The Government’s Tax Package:
Short-run Implications for Employment by Industry, Region, Occupation,
Age and Gender
by Peter B. Dixon and Maureen T. Rimmer
Centre of Policy Studies, Monash University
Report prepared for the Department of the Senate
March 19, 1999.
1. Introduction
This report is designed to throw light on the issues listed in the terms
of reference in Appendix A. It is an extension of our earlier paper (dated
January 25, 1999) prepared for the Senate Select Committee on a New Tax
System, and published as an appendix to the Select Committee’s First
Report.
In our paper of January 25 we considered the macro-economic implications
of the Government’s tax package under seven sets of assumptions (scenarios).
Here we extend the analysis for two of the scenarios: the central and
first sensitivity cases. The key difference between these cases is the
labour market assumption. In the central case we assume that in making
wage bargains workers think in terms of real after-tax wage rates. This
means that their wage demands would be moderated by the income-tax cuts
which are part of the Government’s package. In the first sensitivity
case we assume that workers bargain in real before-tax terms. Thus income-tax
cuts become irrelevant to short-run wage negotiations. Under these circumstances,
implementation of the Government’s package would generate a short-run
jump in wage rates in line with the GST-induced jump in the CPI.
As explained in the January 25 paper, the Government’s tax package
under the assumptions of the central simulation would generate a short-run
employment gain of about 30,000 jobs. That is, after about a year employment
would be about 30,000 jobs greater with the implementation of the Government’s
package than without the implementation of the package. As argued in the
January 25 paper, the increase in employment reflects the unbalanced nature
of the Government’s package. The cuts in income taxes outweigh the
net increase in indirect taxes by about $6 billion.
In the first sensitivity simulation the implementation of the Government’s
package reduces aggregate employment in the short run by about 120,000
jobs. Short-run employment reduction in this simulation results from an
increase in wage costs relative to producer prices generating a squeeze
on profits and a cut in the profit-maximising level of employment. The
increase in wage costs relative to producer prices is an inevitable consequence
of the assumption that before-tax wage rates jump with the CPI. Under
this assumption wages must move ahead of producer prices because the GST
increases consumer prices relative to producer prices.
In Tables 1 to 4 we disaggregate the short-run changes in employment
in the two simulations into effects on employment: by industry (112 input-output
categories); by region (57 statistical divisions, see map in Appendix
B); by occupation (340 ASCO categories); and by age and gender. In each
table the first column shows the percentages of total employment in the
industry, region, occupation and age/gender categories identified in the
rows. For example, Table 1 indicates that 3.54 per cent of employment
in Australia is in the Agriculture, forestry and fishing sector. The second,
third and fourth columns in each table refer to the central simulation:
column (2) shows the percentage effects on employment; column (3) ranks
the percentage effects; and column (4) translates the percentage effects
into numbers of jobs. For example, with reference Table 1, we see that
in the central simulation, employment in the Pastoral zone (I1) falls
by 4.16 per cent, that the Pastoral zone is the 108th ranked industry
by percentage employment growth and that the change in employment in the
Pastoral zone caused by the tax package is a loss of 591 jobs. Columns
(5) to (7) of each table give results for the first sensitivity simulation.
These columns have the same format as columns (2) to (4).
The slight discrepancies between the total job changes shown in the last
row of the 4th column of Tables 1 to 4 are caused by rounding errors in
our calculations. Similarly, there are small discrepancies between the
total job changes shown in column (7) of the tables.
2. Industry results (Table 1)
In the central simulation (columns (2) to (4) in Table 1) the tax package
produces a strong short-run stimulation of investment associated with
a reduction in the costs of capital relative to the costs of labour. There
is also a short-run expansion in private consumption associated with an
increase in aggregate employment. These increases in demand (investment
and consumption) favour non-trade-exposed industries, e.g. Construction
(I87 and I88), Building materials (most of I57 to I67), Wholesale and
Retail trade (I89 and I90), Banking and Finance (I99 and I100) and Health
and Welfare (I107 and I109).
An effect of increases in demand, especially investment demand, is to
generate a loss in short-run international competitiveness, that is a
real appreciation. This could be through exchange rate appreciation or
increased inflation. Via real appreciation, resources are transferred
away from trade-exposed industries towards non-trade-exposed industries
oriented to satisfying increased domestic demands. Another way of thinking
about exchange-rate effects is to recognize that increased investment
in Australia normally requires increased foreign-capital inflow. This
increases demand for the Australian dollar.
A downside of real appreciation is that it reduces employment in trade-exposed
industries. This is apparent in column (2) of Table 1 where employment
falls in all agricultural industries. Employment also falls in most mining
industries. However the adverse short-run effects on mining are less pronounced
than those for agriculture because, relative to the agricultural industries,
the mining industries benefit from sharper reductions in costs associated
with the proposed reductions in producer taxes. In the case of Iron ore
(I12), the reduction in costs is sufficient to outweigh the real exchange
effects leaving this industry with a short-run employment increase.
In column (2) of Table 1, real appreciation adversely affects both export-oriented
manufacturing industries (e.g. Food processing, I18 to I22) and import-competing
manufacturing (e.g. Textiles, Clothing and Footwear, I31 to I39). One
trade-exposed manufacturing industry which is projected in column (2)
to experience short-run gains from the Government’s tax package is
Motor vehicles (I68). This industry will benefit from sharp reductions
on sales taxes on cars.
Finally in column (2) of Table 1 we see significant employment reductions
in tourism-related industries (I96 and I110 to I112). As explained in
our paper of January 25, failure to exempt tourism exports from the GST
will have a significant negative impact on the number of international
visitors to Australia. The GST will also encourage Australians to take
holidays overseas rather than locally.
In the sensitivity simulation [columns (5) to (7) of Table 1], the short-run
investment response to the implementation of the tax package is much weaker
than in the central simulation. This is because in the sensitivity simulation
businesses suffer a profit reduction associated with the increase in wage
costs relative to producer prices. Consumption is also weaker in the sensitivity
simulation than in the central simulation, because in the sensitivity
simulation aggregate employment contracts whereas in the central simulation
it increases. Reflecting weaker demand, there is much weaker real appreciation
in the sensitivity simulation than in the central simulation. Thus, export-oriented
industries fare better in the sensitivity simulation than in the central
simulation. For example, in the sensitivity simulation mining employment
rises by 0.29 per cent whereas in the central simulation it falls by 1.08
per cent.
For import-competing manufacturing industries, comparative performances
in the two simulations depend on the relative strengths of two opposing
forces. On the one hand these industries benefit in the sensitivity simulation
relative to the central simulation from less real appreciation. On the
other hand these industries are harmed as we move from the central simulation
to the sensitivity simulation by a lower level of domestic demand. For
most import-competing manufacturing industries the demand effect outweighs
the real exchange rate effect. For example, for the Motor vehicle industry
(I68) employment growth is reduced from 1.59 per cent in the central simulation
to 0.38 per cent in the sensitivity simulation. Nevertheless, there are
some import-competing manufacturing industries for which the employment
effects go the other way. An example is Synthetic yarns (I31). In the
central case the reduction in employment is 4.55 per cent whereas in the
sensitivity simulation the reduction in employment in this industry is
restricted to 3.70 per cent. For the tourism-related industries (I96 and
I110 to I112) the demand effects are more important than the exchange
rate effects. Consequently the employment results for these industries
are even weaker in column (5) than in column (2).
Industries with only a weak exposure to international trade are clearly
worse off in the sensitivity simulation than in the central simulation.
For example, the reduction in investment as we move from the central simulation
to the sensitivity simulation turns the employment result in Construction
(I87 and I88) from a gain of 3.56 per cent to a loss of 0.50 per cent.
Similarly, reductions in consumption in the sensitivity simulation relative
to the central simulation turn the employment result for the Wholesale
and Retail trade sector (I89 to I92) from a gain of 1.09 per cent to a
loss of 1.05 per cent.
3. Regional results (Table 2)
The main ingredients in our regional calculations are the industry results
discussed in the previous section. These are combined with information
on the industrial composition of output in each region. Thus we find in
Table 2 that regions with an over-representation of favourably-affected
industries are projected to gain employment from the Government’s
tax package while the opposite is true for regions with an under-representation
of favourably-affected industries.
A striking feature of the results in Table 2 for States and Territories
is the narrowness of their range. In the central simulation the strongest
State/Territory employment result is for Western Australia, a gain of
0.59 per cent, and the weakest result is for the Northern Territory, a
gain of 0.29 per cent. Similarly, in the sensitivity simulation the State/Territory
employment results are confined to a narrow range, -1.42 for Victoria
to -0.80 for Western Australia. The closeness of the results for the worst-affected
and best-affected States/Territories reflects the similarities across
these economies in their industrial structures. Employment in all of them
is dominated by service industries such as Wholesale trade, Retail trade,
Transport, Communication, Banking, Education, Health, Welfare, Public
administration and Entertainment. Each of these industries accounts for
a similar percentages of employment in every State and Territory. For
some other industries there are sharp differences in their employment
shares by State and Territory. For example, Textiles, Clothing and Footwear
account for a higher share of employment in Victoria than in other States
and Territories. Motor Vehicles are strongly over-represented in the economies
of Victoria and South Australia, and Mining is over-represented in Western
Australia. However these industries account for relatively small shares
of employment even in the States in which they are primarily located.
The slightly above average performance of Western Australia in both simulations
mainly reflects the State’s comparatively low dependence on tourism.
Similarly, the slightly below average performance of the Northern Territory
in the central simulation reflects its comparatively high dependence on
tourism. As we move from the central simulation to the sensitivity simulation
the employment performance of the Northern Territory declines. Nevertheless,
the Northern Territory improves its position relative to other States/Territories.
This is because export-oriented industries in the Northern Territory such
as Northern beef are relatively sensitive to the real exchange rate.
At first glance the results for South Australia may seem surprising.
This State will benefit from the GST via its dependence on the Motor vehicle
industry. Nevertheless, it is a slightly below-average performer in both
simulations. The advantages it derives from the Motor vehicle industry
are offset by the disadvantages in derives from over-representation of
the wine industry (a component of I28) and grape growing (a component
of I6). As can be seen from Table 1, industries I28 and I6 have comparatively
large employment losses in both simulations.
Like South Australia, Victoria benefits from an over-representation of
the Motor vehicle industry yet has a slightly below-average employment
performance in both simulations. For Victoria, the short-run negatives
from the GST flow from over-representation of adversely-affected import-competing
industries such as Textiles, Clothing and Footwear and Chemicals.
In the case of Queensland, the slightly below-average performances in
both simulations reflect comparatively heavy tourism dependence. However,
much of tourism expenditure (especially on air fares and shopping) is
outside Queensland even for tourists who spend most of their holiday in
Queensland. Thus, the GST-induced downturn in tourism causes only a slightly
stronger contraction in the Queensland economy than in other State/Territory
economies, especially New South Wales.
The Australian Capital Territory does better than average in both simulations.
In the central simulation the ACT benefits from its lack of dependence
on agriculture and mining. In the sensitivity simulation in which employment
in most industries contracts, the ACT benefits from its dependence on
public expenditure. In both simulations we assumed that real public expenditure
is unaffected by the proposed tax changes.
Tasmania has slightly above average employment performances in both simulations.
This reflects its below-average dependence on trade-exposed activities
including international tourism.
Finally, New South Wales performs close to average in both simulations.
The NSW economy accounts for more than a third of the Australian economy
and has a well-balanced representation of industries. Inevitably, the
performance of NSW under economy-wide shocks such as the proposed tax
changes is projected to be close to the Australian average.
The results in the central simulation for the sub-State regions follow
a clear pattern. In all States except Victoria the capital city is the
best performer. This reflects the over-representation in capital cities
of service industries (favourably affected in the central simulation)
and the under-representation of agriculture and mining (unfavourably affected
in the central simulation). In Victoria, Barwon has a slightly more favourable
employment result than Melbourne. Barwon (which includes Geelong) benefits
from its heavy dependence on the Motor vehicle industry.
In the sensitivity simulation there is little difference between the
employment results for the capital cities and for the other divisions.
As explained earlier, the traditional export industries fare better in
the sensitivity simulation than in the central simulation and the service
industries fare worse. This produces a more even set of industry results
in the sensitivity simulation than in the central simulation, and thus
a more even set of regional results.
One interesting pair of sub-State results are those for Moreton in the
two simulations. Moreton includes the Gold Coast and the Sunshine Coast.
Thus Moreton has a strong dependence on tourism. Nevertheless, its employment
result in the central simulation ranks quite high, fifteenth. In this
simulation, Moreton suffers from the GST-induced decline in international
tourism. However this effect is largely offset in the central simulation
by favourable short-run movements in macro variables. With an increase
in aggregate employment and consumption, Moreton benefits from increased
domestic tourism. When we move to the sensitivity simulation, Moreton’s
ranking drops to fifty-seventh, that is last. In the sensitivity simulation
Moreton continues to suffer from the GST-induced reduction in international
tourism and also suffers from the GST-induced reduction in aggregate employment
and consumption.
4. Occupation results (Table 3)
As with the regional results, the occupational results follow from the
industry results. For the central simulation we see in column (2) of Table
3 that the worst affected occupations are associated with tourism-related
industries, with agriculture and with Textiles, Clothing and Footwear.
Adversely-affected tourism-related occupations include 100, 120-126, 148,
180-181, 196, 220, 245-248, 300 and 308-309. Adversely-affected agricultural
occupations include 21-24, 182-183 and 331, and adversely-affected TCF
occupations include 197, 199-200 and 265-266. At the other end of the
spectrum, positive results are shown in column (2) for occupations associated
with Construction (168-177 and 327-330) and with Motor vehicles (157-161).
In the sensitivity simulation the results in column (5) of Table 3 are
relatively uniform, with almost all occupations showing employment losses
of between zero and two per cent. This reflects the more uniform industry
results in the sensitivity simulation than in the central simulation.
Nevertheless, the tourism-related occupations stand out from the rest
as the worst affected.
For many occupations, industrial structure is only a minor determinant
of employment. These are the occupations that are not closely identified
with a particular industry or narrow group of industries. Examples of
such occupations include general-purpose clerical workers (e.g 212-213
and 224-226). For such workers the employment results in columns (2) and
(5) must be close to the economy-wide average.
5. Age/gender results (Table 4)
In the central simulation short-run employment prospects for males are
enhanced relative to those for females (column (2), Table 4). Relative
to female employment, male employment in this simulation is more heavily
dependent on occupations favoured by the Government’s tax package.
Examples of favoured male-dominated occupations can be found in the Motor
vehicle industry (occupations 157-161 in Table 3) and in Construction
(168-177 and 327-330). Relative to male employment, female employment
in the central simulation is more heavily dependent on occupations harmed
by the package. Examples of harmed female-dominated occupations can be
found in the tourist sector (particularly occupations 246-248) and in
TCF (particularly occupation 265).
Short-run employment prospects for both genders in the central simulation
are weakest for older workers. This is explained by their over-representation
in the agricultural occupations (21-24). Short-run employment growth is
also relatively weak in the central simulation for young females. These
workers are strongly over-represented in tourist-related occupations,
especially 246-248.
In the sensitivity simulation (column (5) in Table 4) there is little
variation across the age/gender groups in the short-run employment effects
of the Government’s tax package. The relative uniformity of the industry
results in the sensitivity simulation generates relative uniformity in
the occupation results which in turn generates relative uniformity in
the age/gender results.
6. Other issues
6.1 Unemployment versus employment
The terms of reference in Appendix A is concerned with short-run unemployment
by industry, region, occupation, age and gender. For this report we have
been able to generate results for employment classified by these dimensions
rather than for unemployment. To move from our results on employment to
disaggregated results for unemployment would require detailed information
on the mobility of workers in different age/gender groups between industries,
regions and occupations. It would also require information for different
categories of workers on the sensitivity of their labour force participation
rates to changes in their employment opportunities. Finally it would require
disaggregated background forecasts of employment opportunities. Worthwhile
research on mobility, participation and forecasting could be undertaken
but it would require much more resources than were available for this
project. In the absence of the required research we must rely on employment
results as negative indicators of likely unemployment effects.
6.2 Aboriginal unemployment
The terms of reference are concerned with the effects of the Government’s
tax package on aboriginal unemployment. We look at this issue briefly
by examining the industry/occupation profile of Aboriginal employment
in relation to the short-run structural effects that we are projecting
from the Government’s tax package.
Industry profile
Data in Table 5 show shares of major industry
groups in the employment of indigenous and non-indigenous Australian males
and females. Public administration and Community services dominate indigenous
employment, accounting for 37.7 per cent of indigenous males employed
and 53.0 per cent of indigenous females employed. By comparison 16.5 per
cent of non-indigenous employed males and 32.3 per cent of non-indigenous
employed females are in these sectors. Consequently the effect of the
Government’s proposed tax package on employment prospects in these
sectors is important in determining the likely impact on indigenous employment
relative to non-indigenous employment.
In both the central and sensitivity simulations employment in Public
administration and Community services is favoured relative to employment
in general (see the results for I105 to I109 in Table 1). On this account,
the industrial employment profile of indigenous Australians is relatively
favourable.
Occupations
Table 6 shows that indigenous employment is
relatively heavily weighted towards labouring occupations (occupations
291-340 in Table 3). Employment in these occupations declines slightly
relative to employment in general in both of our tax-package simulations.
Employment in management and administration (occupations 1-24) also declines
slightly relative to employment in general in both simulations. Indigenous
people are strongly under-represented in these occupations. We conclude
that the occupational profile of indigenous people is close to neutral
with respect to the short-run employment implications of the Government’s
tax package.
6.3 Accelerated depreciation and company taxes
The terms of reference are concerned with the effects of eliminating
accelerated depreciation allowances and reducing company taxes. This has
been recommended recently by the Ralph committee. In the time available
for this report, we can consider this issue in broad qualitative terms
rather than in quantitative terms.
The Ralph committee has proposed a reduction in company taxation from
36 to 30 per cent combined with the elimination of accelerated depreciation
allowances. Treasury estimates imply that the proposed cut in company
taxes would cost about $2 billion while the elimination of accelerated
depreciation allowances would save about $2 billion. Thus it is likely
that the proposed changes would have only a small effect on the overall
required pre-tax rate of return on capital in Australia. Consequently
we would expect the effects on investment, the capital/labour ratio and
other macro-economic variables to be minor.
At the micro level, the proposed changes would enhance the desirability
of some investments and reduce the desirability of others. To see how
this could happen it is useful to work through some algebra. Consider
an equipment investment which costs $C, has an economic life of T years
and earns an annual profit of $Q. Assume that the company tax rate is
t and that depreciation is allowed at an accelerated rate over S years
where S is less than or equal to T. If the rate of interest to firms making
this sort of investment is r per cent then the present value of the investment
is given by
. (1)
In terms of this formula the proposed changes are to reduce t from 0.36
to 0.30 and to increase S to T. These changes could either increase or
decrease PV. They will tend to increase PV if S is close to T, that is
they will increase PV for investments on which the present accelerated
depreciation allowances are not generous. They will tend to decrease PV
when r is high, that is they will decrease PV if bringing forward tax
savings is valuable. Some industries may have a predominance of projects
in which PVs are increased by the proposed tax changes. Prima facie, it
seems that for these industries capital expansion is likely. Other industries
may have a predominance of projects for which PVs are reduced. For these
industries capital contraction seems likely. In the time available for
this section of the present study (approximately one day) it is clearly
impossible to classify industries into those likely to expand and those
likely to contract.
For working out the likely industry effects of the proposed changes in
business taxes there are various other issues to consider in addition
to the complexities of formula (1). These include: (a) the extent to which
firms in an industry are incorporated or unincorporated; (b) the extent
to which firms in an industry are foreign-owned; and (c) the extent to
which firms in an industry pay dividends or retain their profits.
Consider first industries such as agriculture which are dominated by
domestically-owned unincorporated enterprises. For these industries the
company tax is largely irrelevant. On the other hand they benefit from
accelerated depreciation. Thus, the proposed tax changes are likely to
increase their required rates of return on capital, reducing investment,
output and probably employment.
Next consider industries, such as banking, which are dominated by mainly
domestically-owned corporate enterprises. The simplest case is when the
industry returns most of its profits to its shareholders. In this situation
company tax and accelerated depreciation are not important. This is because,
via dividend imputation, tax savings to corporations will translate into
extra personal tax for the shareholders. Similarly, additional taxes imposed
on corporations will translate into tax savings for shareholders.
However Australian corporations tend to retain about 40 per cent of their
profits. This can be thought of as additional investment in the corporations
by the shareholders. In these circumstances a reduction in the taxes paid
by the corporations is advantageous to shareholders. For example, if a
corporation earns $100 profit and the corporate tax rate is lowered from
36 per cent to 30 per cent, then through retention of profits the shareholders
can reinvest $70 in the corporation rather than $64. Thus we conclude
that the proposed tax changes are likely to favour corporatized industries
with strong growth prospects justifying high rates of profit retention.
This conclusion is strengthened if these industries are not beneficiaries
of generous accelerated depreciation allowances. We suspect that this
is the case for industries such as banking in which the capital stock
consists largely of land and buildings.
The next case to consider is a corporatized industry with a large share
of foreign ownership. Examples can be found in the mining sector. Again
the simplest case is when the corporations in the industry pay out most
of their profits in dividends. In this case it is probably advantageous
for Australia to impose high taxes on corporations (high company tax rates
and ungenerous depreciation allowances). The reason is that most foreign
investors in Australian companies can claim tax reductions in their own
countries in recognition of taxes paid to the Australian government. Consider
for example a U.S. investor with a personal tax rate of 50 per cent. If
the company tax rate in Australia is 36 per cent then the U.S. investor
will pay 14 per cent to the U.S. government on dividends received from
Australia. If the company rate is reduced in Australia to 30 per cent
then the U.S. investor will simply pay 20 per cent to the U.S. government.
Thus reductions in the business taxes do not change the desirability of
investments in Australia to the U.S. investor. They simply transfer revenue
from the Australian Treasury to the U.S. Treasury.
If foreign-owned Australian corporations retain substantial shares of
their profits, then the desirability to foreigners of investments in these
companies is likely to be enhanced by reductions in company taxes. The
argument is the same as that given earlier: reductions in company taxes
increase the share of retained profits which is reinvested in the corporation
on behalf of the shareholders (either domestic or foreign). On the other
hand, the desirability of investments will be reduced by elimination of
accelerated depreciation allowances.
In summary, the following conclusions emerge from this discussion.
- Industries dominated by unincorporated enterprises (e.g. agriculture)
are likely to lose from the proposed changes.
- From the point of view of either domestic or foreign investors,
the desirability of investments in industries with low profit-retention
rates is likely to be little effected by the proposed tax changes.
- Both domestic and foreign investors will be affected by changes
in taxes applying to industries with high profit-retention rates.
In such industries with ungenerous depreciation allowances investment
will be encouraged. On the other hand, in industries such as mining
which benefit from generous depreciation allowances investment is
likely to be discouraged.
- A disadvantage of reducing business taxes in Australia is that
this may generate a transfer of revenue from the Australian Treasury
to foreign treasuries with little overall encouragement of foreign
investment in Australia. This will be a likely outcome if reductions
in taxes are concentrated in industries with profit-retention rates
and high shares of foreign ownership.
- A second disadvantage of reducing business taxes is that this
may tend to lock funds into existing corporations. For example,
if the typical investor has a personal income-tax rate of 50 per
cent then a reduction in the company-tax rate from 36 per cent to
30 per cent will enhance the advantages of retaining profits. From
this point of view it would be advantageous to increase company
taxes rather than to reduce them.
- A serious quantitative analysis of the proposed changes in business
taxes would require an input of several person-months of high quality
economic research. In the absence of this work all that is possible
is a qualitative discussion.
7. Concluding results
The overwhelming conclusion from the detailed calculations presented
in this report is that the Government’s tax package will have only
minor structural effects on employment in the short run. Most of the percentage
changes in employment in Tables 1 to 4 lie between -2 and 2 per cent.
However there are some numbers outside this range. In some tourist-related
categories, job losses of up to 8 per cent are projected. Other categories
of employment in which the Government’s tax package could produce
significant short-run effects are associated with Construction (favourable),
Agriculture (unfavourable), TCF (unfavourable) and Motor Vehicles (favourable).
It was not possible in this report to consider all of the terms of reference
(Appendix A) in detail. We gave only light coverage to the effects of
the Government’s tax package on the employment of Aborigines. However
on the basis of what we were able to do in the time available, we conclude
that the package is likely to have an effect on Aboriginal employment
similar to its effect on employment in general. We also gave only light
coverage to the issue of company taxes and accelerated depreciation allowances.
This topic warrants detailed quantitative modelling before policy changes
are implemented.
Appendix A.
Terms of Reference
The Committee wishes to commission a research and modelling project according
to the following terms of reference:
a) The impact of the governments tax package on unemployment in the
short term, specifically in relation to:
- National unemployment rate
- State and Territory unemployment rates
- Regional unemployment
- Unemployment by industry
- Unemployment rates by gender and age
- Labor force participation rates by gender
- Youth unemployment
- Aboriginal unemployment
b) The impact of the governments tax package on unemployment in the
short term (including proposals to eliminate accelerated depreciation
in the context of a 30 cents in the dollar company tax rate) specifically
in relation to:
- The national unemployment rate
- State and Territory unemployment rate
- Regional unemployment
- Unemployment by Industry
- Unemployment rates by gender and age
- Labor force participation rates by gender
- Youth unemployment
- Aboriginal unemployment