Determinants of labour supply amongst aged
care workers: A multivariate analysis
Report to the
Department of Health and Ageing
National Institute of Labour Studies, November 2005
Bill Martin
Table of Contents
EXECUTIVE SUMMARY.......................................................................................................................... 1
1.
INTRODUCTION ................................................................................................................................ 4
2.
DATA AND ANALYSIS...................................................................................................................... 5
3.
LABOUR SUPPLY – EXPECTATIONS ........................................................................................ 8
4.
LABOUR SUPPLY – CURRENT CONTRACT TYPE...............................................................16
5.
LABOUR SUPPLY – DESIRE TO WORK MORE HOURS .....................................................19
6.
WHAT DETERMINES JOB SATISFACTION? ..........................................................................24
7.
WAGE DETERMINANTS ...............................................................................................................29
8.
CONCLUSION ...................................................................................................................................34
List of Tables
TABLE 3.1:
NURSES’ AND PERSONAL CARERS’ EXPECTATIONS ABOUT FUTURE EMPLOYMENT IN THE
AGED CARE INDUSTRY .............................................................................................................. 9
TABLE 3.2:
DETERMINANTS OF NURSE’S EXPECTATIONS ABOUT STAYING IN AGED CARE OVER NEXT 12
MONTHS AND NEXT 3 YEARS .................................................................................................. 11
TABLE 3.3:
DETERMINANTS OF PC’ S EXPECTATIONS ABOUT STAYING IN AGED CARE OVER NEXT 12
MONTHS AND NEXT 3 YEARS .................................................................................................. 13
TABLE 4.1:
PROPORTION OF NURSES AND PCS WHO ARE EMPLOYED CASUALLY AND WHO WORK FULLTIME ........................................................................................................................................ 17
TABLE 4.2:
DETERMINANTS OF WHETHER NURSES ARE EMPLOYED CASUALLY AND WORK FULL TIME 17
TABLE 4.3:
DETERMINANTS OF WHETHER PCS ARE EMPLOYED CASUALLY AND WORK FULL TIME...... 18
TABLE 5.1:
PROPORTION OF NURSES AND PCS WHO WOULD PREFER TO WORK MORE AND FEWER
HOURS PER WEEK .................................................................................................................... 21
TABLE 5.2:
PROPORTION OF NURSES AND PCS WHO WOULD PREFER TO WORK MORE AND FEWER
HOURS PER WEEK BY WHETHER CURRENTLY FULL-TIME OR PART-TIME ............................. 21
TABLE 5.3
DETERMINANTS OF ADDITIONAL HOURS NURSES AND PCS CURRENTLY WORKING PARTTIME WOULD LIKE TO WORK ................................................................................................... 22
TABLE 6.1:
JOB SATISFACTION AMONGST NURSES AND PCS ................................................................... 25
TABLE 6.2:
DETERMINANTS OF NURSES’ AND PCS’ JOB SATISFACTION ................................................ 27
TABLE 7.1:
DETERMINANTS OF NURSES’ AND PCS’ HOURLY WAGES .................................................... 32
TABLE 7.2:
DETERMINANTS OF PCS’ AND NURSES’ WAGES ................................................................... 33
Executive Summary
What factors affect labour supply in aged care facilities is a crucial issue for those
managing facilities, and those making policy in the area. In this report, we examine
the factors that affect labour supply by analysing the behaviour, attitudes and
experience of employees surveyed in 2003. The report uses information from a census
of aged care facilities and a random sample survey of direct care workers to
investigate these issues. We use multivariate techniques of data analysis to investigate
the unique contribution of a wide range of factors to outcomes related to labour
supply.
The behaviour, expectations and intentions of those currently employed as direct care
workers are very important factors in the future supply of such labour. Our earlier
research showed that aged care facilities currently replace about 20% of their Nurses
and Personal Carers each year, a fairly high rate of turnover. Clearly, understanding
the factors that predict turnover is important. We also know that 65% of all direct care
workers work part-time, thus forming a large potential pool of additional labour.
Indeed, 28% of all direct care workers indicated that they would like to work more
hours than they currently do. Thus, understanding what factors affect part-timers’
interest in working additional hours is also important in fully comprehending the
determinants of future labour supply.
This report focuses on the following six labour supply related outcomes amongst
Nurses and PCs employed in aged care facilities at the time of our surveys:
•
Their expectations of remaining in the aged care sector in 12 months and 3
years;
•
Whether they work part-time or full-time;
•
Whether they are employed on permanent or casual contracts;
•
Their desire to work more hours;
•
Their job satisfaction;
•
Their wages.
-1-
In investigating the determinants of these outcomes, we focus on four sets of factors
related to:
•
Employees’ employment arrangements and preferences;
•
Employees’ experience of work;
•
Employees’ personal characteristics;
•
The characteristics of the facilities where employees work.
The dominant factors affecting employees’ expectations about remaining in the aged
care sector are how well their employment arrangements fit with their preferences,
and how they experience their work. Thus, employees are more likely to expect to
leave the sector if: they work unsocial hours, they would prefer different shifts or
different hours, they feel their skills are not used at work, they feel under pressure to
work harder, or they have relatively low job satisfaction. There are some indications
that those with more employment choices (because they have greater human capital)
are more likely to expect to leave the sector, but these are equivocal. Thus,
employment arrangements and how employees experience work, both under the
influence of management practices, are the dominant determinants of current
employees’ expectations about remaining in the aged care sector.
Employers’ preferences and practices appear to be the dominant influences on
whether employees work on casual or permanent contracts. They also have a major
influence on the hours direct carers work. However, hours of work are also influenced
by carers’ needs and the demands of their family roles, an unsurprising finding given
that almost all direct care workers are women. Nevertheless, there is little doubt that
employers have real additional labour at their disposal in the form of employees who
are prepared to work more hours.
Analysing what influences the number of additional hours employees would like to
work shows that those wanting to work longer or shorter hours are not sharply
distinguished from others. In the case of PCs, this is largely due to the fact that hours
of work appear to be determined mostly by employers’ preferences, with many PCs
wishing to work more hours. In contrast, most Nurses wanting to change their hours
would prefer to work fewer hours. Again, employers’ preferences, this time for
Nurses to work longer hours than they would like, appear to be the primary
-2-
determinant of their hours. It also appears that employers often trial new employees
on limited hours and casual contracts before giving them more permanent
employment and longer hours.
Job satisfaction is important in determining future labour supply since it has
significant influence on employees’ expectations about remaining in the aged care
sector, as do related subjective experiences of work. Our analysis shows that we can
identify many of the major influences on job satisfaction, and that most are under the
influence of employers. Far and away the most important determinants of job
satisfaction are employees’ direct work experiences – how much time they are able to
spend in direct care, whether they use their skills on the job, whether they have some
freedom to decide how to do their work, and whether they feel under great pressure to
work harder. The other major determinants of work satisfaction relate to whether
employees are able to get the shifts and hours they prefer.
Our analyses of Nurses’ and PCs’ wage levels shows, first, that both groups have
quite compressed wage distributions. Nurses experience some wage premiums from
higher levels of education and greater experience. However, PCs do not receive these
premiums. Indeed, PCs who complete aged care qualifications (Aged Care Certificate
III or IV) cannot expect to experience any rise in wages. We do find a premium to
being employed as a Nurse rather than a PC that cannot be explained by differences in
any of a large range of labour market and personal factors. This suggests that PCs
would face a strong incentive to upgrade to nursing skills and qualifications if an
appropriate pathway existed.
-3-
1.
Introduction
The determinants of labour supply in aged care facilities are a crucial issue for those
managing facilities, and those making policy in the area. The main report of our
project on the labour force in the industry suggested that there is not a current crisis in
the labour market for direct care staff, though there are significant signs of stress,
particularly in relation to registered Nurses (Richardson and Martin 2004). However,
these signs of stress are of policy concern, and it remains possible that they could turn
into a more substantial difficulty for the industry under certain conditions. Even
without the sense of possible crisis, the factors that affect labour supply will be of
great interest to managers and policy makers as they seek to satisfy labour demand
most efficiently.
In this report, we examine the factors that affect labour supply by analysing the
behaviour, attitudes and experience of employees surveyed in our 2003-2004 study.
We are fortunate in being able to link what employees tell us about themselves and
their work experiences with data about the facilities in which they work (obtained
from our facilities census). This gives us the capacity to assess the contribution of
both individuals’ characteristics and those of their workplaces in determining their
labour supply behaviours and intentions.
The labour employees supply to the industry is affected by two sets of issues: whether
they remain in the aged care industry, and, if they do, how many hours they work. Our
main report identified a significant issue of labour turnover in the industry, with
around 20% of both Nurses and Personal Carers needing to be replaced every year
(Richardson and Martin 2004: 31). Indeed, 29% of Nurses and 24% of Personal
Carers indicated that they did not expect to be working in aged care 3 years after they
were surveyed (p. 43). Our first step therefore is to analyse the factors that affect
employees’ intentions to remain in the aged care workforce. A second determinant of
labour supply is the hours that employees work. Part-time work is the norm amongst
aged care workers, with 65% of direct care workers being employed less than full
time (p. 23). Moreover, about 18% of Nurses and just over 20% of Personal Carers
are employed on non-permanent contracts, mostly as casuals (p. 20). Both part-time
workers and casual workers are likely to provide a source of additional labour if
demand rises, so we examine what factors are associated with whether workers fall
-4-
into either of these categories. Finally, in relation to labour supply, about 28% of
direct care employees said that they would prefer to work more hours than they
currently do (p. 24). This gives us a direct measure of employees’ willingness to
supply additional labour to the industry, so we examine what affects these
preferences.
Our earlier report suggested that the satisfactions direct carers experience in their
work is a major factor in what they like most about their jobs, and in their decisions to
stay in the industry (pp. 42-43). Our analyses here on employees’ intentions confirm
this picture. Our next step in this report, therefore, is to examine what factors affect
workers’ job satisfaction. In particular, we examine how facility characteristics and
work experiences affect job satisfaction, since these are under the control of managers
and/or policy makers, at least to some extent.
Finally, we examine the determinants of wages. Wage variation amongst Nurses and
amongst Personal Carers is relatively small. It is therefore not surprising that our
analyses in this report show that the variations that do exist have little or no effect on
labour supply decisions. Our analysis of the wage variation that does exist is relevant
mainly to future thinking about how wage patterns might be altered if it is necessary
to search for mechanisms to increase labour supply. Analysing the determinants of
wages helps us to assess whether there are any indications that Nurses and Personal
Carers experience clear career paths that might induce them to remain in the industry.
For example, do Personal Carers experience a wage premium for completing
qualifications in aged care?
2.
Data and Analysis
This report uses the same data as the main report for our project (for details, see
Martin and Richardson 2004). We focus on a survey of a random sample of direct
care workers in Australian residential aged care facilities. The survey was conducted
in late 2003, along with a census of all Australian residential aged care facilities. In
this report, we use this data to investigate which factors affect a range of outcomes
related to labour retention in aged care facilities. We have linked the survey and
census data so that we are able to assess the impact of both employees’ individual
characteristics and, those of the facilities where they work, on outcomes. So, for
-5-
example, we can assess both whether an employees’ age affects their expectation to
remain in the aged care sector, and whether there are differences in expectation
between those employed in rural and metropolitan facilities.
We examine the factors affecting the following six sets of outcomes, in this order:
1.
Employees’ expectations about remaining in aged care work in the future;
2.
Whether employees work on casual or permanent contracts;
3.
Whether they work full-time or part-time;
4.
Whether employees would prefer to work longer hours;
5.
Employees’ job satisfaction;
6.
Employees’ wages.
In this report, we focus on Nurses and Personal Carers, primarily because these are by
far the largest direct care occupations, and those about which there is greatest concern
over future labour supply.
We examine the effect of a broad range of factors on these five sets of outcomes.
These factors can be placed into four groups:
•
Employees’ employment arrangements and preferences;
•
Employees’ experience of work;
•
Employees’ personal characteristics;
•
The characteristics of the facilities where employees work.
Although factors from every group are assessed in relation to each outcome, not all
factors are included in analyses of every outcome. So, for example, our analysis of
employees’ wages does not include some employment preferences since there is no
reason to expect these to affect wages. And, in some cases, factors that may affect an
outcome are later treated as outcomes themselves. Employees’ employment contract
types, job satisfaction and wage levels, for example, are analysed as possible
influences on whether employees expect to remain in the aged care sector. However,
later in the report each is itself treated as an outcome. This analysis allows us to build
-6-
up a detailed picture of how employees’ labour supply intentions and preferences are
determined.
In more detail, we analyse the impact of the following factors on one or more of our
five sets of outcomes:
•
Employees’ employment arrangements and preferences:
o Whether they work a normal day shift, an evening or night shift, or
another irregular kind of shift (i.e., the analysis compares three groups)
o Whether they would prefer to work a different kind of shift
o Whether they would prefer to work more, fewer or the same number of
hours as they currently do
o Whether they are employed on a casual or permanent contract
o Their hourly wage
•
Employees’ experience of work
o The amount of time they spend directly caring for residents in a typical
shift
o Their experience of work (including whether they are able to spend
enough time with residents, their experience of skill usage, etc.)
o Their job satisfaction
o The amount of time they have worked for their current employer
•
Employees’ personal characteristics:
o Their sex
o Their age
o Whether they were born in a non-English speaking country
o Whether they live with a partner
o Whether they are the main earner in the household
o How good their health is
o Their care responsibilities at home
o Their level (and type for PCs) of education
o Whether they are currently studying an aged care qualification
•
The characteristics of the facilities where employees work:
o Whether they work in a metropolitan, regional or rural facility
o Whether the facility has only high care places
o The total number of employees in the facility
-7-
o The ownership of the facility (not-for-profit, for-profit, or public
ownership)
To assess the impact of these factors, we use multivariate analyses – logistic
regression and OLS regression. These common techniques allow us to assess the
unique effect of each factor in our analysis on an outcome. For example, we can
assess the effect of a person’s level of post-secondary education on wages
independent of a range of other factors such as their age, what type of shift they work,
whether they are employed on a casual or contract basis, etc. In all our analyses, we
are able to decide whether a factor has an influence on an outcome, and the direction
of that influence. For example, we can say whether or not having higher job
satisfaction affects a person’s expectation of remaining in the aged care sector in 3
years. If it does have such an effect, we can say whether higher job satisfaction makes
a person more or less likely to remain in the sector. In some of our analyses, where we
use OLS regression, we are able to be more precise about the size of the effects of
each factor and their relative importance.
3.
Labour Supply – Expectations
As we have already noted, our previous report found indicators of substantial turnover
amongst direct care workers. Although some of this turnover will be due to movement
between facilities within the aged care industry (which does not affect overall labour
supply in the industry), a significant part will also be due to employees leaving the
aged care industry altogether. Since departure from the industry is of greatest concern,
we focus on whether employees intend to remain in the industry (rather than simply
whether they expect to remain in their current position or organization). Our survey
asked workers both where they expected to be in 12 months and in 3 years, and we
examine each of these responses. Table 3.1 shows the proportion of Personal Carers
and Nurses expecting to be in the aged care industry over each time period. It
confirms the earlier picture of quite substantial turnover expectations amongst direct
care workers – nearly 30% of Nurses and nearly a quarter of PCs do not expect to be
working in aged care in 3 years. But are some workers more likely than others to
expect to be working outside the aged care industry in the future?
-8-
Table 3.1:
Nurses’ and Personal Carers’ expectations about future employment in
the aged care industry
Do not expect to be working in aged care in 12 months
Do not expect to be working in aged care in 3 years
Total
Nurses
17.9%
29.1%
1097/1122
PCs
13.6%
24.2%
1314/1358
Our analysis involves estimating logistic regression models for whether or not
workers expect to be in the aged care industry in 12 months and 3 years. This analysis
allows us to assess whether expectations are affected by most of the factors described
above (Section 2). It provides estimates of the effects of each factor, independent of
all the other factors in the analysis (or, to put it another way, controlling for all the
other factors in the analysis). For example, even though we know that rural facilities
tend to be smaller than other facilities, this procedure allows us to assess whether
facility size or facility location or both factors (or neither) are affecting employee
intentions.
Table 3.2 shows the results of this procedure for Nurses’ expectations in 12 months
and 3 years. It indicates that the following factors make Nurses more likely to expect
to be working in aged care in 12 months:
•
Employees’ employment arrangements and preferences:
o Not being on a permanent evening or night shift
o Preferring a different shift
o Not being casually employed
•
Employees’ experience of work
o Feeling that many of one’s skills are used in one’s current job
o Having higher job satisfaction
•
Employees’ personal characteristics:
o Being older
o Having more years of secondary education
o Having fewer years of post-secondary education
•
The characteristics of the facilities where employees work:
o Not working in a for-profit facility
Nurses are more likely to expect to be working in aged care in 3 years if:
-9-
•
Employees’ employment arrangements and preferences:
o They are not on a permanent evening or night shift
o They prefer a different shift to the one they currently work
o They prefer to work more or less hours than currently employed
•
Employees’ experience of work
o They feel that many of their skills are used in their current job
o They feel less strongly that they have the skills to undertake their job
o They have higher job satisfaction
•
Employees’ personal characteristics:
o They are female
o They are older
o They were born in a non-English speaking country
o They are the main income earner in their household
o They spend more time caring for family members at home
•
The characteristics of the facilities where employees work:
o They are employed in a rural or regional facility (rather than a
metropolitan one)
o They are employed in a facility with only high care places
o They are not working in a publicly owned facility
-10-
Table 3.2:
Determinants of Nurse’s expectations about staying in aged care over
next 12 months and next 3 years
Next 12 months
B
Exp(B)
Shift type (0=regular day shift)
Regular eve/night shift
Irregular shift
Prefer different shift
Hours preferences (0=same as current)
Prefer work less
Prefer work more
Months at current facility
Casual employee
Wage per hour
Time spent in direct care (0=more than two thirds)
Less than a third time direct care
Between one third and two thirds time
Male
direct care
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
Excellent health
No. hrs caring for people in own household
Years secondary education
Years post-secondary education
Currently studying aged care qual.
Able to spend enough time with each resident
Have the skill I need to do my job
Use skills in current job
Have freedom to decide how I do my work
Do not feel under pressure to work harder
Job satisfaction
Facility location (0=metropolitan)
Regional facility
Rural facility
High care places only
Total no. employees
Facility ownership (0=not-for-profit)
For-profit facility
Publicly owned facility
Constant
N
2
Nagelkerke R
*p≤ .05
**p≤ .01
-11-
Next 3 years
B
Exp(B)
-.966**
-.034
.532*
.381
.967
1.702
-.796**
-.239
.527*
.451
.787
1.693
.498
.009
-.002
-.776*
-.009
1.646
1.009
.998
.460
.991
.724**
.807*
.002
-.584
.014
2.062
2.242
1.002
.558
1.014
.012
-.056
-.328
.054**
-.438
.405
.176
1.012
.946
.720
1.056
.645
1.500
1.192
.278
.210
-.785*
.026*
-.766*
.033
.467*
1.321
1.234
.456
1.027
.465
1.034
1.596
-.068
.022
.003
.229*
-.244*
.153
.093
.005
.148*
-.146
.019
.053**
.934
1.023
1.003
1.257
.784
1.165
1.098
1.005
1.159
.864
1.019
1.055
.031
-.067
.006*
-.047
-.101
.737
.013
-.301*
.256**
.099
-.003
.070**
1.031
.935
1.006
.954
.904
2.089
1.013
.740
1.291
1.104
.997
1.072
.069
-.215
.309
.001
1.072
.807
1.362
1.001
.505*
.556*
.779**
.000
1.657
1.743
2.179
1.000
.492
.638
.035
-.148
-.660*
-3.367*
719
.321
.862
.517
.034
-.709**
-.449
-3.343*
700
.193
Personal Carers’ expectations about their future in the aged care industry are affected
by some of the same factors as Nurses, but there are also differences. Table 3.3 shows
that the likelihood of PCs expecting to be working in aged care in 12 months is not
affected by their employment arrangements or preferences, or by the characteristics of
the facilities that employ them. However, the likelihood that they expect to remain
after 12 months is increased if:
•
Employees’ experience of work
o They feel under less pressure to work harder
o They have higher job satisfaction
•
Employees’ personal characteristics:
o They are older
o They have aged care qualifications
o They are not currently studying for aged qualifications
By contrast, their expectations about remaining in the sector 3 years into the future are
affected by a broader range of factors. The expectation that they will be in the aged
care sector in 3 years is increased if:
•
Employees’ employment arrangements and preferences:
o They do not work permanent night or evening shifts
o They would prefer to work more hours than they currently do
o They have worked in their current facility for a shorter time
•
Employees’ experience of work
o They feel under less pressure to work harder
o They have higher job satisfaction
•
Employees’ personal characteristics:
o They are older
o They have less secondary schooling
•
The characteristics of the facilities where employees work:
o They work in facilities with fewer employees
-12-
Table 3.3:
Determinants of PC’s expectations about staying in aged care over next
12 months and next 3 years
Next 12 months
B
Exp(B)
Shift type (0=regular day shift)
Regular eve/night shift
Irregular shift
Prefer different shift
Hours preferences (0=same as current)
Prefer work less
Prefer work more
Months at current facility
Casual employee
Wage per hour
Time spent in direct care (0=more than two thirds)
Less than a third time direct care
Between one third and two thirds time
Male
direct care
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
Excellent health
No. hrs caring for people in own household
Years secondary education
Years post-secondary education
Hold aged care qualification
Currently studying aged care qualification
Able to spend enough time with each resident
Have the skill I need to do my job
Use skills in current job
Have freedom to decide how I do my work
Do not feel under pressure to work harder
Job satisfaction
Facility location (0=metropolitan)
Regional facility
Rural facility
High care places only
Total no. employees
Facility ownership (0=not-for-profit)
For-profit facility
Publicly owned facility
Constant
N
2
Nagelkerke R
*p≤ .05
**p≤ .01
-13-
Next 3 years
B
Exp(B)
-.485
.023
-.272
.616
1.023
.762
-.544*
-.060
.210
.580
.941
1.234
.389
.207
.002
-.336
.025
1.475
1.229
1.002
.714
1.025
-.387
1.091**
-.004*
-.276
-.001
.679
2.976
.996
.759
.999
.225
-.212
.229
.025*
-.038
.307
-.208
1.253
.809
1.257
1.025
.962
1.359
.812
.408
-.244
.364
.039**
-.051
.463
.222
1.504
.783
1.439
1.040
.950
1.589
1.249
-.022
.208
.005
-.154
.026
.746*
-.962**
.059
-.150
.081
-.050
.184**
.062**
.979
1.231
1.005
.858
1.026
2.109
.382
1.061
.860
1.085
.951
1.202
1.064
-.174
-.454
.004
-.229*
-.078
.479
-.308
-.016
-.123
.056
.102
.147**
.063**
.840
.635
1.004
.795
.925
1.615
.735
.984
.884
1.058
1.107
1.158
1.065
-.203
-.383
.056
.000
.816
.682
1.058
1.000
-.174
-.454
.004
-.229*
.840
.635
1.004
.795
-.394
.751
-1.744
752
.207
.674
2.118
.175
.150
.317
-2.788*
780
.278
1.161
1.373
.062
Together, these results show that some factors have consistent large effects on
Nurses’ and Personal Carers’ intentions. First, employees with higher job satisfaction
are consistently more likely to expect to remain in the aged care sector. There are also
strong indications that workers who feel their skills are used in their jobs, and who do
not feel under pressure to work harder, are more likely to expect to remain in the
industry.
Second, employment arrangements and preferences also affect expectations
significantly. Those on permanent night or evening shifts are particularly unlikely to
expect to remain in the industry. Both Nurses and PCs who would prefer more hours
are also much less likely to expect to remain in the sector in 3 years. And, in an
indication that overwork may be a problem amongst some Nurses, preferring fewer
hours makes Nurses (but not PCs) significantly less likely to expect to remain in the
industry. In general, it appears that workers who are able to obtain the shift
arrangements they would like are more likely to expect to remain in the aged care
industry.
Third, some personal characteristics affect employees’ likelihood of expecting to
remain in the industry. In particular, the older an employee is, the more likely he/she
is to have this expectation. There are two possible explanations for this result. Older
workers may find it more difficult to obtain alternative employment, and may
therefore expect to remain in the industry because they have more limited choices
than younger workers. On the other hand, it may be that older workers have the same
range of labour market choices as equivalent younger ones, but find aged care work
more conducive than do younger workers, and therefore prefer it to the alternatives.
The direct care workforce is generally significantly older than the general Australian
workforce, a matter that has caused concern to some policy makers. For this reason,
clearly establishing why older workers are more likely to expect to remain in the
sector, and how work in the sector typically fits into careers, are important future
research questions.
Our results do indicate that workers with personal characteristics that give them less
labour market capacity are often more likely to expect to remain in the aged care
industry. For example, Nurses with less post-secondary education are less likely to
expect to leave the sector in 12 months, and PCs with less secondary education are
-14-
less likely to expect to leave the sector in 3 years. On the positive side, PCs who have
invested in their skills in the area by obtaining aged care qualifications are more likely
to expect to remain in the sector in 12 months (though, apparently, not in 3 years).
Finally, facility characteristics have small effects on Nurses’ expectations in the
future, but none on those of PCs. The most interpretable of these results is that Nurses
in metropolitan facilities are less likely to expect to remain in the sector for three
years than those in rural or regional facilities, and that those in facilities with only
high care places (i.e, pure ‘nursing homes’) are more likely to remain. The former
effect is almost certainly a product of more limited employment opportunities in nonmetropolitan areas. The latter may be a result of the more ‘technical’ nursing in high
care facilities being more attractive to Nurses.
It is worth noting that a number of factors have no effect on workers’ expectations
about remaining in the sector. In particular, those who are higher paid are no more or
less likely to expect to remain. This may be partly because the distribution of wages is
compressed, especially for PCs, so that the variations that do exist are not large
enough to affect employees’ expectations (see Section 7 below). Secondly, a number
of aspects of workplace experiences (such as how much time employees spend in
direct caring, whether they are able to spend enough time with each resident, whether
they have freedom to decide how to do their job, etc.) have no effect on expectations.
As our later analysis of the determinants of job satisfaction indicate, this is essentially
because these factors impact on intentions primarily by affecting job satisfaction.
Thus, for example, spending more time in direct care work probably does increase the
likelihood that employees will expect to remain in the sector. However, this effect
occurs primarily by increasing their job satisfaction which in turn affects their
expectations.
Overall, these results indicate that the expectations of currently employed Nurses and
PCs about their future in the aged care industry are affected by their preferences, their
experience of the industry’s ability to meet those preferences, and their overall labour
market opportunities. Employees who have high job satisfaction, feel they have the
skills to undertake their jobs and do not feel under strong pressure appear to enjoy
their jobs more and are therefore more likely to try to remain in the industry.
However, unattractive shifts and being unable to work the hours they would like can
-15-
negate the positive experience of work, and make employees more likely to expect to
leave the industry. Finally, unsurprisingly, some human capital and labour market
factors that mean employees have more employment choices are associated with
being more likely to expect to leave the industry. It is worth noting, though, that the
latter effects are not particularly large or consistent. This suggests that even where
employees do have opportunities to leave the sector, they will not do so unless they
find the work unsatisfying or unconducive, or they are unable to achieve the working
conditions they would like.
4.
Labour Supply – Current Contract Type
The factors that affect whether employees are employed casually or on permanent
contracts, and whether they work full-time or part-time, may help in understanding
the determinants of labour supply. Working casually and working part-time may be
the result of lack of demand for the labour of employees, or the constraints they face
in supplying labour. Our analyses consider the impact of a range of variables on these
outcomes. The potential determinants fall into three groups. They are:
•
Employees’ experience of work
o The amount of time they have worked for their current employer
•
Employees’ personal characteristics:
o Their sex
o Their age
o Whether they were born in a non-English speaking country
o Whether they live with a partner
o Whether they are the main earner in the household
o How good their health is
o Their care responsibilities at home
o Their level (and type for PCs) of education
o Whether they are currently studying an aged care qualification
•
The characteristics of the facilities where employees work:
o Whether they work in a metropolitan, regional or rural facility.
o Whether the facility has only high care places.
o The total number of employees in the facility.
-16-
o The ownership of the facility (not-for-profit, for-profit, or public
ownership)
Table 4.1 shows the proportion of Nurses and PCs in our sample employed on casual
contracts, and who work part-time. Tables 4.2 and 4.3 show the results of our analyses
of the determinants of working casually and of working part-time. Overall, our
analyses indicate that a small number of factors consistently affect the type of contract
under which employees work or whether they work full-time or part-time. However,
the majority of factors have no effect on these outcomes.
Table 4.1:
Proportion of Nurses and PCs who are employed casually and who work
full-time
Employed casually
Work full-time (35+
N
hours/week)
Table 4.2:
Nurses
8.6%
41.4%
1148/1141
Personal Carers
17.9%
29.2%
1371/1354
Determinants of whether Nurses are employed casually and work full
time
Months at current facility
Male
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
Excellent health
No. hrs caring for people in own
Years
secondary education
household
Years post-secondary education
Currently studying aged care qual.
Facility location (0=metropolitan)
Regional facility
Rural facility
High care places only
Total no. employees
Facility ownership (0=not-for-profit)
For-profit facility
Publicly owned facility
Constant
N
2
Nagelkerke R
Employed casually
B
Exp(B)
-.006**
.994
.745
2.106
.003
1.003
.089
1.093
-.329
.719
-.218
.804
Work full-time
B
Exp(B)
.003**
1.003
.133
1.142
-.012
.988
-.579**
.561
.125
1.133
.927**
2.526
.846**
.911**
.000
-.177
-.099
.488
2.330
2.487
1.000
.838
.906
1.629
-.138
.120
-.006**
-.056
.189**
.743**
.871
1.128
.994
.946
1.208
2.102
.280
.068
-.105
-.003
1.323
1.071
.900
.997
-.573**
-.236
.071
.001
.564
.790
1.074
1.001
.082
-.658
-.993
944
.086
1.086
.518
.371
.080
.223
-.227
938
.136
1.083
1.250
.797
*p≤ .05
**p≤ .01
-17-
Table 4.3:
Determinants of whether PCs are employed casually and work full time
Employed casually
B
Exp(B)
-.008**
.992
.534
1.707
.003
1.003
-.015
.985
.088
1.092
-.086
.918
Months at current facility
Male
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
.447*
Excellent health
.262
No. hrs caring for people in own -.002
Years secondary education
.090
household
Years post-secondary education
.096
Currently studying aged care qual.
-.297
Facility location (0=metropolitan)
Regional facility
-.441
Rural facility
.485*
High care places only
-.009
Total no. employees
.004**
Facility ownership (0=not-for-profit)
For-profit facility
-.371
Publicly owned facility
-.660
Constant
-2.304**
N
989
2
Nagelkerke R
.096
Work full-time
B
Exp(B)
.004**
1.004
.222
1.249
.001
1.001
-.379
.684
-.369**
.691
.321
1.378
1.564
1.300
.998
1.094
1.101
.743
.260
.287
-.007**
-.077
-.083
-.086
1.297
1.333
.993
.926
.920
.918
.644
1.624
.991
1.004
-.377**
-.024
.452**
-.002
.686
.976
1.572
.998
.690
.517
.100
.235
-.596
-.395
979
.118
1.265
.551
.674
*p≤ .05
**p≤ .01
The length of time employees have been working at facilities is an important
determinant. For both Nurses and PCs, employees who have been working at facilities
for longer are less likely to be on casual contracts, and more likely to be working fulltime. The importance and consistency of this result suggests that casual and part-time
employment are often largely results of employer preferences as employers limit their
initial contractual commitment to workers while they assess their suitability for the
work.
Generally, employees ‘human capital’, particularly their education, have no effect on
the type of contract or hours they work. The exception to this is that Nurses with more
secondary and post-secondary education are more likely to be employed full-time.
Presumably this is a result of employers preferring better educated Nurses with more
‘human capital’. The lack of effect of education on PCs’ hours of work and on
Nurses’ and PCs’ likelihood of being employed casually does suggest that the human
-18-
capital variations in these two workforces have only limited impact on their
attractiveness as employees.
Whether employees work full-time or part-time is clearly affected by their own
income needs and the non-work demands placed on them. Nurses who are the main
income earners in their households are more likely to work full-time, and PCs without
live-in partners are less likely to be full-time. Spending more time caring for their
household members also makes both Nurses and PCs less likely to be employed fulltime. Older Nurses are also less likely to work full-time.
The location, size (as measured by the total number of employees), and bed mix of
facilities, also have some effects. These are not consistently present, and seem most
likely to be due to management practices in facilities. PCs in larger facilities are more
likely to be employed casually than those in small facilities, and those in high care
only facilities are more likely to be full-time. Both Nurses and PCs in regional
facilities are less likely to be full-time than those in metropolitan ones.
Overall, it appears that employers’ preferences and management practices are the
overwhelming determinants of whether Nurses and PCs are employed casually rather
than on permanent contracts. They also have a major impact on whether the
employees are full-time or part-time. At the same time, the needs and availability of
employees also affect this outcome. It appears that, even though their availability may
be somewhat constrained, the group of employees who work casually (a small
minority) or part-time (a large majority) do represent a pool of available labour in the
industry, as our previous report suggested. To further investigate this issue, we next
examine the factors that make employees willing to work more hours.
5.
Labour Supply – Desire to Work More Hours
Employees make choices about how many hours they work, and the availability of
labour can be substantially affected by these choices. Amongst Nurses and PCs in
aged care facilities, this is a significant issue since most work part-time. Under these
conditions, an understanding of the factors that affect employees’ desire to work more
hours is important for policy makers. Our analysis examines the factors that affect the
number of additional hours employees would like to work. It allows for some
employees to prefer to work fewer hours than they currently do (i.e., they would
-19-
prefer to work a negative number of additional hours). Again, we analyse this issue
using multivariate models, and, again, we group the factors that may affect
willingness to work more time into four groups. Thus, our analyses examine whether
the number of additional (or fewer) hours employees would like to work are affected
by:
•
Employees’ employment arrangements and preferences:
o Whether they work a normal day shift, an evening or night shift, or
another irregular kind of shift (i.e., the analysis compares three groups)
o Whether they are employed on a casual or permanent contract
o Their hourly wage
•
Employees’ experience of work
o The amount of time they spend directly caring for residents in a typical
shift.
o Their experience of work (including whether they are able to spend
enough time with residents, their experience of skill usage, etc.)
o Their job satisfaction
o The amount of time they have worked for their current employer
•
Employees’ personal characteristics:
o Their sex
o Their age
o Whether they were born in a non-English speaking country
o Whether they live with a partner
o Whether they are the main earner in the household
o How good their health is
o Their care responsibilities at home
o Their level of education
o Whether they are currently studying an aged care qualification
•
The characteristics of the facilities where employees work:
o Whether they work in a metropolitan, regional or rural facility.
o Whether the facility has only high care places.
o The total number of employees in the facility
o The ownership of the facility (not-for-profit, for-profit, or public
ownership)
-20-
Table 5.1 shows that just under half of PCs and over one-third of Nurses would prefer
to work different hours than they currently do. PCs represent a large pool of untapped
labour, with 40% preferring to work longer than they currently do, and only 8%
preferring to work less. In contrast, about 15% of Nurses would like to work more
than they currently do, but over 20% want to work less. Unsurprisingly, interest in
working more hours is much more common amongst those who currently work parttime hours (i.e., less than 35 hours per week) than those who currently work full-time.
Table 5.2 shows that nearly half of part-time PCs and over 20% of part-time Nurses
would prefer more hours. By contrast, only 20% of full-time PCs want more hours,
with two-thirds being happy with their current hours, and only 6% of full-time Nurses
want to work longer hours with 37% wanting to reduce their hours. Given the
concentration of those wanting to work more hours amongst part-time workers, we
focus on the factors that affect whether part-time workers would like to work more
hours.
Table 5.1:
Proportion of Nurses and PCs who would prefer to work more and fewer
hours per week
PCs
3.3%
5.1%
51.9%
18.5%
14.1%
7.1%
1251
10+ hours less
1-9 hours less
No change in hours
1-5 hours more
6-10 hours more
11+ hours more
N
Table 5.2:
Part-time
Total
Full-time
Nurses
8.8%
12.7%
63.4%
7.0%
6.2%
1.9%
1061
Proportion of Nurses and PCs who would prefer to work more and fewer
hours per week by whether currently full-time or part-time
PCs
47.6%
46.0%
6.4%
892
20.1%
66.6%
13.4%
359
Prefer more hours
Prefer same hours
Prefer fewer hours
Prefer more hours
Prefer same hours
Prefer fewer hours
Total
Nurses
21.1%
67.9%
11.0%
635
6.3%
56.7%
37.0%
427
While our analyses of the factors affecting these preferences do account for some of
the variation we observe in how many additional hours people would like to work,
there remains significant variation unexplained. This is particularly so for PCs. In
fact, we able to explain about 7% of the variance in PCs’ preferences and 14% of that
of Nurses (Table 5.3). Although the factors that affect hours preferences are relevant
-21-
in interpreting the effect of any interventions, it is certainly important to bear in mind
that other issues may be significant too.
Table 5.3
Determinants of additional hours nurses and PCs currently working
part-time would like to work
Nurses
B
Beta
Shift type (0=regular day shift)
Regular eve/night shift
Irregular shift
Months at current facility
Casual employee
Wage per hour
Time spent in direct care (0=more than two thirds)
Less than a third time direct care
Between one third and two thirds time
Male
direct care
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
Excellent health
No. hrs caring for people in own household
Years secondary education
Years post-secondary education
Currently studying aged care qual.
Able to spend enough time with each resident
Have the skill I need to do my job
Use skills in current job
Have freedom to decide how I do my work
Do not feel under pressure to work harder
Job satisfaction
Facility location (0=metropolitan)
Regional facility
Rural facility
High care places only
Total no. employees
Facility ownership (0=not-for-profit)
For-profit facility
Publicly owned facility
Constant
2
R
N
*p≤ .05
**p≤ .01
-22-
PCs
B
Beta
-.309
.485
-.010**
1.054
.045**
-.026
.044
-.161**
.066
.226**
-1.001
.502
-.012*
1.875**
.156**
-.064
.038
-.117*
.113**
.118**
-.129
-.900
3.853**
.008
-1.304
-1.135
-.548
-.012
-.088
.173**
.014
-.079
-.093
-.053
.884
-.422
1.041
-.014
-1.183
-.761
1.014
.045
-.031
.039
-.023
-.061
-.053
.076
1.566**
.639
.012*
.057
-.209
-.022
.051
.202
.195
.194
-.084
-.023
.155**
.055
.116*
.011
-.047
-.001
.016
.034
.061
.061
-.034
-.055
.712
.462
.007
-.050
-.415
-.513
.102
.059
.203
.051
-.049
-.121**
.597
1.524*
-.225
.000
.052
.137*
-.022
.008
.718
.608
.671
-.009*
.152
.244
-1.358
.119
426
.014
.019
.500
-2.009
5.784
.101
542
.055
.027
.042
-.008
-.065
-.023
.026
.010
.039
.013
-.015
-193**
.049
.041
.047
-.106*
.032
-.069
Our results indicate that a range of factors across all major features of Nurses’ lives
affect whether they wish to work more hours. It appears that part-time Nurses prefer
to work more hours if:
•
Employees’ employment arrangements and preferences:
o Their hourly wage is higher
•
Employees’ experience of work
o They have been working at their current facility for a shorter period
•
Employees’ personal characteristics:
o They are male
o They have ‘very good’ health
o They spend more time in care responsibilities at home
•
The characteristics of the facilities where employees work:
o They work in a rural facility
These results suggest that part-time Nurses’ willingness to supply additional labour is
partly a function of how facilities are operated: presumably longer serving employees
are less likely to want more hours because employers give longer serving, trusted
employees the hours they want; and higher wages act as an incentive to work more. In
addition labour market factors play a part: the greater desire of Nurses in rural
facilities to work more is probably due to the generally more limited availability of
work in rural areas. It also appears that workers with greater personal capacity (better
health) and with greater responsibilities (having more care responsibilities at home)
want more work. Finally, taking account of all the other factors, men are more likely
than women to want to work more hours, possibly because of societal expectations.
Whether part-time PCs prefer to work more hours is affected by a somewhat more
limited range of variables. They prefer to increase their hours if:
•
Employees’ employment arrangements and preferences:
o Their hourly wage is higher
o They are employed on a casual contract
•
Employees’ experience of work
o They have been working at their current facility for a shorter period
-23-
o They have lower job satisfaction
•
The characteristics of the facilities where employees work:
o They are employed in a smaller facility
Like part-time Nurses, it appears that part-time PCs are affected by employers’
tendency to give longer serving employees the hours they desire, and that they are
attracted to work more by higher wages. Casual employees also appear to experience
a greater gap between desired and actual hours than permanent ones. The association
between lower job satisfaction and desiring more hours is, presumably, traceable to
the fact that a significant gap between actual and desired hours reduces job
satisfaction.
Overall, as we noted above, the above factors explain only a small proportion of the
variation in additional hours that part-time Nurses and PCs want to work. In the case
of PCs, the likely explanation is that underemployment is so general that no particular
factors are capable of distinguishing those who wish to work more from those who
don’t. In the case of Nurses, the picture is almost opposite: nearly 80% of part-time
Nurses want to work the same amount they currently do, or less. Thus, the small
proportion who want to work more are not sharply distinguishable from this large
majority.
6.
What Determines Job Satisfaction?
Earlier analyses in this report clearly indicate that job satisfaction is associated with
important labour supply intentions and expectations amongst direct care workers in
the aged care industry. In particular, job satisfaction has a very significant impact on
employees’ expectations about remaining in the industry, with those with higher job
satisfaction much more likely to expect to remain. Our measure of job satisfaction is a
scale whose scores range from 0 (completely dissatisfied with all aspects of the job) to
60 (completely satisfied with all aspects of the job).1 This scale results from
employees’ responses to 6 questions about job satisfaction covering pay, job security,
the work itself, hours of work, flexibility to balance work and non-work activities, and
overall job satisfaction. Most workers are fairly satisfied with their jobs, and aged
care employees are no different in this respect (for a more detailed comparison of
1
This scale has appropriate reliability (Alpha =0.78) with item-total correlations being above 0.3.
-24-
aged care workers’ job satisfaction with that of all Australian female employees, see
Healy and Moskos 2005). Table 6.1 shows the proportion of respondents to our
survey who rated their job satisfaction in each third of our scale. Clearly, very few are
highly dissatisfied with their jobs (only 4% of PCs and 7% of Nurses were in the
bottom third of our scale, which would result if they said they were dissatisfied on
most aspects of their jobs). However, there is still considerable variation in job
satisfaction, with over 40% of both groups giving responses that place them in the
middle third of our scale and about half placing themselves in the top third.
Table 6.1:
Job satisfaction amongst Nurses and PCs
Job satisfaction
0-19
20-39
40-60
Total
PCs
4.2%
45.3%
50.4%
1372
Nurses
6.9%
42.1%
51.0%
1146
Job satisfaction is likely to result from a range of factors, including employment
arrangements and preferences, work experience, personal characteristics, and the
characteristics of workplaces. As in previous analyses, we examine the effects of a
range of variables that fall into these four broad categories:
•
Employees’ employment arrangements and preferences:
o Whether they work a normal day shift, an evening or night shift, or
another irregular kind of shift (i.e., the analysis compares three groups)
o Whether they would prefer to work a different kind of shift
o Whether they would prefer to work more, fewer or the same number of
hours as they currently do
o Whether they are employed on a casual or permanent contract
o Their hourly wage
•
Employees’ experience of work
o The amount of time they spend directly caring for residents in a typical
shift
o Their experience of work (including whether they are able to spend
enough time with residents, their experience of skill usage, etc.)
o The amount of time they have worked for their current employer
•
Employees’ personal characteristics:
o Their sex
-25-
o Their age
o Whether they were born in a non-English speaking country
o Whether they live with a partner
o Whether they are the main earner in the household
o How good their health is
o Their care responsibilities at home
o Their level of education
o Whether they are currently studying an aged care qualification
•
The characteristics of the facilities where employees work:
o Whether they work in a metropolitan, regional or rural facility
o Whether the facility has only high care places
o The total number of employees in the facility
o The ownership of the facility (not-for-profit, for-profit, or public
ownership)
Together, these factors give considerable purchase in understanding the determinants
of direct care workers’ job satisfaction. In formal statistical terms, they explain 41%
of the variance in Nurses’ job satisfaction responses and 33% of that in PCs’
responses.
Table 6.2 provides the results of our analyses. It shows that a large range of factors
affect job satisfaction. However, it is clear that the major factors are the extent to
which employment preferences are met, and experiences at work. Actual employment
arrangements and personal characteristics have smaller effects and facility
characteristics much smaller ones.
-26-
Table 6.2:
Determinants of Nurses’ and PCs’ job satisfaction
Nurses
B
Beta
Shift type (0=regular day shift)
Regular eve/night shift
Irregular shift
Prefer different shift
Hours preferences (0=same as current)
Prefer work less
Prefer work more
Months at current facility
Casual employee
Wage per hour
Time spent in direct care (0=more than two thirds)
Less than a third time direct care
Between one third and two thirds time direct
Male
care
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
Excellent health
No. hrs caring for people in own household
Years secondary education
Years post-secondary education
Currently studying aged care qual.
Able to spend enough time with each resident
Have the skill I need to do my job
Use skills in current job
Have freedom to decide how I do my work
Do not feel under pressure to work harder
Facility location (0=metropolitan)
Regional facility
Rural facility
High care places only
Total no. employees
Facility ownership (0=not-for-profit)
For-profit facility
Publicly owned facility
Constant
2
R
N
*P≤ .05
**P≤ .01
-27-
PCs
B
Beta
-.016
-.022
-.028
1.148
2.526**
-4.141**
.038
.092**
-.170**
-.393
-.475
-.587
-4.233**
-5.020**
.001
.270
.013
-.143**
-.147**
.004
.006
.022
-4.463**
-4.296**
-.007
-1.758**
.089
-.122**
-.201**
-.044
-.062**
.041
-4.825**
-2.993**
-2.254
.033
2.322**
-.957
-2.034**
-.202**
-.122**
-.045
.025
.068*
-.035
-.086**
-2.887**
-2.082**
-.627
.120**
-1.620
-1.521
-1.552*
-.098**
-.095**
-.016
.123**
-.056
-.070
-.075*
-.245
2.319*
.010
-.430
.414
.328
1.146**
-.194
1.507**
2.383**
1.104**
-.010
.084*
.035
-.037
.037
.007
.155**
-.014
.196**
.330**
.191**
3.137**
4.028**
.016
-.287
-.497
.380
1.329**
.787*
.868**
1.068**
.760**
.152**
.156**
.059
-.030
-.050
.011
.222**
.081*
.104**
.172**
.147**
.489
-.527
-.219
.006
.018
-.020
-.009
.063
1.187
3.132**
-1.208
.013**
.050
.129**
-.055
.087**
-.945
1.430
15.756*
.409
733
-.037
.047
.656
.103
15.713**
.327
783
.027
.002
For Nurses, preferring to work a different shift or different hours has quite large
negative effects on job satisfaction, while for PCs only preferring different hours
reduces job satisfaction. Employment arrangements have small effects for both groups
once these preferences are taken into account: for Nurses being on an irregular shift
actually increases job satisfaction, and for PCs being on a casual contract decreases it.
Workplace experiences are extremely important for both groups (in fact, these
experiences together uniquely explain just over 30% of the variance in Nurses’ job
satisfaction and just over 20% of that in PCs’ job satisfaction). First, how much of
their workplace time employees spend with residents matters, though the effect is
more important amongst Nurses than PCs. For Nurses, there is a gradient of effect: the
more time Nurses spend in direct care, the higher their job satisfaction. For PCs, the
key issue appears to be whether they spend less than two-thirds of their time in direct
care work. These differences between Nurses and PCs undoubtedly arise from the
different job expectations of Nurses and PCs: PCs expect to spend most of their time
in direct care and are unhappy as soon as this expectation is not met; Nurses may
expect that direct care is a smaller part of their job, but the smaller it becomes the
lower their job satisfaction.
Both Nurses’ and PCs’ job satisfaction is substantially affected by other features of
their work experience too. For both groups:
•
Being more able to spend enough time with residents increases job satisfaction;
•
Being able to use ‘many’ of one’s skills on the job increases job satisfaction;
•
Having more freedom to decide how to do one’s work increases job satisfaction;
•
Feeling under pressure to work harder decreases job satisfaction.
Although all these factors are important for both groups, their relative importance
does vary somewhat. For PCs the most important is whether they are able to spend
enough time with each resident, whereas for Nurses having freedom to decide how to
do one’s work is the most important.2 One additional factor, the extent to which
employees feel that they have the skills to do their jobs, affects PCs’ job satisfaction
2 We assess relative importance using standardized regression coefficients (Beta). These coefficients
can be directly compared across variables to give a direct measure of the relative importance of each
variable in our regression analysis in predicting job satisfaction.
-28-
but not Nurses’. Overall, both groups are highly likely to feel that they do have the
skills to do their jobs, though PCs are slightly less emphatic in this belief than Nurses.
Several personal characteristics of workers have small effects on job satisfaction.
Nurses who were born in non-English speaking countries and those who are the main
income earners in their household have somewhat lower job satisfaction, while those
in ‘excellent’ health have higher job satisfaction. Amongst PCs, being older and in
better health (very good or excellent) increases their job satisfaction quite
substantially. Being the main income earner also has much the same negative effect
on job satisfaction as it does amongst Nurses.
Finally, PCs in rural facilities and those in larger facilities are more satisfied with
their jobs. However, there are no significant effects of facility characteristics on
Nurses’ job satisfaction.
In summary, far and away the most important determinants of job satisfaction are
employees’ direct work experiences – how much time they are able to spend in direct
care, using their skills on the job, having some freedom to decide how to do their
work, and not feeling under great pressure to work harder. These factors are very
largely under the control of facility managers, and are likely to be largely determined
by the way work is organised in facilities. Moreover, the other major determinants of
work satisfaction in our analysis relate to whether employees’ are able to get the shifts
and hours they prefer. Again, these are matters that managers are in a position to
negotiate, and that they may seek to mitigate even where they cannot fully satisfy
employees’ preferences.
7.
Wage Determinants
How employees’ earnings are determined is an important feature of any labour
market. Wages affect the choices employees make between available jobs, and their
subjective response to the jobs they accept. We have already shown that labour
turnover is an important issue in the aged care sector, particularly for the adequacy of
future labour supply. However, wages seem to have little effect on employees’
expectations about remaining in the sector, though they do affect whether part-time
employees are willing to work more hours. One likely explanation for this lack of
impact is that variations in earnings amongst aged care workers are small.
-29-
The distribution of PCs’ wages in our data is quite compressed: 87% earn between
$10 and $20 per hour, with 49% earning between $15 and $20 per hour.3 Nurses’
earnings are less compressed, although their variation is also quite small: 78% earn
between $15 and $30 per hour.4 Given these relatively small wage dispersions and the
desire of the aged care sector to retain its workforce and to upgrade its employees’
qualifications (particularly in the case of PCs), understanding the factors that currently
affect wages is vital to comprehending the incentives employees currently face. A key
issue will be whether PCs who complete aged care qualifications are paid a wage
premium, and a further issue will be overall indications of career pathways for Nurses
and PCs.
Our approach to wage determination is to estimate wage equations for Nurses and
PCs separately, and then to estimate an equation with both groups together. As is
conventional, we predict the logarithm of hourly earnings. Our wage equations use
fairly standard human capital and labour market variables as determinants of wages:
•
Human capital variables:
o Education (secondary and post-secondary and specific qualifications)
o Age
o Duration of current employment
o Birthplace
o Family responsibilities (living with partner, main household income
earner, hours of caring for household members)
o Health
o Gender
•
Labour market variables:
o Type of shift worked (regular daytime vs. regular evening or night vs.
irregular)
o Casual or permanent employment contract
3
These figures are based on calculation of hourly earnings from questions about the amount employees
received in their most recent pay and the number of hours they usually work per week. In calculating
the figures quoted here, and in the analyses that follow, we have excluded the small number of PCs
whose calculated hourly earnings are less than $10 (about 5% of PCs) or above $40 (about 0.5% of
PCs), since these figures are highly likely to be inaccurate and have the potential to bias our results.
4
Again, we have excluded the very small number of Nurses whose calculated hourly earnings are less
than $10 (1.4%) or over $50 (0.4%).
-30-
o Location of facility (metropolitan vs. regional vs. rural)
o Size of facility (total number of employees)
o Facility ownership (not-for-profit vs. for-profit vs. public)
Overall, the proportion of the variation in wages within each occupational group that
our analyses explain is quite small (15% of variance in Nurses’ hourly earnings is
explained and 8% of that in PCs earnings). Nevertheless, the determinants of earnings
are illuminating.
Table 7.1 shows coefficients for our wage analyses for Nurses and PCs. The
coefficients can be interpreted as percentage increases in wages due to each
independent variable, controlling for the other variables in the analysis. Thus, for
example, Nurses working regular evening or night shifts earn 9.4% more per hour
than those working regular day time shifts, all other things being equal. Or, Nurses
earn an extra 6.3% in hourly earnings for each year of post-secondary education they
obtain.
Amongst Nurses, human capital variables have significant impact on wages: those
who are older, better educated, the main income earners in their households, and in
better health are paid more, with the amount of post-secondary education being
particularly significant. Labour market factors also matter: those working regular
evening or night shifts are paid more than others, as are those working in larger
facilities and working in publicly owned facilities.
For PCs, the factors affecting wages are more limited. The only human capital effects
on their wages are that men earn slightly less than women, employees who are the
main income earners in their households earn more, and longer term employees earn
less (all other things being equal). In general, key human capital variables such as
education and age (as a proxy for experience) have no effect on PCs earnings. It is
particularly notable that PCs receive no wage premium for obtaining aged care
qualifications. The negative effect of job tenure on wages also appears perverse.
Labour market variables do have some effect on PCs wages: those on regular daytime
shifts earn less than others and casual employees earn a little more, as do those in
larger facilities and those in publicly owned facilities.
-31-
Table 7.1:
Determinants of Nurses’ and PCs’ hourly wages
Nurses
B
Beta
Shift type (0=regular day shift)
Regular eve/night shift
.094**
Irregular shift
.013
Months at current facility
.000
Casual employee
.051
Male
.027
Age
.003**
Born non-English speaking country
-.050
Live with a partner
.011
Main income earner
.058**
Self assessed health (0=good, fair or poor)
Very good health
.050*
Excellent health
.025
No. hrs caring for people in own
.000
Years
secondary education
.030**
household
Years post-secondary education
.063**
Hold aged care qual. (PCs only)
Currently studying aged care qual.
-.007
Facility location (0=metropolitan)
Regional facility
-.015
Rural facility
-.017
High care places only
.014
Total no. employees
.000**
Facility ownership (0=not-for-profit)
For-profit facility
.028
Publicly owned facility
.069*
Constant
2.563**
2
R
.145
N
742
PCs
B
Beta
.133**
.019
-.024
.049
.022
.107**
-.061
.017
.104**
.053*
.052**
.000**
.062**
-.080**
.002
-.006
.027
.054**
.095*
.112**
-.133**
.101**
-.090**
.077
-.010
.056
.118**
.090*
.038
.025
.111**
.241**
-.005
.006
.012
4.382E-.009
05
-.002
-.028
-.011
.011
-.007
.055
-.041
-.002
-.035
-.023
-.027
.025
.149**
-.020
-.014
-.023
.000*
-.039
-.026
-.047
.078*
.046
.096*
-.038
.119**
2.658**
.084
774
-.072
.105**
-.007
a Dependent Variable: Log wage per hour
*p≤ .05
**p≤ .01
Given the compressed distribution of PCs’ and Nurses’ wages, and the fact that they
work side by side in aged care facilities, it is particularly relevant to assess whether
the differences in their wages can be explained in terms of human capital and labour
market characteristics. To assess this issue, we pooled the two groups and reanalysed
their earnings. Our analysis assumes, with one exception, that human capital and
labour market factors have the same effects on PCs and Nurses’ wages. It then takes
account of the effects of these factors, and asks whether there is any remaining
difference in wages between the two groups. We do allow that the effects of postsecondary education may vary between the groups since Nurses’ post-secondary
-32-
education is generally at university level, while that of PCs is at TAFE level, and the
human capital effects of each system are likely to be different. Our results show that
post-secondary education does indeed have a different effect on wages for Nurses and
PCs (Table 7.2). For the former, it significantly increases their wages, while for the
latter it has no effect at all.
Table 7.2:
Determinants of PCs’ and Nurses’ wages
B
Shift type (0=regular day shift)
Regular eve/night shift
Irregular shift
Months at current facility
Casual employee
Male
Age
Born non-English speaking country
Live with a partner
Main income earner
Self assessed health (0=good, fair or poor)
Very good health
Excellent health
No. hrs caring for people in own household
Years secondary education
Years post-secondary education (PCs)
Years post-secondary education (nurses)
Currently studying aged care qual.
Facility location (0=metropolitan)
Regional facility
Rural facility
High care places only
Total no. employees
Facility ownership (0=not-for-profit)
For-profit facility
Publicly owned facility
Nurse
Constant
2
R
N
Beta
.076**
.041**
.000**
.057**
-.039
.002**
-.026
.020
.052**
.099**
.062**
-.059**
.060**
-.031
.079**
-.030
.030
.084**
.020
.009
.000
.020**
-.011
.079**
-.016
.032
.012
.004
.072**
-.051
.410**
-.014
-.016
-.011
-.003
.000**
-.022
-.015
-.004
.103**
-.009
.069**
.124**
2.556
.399
1517.00
-.014
.071**
.201**
Dependent Variable: Log wage per hour
*p≤ .05
**p≤ .01
Perhaps more significantly, after accounting for the differences in human capital of
Nurses and PCs and any differences in the labour markets in which they find jobs,
Nurses still earn about 12% more than PCs. Thus PCs can be seen to face a double
-33-
wage incentive to consider undertaking nursing training – not only will they be
rewarded for the additional human capital they attain, but they will also achieve a
significant wage premium simply for being able to enter the nursing labour market.
Our analysis of the determinants of Nurses’ and PCs’ hourly wages has shown, first,
that both occupations have rather compressed wage distributions. Our capacity to
explain variation in wages within each occupation is limited, particularly for PCs.
Nurses’ wages are clearly affected by their human capital, with older (presumably
more experienced), better educated Nurses being better paid. However, human capital,
at least as we are able to measure it, appears to have virtually no impact on PCs
wages. Instead, their wages are affected by the kinds of shifts they work and the types
of employers they work for. Nurses’ wages are also influenced by these variables,
though clearly not to the exclusion of human capital factors. For PCs, there is little
wage incentive to undertake aged care qualifications, since there is no wage premium
associated with them. However, PCs would face a significant wage incentive if they
could enter the nursing labour market since they would both upgrade their human
capital and also enter a labour market where it is rewarded.
8.
Conclusion
Together, the analyses in this report paint a detailed picture of the operation of the
labour market for Nurses and PCs in Australian residential aged care facilities, and
how the operation of these labour markets may impact on labour turnover and supply.
In terms of conventional images of labour market rewards, our analyses indicate that
wage incentives and human capital have only limited effects on employees’
expectations about their future in the aged care sector and in their desire to work
more. Wage levels have no effect on employees’ expectations about whether they will
be working in the sector in the future. However, higher wages do induce part-time
workers to want to work more, though the effect is rather small. Moreover, having
more human capital (as measured by education) generally does not make Nurses or
PCs any more likely to expect to leave the aged care sector, despite the greater general
employment opportunities it should offer. Our results suggest that the apparent
weakness of wage incentive and human capital effects amongst these workers arises
from two features of this workforce. First, aged care workers receive large non-wage
-34-
rewards from the work they do, and this reduces their sensitivity to wage incentives.
Certainly our earlier report suggested that non-wage rewards were important to these
workers. On the other hand, the apparent weakness of wage effects on employees’
expectations is probably also partly due to the limited variation in wages amongst
these employees.
Focusing first on non-wage rewards, workers’ expectations of staying in the industry
are affected largely by the quality of their workplace experience. In part this has to do
with pragmatic issues of whether they are able to work the shifts and hours they
would prefer. These are clearly important issues in a workforce that is predominantly
female and part-time, where other significant responsibilities are fitted around paid
work commitments. The other component of workplace experience is that of actually
doing the work. Here, higher job satisfaction makes employees significantly more
likely to expect to stay in aged care. In addition, Nurses’ expectations are affected by
whether they feel that they use their skills in their jobs, and PCs’ expectations are
affected by whether they feel under pressure to work harder.5 Again, there can be little
doubt that how facilities are managed can have significant effects on these
experiences of work.
We have shown the rather limited dispersion of wages amongst Nurses and PCs. Our
analysis indicates that human capital impacts on wages in these occupations are also
fairly small, especially for PCs. However, we have suggested that PCs do face a
significant wage incentive if there is a realistic pathway for them to enter the Nursing
labour force. Providing PCs with such a route may well have the effect of introducing
an effective wage incentive for them to remain in the aged care sector too, since it
would substantially increase the wage dispersion amongst those who begin their aged
care careers as PCs.
Our analysis of what affects the hours Nurses and PCs work, and whether they are
employed casually or permanently, also helps us understand why there has not yet
been strong pressure to introduce such pathways systematically. It seems clear that,
especially for PCs, hours of work and contract types are largely determined by
5
This difference points to different occupational expectations. Nurses probably see themselves as
skilled professionals who expect to use their skills in their work, and who will search for other work if
this expectation is not met. PCs do not have such a self-image, but do not like work situations where
they feel pressured.
-35-
employers’ preferences and employment practices. This is certainly consistent with
the conclusion in our earlier report that there is not a crisis in the aged care labour
market. As a group, the current PC workforce is prepared to supply considerably more
labour than employers require.
Of course, the ready supply of PC labour is unlikely to remain forever, and there are
strong indications that some employers already face difficulty finding the Nurses
(especially RN1s) they would like. Our analyses suggest, first, that many of the
factors that will determine whether PCs remain in the aged care industry and are
willing to work more hours are quite directly under employers control, since they are
aspects of how work is organised in facilities. Perhaps of more immediate
significance, it appears that if PCs were presented with a straightforward pathway to
upgrade their skills to nursing qualifications, there would be strong wage incentives to
pursue this pathway. Moreover, to the extent that the experience of work is attractive
to them (which can be influenced by facility management), many PCs who upgraded
to nursing training could be expected to remain in the aged care industry because of
the intrinsic rewards it had already given them.
References
Healey, Joshua and Megan Moskos (2005) How do Aged Care Workers Compare
With Other Australian Workers? National Institute of Labour Studies, Flinders
University.
Richardson, Sue and Bill Martin (2004) The Care of Older Australians: A Picture of
the Residential Aged Care Workforce, National Institute of Labour Studies,
Flinders University.
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