What are the characteristics of the employers of the low paid in Australia?Abstract
Service-sector employers from Communications; Accommodation, cafes and restaurants; Personal and other services; Retail trade; and Manufacturing have the highest densities of low-wage employees in Australia. In addition, the majority of all employers of the low paid were service-industry employers. A multivariate analysis found that employers of the low paid were more likely to be small firms employing a disproportionate share of casual labour. Employers of the low paid were more likely to be located in industries where labour costs form a relatively smaller proportion of turnover (possibly because of high material costs) and where there were higher rates of businesses recording a loss of profit. In addition, substantial regional differences remain in the presence of industry controls, indicating that state-level differences in the incidence of low-paying employers cannot be fully accounted for by the other factors.
While much is assumed with respect to the principal characteristics of employers of the low paid no serious attempt has been made (to date) to provide objective data on the matter. This paucity of evidence mostly reflects a lack of accessible plant-level data a situation common to both Australia and other countries.
This paper seeks to address this lack. While the flurry of research activity that accompanied the introduction of the national minimum wage in the United Kingdom in 1998 did examine the employment implications for low-wage workers generally (Stewart 2001; Dickens and Manning 2002) and within particular industries (Machin and Wilson 2001), very limited attention was paid to employers. The one exception to this was a study by Forth and Millward (2001) who--using data from the 1998 Workplace Employee Relations Survey--found that, on average, employers of the low paid had higher densities of part-time staff, were smaller, were domestically owned, operated in uncompetitive markets, and were non-unionised.
In this paper, we provide a descriptive analysis of low-pay employers. Section 2 describes the data and methods used, together with our definitions of low wages and of the employers of the low paid. Section 3 presents data on the average densities of low-wage employees within workplaces by industry, firm size and region. Section 4 reports the number of employers of the low paid, as defined by us, and presents their distribution by industry, firm size and State. A probit model of the probability of being an employer of the low paid is estimated using both firm and industry-level data. The results from this regression are given in Section 5. Finally, Section 6 provides a summary and conclusions.
2. Data and Methods
Data for this study are derived from the 2004 Survey of Employee Earnings and Hours (SEEH)which is carried out on a biennial basis by the Australian Bureau of Statistics (ABS). The SE E H collects information on approximately nine thousand non-agricultural businesses and, after weighting, the data reflect the structure of employment within the Australian economy. Both part-time and full-time employees are included, but information on owner/managers and junior employees is excluded from this study The nine thousand management units in the sample have been weighted to reflect the full Australian population of 837,078 non-agricultural employing management units (employers). (1)
Three low-wage thresholds are considered: $12, $15 and $17 per hour. The lowest represents the minimum wage in May 2004 (Fair Work Australia 2011) and is the main threshold we use; we also included two alternative wages, in selected cases, as a sensitivity analysis. For this study, an enterprise is defined as being an 'employer of the low paid' if more than 50 per cent of its employees are paid at or below the designated low-wage threshold.
Wages for permanent employees relate exclusively to ordinary-time earnings and for casual employees they relate to hourly wages multiplied by 0.8 to account for the absence of sick leave and holiday pay. (2) For comparative purposes, however, we also present the unadjusted casual wage rates in some instances.
Since the SEEH dataset is drawn from a sample of management units, and within these units from a sample of employees, our estimates are subject to sampling error. (3) These errors are not easy to detect, but future work could present confidence intervals based on bootstrapped standard errors.
3. Percentage of Low-wage Employees per Employer (low-wage density)
In this section, we report the proportions of low-wage employees per employer averaged across all employers for Australia as a whole and by industry, employer size and State. (4) We call this a low-wage density. It is important to stress that this is not the average percentage of low-wage employees. That is, it is a simple average of low-wage percentages in each management unit. It is not weighted by employer size. Since about 99 per cent of all employers are small or medium-sized enterprises (SME) employing between one and 199 persons, these densities predominantly reflect the SME situation. The overall incidence of low-wage employment within Australia is given in McGuinness, Freebairn and Mavromaras (2007).
Table 1 gives the average low-wage densities across employers for each low-wage threshold before and after adjustments have been made for the casual loading. Dealing first with the unadjusted figures, we see that the average low-wage density at $12 per hour was 6.7 per cent. This density rises to 30.2 per cent for the $15 threshold and to 50.9 per cent for the $17 threshold. The relatively steep increase in average density between the $15 and $17 thresholds suggests that the distribution of pay within firms is concentrated within a range of between 25 and 45 per cent above the federal minimum wage.
After adjusting wages to remove the estimated loading for casual employees (row 2 of Table 1) the average density figures increase dramatically for the $12 threshold: from 6.7 per cent to 13.6 per cent. If the appropriate casual loading is 15 per cent--and not the conventionally assumed 25 per cent-13.6 per cent will be an overstatement of the average low-wage density; however, if the appropriate casual loading is 50 per cent, we will understate the true low-wage density.
Figure 1 presents estimates of the $12 low-wage density levels across all employers after adjustment is made on casual wages to remove the estimated casual loading. Kernel density charts are similar to histograms, in that they show the distribution of employing firms with different proportions of low-wage employees. They a re especially useful for illustrating continuous variables such as low-wage densities. Since they involve a n artificial smoothing process, however, they should not be read literally but, rather, be interpreted as showing the relative preponderance of different x-axis variables.
That said, according to Figure I the vast majority of firms pay all or most workers more than $12 per hour, with a further small proportion of firms employing most or all of their employees at or below $12 per hour. Thus, it would seem that employers are more likely to engage either almost all or almost none of their workers below a particular wage level than to engage them more evenly across a range of scales; however, this pattern varies considerably when the data are disaggregated by industry. The same pattern is also observed when Figure I is produced for the unadjusted hourly wage distribution. (5)
[FIGURE 1 OMITTED]
The distribution of low-wage densities across employers is also illustrated by Lorenz curves. Lorenz curves show the cumulative frequency of firms ranked according to their low-wage density. Taken as a whole, these curves illustrate how evenly (or unevenly) low-wage employment is distributed across employers. If all employers had the same low-wage density, the Lorenz curve would be a 45-degree '/'-shaped line. This 45-degree line is called the line of equality. If one employer accounted for all of the low-wage employees, then the Lorenz curve would be '[??]'-shaped.
Figure 2 gives the Lorenz curve for low-wage densities at the $12 per hour low-wage threshold. It indicates that approximately 80 per cent of employers do not employ any workers below this rate. Twenty per cent of employers account for all employers of the low paid. The slope of the Lorenz curve is quite steep and indicates that just 10 per cent of firms account for over half of the entire low-wage distribution. Most of these enterprises are likely to be almost entirely low-wage, although it is not possible to derive an exact proportion from the graph. This high level of equality at the $12 threshold is confirmed by the Gini coefficients. Gini coefficients measure the area between the Lorenz curve and the 45-degree line of equality. (6) The greater is this area, the more unequal is the distribution. The Gini coefficient at the $12 cut-off point was 0.908 indicating that the distribution of low-wage densities is highly polarised at this wage rate (as we would expect).
[FIGURE 2 OMITTED]
Table 2 presents average low-wage densities (adjusted for 25 per cent casual loadings) by industry. Industries with the highest average low-wage densities were Communications; Accommodation, cafes and restaurants; Personal and other services; Retail trade; and Manufacturing. Enterprises in Mining, Government administration and defence; Electricity, gas and water supply; and Wholesale trade had the lowest densities. As expected, average density levels are much lower in the public sector. As the low-wage cut-off increased, not surprisingly, the low-wage densities increased substantially.
One minor exception to this is Construction. While Construction had a relatively high low-wage density at the $12 threshold, it was less than the average at the $17 threshold thus suggesting a more polarised wage dispersion than the national average.
The Gini coefficients (Appendix Table A1)--which indicate the degree of concentration of low-wage employees among employers--indicate that industries with low densities of low-wage employers, such as Finance and insurance, Electricity, gas and water supply and Mining, have the most uneven distributions. So while there are few low-wage employees in these industries, those that do exist tend to be concentrated among a small percentage of employers.
Table 3 details the average low-wage densities according to the employment size of employers. The average low-wage density is highest within the smallest size band. It is also relatively high for firms in the 50-99 employment category. As the low-wage threshold moves from $12 to $15 and $17 an hour we observe that, as expected, the wages within firms, on average, become more dispersed as employment size increases. Again, however, the 50-99 grouping appears to be the exception with wage levels being less dispersed relative to the 20-49 grouping. Potential factors explaining this apparent anomaly are discussed more fully in Section 4 of the paper.
Finally, average firm-level low-wage densities by State are given in Table 4. There are substantial variations in the data, with firms in the Australian Capital Territory and the Northern Territory having, on average, much lower rates of low-wage employment. Conversely, relative to the national average, firms in Queensland tend to employ relatively larger proportions of workers at below $12 per hour. These regional variations persist as the wage threshold points are raised; for instance, on average, approximately 30 per cent of employees in Queensland, South Australian and Tasmanian firms earn more than $17 per hour, and the comparable figure for the remaining states is over 40 per cent.
While New South Wales and Victoria are very close to the national proportions, Queensland and Tasmania appear to have somewhat larger proportions of firms engaging up to 50 per cent of their workforce at below $12 per hour. Somewhat less variation could be traced by examining the Lorenz curve; but firms in Queensland and Tasmania appeared more likely to pay at least some of their employees less than $12 per hour (see the State-level Gini coefficients in Appendix Table A2).
4. The Distribution of Employers of the low Paid
The previous section examined the average low-wage density across employers. In this section, we examine the issue from a slightly different perspective. We define those employers who pay more than half of their employees at or below the low-wage threshold as 'employers of the low paid' and we examine their distribution in the economy. In addition to this, we check the sensitivity of the analysis to the casual loading by making explicit comparisons between distributions with and without the loading adjustment discussed in Section 3.
Table 5 shows that the percentage of firms categorised as employers of the low paid rises from 5.2 to 11.4 per cent after removing our estimated 25 per cent casual loading. 7 To put this in context, the ABS estimated that in 2004 there were 837,078 employing enterprises in Australia and, of these, more than 95 thousand paid the majority of their staff less than $12 per hour after the casual loading was taken into account.
Table 5 also shows the percentages of employers within each industry that have been identified as employers of the low paid for both the unadjusted and adjusted wage distributions. We deal first with the unadjusted industry shares which, as well as being consistent with the previous section, also correspond with the findings of the McGuinness, Freebairn and Mavromaras (2007) study of employee-level data using the 2004 wave of the Household, Income and Labour Dynamics in Australia (HILDA) database. The highest concentrations of employers of the low paid were found in the Personal and other services; Construction; Accommodation, cafes and restaurants; and the Retail trade industries, each of which was identified as low waged in the context of either the full-time or part-time employee distributions, or both (McGuinness, Freebairn and Mavromaras 2007). Consistent with the employee study, few employers in the Mining or Electricity, gas and water industries, or in the public sector, were low waged.
Of course, the impact of the adjustment for the casual loading is most pronounced in industries with a high concentration of casual workers. For instance after this adjustment, the percentage of employers paying the majority of their workforce less than $12 per hour increased by almost 1000 per cent in Cultural and recreational services, approximately tripled in Accommodation, cafes and restaurant; Manufacturing; Personal and other services; and Transport and storage; it more than doubled in Retailing; and in Health and community services.
The large increases in the Education and Communication services industries are slightly less intuitive, but are likely to relate to certain categories of staff, for example, certain types of call-centre staff in the Communication services industry. Table 5 also confirms the low usage of casual contracts within the public sector and in Construction; Mining; Electricity, gas and water; and Finance and insurance. (8)
By applying the rates in Table 5 to the estimated population of employers in 2004 by industry--which is given in Appendix Table A3 and is taken from ABS published data (9)--we ca n estimate the distribution of employers of the low paid by industry. Estimates could not be provided either for the Agriculture, forestry and fishing or for the Government, administration and defence industries. As a consequence, the total number of low-paying businesses presented in Table 6, based on both the unadjusted and adjusted wage distributions, will be underestimated by factors of approximately 7 thousand and 14 thousand enterprises respectively.
With respect to the unadjusted distribution, the Construction and Retail trade industries account for more than half of all employers of the low paid, with the Personal and other services; Accommodation, cafes and restaurants; and Manufacturing industries each accounting for approximately 9 percent of the total respectively. Again, the pattern changes somewhat within the adjusted distribution, with the Construction industry becoming much less dominant. Nevertheless, the Retail trade; Construction; Property and business services; Accommodation, cafes and restaurants; and Manufacturing industries collectively accounted for 75 per cent of all employers of the low paid in 2004. The majority of all employers of the low paid are in the service industries. Thus, to conclude, with the exception of Construction, service-sector employers with a heavy reliance on casual labour are likely to be the most heavily affected by the introduction of a universal federal minimum wage.
The concentration of employers of the low paid within various business-size bands is given in Table 7.
Two points become immediately obvious. First, the pattern is again nonlinear in that the predominant concentration of employers of the low paid does not decline consistently with employer size. Consistent with Section 3, employers in the 1-19 and 50-99 employee-size bands are most likely to be employers of the low paid. These observations are not wholly surprising, as the recent employee study by McGuinness, Freebairn and Mavromaras (2007) found that while the incidence of below minimum wage employment declined linearly with firm size among full-time employees, it was nonlinear for part-time workers with the employee data following a similar pattern to that in Table 7.Thus, it is likely that the inclusion of part-time employees in the density calculations is largely responsible for the slight nonlinearity in the data.
Second, the adjustment for the casual loading has the greatest impact within the 1-19 and 20-49 employee-size bands. We cannot quantify the number of employers of the low paid within each size band, as the ABS does not publish data disaggregating the 2004 population of employing businesses by the size categories shown in Table 7. In fact, a breakdown is available only for the 1-19, 20-199, and 200+ employee groupings, which do not correspond well with the rest of our data.
Nevertheless, from the published information we know that 753,370 (90 per cent of the 837,078) employers were in the 1-19 employee grouping, which (following the 12.3 percentage share of employers in Table 7) equates to 92,664 employers of the low paid within the 1-19 employee category and, by simple subtraction, 2762 among firms employing 20 or more. 10 Clearly, a more detailed breakdown of the 1-19 category is desirable; but until more disaggregated data by firm size become available we can only guess at the likely nature of the distribution of low-wage employment within these small firms.
The percentage of employers of the low paid within states is given in Table 8. Within the unadjusted data, much more regional variation is apparent relative to that observed in the previous section. Victoria, at 6.7 per cent, has a much higher concentration of employers of the low paid relative to the other large states of New South Wales and Queensland. The degree of concentration is well below the national average in the Australian Capital Territory, the Northern Territory, Tasmania, and Western Australia, with South Australia being the only one of the five smaller geographic regions to have an above average concentration.
Very substantial changes occur in the proportions when the data are adjusted for the casual loading. The proportion of employers of the low paid converges substantially across the three largest states, and the shares in Tasmania and Western Australia increase substantially. Table 8 indicates substantial variations in the usage of low-wage casual labour across states. A potential explanation for the observed changes lies in differences in the sectoral composition of employment. For instance, both Queensland and Tasmania have higher proportions of Retail trade and Accommodation, cafes and restaurants than Victoria does. The extent to which this hypothesis holds can be tested more fully under the multivariate framework on the grounds that, if sectoral influences fully explain state-level regional variations, we would expect all state effects to disappear in the presence of industry controls. Table 9 a pp lies the rates to the population data given in Appendix Table A4. It is apparent that the removal of the casual loading results in substantial changes in the relative importance of both Victoria and Queensland with respect to the overall distribution of employers of the low paid within Australia.
5. Multivariate Analyses
To determine the likelihood that a firm will be an employer of the low paid we regressed the probability of being an employer of the low paid on a set of employer and industry characteristics using a probit model. For the dependant variable, firms were assigned the value 1 if they were an employer of the low paid (that is, employers who employ over 50 per cent of their workers at a wage rate on or below $12 per hour) and zero otherwise. The model was estimated using the SEEH ABS firm-level dataset, merged with a file containing the 2004 industry-performance information at the 2-digit level of the Australian and New Zealand Standard Industrial Classification (ANZSIC).The probit model was, therefore, estimated on a dataset containing basic information on the firm with merged information of performance-level indicators for the firms at the 2-digit industry level, and combined with State dummies. At the level of the employer, the model includes information on total employment (in log form since we believe that there is a diminishing effect of employer size) and the casual share of total employment. To each record we appended a number of 2-digit industry indicators such as the size of the industry (gross value added), industry wage share (total labour costs as a proportion of total income) and the percentage of firms within the industry that recorded a loss of profit in 2004.
In keeping with the previous analyses, the model was estimated on both the unadjusted and adjusted wage data and the results are given in Table 10. Turning first to the model estimated prior to the adjustment for the casual loading, we confirm that the likelihood of being an employer of the low paid is inversely related to employer size (as measured by number of employees). Contrary to our bivariate results, however, the model suggests that, ceteris paribus, employers of the low paid tend to have lower concentrations of casual employees. In relation to the industry-level variables, the model indicates that employers of the low paid were less likely to be in sectors that had a high wage share; but employers of the low paid were more likely to be in industries that were highly competitive with relatively tight margins, as approximated by the industry rate of profit loss. Finally, the probability of being an employer of the low paid was inversely related to industry size, indicating that such employers tend to be located in smaller industries. There was little evidence of any significant geographic differences in this model.
The results change significantly when the model is re-estimated on the data with the estimated 25 per cent loading removed from the wage rates of casual workers. As before, employers of the low paid were more likely to be small and located in industries with higher proportions of businesses reporting a loss of profit.
The casual employment variable is now hugely significant, with the opposite sign, indicating that employers of the low paid tend to employ a higher proportion of casual labour. Taken together the results from both models suggest that firms employing high proportions of casual workers tend to engage such employees at wage rates that are at or near the federal minimum wage, after adjustment for the estimated loading. Following adjustment for the loading, the regional effects become more pronounced with the majority of States having a higher concentration of employers of the low paid relative to the Australian Capital Territory, which remains statistically inseparable from the Northern Territory.
If we do not adjust for casual loadings, we find that approximately 5 per cent of employers paid more than half of their workforce less than $12 an hour. But when we adjusted downwards the hourly wage rate of casual staff for an estimated 25 per cent casual loading, the average low-wage density of firms increased to about 11 per cent. This translates to a total population of more than 95 thousand enterprises.
The data indicate that the use of casual labour was a significant correlate of the phenomenon of low pay. This is confirmed when the data are disaggregated by industry. Those industries tending to rely most on casual labour become much more dominant in the distribution of employers of the low paid after the 25 per cent loading is removed. With the exception of Construction, and to a much lesser extent Manufacturing, it was found that service-sector-based employers in industries such as Retail trade; Accommodation, cafes and restaurants; and Property and business services--all with a heavy reliance on casual labour--are likely to be the most heavily affected by the introduction of a universal federal minimum wage. In fact, the majority of all employers of the low paid were found to be in the service industries.
Finally, multivariate regression analyses confirmed that the employers of the low paid were more likely to be small firms employing a disproportionate share of casual labour. The analyses also find that employers of the low paid were more likely to be located in industries with a smaller proportion of labour costs in their turnover (possibly because of high material costs) and where there were relatively high rates of businesses recording a loss of profit. In addition, substantial regional differences remain in the presence of industry controls, indicating that State-level differences in the incidence of low-paying employers ca n not be fully accounted for by the other factors.
Table A1: Gini Coefficients-$12 Low-wage Rate, Adjusted for Casual Loading, by Industry Industry Gini coefficients Agriculture, forestry and fishing -- Mining 0.971 Manufacturing 0.920 Electricity, gas and water supply 0.971 Construction 0.921 Wholesale trade 0.950 Retail trade 0.855 Accommodation, cafes and restaurants 0.843 Transport and storage 0.936 Communication services 0.896 Finance and insurance 0.982 Property and business services 0.921 Government and defence 0.951 Education 0.916 Health and community services 0.843 Cultural and recreational services 0.874 Personal and other services 0.866 Private sector 0.904 Public sector 0.928 Total 0.908 Table A2: Gini Coefficients-$12 Low-wage Rate, Adjusted for Casual Loading by State State Gini coefficients New South Wales 0.932 Victoria 0.911 Queensland 0.888 South Australia 0.916 Western Australia 0.891 Tasmania 0.881 Northern Territory 0.906 Australian Capital Territory 0.894 Australia 0.908 Table A3: Percentage Distribution of Employing Businesses in Australia by Industry, 2004 Industry Number Percent Agriculture, forestry and fishing 74111 8.9 Mining 2731 0.3 Manufacturing 61888 7.4 Electricity, gas and water supply 599 0.1 Construction 113426 13.6 Wholesale trade 46800 5.6 Retail trade 126160 15.1 Accommodation, cafes and restaurants 39342 4.7 Transport and storage 37374 4.5 Communication services 8089 1.0 Finance and insurance 51708 6.2 Property and business services 171182 20.4 Education 6880 0.8 Health and community services 49008 5.9 Cultural and recreational services 17300 2.1 Personal and other services 30480 3.6 Total 837078 100.0 State Number Per cent New South Wales 298084 35.6 Victoria 214775 25.7 Queensland 157628 18.8 South Australia 55380 6.6 Western Australia 79169 9.5 Tasmania 15690 1.9 Northern Territories 5464 0.7 Australian Capital Territory 10888 1.3 Total 837078 100.0 Table A4: Percentage Distribution of Employing Businesses in Australia by State, 2004 State Number Percent New South Wales 298084 35.6 Victoria 214775 25.7 Queensland 157628 18.8 South Australia 55380 6.6 Western Australia 79169 9.5 Tasmania 15690 1.9 Northern Territories 5464 0.7 Australian Capital Territory 10888 1.3 Total 837078 100.0
Australian Bureau of Statistics (ABS) (2004), Survey of Employee Earnings and Hours, Canberra, unpublished data.
Dickens, R. and Manning, A. (2002), 'Has the Impact of the Minimum Wage Reduced Inequality?', Centre for Economic Performance, London School of Economics.
Fair Work Australia (2011), 'Wage Case Outcomes since 1906 (updated to include the June 2011 decision of the FWA Minimum Wage Panel)', mimeo, Fair Work Australia, Melbourne.
Forth, J. and Millward, N. (2001), 'The Low-paid Worker and the Low-paying Employer: Characteristics using WERS98', NIESR Discussion Paper No. 179.
McGuinness, S., Freebairn, J. and Mavromaras, K. (2007), 'Characteristics of Minimum Wage Employees', report prepared for the Australian Fair Pay Commission, pp. 1-44.
Stewart, M. B. (2004), 'The Impact of the Introduction of the Minimum Wage on the Employment Probabilities of Low-wage Workers', Journal of the European Economic Association, vol. 2, 67-97.
(1) An employing unit is defined as an establishment with at least one employee.
(2) This assumes that the value of sick leave and holiday pay is 25 per cent, which is in line with the majority of non-casual employment contracts.
(3) The SEEH data set is sampled on Management Unit (MU).This is close to, but not the same as, workplace. This design does not sample all MUs within the same employer parent, so that we cannot aggregate beyond the MU level. After an MU is chosen, the ABS selects 1 in 2 employees in MUs under 10 employees, 1 in 6 for MUs 11-50 employees, 1 in 8 for 51-200 employees, 1 in 10 for 201-1000 employees, and 1 in 20 for 1001-3000 employees.
(4) Excluding Agriculture, forestry and fishing.
(5) The adjusted and unadjusted charts are not directly comparable as the width around each observation will be different across the two distributions. These widths are set to their optimal level by our statistical program, Stata.
(6) It was not possible to apply weights when calculating the Gini coefficient and, as a consequence, the statistic is likely to be biased towards larger firms, given that these are generally over-sampled by the ABS.
(7) Since our data set is an average of all employers, not weighted by employees, these figures will differ from data based on employees. Since our data set gives equal weight to micro businesses and large businesses, our averages will predominately reflect the SME situation.
(8) Contract and piece rate workers are not classified as employees.
(9) ABS, cat. no. 8161.0.55.001
(10) There being 837,078 x 0.114 = 95,427 employers of the low paid in total.
Seamus McGuinness *
Economic and Social Research Institute Dublin, and Trinity College, Dublin
The University of Melbourne
* We thank John Freebairn, Ben Ryland and Miranda Pointon for comments, Rick Leach, Fiona Johnson and Gordon Wragg from the ABS for assistance with accessing the data, and the Australian Fair Pay Commission for financial support.
Table 1: Percentage of Low-wage Employees per Employer (low-wage density), Simple Average over Employers Low-wage Threshold $12 $15 $17 Not adjusted for casual loading 6.7 30.2 50.9 Adjusted for casual loading 13.6 42.3 60.5 Source: ABS (2004) Note: Averages are not weighted by employer size. Table 2: Percentage of Low-wage employees per Employer (low-wage density), Simple Average over Employers by Industry (adjusted for casual loading) Industry Low-wage tow-wage Low-wage Threshold Threshold Threshold $12 $15 $17 Agriculture, forestry and fishing -- -- -- Mining 2.0 14.8 20.9 Manufacturing 17.0 40.5 55.2 Electricity, gas and water supply 4.0 16.5 29.7 Construction 16.1 28.2 50.6 Wholesale trade 3.2 39.6 56.0 Retail trade 17.0 61.1 79.0 Accommodation, cafes and 27.1 73.1 86.8 restaurants Transport and storage 15.6 43.2 57.7 Communication services 27.8 71.1 78.2 Finance and insurance 4.1 30.2 47.2 Property and business services 6.5 30.7 47.4 Government and defence 3.3 20.9 32.3 Education 9.0 36.0 44.5 Health and community services 8.9 33.9 54.1 Cultural and recreational 16.3 42.3 67.6 services Personal and other services 18.7 55.1 68.9 Private sector 13.8 43.4 60.7 Public sector 3.4 37.4 46.4 Total 13.6 43.3 60.5 Source: ABS (2004) Note: Averages are not weighted by employer size. Table 3: Percentage of Low-wage Employees per Employer (low-wage density), Simple Average over Employers by Employer Size (adjusted for casual loading) Employer Size Low-wage Low-wage Low-wage (number of employees) threshold threshold threshold $12 $15 $17 <20 14.5 44.6 61.7 20-49 6.5 33.1 50.6 50-99 7.3 35.2 53.8 100-499 4.7 25.7 42.1 500-999 3.4 17.8 30.7 1000+ 2.3 12.8 23.3 All firms 13.6 42.3 60.5 Source: ABS (2004) Note: Averages are not weighted by employer size. Table 4: Percentage of Low-wage Employees per Employer (low-wage density), Simple Average over Employers by State (adjusted for casual loadings) State Low-wage Low-wage Low-wage threshold threshold threshold $12 $15 $17 New South Wales 12.6 38.3 56.9 Victoria 13.2 40.5 57.2 Queensland 17.8 51.7 67.8 South Australia 12.9 50.9 69.6 Western Australia 11.1 42.3 56.9 Tasmania 14.7 50.3 74.2 Northern Territory 10.3 39.3 54.2 Australian Capital Territory 6.6 42.2 55.4 Total 13.6 42.3 60.5 Source: ABS (2004) Note: Averages are not weighted by employer size. Table 5: Percentage of Employers of the Low Paid by Industry Industry Not adjusted Adjusted for casual for casual loadings loadings Agriculture, forestry and fishing -- -- Mining 0.0 1.4 Manufacturing 5.7 15.7 Electricity, gas and water supply 2.8 3.3 Construction 10.1 15.1 Wholesale trade 2.0 2.0 Retail trade 6.5 14.0 Accommodation, cafes and 8.0 21.8 restaurants Transport and storage 4.7 15.0 Communication services 0.2 20.8 Finance and insurance 2.1 2.1 Property and business services 0.9 4.2 Government and defence 1.5 2.0 Education 3.2 9.0 Health and community services 2.4 5.7 Cultural and recreational services 1.5 14.9 Personal and other services 10.2 16.0 Public sector 5.2 11.5 Private sector 0.9 1.3 Total 5.2 11.4 Source: ABS (2004) Note: An employer of the low paid is defined as one paying 50 per cent or more of its employees a wage of $12 per hour or less. Table 6: Distribution of Employers of the Low Paid by Industry Industry Not adjusted for casual loadings Number Percentage distribution Agriculture, forestry and -- -- fishing Mining 0 0.0 Manufacturing 3528 9.7 Electricity, gas and water 17 0.0 supply Construction 11456 31.4 Wholesale trade 936 2.6 Retail trade 8200 22.5 Accommodation, cafes and 3147 8.6 restaurants Transport and storage 1757 4.8 Communication services 16 0.0 Finance and insurance 1086 3.0 Property and business 1541 4.2 services Education 220 0.6 Health and community 1176 3.2 services Cultural and recreational 260 0.7 services Personal and other services 3109 8.5 Total 36448 100.0 Industry Adjusted for casual loadings Number Percentage distribution Agriculture, forestry and -- -- fishing Mining 38 0.0 Manufacturing 9716 12.1 Electricity, gas and water 20 0.0 supply Construction 17127 21.3 Wholesale trade 936 12 Retail trade 17662 21.9 Accommodation, cafes and 8577 10.7 restaurants Transport and storage 5606 7.0 Communication services 1683 2.1 Finance and insurance 1086 1.3 Property and business 7190 8.9 services Education 619 0.8 Health and community 2793 3.5 services Cultural and recreational 2578 3.2 services Personal and other services 4877 6.1 Total 80508 100.0 Source: ABS (2004) Note: An employer of the low paid is defined as one paying 50 per cent or more of its employees a wage of $12 per hour or less. Table 7: Percentage of Employers of the Low Paid by Employer Size Employer Size Not adjusted for Adjusted for (number of employees) casual loadings casual loadings 0-19 5.6 12.3 20-49 0.7 3.0 50-99 2.7 3.8 100-499 1.1 2.0 500-999 1.3 1.5 1000+ 0.2 0.6 All firms 5.2 11.4 Source: ABS (2004) Note: An employer of the low paid is defined as one paying 50 per cent or more of its employees a wage of $12 per hour or less. Table 8: Percentage of Employers of the Low Paid by State State Not adjusted for Adjusted for casual loadings casual loadings New South Wales 5.5 11.0 Victoria 6.7 11.1 Queensland 4.7 14.4 South Australia 6.6 11.3 Western Australia 1.3 8.7 Tasmania 4.6 11.0 Northern Territory 4.6 8.2 Australian Capital Territory 0.1 3.1 Australia 5.2 11.4 Note: An employer of the low paid is defined as one paying 50 per cent or more of its employees a wage of $12 per hour or less. Source: ABS (2004) Table 9: Percentage Distribution of Employers of the Low Paid (a) by State State Not adjusted for casual loadings Number Percentage distribution NUW South Wales 16395 37.4 Victoria 14390 32.8 Queensland 7409 16.9 South Australia 3655 8.3 Western Australia 1029 2.3 Tasmania 722 1.6 Northern Territory 251 0.6 Australian Capital Territory 11 0.0 Australia 43861 100.0 State Adjusted for casual loadings Number Percentage distribution NUW South Wales 32789 34.5 Victoria 23840 25.1 Queensland 22698 23.9 South Australia 6258 6.6 Western Australia 6888 7.3 Tasmania 1726 1.8 Northern Territory 448 0.5 Australian Capital Territory 338 0.4 Australia 94985 100.0 Source: ABS (2004) Note: An employer of the low paid is defined as one paying 50 per cent or more of its employees a wage of $12 per hour or less. Table 10: Low-wage Employer Probit Model Unadjusted Adjusted Employer characteristics Employment level -0.552 (0.057) *** -0.481 (0.042) *** (logged) Percentage of employment -0.389 (0.076) *** 0.905 (0.053) *** casual 2-digit Industry-level characteristics Gross value added -0.306 (0.059) *** -0.090 (0.043) ** (logged) Wage share in turnover -0.696 (0.335) ** -0.643 (0.247) *** Percentage of business 0.012 (0.004) * 0.006 (0.003) * recording a loss State dummies (reference ACT) New South Wales 1.407 (0.929) 0.778 (0.286) *** Victoria 1.527 (0.929) * 0.921 (0.286) *** Queensland 1.447 (0.929) 0.842 (0.286) *** South Australia 1.612 (0.934) * 0.658 (0.298) ** Western Australia 0.505 (0.989) 0.653 (0.262) ** Tasmania 1.424 (0.949) 0.628 (0.295) *** Northern Territory 1.448 (0.977) 0.693 (0.388) Constant -1.185 (0.968) -1.653 (0.359) N 5374 5374 Pseudo R2 0.112 0.431 LR chit (13) 239.53 *** 545.25 *** Note: An employer of the low paid is defined as one paying 50 per cent or more of its employees a wage of $12 per hour or less; standard errors in brackets.