Transport + communications,
energy and water. 9.30** 11.49** 7.66**
Transport + communications, energy and water and other
services 9.19** 10.37** 7.36**
Relatively Low Levels of
Unionisation
Agriculture and distribution 16.54** 18.70** 10.99**
Agriculture, distribution and
banking and business services 14.06** 11.35** 13.46**
Notes: The regression equation used Ln weekly earnings as the dependent variable and four education dummies,experience, experience 2,X, education*X, marital status, location and five occupational dummies (it was necessary to combine farm workers with semi and unskilled workers as farm workers are not found in all industries).
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Figure 6.7: Predicted Earnings for Australian Men in Industries with High and Low Levels of Unionisation.
Ln Earnings
Graduates (high)
Figure 6.8: Predicted Earnings of British Men in Industries with High and Low Levels of Unionisation. Ln Earnings - Graduate (high) 4 .9 - Graduate (low) Unqualified (high) 4 .7 - 4 .5 Unqualified (low) 4.1 - 3 .7 - f t t t ft-ft-ft-f-t-t-ft— t— t— t— t— t 1-t-t i t i t i t I i i ) i Experience
Figure 6.9: Predicted Earnings for American Men in Industries with High and Low Levels of Unionisation.
Ln Earnings Graduates (high) 6.1 ■■ Graduates (low) 5 .7 ■■ Unqualified (high) 5 .3 Unqualified (low) 4 .9 '■ 4 .7 ■■ I I I I «— t i 1-4- » < I t < ■4't t I I I ) I Experience
161
more unionised sector, this difference did not remain. After 10 years of labour market
experience, the profiles were the same. In the US earnings of those graduates in the less
unionised industries were above those in the highly unionised industries until about 30
years of labour market experience, after which the predicted earnings profile of graduates
in the more unionised industries lay above that of the less unionised industries.
Summary
The results of this section are consistent with the hypothesis that trade unions
cause the age earnings profile to be flatter. In the industries where the level of
unionisation was relatively high in each country, there tended to be smaller increases in
earnings with additional experience for most education groups.
A number of studies find that trade union members receive a premium over non
union members who are similar in other respects. The predicted earnings for the
unqualified in the more unionised industries lay above those of the unqualified in the less
unionised industries for each sample. The difference in the level of these profiles was
smallest for Australia, a result consistent with the hypothesis that a centralised wage
setting system where most workers are covered by awards, should be expected to
produce a smaller difference between the highly unionised and less unionised sectors
than a more free market system. The fact that the differences were less pronounced for
university graduates might be explained by the fact that white collar workers are less
unionised than the rest of the w o r k fo r c e .^ ) The results we have presented compare
industries within countries where the level of unionisation differed markedly in the early
1980’s. In Australia and Great Britain, a much larger part of the workforce was
influenced by union activities than in the US. In Australia, 53 per cent of the male
workforce were union members. In Great Britain about 70 per cent of the male
workforce was covered by a collective agreement but in the US, union members only
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effects of trade unions on the industry wage structure appear less pervasive in the US
than in Australia and Great Britain.
5. Conclusions
In this chapter we have confirmed results of many other studies that industry of
employment is an important determinant of earnings. In each country there appeared to
be a negative relationship between the industry intercept term and the growth of earnings
with experience. The industry intercept terms were also positively correlated across the
countries. These conclusions are consistent with a number of hypotheses concerning the
underlying cause of the industry differences. Whatever it is, it appears to be operating in
each of the three countries. Different institutional settings have produced broadly similar,
but not identical, results in terms of the effect of industry on earnings.
While the results of the decomposition of the relative earnings gap between
Australia and Great Britain and between Great Britain and the United States did not
change substantially, the inclusion of industry and occupational variables somewhat
changed the results o f the Australia/ United States comparison. In comparing Australia
and Great Britain, the positive effect of higher rewards for a given set of human capital
endowments in Great Britain was offset by relatively lower stocks of human capital
endowments at most ages compared with Australia. There is little evidence of systematic
differences in the shapes of the age earnings profiles of Australia and Great Britain. The
earnings of British men did not rise as much with age as for American men because of
the relatively lower levels of human capital endowments among older Britaish men. The
results presented here comparing Australia and the US show that coefficient differences
were a more important source of differences in relative earnings by age between the two
countries than the results of chapter 4 indicated. However, it was not differences in the
rewards to industry and occupational endowments which were important in explaining,
the gap in relative earnings but the rewards to the endowments included in the basic
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In the final section, we considered the hypothesis that the effect of industry on
earnings is in part the effect of trade unionism on earnings. We tested for each country
whether more unionised industries had different experience earnings profiles than the
less unionised industries. In general, we found for most education groups, that the
predicted age earnings profiles were flatter in the highly unionised compared with the
less unionised industries. The industry variables in the regressions covering the whole
sample may be picking up a union effect on earnings rather than the effect of investment
in human capital or a steep profile to reduce shirking. Although the ranking of industries
by level of unionisation was similar across the three countries, the actual levels of union
influence in the labour market differed markedly. In the early 1980’s unions were more
important in Australia and Great Britain than in the US. Our results are consistent with
trade unions effecting the industry wage structure more pervasively in Australia and
Great Britain than in the US.
Footnotes
1. See Katz (1986) and Krueger and Summers (1987) for fuller discussions.
2. See Katz (1986), Krueger and Summers (1987) and (1988) for summaries of US
evidence.
3. Participation in a superannuation scheme was included, the authors argued, as it may
affect the age earnings profiles of otherwise identical individuals.
4. The limited evidence available suggests that job durations may be higher in the US
than in Australia. The information relates to time with particular employers not with a
particular industry. Individuals may change jobs more frequently in Australia but stay in
the same industry.
5. These theories are presented in detail in chapter 2 so we have not repeated this earlier
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6. Murphy and Topel (1987) dispute this result. They used panel data to track the change
in earnings of individuals who moved between industries. They concluded " A key
finding is that actual wage changes in this population are only weakly related to the
industry wage differences that are observed in the cross-section. The implication is that
unobserved differences in individuals' earnings capacities account for a majority of
observed cross-sectional wage differences." ( p i37)
7. For a fuller list of factors which may generate compensating differentials see chapter 2
footnote 1.
8. It has been argued in the US literature (see Krueger and Summers (1988) for a
discussion) that the industry wage differential may be in response to the different costs
associated with the threat of unionisation in different industries. Employers in different
industries raise wages to varying degrees as a protection against unionisation depending
on the costs they face. In the Australian and British contexts, with relatively high
unionisation and coverage by collective agreements and awards in all industries, this
seems an unlikely explanation of the industry differentials. We have therefore not
considered this argument further.
9. See Krueger and Summers (1988) and Dickens and Katz (1987) for summaries of US
evidence. Hatton and Chapman (1989) present Australian evidence.
10. Prais et al. (1981) compared plant sizes in 33 manufacturing subsectors in Great
Britain, the US and West Germany. Bollard and Daly (1985) used this study to extend
the comparison to Australia and New Zealand. The latter study distinguished 12
manufacturing industries and found a close correlation between the size of plants in
Australia and the original three countries.
11. The results of the industry regressions omitting the occupational dummies are
presented in Appendix F.
12. Only broad occupational groups were available for the British data, although more
detailed information was available on occupation for Australia and the United States. The
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occupation on earnings because of the diversity of actual jobs included within a category;
for example professional workers include doctors, nurses, accountants and lawyers. On
the other hand, if the importance of occupation in determining earnings relates to the
degree of substitutability between individuals in different occupations, these broad
groups may at certain skill levels, more accurately cover individuals who are in fact close
substitutes for each other than a finer classification. So for example, most workers
classified as semi or unskilled may be close substitutes for each other across a range of
detailed occupations such as labourers, textile workers, packers and storemen. Any
effect of occupation on earnings may be related to being semi or unskilled, not to their
detailed classification.
13. The data which have been used for these tests are presented in Appendix F. They are
a reworking of the regression coefficients.
14. The calculation of a simple correlation coefficient between the two estimated values
is not really appropriate because of the bias that will arise where the coefficients come
from a shared regression (see Chapman and Tan (1980). However, the simple
correlation coefficient between the two coefficients for each country were for Australia, r
= -0.54, Great Britain, r = -0.81, the US, r = -0.36.
15. As with the American regression results reported in chapter 4, the equations
including industry and occupation over-predicted the earnings of men in their 40s. There
was a sizeable residual error for the American regression at these ages; for example see
Table F6 in appendix F.
16. Hirsch and Addison (1986) summarised the US evidence as follows, " There is a
fairly strong consensus that unions act to decrease the slope of the log eamings-
experience profile. This conclusion is based primarily although not exclusively on cross-
sectional evidence showing flatter and less concave earnings and wage profiles among
union members, and a larger union-nonunion wage differential for younger workers."( p
170). US evidence also shows a positive relationship between unionisation and fringe
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have the data available in this study to test whether unionisation is associated with flatter
total compensation packages than non-union members receive.
17. If the effect of unions spreads beyond their members to all those who work or
compete with union members, the use of industry data may better represent the area
covered by unions than a straightforward count of union membership. In a centralised
system of wage determination as found in Australia, the most important effect of unions
may well be on the structure of the awards which apply to industries and/or occupations
regardless of whether individuals belong to unions or not. Even in a more free market
environment the effects of unionisation may go beyond union members. US evidence
suggests that unions have a positive effect on the earnings of non-union members in the
same industry, see Hirsch and Addison (1986).
18. One part of the classification which is not entirely satisfactory is the inclusion of
"other services" in the highly unionised group. This industry covers public
administration and community services which are highly unionised industries and
personal services which is not (see Table 3.7 and 3.8 Chapter 3). The first two
industries accounted for 92 per cent of employment in the US, 83 per cent in Australia
and 75 per cent in Great Britain in "other services".
19. The difference between the aggregate level of unionisation and the level of
unionisation among professional workers and managers and administrators was greater
in the US than Australia. In the US, 14 per cent of these two occupational groups were
union members but in Australia, 43 per cent of these groups were members of trade