A New Measure of Job Searchers for Australia | Bulletin – October 2025

23 October 2025

Joyce Tan

labour market, monetary policy

Photo: Delmaine Donson – Getty Images

Abstract

The RBA’s assessment of spare capacity in the labour market incorporates the signal from a broad suite
of indicators. The ratio of job vacancies to unemployed persons, which attempts to assess the imbalance
between unmet labour demand and the labour supply available to meet this demand, is a standard measure of
spare capacity in the labour market. One shortcoming of this measure is that it implicitly assumes that job
vacancies are only filled by the unemployed. In practice, job vacancies are also filled by other job
searchers who may be outside the labour force or searching on the job. This article describes the
construction and characteristics of a more comprehensive measure of job searchers (the Searchers Index) that
considers both the unemployed and those who are not classified as being unemployed. The Searchers Index
allows us to construct an alternative measure of spare capacity (the vacancies-to-searchers ratio), which
exhibits different properties to the vacancies-to-unemployed ratio. The vacancies-to-searchers ratio will be
included in the suite of indicators that we monitor to assess spare capacity in the labour market moving
forward.

Introduction

Understanding the extent of spare capacity (or conversely, tightness) in the labour market is
important for the RBA’s dual mandate of price stability and full employment. First, the
Statement on the Conduct of Monetary Policy requires the RBA to communicate its assessment
of how labour market conditions stand relative to full employment (Ballantyne, Sharma and Taylor
2024). Second, tightness in the labour market can impact the degree of inflationary pressures in the
economy. RBA staff therefore closely monitor a number of measures of tightness when assessing
conditions in the labour market. One commonly used measure is the ratio of job
vacancies to unemployed persons (the V-U ratio), which attempts to gauge the mismatch between labour
demand (proxied by job vacancies) and the potential labour supply that could meet this demand
(proxied by the unemployed). The V-U ratio has eased since its mid-2022 peak but continues to be well
above pre-pandemic levels.

A key shortcoming of the V-U ratio is that the unemployed are only a subset of all job searchers and
hence the ratio effectively ignores how searchers outside of unemployment contribute to the filling
of vacancies. The Australian Bureau of Statistics (ABS) defines the unemployed as non-working
individuals aged 15 years and over who have either actively looked for work in the previous four
weeks and were available to work in the reference week of the Labour Force Survey or were waiting to
start a job within four weeks from the end of the reference week but could have started working
during the reference week had the job been available. However, many people fall outside this
definition despite being able to fill vacancies, such as those who are looking for work but only
passively, or those actively looking for work but who were not available to start work in the
reference week. Furthermore, the V-U ratio places equal weight on each unemployed person despite some
unemployed people (e.g. those who have remained unemployed for a long time) having a persistently
lower probability of finding a job.

To address these limitations, I construct a more comprehensive measure of ‘effective job
searchers’ called the ‘Searchers Index’ (SI). This measure of effective searchers not
only accounts for the unemployed but also accounts for those ‘not in the labour force’
(NILF) and those who are employed who may be searching on-the-job. To do this, I first disaggregate
the working age population into 11 labour market cohorts. Using microdata from the ABS’
Longitudinal Labour Force Survey, I calculate each cohort’s share of the population and their
probability of finding a job – their job-finding rate (JFR) – over time (which is used to
construct the SI). I then apply weights to each labour market cohort to capture variation in these
JFRs and population shares, resulting in a measure of ‘effective searchers’ in the economy.
Due to limitations on data availability, the sample begins in 2001.

Several overseas studies have also attempted to construct measures of effective job searchers. They
have also first divided the population into several cohorts of searchers. In these studies, the
weight applied to each cohort is fixed at either the ratio of the cohort’s JFR at a point in
time or the cohort’s long-run average JFR relative to that of a chosen base cohort (Abraham,
Haltiwanger and Rendell 2020; Byrne and Conefrey 2017; Heise, Pearce and Weber 2024; Hornstein,
Kudlyak and Lange 2014; Kudlyak 2017). The key disadvantage of using a fixed weight is that the
chosen weight may become less reflective of the cohort over time. My approach extends the literature
by using Australian microdata and by allowing the weights to vary over time.

In this article, I discuss different cohorts of job searchers and describe how the SI is constructed
using these cohorts. I find that drawing together information on job vacancies and effective
searchers into a vacancies-to-searchers ratio (V-S ratio) leads to a new and more comprehensive
indicator of labour market tightness.

Job searchers in Australia

There are different types of job searchers in the economy, each with varying degrees of attachment to
the labour market and hence impacts on labour market outcomes. For example, an individual who has
been unemployed for a short period of time is more attached to the workforce than someone outside the
labour force who has reported that they are unable to work or has retired. Figure 1 shows a
disaggregation of the working age population into 11 mutually exclusive labour market cohorts,
or types of searchers, based on their likely attachment to the labour force or, for the employed,
their assessed incentive to find another job (see Appendix A
for further detail on these cohorts).

Figure 1: Labour Market Cohorts

I initially divide the working age population into the three main labour market states – the
employed, unemployed and those not in the labour force. In turn, I split the employed into those who
are underemployed and those who are not (i.e. the ‘fully employed’); the underemployed
likely have a greater incentive to switch jobs or find an additional job as they tend to be
dissatisfied with their current working hours. I generally group the unemployed based on their
duration of unemployment, split into short-, medium- and long-term unemployed. Finally, I
categorise those not in the labour force into those who are conceptually most similar to the
unemployed but who do not meet the criteria to be officially classified as being unemployed (i.e.
those who actively or passively looked for work) and those less likely to engage in job search
activities (i.e. those who have reported that they are ‘not looking’ for work or
‘unable to work or retired’). I split out the individuals who are waiting to start a job
(classified as either unemployed or being outside the labour force) because their attachment to a job
means they are much more likely to find a job compared with other cohorts.

I consider how each cohort’s share of the population and JFR (which are inputs into the SI)
varies. For the employed, the JFR refers to the probability that they either switch a job or gain an
additional job over a one-month period. For the unemployed or those outside the labour
force, the JFR is the likelihood that the individual transitions into employment over the month. The
JFRs for each cohort subsequently imply a relative JFR for the cohort, which is defined as
the cohort’s JFR as a ratio to the average JFR for the population (where the average JFR can be
interpreted as the probability that the average individual in the population is able to secure a
job).

There is considerable variation in relative JFRs and population shares across cohorts, which lends
support to the differentiated treatment of each cohort in the SI. Relative JFRs are generally
highest for cohorts who are waiting to start a job; these individuals are already attached to a job
and are therefore most likely to transition into employment within a month (Graph 1). Those who
have been unemployed for shorter durations (the short- and medium-term unemployed) and cohorts
outside the labour force who are actively or passively looking for work have the next-highest
relative JFRs. For example, the short-term unemployed are around seven times more likely to find a
job in the month than the average individual in the population. By contrast, the relative JFRs of the
employed, particularly the fully employed, are low; the fully employed are around 30 per cent less likely
to switch jobs or find an additional job than an average individual in the population. In general,
this is likely because the fully employed have less incentive to switch jobs or find a secondary job
if they are already satisfied with their current working hours. As expected, those who are long-term
unemployed or who are outside the labour force and have indicated that they are either unable to work
or retired or not looking for work also have low JFRs.

Graph 1

Cohorts with lower relative JFRs tend to have larger population shares (and vice versa). For instance,
the fully employed account for a sizeable share of the population (around 60 per cent) but
have a relatively low JFR, as do those that are outside the labour force who have either reported
that they are not looking for work or are unable to work or retired (who account for 14 and
18 per cent of the working age population respectively) (Graph 2). Conversely, those
waiting to start a job have the highest relative JFRs but account for a very small share (around
0.6 per cent) of the population (Graph 3).

Graph 2

Graph 3

Changes in population shares over time reflect broader demographic and labour market trends. The
increased rate of participation in the workforce over time, especially by women, has contributed to
the share of the population that is fully employed rising to be around its highest level since the
early 2000s; the fully employed share of the population has remained around this elevated level since
late 2022. Relatedly, the share of the population that is outside the labour force and reportedly not
looking for work has trended down. An ageing population has also contributed to the upwards trend in
the share of the population who are unable to work or retired. The downwards trend in the short-term
unemployed share (which typically captures the unemployed who are between jobs) could partially
reflect the long-run decline in the job mobility rate and, in turn, a general decline in business
dynamism (Ellis 2021).

How is the Searchers Index constructed?

The SI is constructed broadly as follows (with further detail on the methodology provided in
Appendix A):

After disaggregating the working age population into the 11 labour market cohorts discussed
above, each cohort’s share of the population and relative JFR over time is calculated.
The percentage change in the SI in a certain month is given by a weighted average of the rate of
growth in each cohort’s share of the population in that month. The weight assigned to each
cohort is given by their share of total hires and is allowed to vary over time. A cohort’s
share of total hires is equal to the product of their relative JFR and their share of the
population. This means the weight assigned to a cohort
increases with how intensely each cohort searches for a job (proxied by their relative JFR) and
their relative importance (or their share of the population).
Taking together the series of (percentage) changes in the SI over time results in an aggregate
index (i.e. the SI). The SI can be decomposed into the contributions of each underlying cohort;
some of these are presented below. Each cohort’s contribution to the SI mechanically
increases (decreases) alongside an increase (decrease) in their share of the population.

What does the Searchers Index tell us?

The SI and the unemployment rate move together, which suggests they both capture broad trends in
labour market tightness (Graph 4). As with the unemployment rate, a decline (increase) in the SI
is generally indicative of tighter (looser) conditions in the labour market, all else equal. For the
SI, this is because it suggests that there are fewer (more) job searchers available to meet
firms’ demand for labour (as proxied, for instance, by job vacancies). Both series tend to be
countercyclical; the SI tends to increase during a labour market downturn (defined as a period during
which the unemployment rate is rising) and decline during the subsequent recovery. That said, there
are periods in which these measures evolve differently, which may point to differences in effective
searchers among the unemployed and other cohorts. For example, while the SI has declined since early
2024, the unemployment rate has risen over this period. This implies that while there were more
unemployed effective searchers, there was also an offsetting reduction in searchers outside of
unemployment such that the measure of effective searchers declined in aggregate. The SI has
stabilised in recent months alongside several other labour market indicators such as job vacancies
and measures of employment intentions. Together, these outcomes highlight the importance of
considering a range of indicators besides the unemployment rate when assessing labour market
conditions.

Graph 4

The SI is considerably less cyclical compared with the unemployment rate. This is likely because the
SI captures other labour market cohorts who help to dampen the cyclicality of the unemployed. In a
downturn, the unemployed share of the population tends to rise, resulting in an increasing
unemployment rate. However, there could also be a decline in the share of on-the-job searchers during
a downturn such that the SI may not rise as much as the unemployment rate. If we only take signal
from the unemployment rate (for a given level of vacancies), we may therefore overstate the easing in
the labour market relative to the case where we also considered the SI (which accounts for changes in
search activity among, for example, the employed).

The SI captures longer run trends in the participation rate and employment-to-population ratio, as
trends in cohorts’ population shares directly influence their contributions to the SI (as
described above). This can be observed by examining, for simplicity, the contributions of the three
main labour market states (i.e. employment, unemployment and not in the labour force) to the SI. The
contribution of the employed has trended up while the contribution of those outside the labour force
has trended down, consistent with the upwards trends in the employment-to-population ratio and the
participation rate (Graph 5). The overall contributions of the employed and NILF cohorts to the
SI are largely influenced by these long-run trends. By contrast, the contribution of the unemployed
is notably countercyclical.

Graph 5

In general, the redistribution of workers from a cohort with a higher relative JFR to one with a lower
relative JFR tends to weigh on overall search activity and the SI. Over time, as workers have
increasingly moved into employment (which tends to be associated with a lower relative JFR),
consistent with an upwardly trending employment-to-population ratio, the SI has trended down. This is
further shown in Graph 5, with the general downward trends in the contributions of the NILF and
unemployed cohorts (who tend to have higher relative JFRs) dominating the upwards trend in the
contribution of the employed, who tend to have lower relative JFRs. Overall, the slight decline in
the SI since early 2024 largely reflects a reduction in effective searchers who are classified as
being outside the labour force.

These aggregated contributions can mask differences across the underlying cohorts. For example, within
the employed group, the fully employed and underemployed cohorts behave in opposing ways over the
business cycle (Graph 6). Similar to the unemployed, the contribution of the underemployed tends
to move countercyclically, as observed during the global financial crisis, as the underemployment
rate typically rises when the labour market eases. By contrast, the contribution of the fully
employed tends to fall when labour market conditions soften.

Graph 6

The medium-term unemployed, who typically capture cyclical unemployment, look to be driving most of
the cyclicality in the overall contribution of the unemployed (Graph 7). The contributions of
most other unemployed cohorts and cohorts outside the labour force do not tend to respond
systematically to the business cycle.

Graph 7

What does the V-S ratio tell us?

The SI allows us to construct a more comprehensive measure of labour market tightness called the V-S
ratio. As with the V-U ratio, the V-S ratio attempts to capture the balance between the demand for
labour (proxied by job vacancies) and the potential supply of labour that could meet this demand.
That said, unlike the V-U ratio, the V-S ratio recognises that vacancies are not only filled by the
unemployed but also by other job searchers who are either already employed or who are outside the
labour force.

The V-S and V-U ratios tend to co-move as the unemployment rate and SI are correlated (Graph 8).
Both measures suggest that tightness in the labour market increased significantly after mid-2020 to
reach a record high in mid-2022 and that labour market tightness has subsequently eased. More
recently, the V-S ratio looks to have stabilised somewhat while the V-U ratio has declined further.
Both ratios remain at levels that are above pre-pandemic outcomes. Despite the upwards trends in
these series, these indicators provide some evidence that conditions in the labour market remain
somewhat tight.

Graph 8

Given that the V-S ratio captures a much broader set of potential job searchers, we intend to include
the V-S ratio in the suite of measures of spare capacity we monitor on a regular basis. Furthermore,
we plan to investigate its relationship with wages growth and inflation as some overseas studies have
found that the V-S ratio could be a relatively good predictor of these variables (Heise, Pearce and
Weber 2024).

Conclusion

The SI tends to move together with the unemployment rate, although it exhibits considerably less
cyclicality. By considering those searching on-the-job or while outside the labour force, it accounts
for the possibility that an increase in unemployed searchers could be offset by a decline in
searchers from another cohort. This dampens the degree to which effective searchers changes over time
relative to that implied by the unemployment rate. The SI captures the net effect of movements of
workers between cohorts with different (relative) JFRs, including the impact of broader labour market
trends. The V-S ratio constructed using the SI and the V-U ratio evolve similarly; both suggest that
labour market conditions remained somewhat tight over 2025. Nevertheless, it is important to note
that the RBA considers a number of labour market indicators when forming its assessment of full
employment as each measure has its own limitations, and that the V-S ratio is but one of many metrics
that can be included in the RBA’s toolkit.

Appendix A: Description of labour market cohorts and further detail on the Searchers Index
Cohort descriptions

Table A.1 provides descriptions of the 11 labour market cohorts underlying the Searchers
Index.

Table A.1: Labour Market Cohorts


Cohort
Definition




Employed


Underemployed
Consistent with the ABS definition of underemployment, this category includes those
who are working part-time and are willing and able to work more hours and those who
are usually working full-time but who worked less than 35 hours in the reference
week for economic reasons (e.g. there was insufficient work available or they were
stood down).


Fully employed
Any employed person who does not fall within the ABS definition of underemployment.



Unemployed


Waiting to start a job
An unemployed person who is waiting to start a job in the next four weeks and who was
available to work in the reference week if the job was available then.


Short-term unemployed
Those who have been unemployed for less than four weeks and are not an unemployed
person waiting to start a job.


Medium-term unemployed
Those who have been unemployed for four to 52 weeks and are not an unemployed
person waiting to start a job.


Long-term unemployed
Those who have been unemployed for more than 52 weeks and are not an unemployed
person waiting to start a job.


Not in the labour force


Actively looking
Those who have taken active steps to seek work (e.g. by applying to vacancies or
interviewing) but who were not available to start in the reference week and therefore
were not classified as ‘unemployed’.


Passively looking
Those who have taken some steps to seek work (e.g. by looking on job advertisement
platforms).


Waiting to start a job
A person who is waiting to start a job but who did not meet the definition of an
unemployed person waiting to start a job described above.


Not looking
Those who have reported that they have not taken any steps to look for work.


Unable to work or retired
Those who are permanently unable to work, institutionalised or at a boarding school
or who are permanently not intending to work and aged 65 and over.

Sources: ABS; RBA.

Further detail on the construction of the Searchers Index

The SI is constructed using a chained Tornqvist index. Growth in the SI is defined as a weighted
average of the percentage growth in each cohort’s share of the population (Equation 1). The
weight applied to each cohort is a simple average of its share of total hires in the current and
previous months. As a cohort’s share of hires can be expressed as the product of its relative
JFR and population share, cohorts are effectively weighted by (a proxy of) how intensely they search
for work and their importance in the population respectively. In particular, the share of total hires
of cohort
i
at time
t
can be written as
hiresi,ttotal hirest=JFRi,t×Populationi,tJFRt×Populationt=Relative JFRi,t×Population sharei,t.
Equation 1 implies that the (log) SI in month
T
is the sum
of the cumulative contributions of each cohort to the SI over time given an arbitrary and unobserved
initial level for the SI
(SI0)
(Equation 2).

log⁡
SItSIt-1
=∑i=1nxi,tlog⁡Pop sharei,tPop sharei,t-1

(1)

log⁡
SIT=∑i=1n∑t=1Txi,tlog⁡Pop sharei,tPop sharei,t-1+log⁡SI0(2)

Where
n
is the number of cohorts,
xi,t
is the weight applied to cohort
i
and
Pop sharei,t
is cohort
i’s
share of the
population at time
t.

The contribution of cohort
i
to the (log) SI at time
T
given an initial level for the SI
(SI0)
is given by:

∑t=1Txi,tlog⁡Pop sharei,tPop sharei,t-1

Each cohort’s contribution to the change in the SI between period
t-1
and period
t
is
xi,tlog⁡Pop sharei,tPop sharei,t-1.
Since
xi,t
is the weight (or the average share of total hires) for cohort
i
and is non-negative, the sign of each
cohort’s contribution is determined by the percentage change in their share of the population or
log⁡Pop sharei,tPop sharei,t-1.

References

Abraham KG, JC Haltiwanger and LE Rendell (2020), ‘How Tight Is the US Labor
Market?’, Brookings Papers on Economic Activity, 51(Spring), pp 97–165.

ABS (Australian Bureau of Statistics) (2025), ‘Multiple Job-holders’,
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Ballantyne A, A Sharma and T Taylor (2024), ‘Assessing
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Byrne S and T Conefrey (2017), ‘A Non-employment Index for Ireland’, Central
Bank of Ireland Economic Letters No 9.

Cassidy N, I Chan, A Gao and G Penrose (2020), ‘Long-term
Unemployment in Australia’, RBA Bulletin, December.

Ellis L (2021), ‘Innovation and Dynamism
in the Post-pandemic World’, Speech to the Committee for the Economic
Development of Australia, Webinar, 18 November.

Heise S, J Pearce and J Weber (2024), ‘Wage Growth and Labour Market Tightness’,
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Hornstein A, M Kudlyak and F Lange (2014), ‘Measuring Resource Utilisation in the Labour
Market’, Federal Reserve Bank of Richmond Economic Quarterly, 100(1), pp 1–21.

Kudlyak M (2017), ‘Measuring Labor Utilization: The Non-Employment Index’,
Federal Reserve Bank of San Francisco Economic Letter No 2017-08, March.

McCarthy M (forthcoming), ‘Measuring Effective Searchers with Quantity Indexes’,
Working Paper.

RBA (2025), ‘Section
2.4 Assessment of Spare Capacity’, Statement on Monetary Policy,
August.

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