targeted. One alternative labour reservoir is the
manufacturing sector, which is projected to experience a further decline in
non-professional occupational categories over the next decade. This decline is
likely to result in a pool of available labour with broadly compatible skill sets
to that required by the resources sector. For this source of labour to be
accessed by the resources sector, there are significant locational issues to be
overcome;
•
Women also constitute an alternative labour pool for the resources sector.
Crucial challenges associated with targeting women are likely to be ensuring
the provision of childcare in remote locations, the design of family friendly
policies including flexible rosters, and changing the traditionally ‘masculine
culture’ associated with mining;
•
Another labour reservoir lies in the rural, regional and remote communities,
including indigenous communities, in close proximity to many of the mine
sites. This raises a number of fundamental issues related to attraction,
provision of training, and retention;
•
Importing labour from outside of Australia is another option, but we
emphasise that the numerous long-term implications of this must be
5
investigated and such a strategy should not replace growing our own
workforce locally;
•
We believe it is in the resources sector interest to develop an understanding
and expertise in determinants of labour supply in the Australian economy.
This means understanding not only the economic data, but deeper socioeconomic trends that underpin the supply of labour, particularly in nonprofessional occupational groups.
1.1. Purpose of the Report
The purpose of this study is to project the key skills required by the mineral resources
sector for major commodities in Australia from 2006 to 2015. The review is based on
predicted production levels for the major commodities to 2015, supplied by BIS
Shrapnel (2005). In addition, to projecting the demand for skills, the project examines
the capacity of the economy to respond to increased future labour demand from the
resources sector.
The project covers all regions and States of Australia for the nine major commodities
of iron ore, coal, bauxite/alumina, gold, nickel, lead/zinc, copper and uranium,
spanning the operational activities of exploration, open-pit mining, underground
mining, processing and maintenance. In terms of skill levels and skill types, the
objective of the project is to gain an understanding of occupational classifications to
trade level, including technicians. The coverage of this report however encompasses
the six broad occupational categories that constitute the vast majority of all
employees in the minerals industry. This broader coverage has involved no
compromise in the detail of coverage for the non-professional occupational
classifications which we intended as the main focus of the report. Focussing only on
non-professionals would have provided an incomplete analysis in terms of capturing
the relativities and distinctiveness of issues across occupational groups. For example,
one of the main conclusions that have emerged is that the labour supply problem
appears fundamentally different in character and extent in the non-professional
occupations compared with the professional occupations and this is in our view a
critical guide to strategic responses.
It should be noted that available detailed data on actual skills (at the job level)
required by different commodities in the resources sector in Australia is scant. In this
report we use occupational classification as a proxy for skill, on the assumption that
each occupational classification involves an implied and broadly known skill set.
Based on the BIS Shrapnel data, the scope of our review involved providing answers
to the following key questions:
6
•
For each State and for each major commodity what is the projected demand
for labour over the next 10 years?
•
What are the key skills that will be required in each of the main commodities
and different operational activities over the next 10 years?
•
What is the projected supply of labour at a national level to 2015, and how
does this compare to projected labour demand within the minerals resources
sector?
The report is organised into 6 remaining sections. The next section presents an outline
of the methodology and assumptions used in calculating the employment estimates,
with a more detailed explanation of the methodology and assumptions provided in
Appendix B and C. Based on the BIS Shrapnel forecasts, Section 3 explores the
different commodity groups and provides an overview of employment growth to
2015. Section 4 provides information on the number of people required in the sector
by 2015, broken down by the major commodity groups and operational activities,
and skills that are likely be required. The capacity of the economy-wide labour
market (our indicator of supply) to respond to the demand for labour within the
minerals resources sector is explored in Section 5. Finally, conclusions are drawn in
Section 6.
7
2.
PROJECTING THE DEMAND FOR LABOUR: DATA
SOURCES & METHOD
In this section we present a brief outline of the measures and assumptions used in
calculating the 2015 labour demand estimates. A detailed explanation of the
methodology and assumptions is provided in Appendix B and C.
It should be acknowledged at the outset that forecasting and speculation of
technological, economic and social developments needs to be interpreted with
caution, since it is not always a simple matter to understand the present let alone
predict future trends and impacts. The review undertaken here involves what we
prefer to see as making ‘projections’ about people and skill requirements to 2015,
rather than forecasting or predicting per se. As discussed in the previous chapter, our
projections are based on BIS Shrapnel commodity output forecasts together with
current employment data produced by the DoIR (WA) and the Resource Information
Unit (WA). Assumptions embedded in both sources ultimately impact on the accuracy
of our projections.
In addition to assumptions embedded in the source data, we have also made some
assumptions in regard to the resources sector. For example, by assuming that the rate
of growth of employment will be equal to the rate of growth of output we have
effectively assumed that the impact of technological and management change on
mining output per employee will be small.
Considerable caution should be exercised in the treatment of our projections with
regard to uranium. The future output of uranium is particularly uncertain at this time
due to the potential future impact of the Olympic Dam project in South Australia.
While we obtained the most recent update of output predictions for uranium, it is
highly likely that the BIS Shrapnel predictions for uranium are extremely
conservative. We recommend that the employment projections for uranium be
recalculated in collaboration with representatives from BHP Billiton once the
uncertainty surrounding the Olympic Dam project is reduced.
2.1. Outline of the data sources and method used
This study used a number of data sources and methods to project employment and
skills for 2015 and these are outlined below. More detail on data sources and the
method can be found in Appendix B.
The main data sources in this study were:
•
Commodity output forecasts supplied by BIS Shrapnel (2005) - BIS Shrapnel
supplied us with projections of output for each of the commodities to 2015.
These formed the basis for our output by employee projections.
8
•
•
Employment data from the Resources Information Unit (RIU) 2006. The primary
data source for these estimates is the 2006 “Minelist” from the Perth-based
Resource Information Unit (RIU), which provided numbers of employees for
each state and territory (excluding ACT) by major commodity. The Minelist data
is based on a survey of Australian mines (with approximately 95 per cent
coverage of the sector). 2006 was the first year that data (for 2005) on numbers
of employees has been collected. RUI supplied NILS with two custom data sets
based on the 2006 Minelist mine survey:
o
a list of all mines in Australia with numbers of employees, mine type, main
commodity
o
a list of all multi-commodity mines (MCMs) with estimated output of each
mine expressed in refined metal equivalents.
Employment data from state mining and primary industries agencies and
industry organisations. These included:
o
Department of Natural Resources, Mines and Energy, Queensland Coal
Statistics
o
The Department of Industry and Resources (DoIR) in Western Australia
o
Aluminium and the Australian Economy A Report to the Australian
Aluminium Council, May 2000
o
Queensland Mines and Quarriers Safety Performance and Health Report
2004-5
o
NSW Coal Industry Profile, NSW Department of Primary Industries
o
Annual Review 2003/2004 Mineral Resources, Tasmania
The following methods were used to make the employment projections in this study.
An outline of each measure is presented here, with a more detailed discussion
including assumptions and formulae presented in Appendix B.
1.
Calculation of the base employment levels for 2004
Using the data sources outlined above, base employment levels for 2004 (specifically,
the end of 2004) were calculated in order to determine the numbers of employees for
each state and territory (excluding ACT) by major commodity. The presence of multicommodity mines (MCMs), increased the complexity of the task of compiling base
employment data. To calculate the base employment series, all MCMs were removed
from the full Australian mine list creating a separate list for MCMs, with twenty six
Australian mines each producing between two and five distinct mineral outputs.
9
Employees were allocated to commodities according to the relative value of those
commodities in each mine’s output mix1 .
This process resulted in a list of “commodity-distributed employment levels” (CDELs)
by mine. These CDELs were added to numbers of employees by commodity for
single-commodity mines.
From this consolidated data set, sub-totals for employment by state, commodity and
mine type were calculated resulting in the base employment series for 2004. In cases
where employment levels by state and by commodity were available and where
these were greater than the numbers derived from the Minelist data the state-based
data were used in preference.
2.
Distributing employment level across occupations
Once a projected employment level by state and by commodity had been established
for 2005 to 2015, it was next necessary to distribute these totals across occupational
groups. This project used a six-category occupational distribution:
•
Managers
•
Professionals
•
Technicians
•
Tradespersons
•
Semi-skilled workers
•
Labourers and related workers.
A survey of 14 Australian mining companies (with coverage of 33,304 employees,
approximately one third of employees in the commodities of interest) provided
information about the distribution of occupations across all of the commodity groups
and by the four main categories of mining activity (production, processing,
maintenance and exploration). For each year from 2005 to 2015 the projected total
level of employment in each commodity grouping was distributed across the six
occupational classifications.
These data sources and methods formed the basis of our employment projections,
and these projections are the focus of the remainder of this report.
1
The use of refined equivalents rather than the value of ore shipped involves an approximation, that is, to the
extent that different MCMs ship ores of differing qualities that sell for different prices, the use of refined
equivalents will introduce inaccuracies.
10
3.
OVERVIEW OF LABOUR DEMAND 2015
In this section we provide an overview of projected employment growth in the
Australian resources sector in 2015, based on the commodity output forecasts
provided by BIS Shrapnel (2005) together with employment data produced by the
various sources outlined in the previous section.
Before going on to specifically examine employment growth in the resources sector,
it is useful to explore issues related to general employment trends in the sector at a
national level. Figure 1 shows that at a national level, there is a marked overall
positive growth in employment in the resources sector to 2010.
Figure 1: Estimated Employed Persons in Mining Industry (to 2010)
An examination of vacancies in mining (nationally) supports this trend of
employment growth, and this is evident in Figure 2 below (projection only to 2010).
11
Figure 2: Actual and projected vacancies in mining (2000 – 2010)
Source: ABS, Job Vacancies Austra lia, Cat. No. 6354.0
Figure 3 below reveals that employment trends in mining are substantively different
from the rest of industry, where employment growth is highly correlated with
movements in gross domestic product. Figure 3 indicates that employment trends in
mining are cyclical, dependant (among other factors) on commodity prices, state of
reserves, intensity of exploration as well as employment needs at the stage of
operations of different commodity developments (for example exploration followed
by extraction). While we make the assumption that overall growth in employment in
the resources sector is linear, the cycle of peaks and troughs is likely to remain. In
other words, while we are able to project employment growth in 2015 based on the
forecasted outputs by BIS Shrapnel, the timings of the peaks and troughs are unable
to be accurately estimated based on our source data.
12
Figure 3: Trends of Annual Percentage Changes
Source: ABS, Labour Force Austra lia, Cat. No. 6202.0; ABS, Australian System of National Accounts,
Cat. No. 5204.0
Table 1 also shows BIS Shrapnel forecasts of output for each of the major commodity
groups. Increased output is projected for all commodity groups, with nickel, bauxite,
copper and iron ore respectively having a significantly higher level of predicted
output in 2015. The BIS Shrapnel Report cites a number of reasons for the increases in
output. Global prices and export quantities of commodities in Australia have
expanded in response to surging demand from China, and this is forecast to increase
over the next decade. According to BIS Shrapnel, mining output growth may start to
slow down by 2007 or 2008, since the resources boom in Australia may be replicated
overseas resulting in a potential oversupply. Nevertheless, Australia has some of the
largest and richest commodity reserves in the world, and the longer-term outlook
remains very positive for Australia’s minerals industry. Continued investment,
efficient mining operations and vast mineral resources augur particularly well for the
medium to long-term outlook (BIS Shrapnel, 2005).
13
Table 1: Output and Employment, Data Used for Employment Projections
Units
Output
BIS
BIS
Shrapnel Shrapnel DoIR & RIU
2005
2015
Employment
Sector 2005
OUTPUT OUTPUT
2005
2015
2005
% of Total
Employment
Sector
Employment
2015
ALUMINA/BAUXITE
kt
58093
119578
10,244
8.0%
20,956
GOLD
t
270.00
345.00
18,335
14.22%
25,396
IRON ORE
Mt
250.00
483.00
15,131
11.72%
28,572
NICKEL
Kt
199.00
443.50
7,211
7.82%
16,053
URANIUM
t
11263
11391
639
0.49%
1,293
COAL
COPPER
Mt
kt
447.50
912.00
588.9
1885.00
28,904
6,532
22.40%
4.9%
44,689
16,904
LEAD
ZINC
kt
kt
709
1393
1102
2165
1321
3800
1.02%
2.95%
2,265
6147
Total Major Sectors
92,117
68.62%
162,275
Total Mining
(including
commodities not
listed here)
129,400
Notes
(1) Sector Employment for 2015 is based on estimates of output per employee, details of the method of
deriving this measure and associated assumptions are provided in Appendix B and Attachments.
(2) Total Mining employment is from ABS Catalogue6105.0 and includes Petroleum and Gas
Increases in output indicate an increase in workforce numbers. In order to calculate
the numbers of workers required by the resources sector in 2015, the growth rate in
output was applied to the base employment series. From Table 1, it can be seen that
the resources sector will require a dramatically increased workforce by 2015. It is
projected that by 2015, the resources sector workforce in Australia will be in the
vicinity of 162,000 employees, representing an increase of approximately 70,000
workers over the next decade.
Table 2 below shows that the percentage increase is most dramatic in copper, nickel
bauxite and uranium, where the workforces are projected to more than double in
number.
14
Table 2: Percentage of Employment Change in 2015
BAUXITE
GOLD
IRON ORE
NICKEL
URANIUM
COAL
COPPER
LEAD
ZINC
Resources
Sector
Employment
2005
10244
18335
15131
7211
639
28904
6532
1321
3800
Projected
Employment
in
2015
20956
25396
28572
16053
1293
44689
16904
2265
6147
Employment
2005 to
2015
Change
10712
7061
13441
8842
654
15785
10372
944
2347
Employment
2005 to
2015
% Change
105
38
89
123
102
55
159
71
62
Figure 4 reveals the resources sector labour demand for each state and territory
(excluding the ACT). The table indicates that Western Australia and Queensland will
have the strongest demand for labour, followed by New South Wales and South
Australia. The strong demand for labour in Western Australia and Queensland
reflects the locations of the high growth commodities of copper, nickel and bauxite.
Figure 4: State labour demand in 2005 - 2015
These workforce projections for 2015 clearly pose a serious challenge for the
resources sector in Australia. In the next section we provide an account of the
occupations and skills that are likely be required by the main commodity groups in
2015.
15
4.
OCCUPATIONS AND SKILLS REQUIRED IN 2015
4.1. Occupational Structure in the Resources Sector
Prior to this report, the only indicative model of occupational structure in the
resources sector was the Argus (2004) Model. Based on 2001 ABS Census data, the
Argus Report (2004) provided a template of occupational structure within mining (at
the ANZIC one digit level) by indicating the percentage of the mining workforce in
each occupational category (at the 1 digit ASCO level). While the model is useful for
providing a comprehensive and broad profile of the competencies and level of skill
across the minerals industry, it is lacking for our purposes here on two accounts.
First, it does not take into account inter-commodity differences of occupational
structure, and second, it does not encompass different intra-commodity occupational
structures across different operational activities.
In order to determine the occupational structure of each commodity, we conducted a
survey of firms. Twenty-seven resources firms were approached to participate in a
survey of occupational structure (see Appendix A for the survey letter and questions),
to which fourteen companies responded. The firms were asked to indicate what
percentage of their workforce were in the categories of ‘labourer and related
workers’, ‘semi-skilled workers’, ‘tradespersons’, ‘technicians’, ‘professionals’, and
‘’management’, across the operational disciplines of production, processing,
maintenance and exploration. In addition, the firms were asked to indicate if the skill
sets and tasks of occupations on site were undergoing changes, and if so, what types
of changes. Only one responding company indicated a change in skills, all others
indicated stable skill sets. The change in skill set was in the bauxite commodity, where
it was indicated to us that, “process operators are receiving more extensive formal
TAFE training”.
The participating companies consisted of single and multi-commodity mines across
the range of commodities included in this report. The survey resulted in coverage of
33,304 workers, which is approximately 36 per cent of employees in the relevant
commodities. Table 3 displays the occupational structures of the nine commodity
groups. The Argus Report (2004) template is included for the purpose of comparison.
16
Table 3: Occupational Structure by Commodity compared to Argus Model
OCCUPATIONAL
CATEGORIES
Argus Report COAL IRON ORE BAUXITE COPPER
Managers
5
9.2
4.3
0.4
4.7
Professionals
25
7.8
15.2
16.4
9.6
Technicians
13
2.6
9.6
12.6
4.5
Tradespersons
21
26.0
22.9
10.4
42.0
Semi-skilled workers
32
49.9
43.8
32.0
30.9
Labourers & related
workers
4
4.5
4.3
28.2
8.3
GOLD
NICKEL URANIUM
LEAD
1.8
2.3
0.3
1.5
9.5
5.9
3.8
12.7
2.2
3.1
1.5
5.9
64.6
77.4
84.2
72.0
10.8
8.9
0.5
3.7
11.1
2.4
9.8
4.4
ZINC W/AVERAGE
1.5
4.7
12.7
9.6
5.9
4.5
72.0
42.0
3.7
30.9
4.4
8.3
Note: Lead and Zinc were calculated together since we received raw data for the commodities in combined form only.
Table 3 reveals considerable differences in occupational structure between
commodities. For example, Uranium, Nickel, Gold, and Lead/Zinc appear to have
proportionally more tradespersons, while Coal, Nickel and Iron Ore have a higher
proportion of semi-skilled workers. Table 3 also indicates some departure from the
Argus Model of occupational structure across the individual commodities. Moreover,
if we compare the weighted average2 across all nine commodities, it appears that the
Argus Model overstates the proportion of highly skilled occupations and
underestimates the proportion of tradespersons, semi-skilled workers, and labourer
and related workers.
It is important to note that our calculations are based on two assumptions. First, we
have assumed that the occupational structures evident in Table 3 are representative of
all sites in a given commodity. Second, we have assumed that the ratio of
occupational structure will remain the same over time; for example, the ratio of
tradespersons per professionals will not change over the next decade. This second
assumption indicates that the projections of occupations in 2015 needs to be treated
with caution, since cycles of expansion and exploration in the resources sector indicate
that the ratio may differ according to the life-cycle stage of each operation.
Figures 5 and 6 reveal the occupational structure and workforce size for each of the
commodities in 2015 (with the caveat in regard to uranium, as mentioned earlier).
2
The weighted average was calculated by using the tota l number of responses received for each
commodity.
17
Figure 5: Occupational Structure by Six Commodities for 2015
18
Figure 6: Occupational Structure by Three Commodities for 2015
19
Figures 5 and 6 clearly show the predominance of the trades, semi-skilled and
labourer occupations across the commodities in 2015.
4.2. Broad occupations required in each of the commodities
While Figures 5 and 6 shows the projected growth and the occupational structure
for each of the main commodities, additional insight related to projected
occupational requirements is gleaned from examining employment and
occupational structure in each commodity for 2005 and 2015.
Coal
Figure 7a:
Coal - Projected Employment Growth and Occupational
Structure
Australia is geographically well placed to take advantage of the coal supply
shortage in East Asia. Investment in coal mine capacity has increased
dramatically, with increased production already coming on stream (BIS Shrapnel,
2005). It is projected that overall, an additional 15,785 employees will be required
in 2015. This comprises the following:
•
716 additional labourer and related workers
•
7872 additional semi-skilled workers
•
4,107 additional tradespersons
20
•
410 additional technical employees
•
1232 additional professional employees
•
1448 additional managers and administrators
It is important to note that these projections assume the ratios remain unchanged
in 2015. This type of caveat applies equally to each commodity group discussed in
this section.
According to our survey with coverage of 33, 304 employees, the occupations in
coal are distributed across the activities of production, processing, maintenance
and exploration in the following way:
Figure 7b:
Coal - Occupational Distribution by Operational Activity
From Figure 7b, semi-skilled workers dominate in the mining and processing of
coal, while tradesperson play a large role in maintenance activities.
Iron Ore
Iron ore production is currently at record levels, with an estimated 12.7 per cent
growth in 2005. Major expansions in Western Australian production and export
capacity and high prices, have enticed new producers into the market with added
funding from Japan and China. This investment will underwrite continued
growth in production till 2015 (BIS Shrapnel, 2005). As a result it is projected that
21
13,441 additional employees will be required. These includes additional workers
in the following broad occupational groups:
•
573 additional labourer and related workers
•
5,887 additional semi-skilled workers
•
3,073 additional tradespersons
•
1,288 additional technical employees
•
2,048 additional professional employees
•
573 additional managers
Figure 8a:
Iron Ore - Projected Employment Growth and
Occupational Structure in 2015
Our survey revealed that semi-skilled workers were mainly concentrated in
mining (production) activities, while the trades were more pronounced in
maintenance:
22
Figure 8b:
Iron - Occupational Distribution by Operational Activity
Gold
According To BIS Shrapnel (2005) production growth in gold is forecast to reach
14.1 per cent in 2006, largely due to the Telfer mine in Western Australia coming
on stream. Other smaller mines will help boost production, however it may be
the case that production growth may plateau in 2009 to 2010 (BIS Shrapnel, 2005)
According to our projections, 7061 employees will be required:
•
786 labourer and related workers
•
765 semi-skilled workers
•
4,560 tradespersons
•
159 technical employees
•
668 professional employees
•
124 managers
23
Figure 9a:
Gold - Projected Employment
From Figure 8b, it can be seen that tradespersons dominate in the activities of
maintenance and processing, while the lower skill levels are found in mining
(production) activities.
Figure 9b:
Gold - Occupational Distribution by Operational Activity
24
Bauxite
Bauxite production is heading into a strong period of growth, related mainly to
the extent of demand from China for Alumina to feed their Aluminium smelting
industry. Overall, it is predicted that bauxite production will grow at an average
rate of more than 9 per cent per annum to 2010 (BIS Shrapnel, 2005).
Figure 10a: Bauxite - Projected Employment
As a result, it is projected that 10,712 additional employees will be required. These
includes additional workers in the following broad occupational groups:
•
3,019 additional labourer and related workers
•
3,424 additional semi-skilled workers
•
1,118 additional tradespersons
•
1,353 additional technical employees
•
1,757 additional professional employees
•
42 additional managers
Figure 10b reveals that semi-skilled workers in bauxite predominate in mining
processing activities, however, unlike the commodities examined so far, labourer
and related workers are strongly represented in mining production, processing,
25
and maintenance, and play a stronger role in maintenance activities than
tradespersons.
Figure 10b: Bauxite - Occupational Distribution by Operational Activity
Copper
Copper demand has surged in recent years, and the strong growth will continue,
largely due to the increased production at Olympic Dam in South Australia. The
Olympic Dam Expansion Project is currently preparing a pre-feasibility study for
dramatic growth of the site. Commissioning of the expanded site is expected to
occur in 2013, and it is estimated that production will more than double by 2015.
Our projections indicate that 10372 additional workers will be required in 2015:
•
863 additional labourer and related workers
•
3201 additional semi-skilled workers
•
4361 additional tradespersons
•
469 additional technical employees
•
992 additional professional employees
•
487 additional managers
26
Figure 11a: Copper - Projected Employment
Our survey revealed that semi-skilled workers dominated in the mining of
copper, but tradespersons were more likely to be found in maintenance,
processing and mining production activities respectively.
Figure 11b: Copper - Occupational Distribution by Operational Activity
27
Nickel
Nickel production in Australia is based solely in Western Australia. With the
prospect of continued strong growth in the demand for stainless steel (the main
use for nickel) and continued high nickel prices, nickel investment is set to
increase. It is projected that 8842 additional employees will be required in the
following broad occupational groups:
•
213 additional labourer and related workers
•
786 additional semi-skilled workers
•
6845 additional tradespersons
•
272 additional technical employees
•
520 additional professional employees
•
206 additional managers and administrators
Figure 12a: Nickel - Projected Employment
Figure 12b below reveals that for nickel, tradespersons dominate in all four
operational activities of production, processing, maintenance and exploration.
28
Figure 12b: Nickel - Occupational Distribution by Operational Activity
Zinc
Zinc production is estimated to increase largely due to the demand from China.
Expansion of existing mines as well as new projects will see strong growth over
the next decade (BIS Shrapnel).
Figure 13a: Zinc - Projected Employment
29
Our projections indicate that 2347 additional workers will be required in 2015:
•
103 additional labourer and related workers
•
86 additional semi-skilled workers
•
1689 additional tradespersons
•
137 additional technical employees
•
298 additional professional employees
•
34 additional managers
Figure 13b below indicates that tradespersons dominate in the activities
associated with processing, maintenance and production of zinc:
Figure 13b: Zinc - Occupational Distribution by Operational Activity
Lead
Lead mine production is predicted increase by 64 per cent to 2015, however, the
bulk of this increase is early in the projection period (BIS Shrapnel).
30
Figure 14a: Lead - Projected Employment
We project that 944 workers additional workers will be required:
•
41 additional labourer and related workers
•
35 additional semi-skilled workers
•
680 additional tradespersons
•
55 additional technical employees
•
120 additional professional employees
•
14 additional managers
As with Zinc, Figure 14b indicates that that tradespersons dominate in the
activities associated with processing, maintenance and production of lead:
31
Figure 14b: Lead - Occupational Distribution by Operational Activity
Uranium
Uranium production is located in the Northern Territory and South Australia. As
discussed earlier, the Olympic Dam Expansion Project is currently preparing a
pre-feasibility study for dramatic and significant growth of the site.
Commissioning of the expanded site is expected to occur in 2013, and it is
estimated that production will approximately double by 2015. This is likely to be a
conservative estimate. It should be emphasised that the Olympic Dam Project is
potentially so large, that its employment will probably dominate the uranium
industry in Australia over the next decade.
32
Figure 15a: Uranium - Projected Employment
Based on the (in this case) conservative BIS Shrapnel predictions, our projections
indicate that 654 additional workers will be required3 :
•
64 additional labourer and related workers
•
3 additional semi-skilled workers
•
550 additional tradespersons
•
10 additional technical employees
•
25 additional professional employees
•
2 additional managers
Figure 15b below reveals that tradespersons are concentrated in activities
associated with the maintenance and processing of uranium.
3
These are h ighly conservative estimates and should be treated with caution
33
Figure 15b: Uranium - Occupational Distribution by Operational Activity
The discussion above gives us some idea of the broad occupational classifications
likely to be required in 2015, and the types of skills required in 2015 as revealed
through our analysis of occupational distributions for each of the commodities.
This study confirms recent research (NCVER, 2005) that suggests marked
shortages in the trades and semi-skilled workers.
This section has focused on the projected employment demand in defined
commodities in the Australian resources sector in 2015. In order to more fully
understand the implications of labour demand in the sector over the next decade,
the following section explores the capacity of the economy-wide labour market to
respond to these increases.
34
5.
CAPACITY OF THE ECONOMY TO RESPOND TO
GROWING DEMAND FOR LABOUR
5.1. Introduction
Our projections indicate strongly growing demand for labour across the mineral
resources sector with significant variations between commodities and
occupational classifications. Given the labour shortages being experienced in
many sectors of the economy and given that the large demographic group
characterised as the “baby boomers” is reaching retirement age, we need to
consider the capacity of the labour market to respond to these increases in
demand. We examine here projections of employment growth across the
relevant occupational classifications and characterise the extent of labour demand
gaps that are likely to be experienced in specific commodity sectors.
5.2. Limitations of the analysis
It is appropriate to begin by emphasising some fundamental conceptual and
empirical limitations to such an undertaking. Since we have projected demand in
six occupational categories we would ideally like to have supply data in
corresponding categories. With these two sets of projections it would be possible
to draw conclusions about the occupational classifications that are likely to
experience the largest gaps between demand and supply.
There is however, a fundamental conceptual issue, particularly for occupational
categories that require lower levels of qualifications, which is: what are the criteria
for determining whether persons are included in the supply for a particular
occupational category? Take, for example, the occupational category “unskilled
workers”. By definition almost any worker qualifies to work in this category.
Should workers with, say, higher degrees or many years managerial experience
be included in the supply for this category? Probably not, but where precisely
should the cut-off point in terms of qualification and/or experience be? This
conceptual problem places a significant limitation on our ability to meaningfully
define supply.
Another complication, which is primarily empirical, is that employment data
cannot be relied upon to indicate labour supply because the “short side
dominates”. This means that in situations where there is an excess supply of
labour (demand is “short”) measures of employment will reveal demand, and the
excess supply will be manifested as unemployment. In situations where there is
excess demand for labour (supply is “short”) supply will be measured in the
employment statistics (because some employment vacancies will remain unfilled).
This means that observed numbers of employees can not be relied upon to
indicate the supply of labour.
35
Having stated these two caveats, our pragmatic approach is to use the numbers
employed historically in each occupational category as a projected indicator of the
labour market’s capacity to respond to demand growth and thereby identify in
what occupational categories supply bottlenecks are most likely to occur. Before
presenting the occupational categories projections we provide an overview of
trends in the Australian labour force.
5.3. Australian labour force trends
Australia’s aging population
Australia is in the process of a demographic transition characterised by rapid
ageing of the population, with an increasing proportion of the population
accounted for by older age groups. In addition, the size of the working-aged
population (aged 15 to 64 years or over), which also represents the upper limit of
the potential labour force, has generally been growing at a decreasing rate over
time. Any change in the working-aged population can be regarded as a first
approximation of future labour supply changes.
Figure 16:
Total Working Age Population and Annual Percentage Change,
Australia 1990 to 2015.
Data source: Data sources: Population projections of the Productivity Commission (2005) for 2004 to 34; ABS Australian Population
Statistics (cat. no. 3105.0.65.001) for earlier years.
According to the Productivity Commission (2005), there will be a net growth of
around 2.4 million in the working-aged population from 2005 to 2015. The
growth rate per annum of the 15 to 64 age group will continue to decrease from
around 1.5% in 2005 to 1.3% in 2015. Moreover, after 2007 the working age
population will grow more slowly than the total population (Figure 16).
36
We can examine the changes in age distribution in more detail if we further divide
the 15 to 64 age group into three age groups: younger age (15 to 24), primary age
(25 to 49), and older age (50+). The proportion of the younger age group in the
total population will drop moderately from 17.2 to 16.5% from 2005 to 2015. The
share of the prime-age group reached a maximum of 48.3% in 1996 and has
maintained a downward trend since then. It will decrease from 46.9% in 2005 to
42.8% in 2015. By 2018, its proportion (41.7%) will be less than that of the older
age group (42.3%). By sharp contrast, the proportion of the older age group in
the total population will greatly increase from 36.0 to 40.7% from 2005 to 2015.
The changing proportions of the different age groups will impact on the size and
structure of the future labour force. Essentially, the labour force will continue to
shrink relative to the total population and will consist overwhelmingly of the
older segment of the working-aged population (Figure 17).
Figure 17:
Shares of Population, by Age Group, Australia 1990 to 2020.
Data sources: Calculated from population projections of the Productivity Commission (2005) for 2004 to 20; ABS Australian
Population Statistics (cat. no. 3105.0.65.001) for earlier years.
Future labour force
Labour force participation rates are generally higher for men than for women, as
evidenced by the historical data. Figure 18 compares male and female
participation rates across the age spectrum relative to the rates of both genders
across Australia for a single time period. It shows that the female participation
rates decline during early prime-age as women reach child-bearing age and on
average, do not recover to male levels. Labour force participation for both
genders is concentrated in the ages between 20 and 54 years.
Labour force participation rates vary significantly across different age groups.
The participation rates for people in their younger age groups are comparatively
37
low as they engage in education (although many work part-time in unskilled jobs
while they study). Older people’s participation is also much lower than the
participation rate of people in their prime age as they voluntarily or involuntarily
retire from their jobs. Some older people, however, remain engaged in the labour
market via part-time work or self-employment.
Figure 18:
Labour force participation rates in Australia, by sex (January
2005).
Data source: Calculated from ABS Labour Force, Australia, Detailed (cat. no. 6291.0.55.001).
Aggregate labour force participation rates in Australia are anticipated to fall by
2.1 percentage points from 63.5% in 2005 to 62.7% in 2015 (Productivity
Commission 2005). Over time there have been rising female, and declining male,
participation rates across a number of the specific age categories. To date, this
rising female participation has more than offset the trend toward declining male
participation. As a result, the aggregate participation rate increased by around 3%
over the last two decades. Male participation rates are expected to continue to
decrease from 71.2% in 2005 to 68.0% in 2015. Female participation rates are
expected to keep rising over the years between 2005 and 2013, increasing from
56.1% in 2005 to 57.5% in 2013.
From 2013, female labour participation will shift downwards, reaching 56.8% by
2020. Except for those aged 40 to 44 years, all the other age groups are expected
to experience an increase in their labour participation over the period 2005 to
2020. The older age group will experience the largest increase during this period.
For instance, the increases in participation rates are expected to be some 8.5% for
those aged 60 to 64 years, 6.9% for those aged 55 to 59 years, 3.4% for the aged 65
years and over, and 3.2% for those aged 50 to 54 years. In contrast, the
participation rate for the youngest age group (15 to 19 years) will increase by
only 1.9% over the same period.
38
If these patterns prevail, the shift in the age structure of the population over the
period 2005 to 2015 implies that more Australians will be in age groups with lower
labour force participation rates. The decline in labour participation is likely to be
sharper after 2007 when the first of the baby boomer generation reach 65 years
and start to move into retirement. In the next 10 years, the labour force is
expected to grow by a net of around 1.5 million persons, amounting to
approximately 11.2 million by 2015 (see Figure 19). The net addition to the labour
force per annum is anticipated to fall, decreasing from 1.6% in 2005 to 1.2% in
2015. This indicates that potential supply of the overall labour will continue to rise
but at a slowing rate.
Figure 19:
Growth of the labour force, Australia 2002-2020.
Data source: Calculated from the labour force projections of the Productivity Commission (2005) for 2004 to 20; ABS Labour Force,
Australia, Detailed (cat. no. 6291.0.55.001) for earlier years.
5.4. Projections of employees in occupational categories
Table 4 provides projections of numbers of persons employed in the six
occupational categories that we have used in the demand estimates. For more
information of the projection method see Appendix C. It is emphasised that these
figures show the economy-wide projected level of employment in each of the
occupational categories and so the absolute numbers are not comparable with
our projections of demand levels. It is useful however to compare the growth
rates of demand and supply.
39
Table 4: Projected economy-wide employment in occupational categories (No.
of persons)
Managers & Professionals Technicians
administrators
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Figure 20:
770,335
792,228
813,626
834,638
855,462
876,169
896,455
915,818
934,191
951,887
969,073
1,868,367
1,919,548
1,967,971
2,014,015
2,058,310
2,101,171
2,142,047
2,179,891
2,214,714
2,247,421
2,278,508
1,235,378
1,279,798
1,321,970
1,362,073
1,400,520
1,437,505
1,472,668
1,505,304
1,535,428
1,563,683
1,590,442
Trades
persons
1,214,244
1,225,143
1,235,348
1,245,215
1,255,170
1,265,419
1,275,594
1,285,042
1,293,736
1,302,156
1,310,540
SemiLabourers
Total
skilled
& related
workers
workers
793,138
867,413 6,748,875
793,947
866,894 6,877,559
794,271
865,479 6,998,665
794,448
863,602 7,113,991
794,827
861,711 7,226,000
795,585
860,054 7,335,902
796,521
858,470 7,441,754
797,258
856,599 7,539,912
797,799
854,487 7,630,355
798,445
852,491 7,716,084
799,344
850,792 7,798,700
Projected employment in occupational categories: growth rates
40
Figure 20 charts projected annual growth rates of employment for each occupational
category for the projection period and the growth rates for the whole period. All
occupational categories show declining but positive growth rates except for Labourers
and related workers with projected low negative growth rates over the whole period
– this sector is projected to decline in absolute size over the period. Growth rates for
Semi-skilled workers are close to zero over the period.
Figure 21 shows the projected growth rates for total demand and employment for all
six categories. This chart show that in 2006 the projected growth in demand in mining
across the six occupational categories is 10.25 per cent while for employment it is only
1.91 per cent. Although the gap between demand and employment growth rates
decreases significantly after 2008 it should be emphasised that this implies, in terms of
absolute numbers, a widening gap between demand and “supply”.
Figure 21:
Projected annual growth rates
One way to illustrate this gap is to apply our projected employment growth rates to the
2005 demand estimates. Assume, for the purposes of this illustration, that in 2005 all
occupational categories were “in equilibrium”, that is demand equals supply. From
this point then assume demand and supply (with projected employment the proxy for
supply) grow at our projected rates. Figure 22 illustrates this scenario. The blue area
shows the projected increase in the number of persons employed in the six
occupational categories and the orange area show the projected demand for persons
in the mineral sector. The chart clearly shows the widening gap between projected
supply and demand for labour.
41
Because Figure 22 is based on the total number of persons in all occupational
categories there are cases of larger and smaller gaps for each category. Figure 23
shows the corresponding illustration of excess demand for the occupational category
Labourers and related workers. By 2015 “the gap” for this category is more than half
the size of projected “supply”. Note also that, in contrast to the Total figure, supply
move slightly down over the decade.
Figure 22:
Gap between demand and supply: number of persons.
42
Figure 23:
Gap between demand and supply: number of persons.
Figure 23: Gap between demand and supply: number of persons.
Table 5 summarises annual growth rates in employment and demand for each
occupational category for the projection period and the growth rates for the whole
period, 2005-15. The projected growth rate of total employment for the six categories
is 15.6% while the projected growth in demand is 76.2%. The highest growth rate is in
the demand for Tradespersons at 87.7% over the 10 years of the projection period.
The growth rate of “supply” for Tradespersons is expected to be 28.7%.
Table 5: Projected employment and demand in occupational categories:
growth rates
Managers &
administrators
demand
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2005-15
8.43
8.13
5.40
4.70
3.08
5.42
5.14
4.90
4.67
4.47
69.59
Professionals Tradespersons Semi-skilled
workers
supply demand supply demand supply demand supply
2.84
2.70
2.58
2.50
2.42
2.32
2.16
2.01
1.89
1.81
25.80
10.42 2.74
10.14 2.52
6.96 2.34
5.94 2.20
3.86 2.08
4.98 1.95
4.74 1.77
4.58 1.60
4.36 1.48
4.21 1.38
78.98 21.95
9.80 3.60
9.52 3.30
7.87 3.03
6.77 2.82
4.33 2.64
5.96 2.45
5.62 2.22
5.37 2.00
5.08 1.84
4.86 1.71
87.74 28.74
11.60
11.45
7.45
5.70
3.37
3.64
3.51
3.70
3.47
3.55
74.05
0.90
0.83
0.80
0.80
0.82
0.80
0.74
0.68
0.65
0.64
7.93
Labourers &
related workers
Labourers &
related workers
demand
demand
8.69
8.34
5.91
5.46
3.59
5.79
5.47
5.19
4.93
4.70
75.67
supply
0.10
0.04
0.02
0.05
0.10
0.12
0.09
0.07
0.08
0.11
0.78
10.82
10.44
6.90
7.75
4.31
4.49
4.30
4.28
4.06
4.00
80.87
Total
supply demand supply
-0.06 10.25 1.91
-0.16 10.01 1.76
-0.22 6.81 1.65
-0.22 5.84 1.57
-0.19 3.61 1.52
-0.18 4.71 1.44
-0.22 4.50 1.32
-0.25 4.45 1.20
-0.23 4.21 1.12
-0.20 4.13 1.07
-1.92 76.17 15.56
43
Figure 24 shows that the three occupational categories that will experience the
greatest labour supply shortage are Labourers and related workers, Semi-skilled
workers, and Tradespersons. It should be noted, however, even at the bottom of the
supply shortage range, Managers and administrators, will still experience supply
shortages.
Figure 24:
Growth rates by occupational classification.
5.5. Demand-supply ratios
Another approach to summarising relative demand and supply is to calculate a ratio.
We have calculated a “demand supply ratio” (DSR). The DSR is the ratio of projected
demand from the mineral sector divided by the projected “supply” of labour for the
corresponding occupational category (economy-wide). The value of the DSR is set to
one for the base year of 2005. If the growth rate of projected demand exceeds the
growth rate of projected supply (as it does for all occupational categories) the value of
the DSR will increase. The values of the DSR for the six occupational categories from
2006 to 2015 are shown in Figure 25.
The extent to which the DSR line rises above one shows the extent to which demand
will exceed supply. Figure 25 shows that the extent of excess demand for labour is
likely to be greatest for the occupational classifications Labourers and related
workers, tradespersons, and Semi-skilled workers. The DSR rises to its highest value
of 1.84 for Labours and related workers in 2015
44
Figure 25:
Demand Supply Ratio, by Occupational Categories: All
Commodities.
Because coal is the biggest single employer in the mineral sector it is no surprise that
its projected supply shortages broadly mirror those of the sector. Figure 26 shows
that again, Labourers and related workers and Semi-skilled workers are projected to
face the most acute shortages while, in the case of coal, Technicians represent the
lowest level of shortages.
45
Figure 26:
DSR, by occupational categories: coal.
Figure 27 shows that iron ore mining is projected to experience an almost identical
pattern of shortages to coal but at a higher level. Note that the DSR for Labourers and
related workers reaches 1.93 by 20015.
46
Figure 27:
DSR, by occupational categories: iron ore.
Figure 28 show that bauxite again has a similar patter of labour shortages but these
shortages are project to be even more intense than those in iron ore mining. The DSR
for Labourers and related workers reaches a value of almost 2.1 by 2015.
Figure 28:
DSR, by occupational categories: bauxite.
47
Figure 29 shows the DSRs for copper and they reach their highest values in this case –
the DSR for Labourers and related workers reaching a value of 2.6 by 2015 and
Tradespersons reaching 2.4.
Figure 29:
DSR, by occupational categories: copper.
Figure 30: DSR, by occupational categories: nickel.
In the case of nickel, the highest level of shortage is reached for Semi-skilled workers
– 2.2 by 2001. This is because of the very low numbers of Labourers and related
workers involved in the mining of nickel.
48
Figure 31:
DSR, by occupational categories: gold
The distinctive shape of the DSR curves for gold reflect the projected decline in output
of this mineral. Labour shortages peak in 2010 but still are present at lower levels for
all occupational categories by 2015.
In the case of uranium the shapes of the curve over time are again driven by the
projected output. The future output of uranium is particularly uncertain at this time
due to the potential future impact of the Olympic Dam project.
49
Figure 32:
DSR, by occupational categories: Uranium
The DSR curve for lead and zinc have identical pattern because they are based on the
same occupational distributions. Lead, however, is projected to experience slightly
more intense labour supply shortages because of its higher projected growth rates in
output.
50
Figure 33:
DSR, by occupational categories: lead
Figure 34:
DSR, by occupational categories: zinc
51
The foregoing discussion shows the future labour shortages across the nine
commodities examined in this report. Table 6 provides a pointed summary of this
information. From the table, it can be seen that tradespersons required by the
resources sector in 2015 are almost one third of the projected economy-wide
tradesperson pool. The situation is even more significant for semi-skilled workers and
indeed, labourer and related workers.
Table 6: Economy-wide capacity to respond to demand for labour from the
resource sector
2005-2015
Projected economy-wide
employment growth
Projected growth in labour
demand in resources sector
Managers Professionals Technicians Tradespersons Semi- Labourer &
skilled
related
Workers workers
Total
198,738
410,140
355,064
96,296
6,207
-16,621
1,049,825
2,930
7,659
4,154
26,983
22,058
6,377
70,161
These figures are even more problematic when we consider that broad sectoral
changes in the Australian labour market (e.g. the decline of manufacturing industry,
the rise of the feminised service sector, the globalisation of the production process and
the introduction of new technology) has been attributed to a decline in the numbers
of prime aged men, men aged between 25-54, who are actually participating in the
labour market (Gregory 1991; Hancock 2002). It has been shown that in Australia that
at every age group, at least 20 per cent of men without post-school education are not
entering the work-force (Richardson 2003:1). That is, they are not just unemployed
they are not even looking for jobs.
National and international research that has examined the causes of this decline
suggest that the changes in the employment share of different industries (decreased
manufacturing employment to increased service sector employment) over recent
years have significantly reduced the employment opportunities for low-skilled
workers and have increasingly shifted traditional wage earners – blue-collar, male
workers - outside the new economic order.
The little research that has been done to understand this phenomenon (Moskos 2004;
Nixon 2005) suggests that low skilled men would rather opt out of the labour market
than to take jobs that they associate with being female work (call centre, sales
positions etc.) or more importantly for purposes here, jobs that they find to be
demeaning and devaluing of their perception of the value of their labour.
It is interesting then, when considering the future capacity of the economy to respond
to labour demand in the mining industry, and the projected reliance on semi skilled
and unskilled labour, to consider the future potential of men who are experiencing
this labour market exclusion and explore the possible ways in which this cohort of
men can be reengaged with the labour market, in particularly the Australian mining
labour market, to fill the future occupational gaps identified in this research.
52
6.
CONCLUSIONS AND RECOMMENDATIONS
Based on output forecasts supplied by BIS Shrapnel (2005), the resources sector in
Australia will undergo significant overall expansion over the next decade. Increased
output is projected for all commodity groups, with nickel, bauxite, copper and iron
ore having a significantly higher level of predicted output in 2015. The increase in
predicted output is reflected in projected labour demand. By 2015, in the absence of
any sophisticated technology that would reduce the need for the number of workers,
the resources sector workforce in Australia will be in the vicinity of 162,000
employees, representing an increase of approximately 70,000 workers over the next
decade. The increase is most dramatic in copper, nickel bauxite and potentially
uranium, where the workforces are projected to more than double in number.
Our weighted average occupational structure constructed for this study indicates that
semi-skilled workers and tradespersons constitute approximately 73% of employment
in the nine commodities covered in this report. This is vastly different from other
models of occupational structure in mining such as that found in the Argus Report
(2004), which indicated that semi-skilled and trades workers constituted only 53 per
cent. It is thus likely that other studies which have used the Argus Model in projecting
skill needs have understated future requirements for tradespersons and semi-skilled
workers.
By 2015, it is projected that an additional 22,058 semi-skilled workers will be required
in the resources sector nationally. In the mechanical and electrical trades (with the
emphasis on the former) an additional 26,983 workers will be required by 2015. This
picture is set against the current skills shortages in the area of the trades in the
resources sector, as well as a national skills shortage in all areas of the trades.
Competencies associated with mechanical and electrical trades are thus a high priority
for the resources sector, as are skills associated with semi-skilled workers such as
operators.
The projections in this report indicate that the commodities of copper, nickel and
bauxite are likely to take a disproportionate burden of new job creation in the
resources sector. For example, copper and nickel together are projected to require an
additional 11,206 tradespersons in 2015, which is 42 per cent of the projected number
of tradespersons required across the commodities in 2015. Copper and bauxite taken
together are projected to require an additional 6,625 semi-skilled workers by 2015,
which is nearly a third of the additional semi-skilled workers projected to be required
in the resources sector in 2015. Moreover, our findings indicate that the economywide capacity to respond to shortages in these occupational classifications is not
optimal.
At the other end of the spectrum, professionals account for approximately 10 per cent
of employment in the commodities explored in this study (compared to the Argus
53
Report estimate of 25 per cent of the resources sector workforce). Over the last
decade the Australian minerals industry has experienced a chronic shortage of
minerals specialist graduates, especially mining engineers and metallurgical engineers
(Minerals Council of Australia, 1998). Over the next ten years, 7,659 additional
professionals will be required by the resources sector in Australia. While not as
dramatic as the projected shortage of tradespersons and semi-skilled workers, this
nevertheless poses a challenge to all stakeholders associated with the professions in
the resources sector, particularly in regard to the attraction and retention of students
in mining engineering and science programs at tertiary level.
6.1. Skills Shortage or People Shortage?
Our examination of the economy to respond to the growing demand for labour in the
resources sector indicates that there will be significant labour demand gaps. The
findings here indicate that labour shortages are likely to be a major constraint on the
growth of the mineral sector over the next decade. The resources sector clearly needs
a continuing and vigorous program to attract and retain labour in the identified areas
of skill shortages. Given that the projected gaps are largest in occupational
classifications with low skill levels, the labour shortage problem identified here in the
resources sector is not one that training policy can necessarily address. It is more a
matter of attracting people to the industry, in other words, what the sector is facing is a
people shortage, not necessarily a skills shortage per se.
6.2. Recommendations
Against this backdrop of the findings of this study, we make a series of
recommendations:
Harnessing support by promotion of a better understanding of the extent and
composition of the shortages
It is common knowledge that the resources sector faces labour supply shortages,
however, the extent and composition of the shortages have been less widely
understood. The industry needs to promote a broader understanding of these aspects
of the labour shortage in order to encourage broader support for policies to deal with
the problem.
Design of appropriate attraction and remuneration systems
The identified demand gaps suggest that there may be pressure on compression of
wage differentials especially between professional and non-professional employees,
and that the sector will need to investigate ways it can accommodate such changes in
income differentials.
54
Matching of training systems to required skill levels
The finding that the projected shortages will be most acute in the area of semi-skilled
employees suggests that a heightened focus on the development of appropriate
training systems is required, with a particular emphasis on designing systems for
quality on-the-job training provision. This means ensuring the identification and
cultivation of appropriate in-house trainers as well as the design of appropriate onthe-job training evaluation systems.
Increased training efforts in the area of leadership and supervision skills should also
be considered, since a larger workforce will ultimately require increased levels of
leadership and supervision.
Identification and targeting of alternative labour reservoirs
The shortfall of workers is so large that all alternative labour reservoirs need to be
identified and targeted. One alternative labour reservoir is the manufacturing sector,
which is projected to experience a further decline in non-professional occupational
categories over the next decade. This decline is likely to result in a pool of available
labour with broadly compatible skill sets to that required by the resources sector. For
this source of labour to be accessed by the resources sector, there are significant
locational issues to be overcome.
Women also constitute an alternative labour pool for the resources sector. Crucial
challenges associated with targeting women are likely to be ensuring the provision of
childcare in remote locations, the design of family friendly policies including flexible
rosters, and changing the traditionally ‘masculine culture’ associated with mining.
Another labour reservoir lies in the rural, regional and remote communities, including
indigenous communities, in close proximity to many of the mine sites. This raises a
number of fundamental issues related to attraction, provision of training, and
retention;
Importing labour from outside of Australia is another option, but we emphasise that
the numerous long-term implications of this must be investigated and such a strategy
should not replace growing our own workforce locally.
Develop an understanding of socio-economic drivers of labour supply
We believe it is in the resources sector interest to develop an understanding and
expertise in determinants of labour supply in the Australian economy. This means
understanding not only the economic data, but deeper socio-economic trends that
underpin the supply of labour, particularly in non-professional occupational groups.
55
7.
Appendix A
22nd March 2006
Ms ………..
Human Resources Manager
PO BOX
Via email:
Dear Ms…………..
DEMAND FOR LABOUR IN THE MINERALS SECTOR TO 2015
A RESEARCH PROJECT FOR THE NATIONAL SKILLS SHORTAGE STRATEGY
The Chamber of Minerals and Energy WA and the Minerals Council of Australia have
commissioned the National Institute of Labour Studies (NILS) to undertake a research
project on the demand for operational labour in the minerals sector to 2015.
This project is being funded by the Department of Education, Science and Training through
the National Skills Shortage Strategy.
Over the course of the research, NILS has gathered current employment data and projected
overall employment levels in the minerals sector. In order to refine the projections for the
resources sector, NILS now needs to gain detailed information on the industry’s occupational
structure and operational activities.
To assist in gathering this information a survey has been provided which you are asked
to complete for your site only.
The data provided will be used to group mines of a particular type and commodity and the
information will be averaged to give a skills distribution for each commodity and mine type.
Only aggregate data will be used in the final report, and no individual site data will be
published. All information will remain confidential.
If you have any queries regarding this survey please contact Dr. Diannah Lowry at the
National Institute of Labours Studies on (08) 8201 2472
Please return your completed survey via email to Dr Diannah Lowry at the National
Institute of Labour Studies diannah.lowry@flinders.edu.au by the 7th of April, 2006.
I thank you for your assistance with this important research project.
Yours sincerely
Tim Shanahan
Chief Executive
Chamber of Minerals and Energy WA
Mitchell H Hooke
Chief Executive
Minerals Council of Australia
56
Survey of Occupational Groups by Operational Activity
Please indicate the percentage of your workforce
(including contractors) in each of these occupational categories
Column 1
Column 2
Column 3
Column 4
Column 5
Column 6
Column 7
OCCUPATIONAL
SAMPLE OCCUPATIONS
Argus Report
Mining
Processing
Maintenance
Exploration
GROUP
(production)
20%
5%
8%
Labourers and
Mining/petroleum labourer
4%
related workers
Factory/plant operator
19%
Semi-skilled
Crane/hoist operator, Driver,
32%
workers
Miner
Rigger/Dogman, Scaffolder
10%
2%
8%
Tradespersons
Mechanical tradesperson
21%
Electrical tradesperson
Automotive tradesperson,
Plumber
Chef/cook
1%
Technicians
Laboratory technician
13%
Chemical/process designer
Drilling superintendent
Mining/metallurgical technician
9%
2%
10%
Professionals
Surveyor, Mining engineer
25%
Geologist, Drilling engineer,
Environmental scientist,
Community relations
professional, Metallurgist
3%
1%
2%
Managers and
Project manager
5%
administrators
Operations/Production manager
General manager, Mine
managers, Exploration manager
NB: Column 3 of this table contains the percentage distribution of these occupational groupings that were reported for the Western Australian
mining industry in a 2004 study by Argus Research. The Argus Report figures are provided as a guide only and may not be relevant to individual
site’s employee data.
57
COMMODITY: ___________ _______________________________________ (if multi-commodity please indicate Major/Minor)
OPEN CUT OR UNDERGROUND OR BOTH?: (PLEASE CIRCLE)
STATE: (PLEASE CIRCLE)
TOTAL WORKFORCE AT YOUR SITE No’s (incl. Contractors): _______________________________________
ARE THE OCCUPTIONAL DISTRIBUTIONS (AS INDICATED IN THE TABLE) STABLE OR CHANGING?
IF CHANGING, WHAT ARE THE DRIVING FORCES _______________________
ARE SKILL SETS AND TASKS UNDERGOING DRAMATIC CHANGE IN SOME OCCUPATIONS? Y
IF YES, WHICH ARE THESE OCCUPATIONS AND HOW ARE THE SKILL SETS CHANGING?
Thank you for completing this survey.
Please return your completed survey via email to Dr Diannah Lowry at the National Institute of Labour Studies
diannah.lowry@flinders.edu.au by the 7th of April, 2006.
58
8.
APPENDIX B
8.1 Calculating the base employment data set
The first step of the in projecting demand for labour in the mining industry was
to establish a base employment level in the base year by commodity, by state.
The primary data source for these estimates is the 2006 “Minelist” from the Perthbased Resource Information Unit (RIU), which provided numbers of employees
for each state and territory (excluding ACT) by major commodity. The Minelist
data is based on a survey of Australian mines (with approximately 95 per cent
coverage of the sector). Fortunately 2006 was the first year that data (for 2005) on
numbers of employees has been collected. Thus the primary source of data is a
“bottom up” source based on specification of the employment level by individual
mines.
RUI also supplied NILS with two custom data sets based on the 2006 Minelist
mine survey:
•
a list of all mines in Australia with numbers of employees, state, mine type,
main commodity
•
a list of all multi-commodity mines (MCMs) with estimated output of each
mine expressed in refined metal equivalents
Without the Minelist employment data it would have been very difficult to
establish a base employment data set for the mineral industry. There is good data
for some commodity types in some states, for example coal in NSW, but for
others data is very sketchy or non-existent. In order to provide verification of the
Minelist employment figures we examined all of the state-based and commoditybased employment that we could find that was publicly available. In cases where
such data gave higher employment numbers that the Minelist data we used the
former. The sources for this data were:
•
Department of Natural Resources, Mines and Energy, Queensland Coal
Statistics
•
The Department of Industry and Resources (DoIR) in Western Australia
•
Aluminium and the Australian Economy A Report to the Australian
Aluminium Council, May 2000
•
Queensland Mines and Quarriers Safety Performance and Health Report
2004-5
•
NSW Coal Industry Profile, NSW Department of Primary Industries
59
•
Annual Review 2003/2004 Mineral Resources, Tasmania
Given that these various data points were for different years there was some
question over what the base year should be. Our pragmatic solution was the set
the base year at the end of 2004 or the beginning or 2005. The advantage of this
was that is reflected the year in which the Minelist data were collected and
represent a reasonable compromise with respect to the years on which the other
data were based.
A complication involved in calculating employment by commodity was created
by the fact that there are twenty six Australian mines each producing between
two and five distinct mineral outputs. We call these multi-commodity mines
(MCMs).
For the MCMs the problem is how to allocate total mine employment levels
across these multiple commodities produced at each mine. This is an example of
an economic and accounting problem called “joint costs”. There is no theoretically
corret way that the cost of labour can be allocated to each of the commodities
produced at a multi-commodity mine. The generally accepted pragmatic solution
is to allocate costs – in our case number of employees – to each type of output
according to the value of those outputs.
The commodity outputs (generally as refined equivalents) for multi-commodity
mines were provided in the second custom data set from RIU. To derive values
these quantities were multiplied by prices from ABARE 2004, Australian
Commodity Statistics 2004.
The use of refined equivalents rather than the value of ore shipped from each
mine involves an approximation, that is, to the extent that different MCMs ship
ores of differing qualities that sell for different prices, the use of refined
equivalents will potentially introduce inaccuracies. The only alternative would be
to obtain the actual value of all (unrefined ore) commodities shipped from all
MCMs.
The calculated values of output by commodity from MCMs were used to calculate
value ratios that were then used to distribute employment at each MCM to create
a series of commodity-distributed employment levels (CDELs) for each MCM.
The list of “commodity-distributed employment levels” CDELs by mine was then
added to the list of single-commodity mines with their respective employment
levels. From this consolidated list sub-totals for employment by state, by
commodity and mine type (open cut or underground) were calculated resulting
in the base employment series for 2004/5.
The next step was to project demand from the base employment data set ahead
to 2015. For this we used commodity output forecasts supplied by BIS Shrapnel
60
(2005). BIS Shrapnel supplied us with projections of output for each of the
commodities to 2015.
8.2 Calculating projected employment demand
BIS Schrapnel has supplied NILS with annual estimates of output and estimated
growth rates by state and by commodity for 2005 to 210. Growth rates from 2010
to 2015 are at a constant annual rate.
To project employment levels by state and by commodity these growth rates
were applied the base employment dataset. The assumption made at this point is
that the output per worker will not change significantly over the decade.
8.3 Distributing projected demand by occupational classifications
and mine activity
Once a projected employment level by state and by commodity had been
established for 2005 to 2015, it was next necessary to distribute these totals across
occupational groups. This project used a six-category occupational distribution:
•
Managers
•
Professionals
•
Technicians
•
Tradespersons
•
Semi-skilled workers
•
Labourers and related workers.
A survey of 14 Australian mining companies (with coverage of 33,304 employees,
approximately one third of employees in the commodities of interest) provided
information about the distribution of occupations across all of the commodity
groups and by the four main categories of mining activity (production,
processing, maintenance and exploration). For each year from 2005 to 2015 the
projected total level of employment in each commodity grouping was distributed
across the six occupational classifications.
61
9.
APPENDIX C
9.1. Employment share projection: Growth curve models
The class of functions called growth curves or S-shaped curves is motivated by
the fact that rates must be in the range [0,1] and therefore cannot grow as
polynomials or exponentials. We find the curve that best fits the historical data
and extrapolate along this curve under the assumption that the present trends
capture the sum of the effects of diverse factors and will continue to do so in the
future. Richards curves are used in projections of employment share changes in
occupations as well as within mining industry. With Richards curves it is possible
to model any growth in the sigmoid form and distinguish the three phases that
underlie these evolutions: emergent, inflexion and saturation, as well as the
periods of expansion and contraction of economic phenomena.
The occupational employment shares for each occupation and for each age group
were modelled as Richards curves. These shares were predicted separately using
non-linear least squares techniques applied to data on the level of employment in
each of the main occupations, by age. Projections directly focused on finding the
best fits of Richards curves to the available data comprising the employment
share for each occupation and for each age group. The projected employment
shares for each occupation and for each age group were applied to the predicted
overall employment and disaggregated employment by age group to compute
the absolute numbers of employed persons in each occupation and in each age
group. Similarly, the shares and numbers of employment in 2-digit mining
industries and by age group were projected using the same projection techniques.
The Richards functions take the form:
y t = c + a " (1 + be gt ) !
[1]
Some restrictions were set up over the parameters a+c, b, c, g, and lambda (!).
The reason is that the limits at upper and lower infinity are a+c and c, so that in
constraining these to [0,1], which ensures that the curve stays in this range, b is
also constrained to [0,1]. Lambda is constrained to [-1, -20], g is constrained to
either [-20,0] or [0,20], depending on whether the curve is nominally increasing or
decreasing. The ceiling (a+c) is the maximum occupational level either attainable
in the past and present economic paradigm or to be reached in the future, whilst
the floor (c) represents the minimum level, which might have been reached in the
preceding paradigm or may be reached in the future. Richards curves for each
occupation or industry and for each age cohort have different coefficients,
reflecting dynamics of occupational evolution and disparities in the employment
experience and conditions of people involved in the occupations or industry. The
changes and parametric values vary by occupation or industry and by age.
62
9.2. Data and sources
The outcomes of the projections of the Productivity Commission (PC) and labour
force survey data from the Australian Bureau of Statistics (ABS) are utilised
extensively as data sources for the analysis and scenario constructions of
projections in this chapter. The main data and sources used include:
Population and labour force projections (including civilian population,
participation rates, and unemployment ratio) for Australia from 2004 to 2051,
sourced from the website of the Productivity Commission,
http://www.pc.gov.au/study/ageing/finalreport/data/index.html (accessed 10
October 2005); and
Data files “E07–Employed persons by sex, occupation, age, status in
employment” and “E05–Employed persons by industry subdivision, sex, age,
status in employment” from the ABS Labour Force, Australia, Detailed –
Electronic Delivery, Quarterly (cat. no. 6291.0.55.001);
As longitudinal data on the size and distribution of labour supply or employment
outcomes of people working in the six occupations are lacking, we used synthetic
cohort datasets. These were derived from the quarterly data file “E07–Employed
persons by sex, occupation, age, status in employment” from the ABS Labour
Force, Australia from August 1996 to August 2005.
The derived data were used to develop the projections of occupational
employment shares. The problem of the unevenly spaced age groups in the
original data is resolved by using population interpolation techniques to break
down the 10-year-age groups into 5-year-age groups. The interpolated
quinquennial age groups of datasets laid the basis for cohort analysis. The
calculated annual employment in occupations across the period from 1996 to 2005
for Australia was smoothed using a Hodrick-Prescott filter. In doing so, the
statistical noise of the original data was largely removed, revealing the general
trends of employment shares by age group in the long run.
63
10. REFERENCES
BIS Shrapnel (2005) Outlook for Mining Activity in Australia, Report prepared for the
National Institute of Labour Studies, September 2005
Australian Bureau of Statistics , Job Vacancies Australia, Cat. No. 6354.0
Australian Bureau of Statistics, Labour Force Australia, Cat. No. 6202.0
Australian Bureau of Statistics, Australian System of National Accounts, Cat. No. 5204.0
Argus Report (2004) Western Australian Development Projects: Employment Demand
and Predicted Skill Requirements 2003-2007, Report prepared for the Western
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Department of Industry and Resources (2000- 2005) Western Australian Mineral and
Petroleum Statistics Digest (various years).
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Moskos, M (2004) Identity Work: The Identity Construction of Low Skilled, Prime Aged
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NCVER (2005) Current and Future Skill Needs for the Minerals industry, National Centre
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Nixon, D (2005) ‘“I just like working with my hands”: Employment Aspirations and the
Meaning of Work for Low-Skilled Unemployed Men in the British Service
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64