The White Picket Fence: Efficiency of States Spending

Sunday, December 02, 1990

Efficiency of States Spending

Background papers on the public sector:
Studies prepared for the Office of the Economic Planning Advisory Council.

FOREWORD

In examining the size and efficiency of the Australian public sector (see the recently published EPAC Council Paper No.44), the Office of EPAC commissioned Richard Wood to examine different aspects of this topic.

The following paper by Mr Wood looks at differences between the States in expenditures on a range of specified State government services. The first part of the paper examines available indicators of service cost and output in two major areas of State general government activity, namely public education and health services. The study focusses on differences between the States in expenditures per person, although some attention is also given to indicators of the quality and quantity of services delivered. The second part of the paper looks at differences between the States in operating deficits of State government business enterprises (GBEs).

The paper examines data on the profitability of government business enterprises. As well as making use of national accounts data, the paper compiles and summarises financial information from the annual reports of a total of 41 major Commonwealth and State GBEs. The paper notes the significant difference between the financial performance of Commonwealth and State GBEs, and differences between the financial performance of different groups of State GBEs.

The Office is releasing these papers with the proviso that views expressed are those of the author, and should not be attributed to EPAC or the Office of EPAC. In this regard, it should be noted that many members of Council do not share elements of judgement involved in the paper prepared by Mr Wood.

Ross Clare
Acting Director

December 1990

EXECUTIVE SUMMARY

It ought to be axiomatic that government expenditure should be undertaken in the most efficient manner. The real challenge is to assess the achievement of this objective.

This paper identifies differences in expenditure levels amongst the States which arise from policy decisions, including the decision to deliver services at above average cost. Concentrating on the three largest expenditure categories in terms of share of total recurrent expenditure of the States, i.e. public schools, public health institutions and public transport, the paper assesses the extent to which the policy induced differences arise from differences in cost efficiency.

The paper's starting point is data and analysis on State recurrent expenditure levels compiled by the Commonwealth Grants Commission in its Report On General Revenue Grant Relativities 1990 Update. The policy differences identified by the Commission measure the provision of above or below average levels or quality of service, and differences in the efficiency of service delivery.

The Commission's data shows that the policy induced expenditure differences are significant and exhibit common trends. Victoria had the highest expenditure levels after adjusting for cost and need disabilities, with total expenditure exceeding the standardised or adjusted level by 10 percent and education, health and business undertaking deficits exceeding their standardised levels by respectively 16, 12 and 21 percent. Queensland had generally the lowest level of expenditure after adjusting for needs and cost disabilities, with total expenditure falling below the standardised by 23 percent and education and health expenditures falling below their standardised levels by 19 and 28 percent respectively. The other States showed a more convergent overall pattern with substantial variation amongst individual expenditure categories.

Further examination suggested, not surprisingly, that the policy induced expenditure differences arose largely from variation in cost efficiency. Since the standards used to calculate these policy differences were restricted to a comparison of the relative performance of Australian States, they were biased downward as adjudged by comparable overseas and private sector performance. As such the estimated policy differences, large as they are, under-state the inefficiency of State public services. This supports the view that nearly all the $6 billion which could be saved by all States and Territories adopting Queensland's standardised per capita expenditure levels (a figure which represented 17 percent of total recurrent expenditure) could be achieved by efficiency improvements rather than cuts to quality or level of services.

The primary source of inefficiency was labour or human resources policies including staffing levels, staff mix, wage rates and labour productivity. It should not be surprising that such matters account for the greatest source of inefficiency, for wages and on-costs account for 60-70 percent of total recurrent expenditures. What was surprising was the magnitude and the pervasiveness of such inefficiency.

For example. Victoria's high levels of policy induced expenditure on education were largely a result of higher teacher/student ratios (averaging 13 percent above the seven State average) and higher primary school teacher salaries and salaries for other school-based staff. These factors did not translate into a higher quality of educational output. The recent sharp cuts to education staffing levels in Victoria and Tasmania (the second highest spending State on education) confirm this finding.

The examination of Health expenditure yielded a similar finding. Queensland's low level of expenditure on health was largely a result of low non-technical staffing levels as well as more flexible and productive staff policies. In terms of medical services and access to and availability of public hospital facilities, Queensland was found to provide a relatively high level and quality of service. Inefficiencies in the public transport categories were also found to be huge and to arise primarily from staffing decisions. One consequence is that the $1.1 billion consumed by the States in 1988/89 in subsidising the provision of non-metropolitan rail freight transport services was found to be a total misallocation of funds.

The inescapable conclusion is that, at least for "essential services", high levels of policy induced differences in State expenditure arise primarily to provide additional benefits to special interest groups, specifically their unionised work force, rather than in providing additional services to consumers.

1. INTRODUCTION

This paper examines differences in the level of recurrent government spending among the States and attempts to assess the extent to which such differences are due to either the quality of various services or the efficiency with which they are provided. The basic data source is the comparisons of recurrent spending of the six States and the Northern Territory by the Commonwealth Grants Commission (CGC) for purposes of framing its recommendations to the Commonwealth Government on the distribution of general purpose revenue assistance as between the States. (1) Such comparisons covered about 86 percent of recurrent spending of the State general government sector of the States and N.T. in 1988-89, as estimated by the Australian Bureau of Statistics. (2)

The comparisons by the CGC are made with a view to assessing what level of spending would be "needed" by each State in order to provide government services at standards not appreciably different from the standards provided by the other States, while imposing taxes and charges at levels which are not appreciably different from those imposed by other States.

It is not necessary for purposes of this paper to examine all the various aspects of the approach adopted by the CGC in making its assessments. The basic objective of the Commission is to assess the differences between States in per capita revenue assistance that are needed in order to allow (3) each State to provide services of approximately the average level of the States without suffering a financial disadvantage in the sense of having to impose higher taxes and charges on its residents. Thus, if the CGC assesses that it costs more per head to provide a service in State A at the average level, then State A will be assessed as needing higher per capita revenue assistance on that account. For example, it will clearly cost more per head of population for less populous States to operate State Parliaments: the more populous States can "spread the overheads".

By assessing such relative cost differences or disabilities the Commission thus arrives at a "standardised" amount of per capita expenditure for 10 major categories of expenditure for each State. Comparisons between the standardised and actual expenditures per head on any particular service will then provide an indication of whether a State is operating above or below the average level. (It should be noted that, for present purposes, comparisons have not been included for expenditure on debt charges and natural disasters, on the ground that these are largely "unavoidable").

However, a State that is spending more per head than its standardised amount is not necessarily providing a better than average quality service. The above-standard expenditure may simply reflect inefficiency in service delivery. Equally, lower expenditure per head than the standardised amount does not necessarily mean that a lower than average quality service is being provided.

The difficulty is to determine how much of the differences between standardised and actual levels of per capita expenditure -- what the CGC describes as "policy" differences -- is due to differences in quality of services and how much to differences in efficiency. In the end, matters of judgment are necessarily involved.

Even so, it is argued that, through the examination of various sub-categories of expenditure and of various factors contributing to differences between standardised and actual levels of per capita expenditure, it is possible to make broad judgments on this issue. In some cases, comparisons with costs of providing the same or similar services in the private sector may also provide a guide on relative efficiency levels, as may assessments of the demand for comparable services provided in the private sector, particularly where higher prices charged in the private sector ought to encourage the usage of the government services. It may also be possible to draw some conclusions on efficiency levels from international comparisons.

In the case of some business undertakings' deficits, the methodology adopted by the CGC and its consultants allows differences in efficiency to be identified separately. (4) However, a contentious issue in comparing business undertakings is whether all the services provided by them constitute a "public good". If not, it can be argued that their inclusion in the Grants Commission process could result in technical and allocative inefficiencies. This is discussed further in the section on business undertakings.

Several contentious issues also arise in making broad judgments about the reasons for differences between actual and standardised levels of expenditure other than deficits on business undertakings.

First, it is clear that the major factor contributing to differences between standardised and actual per capita expenditure is higher or lower staffing ratios. At first glance, it might seem that where a State provides more staff per unit of service, there is a prima facie case for saying that this reflects a policy decision to provide a higher quality service. On the other hand, it can be argued that a State that is providing the same service with fewer staff per unit of service is operating more efficiently. Drawing on public choice theory, we have started from the assumption that, unless there is evidence to the contrary, high staffing ratios do not provide a better quality service and are a reflection of other factors, such as vote "buying" of public sector unions and other similar pressure groups or attempts to minimise potential vote losses from similar groups by politicians. This point is discussed further in considering some of the particular categories of expenditure.

Second, a similar point arises in regard to situations where differences between standardised and actual per capita expenditures are importantly due to higher than average salaries paid to staff. Again, in the absence of evidence to the contrary, we start from the general presumption that, at least within a range, such differences have no significant effect on quality of service. Moreover, while relative wage rates are determined by State Industrial Commissions, policies of State Governments can have a significant influence on such determinations, as well as on hierarchical structure of the work force and, hence, on average salaries.

Third, it may be argued that, in assessing cost disabilities, the various factors taken into account by the CGC -- units of service, scale, dispersion, social composition, and so on -- may themselves be affected by differences in State policies and may thus reflect differences in efficiency. For example, the CGC normally treats as a cost disability any excess units above the average where a State has a higher than average proportion of school age pupils attending government schools. Such higher than average attendance may, however, at least partly reflect the State's policy regarding (say) location of government schools or (lack of) assistance to non-government schools.

These are matters that have been the subject of extensive submissions and debate at hearings of the CGC over many years, and such issues will doubtless continue to be the subject of such submissions and debate. Indeed the CGC is presently conducting a major review of its methodology which may well involve changes in assessments of cost disabilities. This paper proceeds on the assumption that the existing approach by the CGC provides the best available method of determining "pure" cost disabilities and that the assessed standardised levels of per capita expenditure are thus the most reasonable available reflection of such cost disabilities.

Fourth, it may be argued that the system of fiscal equalisation does not necessarily produce the most efficient allocation of resources across Australia. However, while it may be the case that a move to a unitary system of government would produce a more efficient allocation of resources, the system of fiscal equalisation should not result in any distortion to the decisions which individual States make in allocating their resources. The position as regards allocative efficiency under fiscal equalisation is summed up in the following extract from a note by Mr W.R. Lane, Member of the Commonwealth Grants Commission.

"In some discussions of this matter there is a tendency to judge the effects of horizontal fiscal equalisation (HFE) by reference to criteria which could relate only to a unitary and not to a federal structure of government. The confusion produced by this can be exposed by considering a hypothetical model of a federation in which the member States all have identical fiscal capacity, as measured in terms of revenue-raising capacity and expenditure needs (in other words, they have identical revenue bases and identical population characteristics, including geographical distribution of population and economic activities).
In this model there is no horizontal fiscal imbalance (HFI), inasmuch as all of the State governments would, if they adopted identical revenue and expenditure policies, receive the same amounts of revenue and incur the same amounts of expenditure. Individuals and businesses would be faced with the same set of taxes and charges and State government services irrespective of which State they were in.
If we then take a step towards reality, retaining the assumption of identical fiscal capacities but allowing for differences between States in their revenue and expenditure policies, there will still be no HFI and no HFE. However, individuals and businesses will now be faced with taxes and charges and government services which differ from State to State because of the different policy decisions of the different States.
Contrast this with the situation in the same economy with a unitary fiscal structure. In that case the taxes and charges and services for any individual or business would not differ from State to State. According to the usual criteria for allocative efficiency, these locational differences in the fiscal mix, which are inevitable in a federal structure of government, would produce a loss of efficiency. Setting aside the question whether this represents too narrow a view of the economic consequences of federalism, the loss of efficiency identified in this model clearly has nothing to do with HFI and HFE. Therefore it is not valid to judge the effects of HFE on allocative efficiency by reference to what would happen in a unitary fiscal structure. The question must be considered in the context of a federal structure by comparing the likely effects with and without HFE. This is the approach taken in the Commission discussions." (5)

Accordingly, while it may be of academic interest to speculate on the effects of the allocation of resources under a unitary system, such speculation seems of little practical interest in the present context.

Finally, it is important to emphasise that, while the following analysis focuses on differences between standardised and actual levels of expenditure, no implication is intended to be drawn that States "ought" (in some sense) to operate at the standardised level. The sole purpose of such comparisons is to identify possible differences in efficiency of State spending.

Relative Levels of Recurrent Expenditure

Table 1.1 summarises the per capita expenditure differences for each State for each of the main categories of recurrent expenditure assessed by the CGC in 1988-89, the "% Diff" lines showing the percentage difference between the standardised expenditure per head assessed by the Commission and the actual expenditure per head. The following features of the figures are of interest in the context of the present paper.

First, it will be apparent that Victoria is the highest spending State, with total actual expenditure per head being 10 per cent above standardised expenditure per head. Also, Victoria's actual expenditure is significantly above its standardised level in six out of the ten major categories of expenditure.

Second, and by contrast, Queensland is the lowest spending State, with total actual expenditure per head being 23 percent below total standardised expenditure per head. For each of the ten major categories of expenditure Queensland's expenditure is significantly below standardised.

Third, the remainder of the States and the NT have total actual levels of expenditure per head close to total standardised expenditure per head. However, there are quite wide differences between actual and standardised levels for a number of the major categories of expenditure for different States. Western Australia, for example, has clearly pursued a policy of restraining expenditure in education and public transport while allowing other areas to spend at levels well above standardised.

Fourth, in respect of the major categories of expenditure -- education, health, and business undertakings deficits (which comprise over 70 percent of total recurrent expenditure assessed by the CGC) -- the following aspects might be noted:

In education, there is a very wide difference between the highest spending State, Victoria, and the two lowest spending States of Queensland and Western Australia.
In health, the main feature is the relatively low level of spending by Queensland.
In business undertakings, the actual deficits per head in NSW and Victoria are well above standardised levels while the actuals deficits per head in other States are well below their standardised levels.

TABLE 1.1 RECURRENT SPENDlNG BY STATES -- PER HEAD -- 1988-89

	Educ	Cult/ Recr	Health	Welfare	Law/ Order	Admin Serv	Commun Serv	Regulat Serv	Industry	Bus Deficit	TOTAL
NSW Actual Stndsd % Diff	621.1 633.4 -1.9	34.2 35.4 -3.6	617.0 592.4 4.2	79.7 87.2 -8.6	194.8 195.0 -0.1	150.1 139.1 7.9	13.3 13.0 2.9	9.4 13.6 -30.7	38.7 51.1 -24.2	255.9 217.8 17.5	2014.2 1978.0 1.8
VIC Actual Stndsd % Diff	713.7 616.9 15.7	29.3 35.1 -16.6	646.5 577.7 11.9	93.5 80.1 16.7	179.9 180.0 -0.1	105.0 135.4 -22.5	15.2 11.1 37.7	17.5 14.2 23.4	45.6 47.8 -4.6	272.8 225.3 21.1	2118.9 1913.6 10.2
QLD Actual Stndsd % Diff	589.6 729.3 -19.2	33.8 39.9 -15.3	462.2 642.0 -28.0	64.1 95.8 -33.1	167.9 203.3 -17.4	120.5 154.1 -21.8	7.2 14.2 -49.0	7.5 12.8 -41.9	66.8 79.2 -15.6	143.2 192.1 -25.4	1662.8 2162.8 -23.1
SA Actual Stndsd % Diff	672.8 642.7 4.7	59.8 39.4 51.7	644.0 670.7 -4.0	102.3 94.6 8.1	210.4 179.1 17.5	144.5 166.5 -13.2	14.6 17.1 -14.4	16.3 16.4 -0.4	72.1 79.6 -9.4	115.4 190.8 -39.5	2052.0 2096.8 -2.1
WA Actual Stndsd % Diff	657.2 740.4 -11.2	55.2 43.6 26.7	699.9 657.5 6.5	125.7 95.1 32.2	243.4 208.6 16.7	224.0 166.5 34.5	27.6 21.8 26.7	27.8 15.3 82.0	102.0 95.0 7.4	120.7 176.3 -31.6	2283.5 2219.9 2.9
TAS Actual Stndsd % Diff	733.3 698.8 4.9	64.2 46.7 37.5	632.8 659.8 -4.1	98.8 106.8 -7.5	203.0 187.4 8.4	142.1 202.3 -29.8	17.5 26.8 -34.9	21.4 18.4 16.5	151.2 109.4 38.2	57.3 156.1 -63.3	2121.5 2212.4 -4.1
NT Actual Stndsd % Diff	1270.3 1139.2 11.5	249.6 137.5 81.6	1061.5 1023.5 3.7	175.2 182.1 -3.8	647.0 667.1 -3.0	316.0 486.3 -35.0	95.5 83.4 14.5	88.5 45.2 95.6	466.3 386.4 20.7	95.4 212.1 -55.0	4465.3 4362.9 2.3

In the remainder of this paper we examine in more detail each of the three major categories of expenditure just cited -- education, health and business undertakings deficits. Specifically:

For education, we examine in detail State spending in the areas of primary and secondary (including special) government schools. Between them these two "big ticket" items accounted for between 66 per cent (NSW) and 72 per cent (South Australia) of total spending by States in 1988-89 on education.
For health, we examine in detail spending on general medical services, which in 1988-89 accounted for 96 per cent of total health expenditure by the States.
For business undertakings, we examine in detail the contributions to the overall deficits of State business undertakings deriving from metropolitan transit operations, metropolitan passenger services and non-metropolitan freight services. While per capita deficits of their business undertakings varied very widely between the States, in 1988-89 these three areas accounted for some 84 per cent of such deficits overall.

In the area of education, our main conclusions are as follows:

As already noted, there is a wide difference between the highest spending State (Victoria) and the two lowest spending States (Queensland and W.A.).
Both in its primary and secondary schools, Victoria displays teacher/student ratios which are clearly much higher than in N.S.W., Queensland or W.A.; and which are also higher than in the other two "big spending" (in this area) States, South Australia and Tasmania.
In addition to its high teacher/student ratios, Victoria also recorded average salary levels for its primary school teachers which were well above those for all other States, and for its secondary school teachers which were only exceeded by those for South Australia.
At both primary and secondary levels, Victoria had lower ratios of other school-based staff to students than for any other State (Tasmania and South Australia having the highest). However, since the proportion of other school-based staff to teaching staff in Victoria was only about 14 per cent (primary) and 15 per cent (secondary), this factor did relatively little to offset, in terms of overall costs, Victoria's high teacher/student ratios.
Salaries of other school-based staff were also very much higher in Victoria than in all other States at the primary level, and than in all other States except South Australia (where they were nearly as high) at the secondary level.)
Tasmania's ratio of non-school staff to students was higher than that of any other State; W.A. and South Australia also had high ratios of non-school staff, with Victoria lower than these but still well above those for N.S.W. and Queensland.
Victoria appears to have a markedly different policy attitude towards special schools -- catering for students with various forms of intellectual or other disability -- than most other States, with a higher proportion of its total student population in such schools than any other State except Western Australia (though Queensland's proportion is almost as high).
Despite their relatively high levels of government school spending, the rate of "drift" from government to non-government schools during the decade 1979-89 was highest in South Australia and second-highest in Victoria.
Resistance by teachers' unions and other, generally self-interested groups, to State-wide testing or gathering other empirical evidence of student performance makes interstate comparisons of the quality of educational output difficult.
Nevertheless, such evidence as is available appears to provide no basis for concluding that such quality is higher in those States (e.g. Victoria) displaying high levels of spending on education than in those States (e.g. Queensland) displaying low levels -- a view which has recently been emphasized by a paper released by the new Premier of Tasmania (Mr Field).
The higher levels of spending in such States as Victoria and Tasmania appear to have more to do with the "capture" of governments in those States by teachers' unions, than with a genuine policy to lift educational standards.
Accordingly, there seem to be large savings to be made (without any necessary diminution of educational quality) in the education portfolios in several of the States -- most notably Victoria, South Australia and Tasmania.

In the case of health, there emerge not entirely dissimilar conclusions, namely:

Western Australia undertakes the highest per capita expenditures on health services, followed by Victoria, and with Queensland the lowest spending State (despite its State-financed free hospital service).
After Grants Commission adjustments for relative disabilities in the delivery of services (which are obviously higher in sparsely populated States such as W.A. and Queensland than in Victoria), the State spending most "above standard" is Victoria, with Queensland, on this basis, by far the lowest.
Contrary to what one might expect on the basis of such comparisons, Queensland has a higher supply of "acute beds" relative to population than any other State. Victoria has a relatively low supply of such beds (but uses them -- as would therefore be expected -- more intensively in terms of bed occupancy rates). Waiting lists are therefore short in Queensland and (relatively) long in Victoria.
There appear to be no suggestions at the professional level that Queensland provides a lower quality of medical/hospital competence than other States.
In terms of access, availability and technical quality of service, therefore, government health services in Queensland appear to be (at least) no worse than other States. On this basis, there could even be scope for Queensland to reduce its already very low level of costs even further by bringing its utilisation and capacity rates closer to those of other States.
There are significant variations in labour costs between States; in 1985/86 Queensland had the lowest labour costs per capita and W.A. the highest.
This appears to result not (or not significantly) from differences in average salary levels, but rather from different staffing policies in Queensland's hospitals -- in particular, a staffing "mix" strongly weighted towards technical staff (nurses and salaried medical officers) and the containment of non-technical staff numbers. The two high-cost States, Victoria and W.A., pursued precisely opposite staffing policies.
Again, these differences appear chiefly to reflect the success (or, in Queensland's case, lack of success) of hospital employees' unions in pressing for higher non-technical staffing levels in Victoria (especially) and W.A.

In the area of business undertakings -- more specifically, the costs to State budgets of covering their operating deficits -- our main conclusions are as follows:

Such costs varied widely between States, ranging from 12 per cent of total Victorian budget recurrent outlays to about 2.5 per cent of such outlays in the case of Tasmania (where rail services are provided by the Australian National Railways).
The deficits on metropolitan transit operations (rail, bus and -- in Melbourne's case -- tram) have by far the largest impact on State budgets ($1.7 billion in 1988-89); in turn, these losses are concentrated in two capitals, Sydney and Melbourne, and particularly the latter.
Wage and salary relativities appear to have little to do with the relative magnitudes of these operating losses between the States.
Although Cityrail (Sydney) appears relatively efficient in comparison with Melbourne's rail transit operations, by international standards Cityrail's technical efficiency in 1989 was found to be appalling, with excessive staff levels and inefficient work practices abounding. One can therefore only conclude that a similar investigation in Melbourne's case would have produced even more depressing conclusions (difficult though that might seem to be).
In Melbourne, by far the most inefficient element of the transit operation is that provided by the tramways, particularly their traffic and rolling stock maintenance areas.
Compared with private sector operators, the public sector -- provided bus operations are generally much more costly.
Victoria's fare structure in its metropolitan transit operations appears to have been held down well below levels charged in other States, and to bear no relationship to operating costs.
Non-metropolitan transport operations are also costly to State budgets ($1.1 billion in 1988-89, of which almost $600 million in respect of non-metropolitan freight).
In the non-metropolitan freight area, the chief losses are incurred in N.S.W. and Victoria. Despite these losses being long recognized, they continued to grow (on a real per capita basis) by 1.5-2.0 per cent per annum over the period 1984/85-1988/89.
By contrast with the metropolitan transit area, wages policies appeared to be a major determinant of relative efficiencies between States; N.S.W., which had the least profitable rail operations, has the highest wage rates, while Queensland (despite operating in more isolated areas) has the lowest. Victoria also had high wage levels in this area.
In the case of non-metropolitan passenger operations, all States suffered losses in 1988-89, but N.S.W., Queensland and Victoria had (in that order) the highest levels of "above standardised" expenditure -- in Queensland's case, one of the few areas of State spending in that category.
Between 1984-85 and 1988-89, Victoria went from a "below standardised" to an "above standardised" ranking.
As in the case of non-metropolitan freight operations, wages policies were a major cause of these differences.
W.A., which has by a substantial margin the largest share of its non-metropolitan passenger government transport provided by coaches (as distinct from rail), has the most efficient such operations; by contrast, Queensland, which in this area is the least efficient, provides no government coach services.
The pricing of country passenger services in N.S.W. (and to a perhaps lesser degree in other States also) is wildly irrational.

2. EDUCATION

Table 2.1 shows, by States, a breakdown of the aggregate figures in Table 1.1. for the education function as a whole into seven sub-functions: pre-school education, government primary education, assistance to primary education in the non-government sector, government secondary education, assistance to secondary education in the non-government sector, TAFE and expenditure on the transport of school children. The second and third columns show the corresponding standardised levels of expenditure, and the percentage differences between actual and standardised expenditures, respectively.

Table 2.1: Education Spending, by Category, by State

	Actual $ per capita	Standardised $ per capita	Percentage Difference (%)
New South Wales Pre-school Education Primary Education -- Govt Primary Education -- non-Govt Secondary Education -- Govt Secondary Education -- non-Govt TAFE Transport of School Children	8.65 199.35 44.50 209.50 46.46 93.42 19.24	14.82 217.46 47.79 211.86 44.90 81.52 15.04	-41.63 -8.33 -6.88 -1.11 + 3.47 + 14.60 + 27.93
Victoria Pre-school Education Primary Education -- Govt Primary Education -- non-Govt Secondary Education -- Govt Secondary Education -- non-Govt TAFE Transport of School Children	14.02 223.56 56.95 262.83 64.33 74.78 17.25	13.87 194.51 54.63 206.26 56.94 74.86 15.86	+ 1.08 + 14.93 + 4.25 + 27.43 + 12.98 -0.11 + 8.76
Queensland Pre-school Education Primary Education -- Govt Primary Education -- non-Govt Secondary Education -- Govt Secondary Education -- non-Govt TAFE Transport of School Children	22.09 225.36 41.06 174.22 50.13 58.05 18.65	16.29 260.75 42.58 250.52 52.01 78.07 29.11	+ 35.60 -13.57 -3.57 -30.46 -3.61 -25.64 -35.93
Western Australia Pre-school Education Primary Education -- Govt Primary Education -- non-Govt Secondary Education -- Govt Secondary Education -- non-Govt TAFE Transport of School Children	23.33 240.37 42.66 210.53 42.35 78.83 19.08	17.55 269.76 43.38 248.93 50.11 87.89 22.73	+ 32.93 -10.89 -1.66 -15.43 -15.49 -10.31 -16.06
South Australia Pre-school Education Primary Education -- Govt Primary Education -- non-Govt Secondary Education -- Govt Secondary Education -- non-Govt TAFE Transport of School Children	21.98 266.88 41.83 219.24 34.99 78.07 9.75	15.01 210.21 34.73 243.53 42.77 78.14 18.27	+ 46.44 + 26.96 + 20.44 -9.97 -18.19 -0.09 -46.63
Tasmania Pre-school Education Primary Education -- Govt Primary Education -- non-Govt Secondary Education -- Govt Secondary Education -- non-Govt TAFE Transport of School Children	20.89 249.67 36.21 275.96 39.03 83.80 27.71	16.36 257.95 41.01 244.04 36.46 76.80 26.16	+ 27.69 -3.21 -11.70 + 13.08 + 7.05 + 9.11 + 5.93

In each case, as one might expect, by far the largest spending sub-categories are primary and secondary government education. Spending on TAFE is next, though at a much lower level. Assistance to non-government primary education, and to non-government secondary education, are next, with spending approaching TAFE levels in some States (e.g. Victoria), but more usually much less than that. Spending on pre-school education, and on transport of school children, are smaller again.

If therefore one is to analyse the reasons why (say) education spending in Victoria is significantly above standard, whereas in Queensland (particularly) and Western Australia it is well below standard, it may be best to start by looking at factors influencing expenditure in the two "big ticket" items -- primary and secondary government education.

Table 2.2 sets out figures for teaching staff in government primary schools in 1989 and numbers of full-time primary students. From these are derived the ratios, in each State, of teachers per 1,000 primary students (for information, the comparable 1985 ratios are given to provide a quick impression of the trend in this indicator in each State in recent years). The ratio, for each State, of its teacher/student ratio to the so-called 8-State standard (i.e. including ACT and the Northern Territory) is also shown (again, the comparable 1985 figures are shown for information).

Table 2.2: Government Primary School Teaching Staff/Student Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Teaching Staff	21,593	18,272	12,982	7,083	7,046	2,149	71,522
Full-time students ^(b)	434,098	294,768	242,183	136,911	117,266	36,857	1,302,432
Teachers/1000 students	49.74	61.99	53.60	51.73	60.09	58.31	54.91
(1985)	(50.80)	(66.35)	(55.28)	(51.54)	(62.46)	(67.09)	(57.09) ^(c)
Ratio to 8 States Standard ^(a)	0.9058	1.1289	0.9761	0.9421	1.0943	1.0619	1.0000
(1985)	(0.8897)	(1.1621)	(0.9683)	(0.9028)	(1.0940)	(1.1750)	(1.0000) ^(c)

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents.

^(c) 7-State Average was used for 1985.

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0); Commonwealth Grants Commission papers.

The primary school teacher/student ratio is clearly much higher in Victoria than in most other States -- nearly 13 per cent higher than the Australia-wide average, and nearly 25 per cent higher than in NSW. It seems likely then that this factor provides a large part of the reason for that above-standard spending on education by Victoria which we saw at the outset in Table 1.1. The same factor seems also responsible for part of the same above-standard position of South Australia and Tasmania. In South Australia's case, it is striking to note that although its government primary school student population is only 86 per cent that of Western Australia, it has almost as many primary school teachers as W.A.

Note however that, although the primary teacher/student ratios for Queensland and WA are well below the Victorian (and South Australian and Tasmanian) levels, they are not, particularly in Queensland's case, greatly below the Australia-wide average. This is essentially because, despite the high levels in Victoria, South Australia and Tasmania, the average is dragged down heavily by the "weight" of the low level ratio in NSW.

Table 2.3 shows teaching staff and pupil data for government secondary schools similar to that for primary schools shown in the preceding table.

Table 2.3: Government Secondary School Teaching Staff/Student Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Teaching Staff	23,345	21,142	10,465	5,790	6,066	2,423	71,493
Full-time students ^(b)	310,765	228,021	141,712	73,423	67,259	27,432	874,404
Teachers/1000 students	75.12	92.72	73.85	78.86	90.19	88.33	81.76
(1985)	(76.65)	(95.54)	(70.24)	(75.76)	(87.50)	(85.36)	(82.23) ^(c)
Ratio to 8 States Standard ^(a)	0.9188	1.1341	0.9033	0.9645	1.1031	1.0804	1.0000
(1985)	(0.9321)	(1.1618)	(0.8542)	(0.9212)	(1.0640)	(1.0380)	(1.0000) ^(c)

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents

^(c) 7-State average was used for 1985.

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0); Commonwealth Grants Commission papers.

As for the primary level, the secondary school teacher/student ratio for Victoria is clearly much higher than in most other States -- over 13 per cent higher than the Australia-wide average, and over 23 per cent higher than for NSW. Again, then, it seems likely that this factor provides a large part of the reason for Victoria's above-standard spending on education as a whole, and similarly in the cases of South Australia and Tasmania, whose secondary school teacher/pupil ratios, though slightly lower than Victoria's, are both very much higher than those of all other States. Again, as in the primary school case, note that although South Australia has only 92 per cent of W.A.'s government secondary school student population, it has 5 per cent more secondary school teachers than W.A.

Again as in the primary school case, note that although the secondary school teacher/student ratios for Queensland and WA are well below the Victorian level (and those for South Australia and Tasmania), at least in WA's case the ratio is not very far below the Australia-wide average. Again, this is essentially because, despite the high levels in Victoria, South Australia and Tasmania, the average is dragged down heavily by the "weight" of NSW's low ratio level.

It is also of some interest to note that, unlike the primary school case -- where the teacher/student ratios for every State except (barely) Western Australia declined, in varying degrees, between 1985 and 1989 -- the teacher/student ratio for secondary schools increased between those years for all States except NSW and Victoria, where in both cases they fell.

Table 2.4 shows teaching staff and students (full-time equivalents) data for so-called special schools -- catering for students with various forms of intellectual or other disability -- similar to that tor primary and secondary schools shown in the two preceding tables (but excluding 1985 data which, in this case, were not readily available).

Table 2.4: Government Special School Teaching Staff/Student Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Teaching Staff	875	1,322	810	370	263	160	3,943
Full-time students ^(b)	4,400	4,911	3,543	2,127	1,244	688	17,519
Teachers/1000 students	198.86	269.19	228.62	173.95	211.41	232.56	225.07
Ratio to 8 States Standard ^(a)	0.8835	1.1960	1.0158	0.7729	0.9393	1.0333	1.0000

^(a) Including ACT and Northern Territory.

^(b) Full lime equivalents

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0)

Although special schools do not form a high proportion of the totality of the school education effort in any State, it is clear from even a casual inspection of these figures that policy attitudes towards them must differ very widely from State to State. Thus Victoria, whose total student population in government schools is only 70 per cent of that of NSW, actually has more students in special schools than NSW. Queensland, whose total government school student population is only 52 per cent of that of NSW, has 81 per cent as many students in special schools -- that is, almost 60 per cent more than the number that would be expected on a basis proportional to NSW.

Moreover, in addition to the high proportion of special school students for whom it caters, Victoria also provides for them a teaching staff/student ratio which is very high (less than 4 pupils per teacher) by comparison with any other State -- particularly Western Australia and NSW -- or with the Australia-wide average. Thus the Victorian teaching staff/student ratio in these schools is 55 per cent, and 35 per cent, greater than those for WA and NSW respectively, and nearly 20 per cent higher than the national average -- even though that average is heavily influenced (upwards) by the Victorian component itself.

Thus, despite the relatively small expenditures on special schools within the total of education spending, it seems likely that the apparently singularly heavy emphasis in this area by Victoria would nevertheless account for a not negligible amount of the "excess" spending on education in that State. For some quantification of that comment, see Table 2.14 below.

The analysis of government schools expenditure to this point has been directed towards teaching staff. Most schools, however, have a component of other (non-teaching) staff attached to them; while, in addition to these "other school-based staff", there are staff within the system who are not attached to any particular school (e.g. specialist support staff, whose services may be required at different schools from time to time; executive staff, involved in the "central office", or in some States "regional office", function; and so on).

Table 2.5 provides data for "other school-based staff" in government primary schools in 1989, comparing these again with the numbers of full-time students in such schools.

Table 2.5: Government Primary Schools; Other School-based Staff/Student Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Other School-based Staff	4,252	2,505	2,698	1,755	1,804	637	14,282
Full-time students ^(b)	434,098	294,768	242,183	136,911	117,266	36,857	1,302,432
Ratio/1000 students	9.80	8.50	11.14	12.82	15.38	17.28	10.97
Ratio to 8 States Standard ^(a)	0.8933	0.7748	1.0155	1.1686	1.4020	1.5752	1.0000

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents.

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0).

Perhaps the most interesting point to emerge from these figures is that Victoria, which was clearly the most generously staffed State at the primary teacher level, has the lowest ratio of other primary school-based staff to students of all the States. Of course, since the proportion of other primary school-based staff to primary school teachers is relatively low (only 17 per cent on the Australia-wide average) and since (as we shall see later) the average level of teachers' salaries is in all States well above the average salary level for other school-based staff, the cost of the high primary teacher/student ratio far outweighs the savings from the low ratio of other primary school-based staff to students. Nevertheless the point is worth noting.

By contrast, New South Wales, which had clearly the lowest primary school teacher/student ratio, also has the second lowest ratio of other primary school-based staff to students. Similarly -- but at the other end of the spectrum -- South Australia and Tasmania, which had the second and third highest ratios, respectively, of primary school teachers to students, also had the second highest and highest ratios, respectively, of other primary school-based staff to students.

Table 2.6 presents, for government secondary schools, comparable data regarding "other school-based staff" as were presented in the preceding table for primary schools.

Table 2.6: Government Secondary Schools; Other School-based Staff/Student Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Other School-based Staff	4,731	3,202	1,892	1,402	1,435	651	13,822
Full-time students ^(b)	310,765	228,021	141,712	73,423	67,259	27,432	874,404
Ratio/1000 students	15.22	14.04	13.35	19.09	21.34	23.73	15.81
Ratio to 8 States Standard ^(a)	0.9627	0.8880	0.8444	1.2075	1.3498	1.5009	1.0000

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents.

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0).

Again, perhaps the most interesting point to emerge from these figures is that Victoria, which clearly had the highest secondary school teaching staff/student ratio, has the second-lowest (after Queensland) ratio of other secondary school-based staff to students. Again, as noted at the primary level, since the proportion of other secondary school-based staff to secondary school teachers is relatively low (only 19 per cent on the Australia-wide average), and since the average level of teacher salaries is in all States well above the average salary level for other school-based staff, the cost of the high secondary school teacher/student ratio in Victoria far outweighs the saving from the relatively low ratio of other secondary school-based staff to students.

It is interesting to note that Queensland, which had the lowest secondary school teacher/student ratio among the States (just below NSW), also had the lowest ratio of other secondary school-based staff to students. Any suggestion, therefore, that one approach to education policy is to offset a high teacher/student ratio by a low ratio of other school-based staff to students would not be supported by Queensland experience, at any rate at the secondary school level.

Apropos that point, New South Wales, which had the second lowest secondary school teacher/student ratio (only slightly higher than Queensland) had a ratio of other secondary school-based staff to students which, while higher than the ratios of either Victoria or Queensland, was still somewhat lower than the national average.

At the other end of the spectrum, South Australia and Tasmania, which after Victoria had the second highest and third highest secondary teacher/student ratios, respectively, also had the second highest and highest ratios, respectively, of other secondary school-based staff to students. Again, this "correlation" would not appear to be consistent with any thesis (e.g. in the case of Victoria) that there was some "natural" inverse relationship between the ratios of teaching staff, and other school-based staff, respectively.

Because their relative significance in the total education function is not large, we do not set down a similar analysis for special schools. However, Table 2.7 contains, for completeness, data regarding "other school-based staff" in such schools comparable to those presented in preceding tables for primary and secondary schools.

Table 2.7: Government Special Schools: Other School-based Staff/Student Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Other School-based Staff	696	281	898	301	111	94	2,486
Full-time students ^(b)	4,400	4,911	3,543	2,127	1,244	688	17,519
Ratio/1000 students	158.18	57.22	253.46	141.51	89.23	136.63	141.90
Ratio to 8 States Standard ^(a)	1.1147	0.4032	1.7862	0.9973	0.6288	0.9629	1.0000

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0).

Table 2.8 sets out data, by States, for total non-school staff (which by definition cannot be divided between primary, secondary and special schools), for the staff/student ratio for such staff in each State system (based on total students at all levels of schooling), and for the ratio in each case of non-school staff to total school-based staff.

Table 2.8: Government Schools: Non-School Staff Ratios 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Non-School Staff ^(b)	2,352	2,471	1,397	1,014	1,011	563	9,494
Total Full time students ^(b) ^(c)	749,263	527,700	387,438	212,461	185,769	64,977	2,194,355
Non-School Staff/1000 students	3.139	4.683	3.606	4.773	5.442	8.665	4.327
Ratio to 8 States Standard ^(a)	0.7254	1.0823	0.8334	1.1031	1.2577	2.0025	1.0000
Total School, based staff ^(c) ^(d)	55,490	46,724	29,744	16,700	16,726	6,114	177,547
Ratio of Non-School Staff/1000 School-based Staff	42.39	52.89	46.97	60.72	60.44	92.08	53.47
Ratio to 8 States Standard ^(a)	0.7928	0.9892	0.8784	1.1356	1.1304	1.7221	1.0000

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents.

^(c) All levels of schooling -- primary, secondary and special.

^(d) Teaching staff plus other school-based staff.

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.0).

A number of preliminary conclusions emerge from these data. For example, although as noted earlier Victoria only has a total government school student population some 70 per cent that of NSW, it actually has 5 per cent more non-school staff in its government system than its sister-State. Similarly, South Australia, whose government school population is only 87 per cent that of WA, has almost precisely as many non-school staff in its government system as WA. Most dramatically of all, Tasmania has a non-school staff/student ratio which is almost double that of Victoria, 2.4 times that of Queensland, and almost 2.8 times that of NSW.

To this point we have been examining the staffing ratios -- teaching staff, other school-based staff, and non-school staff -- operating in the government school systems at both primary and secondary school levels (and, to a lesser degree, special schools). Quite apart from what these data tell us about some factors influencing the relative levels of spending on education in the various States, however, another factor which is relevant to that is the relative salary levels of the different categories of staff employed in each area in each State.

Table 2.9 sets out figures for the amounts expended in the financial year 1988-89, by States, on teaching staff salaries, in primary schools, secondary schools and special schools. It also sets out similar data for salaries paid in 1988-89 to other school-based staff and, on an aggregate basis, for non-school (non-teaching) staff.

Table 2.9: Salary Payments 1988-89 ($'000)

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Teaching Staff: Primary schools Secondary schools Special schools	698,175 803,422 28,394	623,649 727,991 43,842	376,132 319,679 27,366	214,167 186,814 11,699	236,632 216,240 8,534	70,554 79,968 4,754	2,300,998 2,416,281 129,537
Other School-based staff: Primary schools Secondary schools Special schools	78,264 83,624 11,640	58,749 74,159 5,746	47,186 37,031 12,666	34,314 31,066 6,054	38,130 32,478 2,073	10,364 12,694 1,320	281,406 283,719 41,929
Non-School (Non-Teaching) Staff: Total	91,435	86,224	41,119	30,326	28,011	15,321	314,035

^(a) Including ACT and Northern Territory

Source: Australian Education Council: National Schools Statistics Collection Manual -- Summary data.(6)

For ease of comparison Table 2.10 brings together figures for staffing, already provided in earlier tables, in the same categories as for the preceding table on salary payments. Note that because these staffing figures are in respect of 1989, they do not provide a precise basis for comparison with the 1988-89 financial year salary payments figures set out in the preceding table. However, the periods are sufficiently close to suggest that calculations of average salaries based upon comparing the two tables will not be seriously in error.

Table 2.10: Staffing Numbers ^(b) 1989

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Teaching Staff: Primary schools Secondary schools Special schools	21,593 23,345 875	18,272 21,142 1,322	12,982 10,465 810	7,083 5,790 370	7,046 6,066 263	2,149 2,423 160	71,522 71,493 3,943
Other School-based staff: Primary schools Secondary schools Special schools	4,252 4,731 696	2,505 3,202 281	2,698 1,892 898	1,755 1,402 301	1,804 1,435 111	637 651 94	14,282 13,822 2,486
Non-School Staff: Total	2,352	2,471	1,397	1,014	1,011	563	9,494

^(a) Including ACT and Northern Territory.

^(b) Full time equivalents

Sources: Schools Australia 1989 (ABS Catalogue No. 4221.O).

From the preceding two tables, and subject to the minor caveat mentioned above, we can now calculate average salaries in each staff category, by State, for 1988-89. These are set out in Table 2.11.

Table 2.11: Average Salary Levels ($) By Category of Staff ^(a)

	NSW	VIC	QLD	WA	SA	TAS	AUST ^(a)
Teachers: Primary school Secondary school Special schools	32,333 34,415 32,450	34,131 34,433 33,163	28,973 30,547 33,785	30,237 32,265 31,619	33,584 35,648 32,449	32,831 33,004 29,713	32,172 33,797 32,852
Other School-based staff: Primary school Secondary school Special schools	18,406 17,676 16,724	23,453 23,160 20,448	17,489 19,572 14,105	19,552 22,158 20,113	21,136 22,633 18,676	16,270 19,499 14,043	19,704 20,527 16,866
Non-School Staff ^(c)	38,875	34,894	29,434	29,907	27,706	27,213	33,077

^(a) Salary costs for 1988-89 divided by numbers of full-time equivalent staff for each category for calendar 1989.

^(b) Including ACT and Northern Territory.

^(c) Ratios of salary costs of non-school non-teaching staff to total non-school staff. Non-school teaching staff (e.g. specialist support staff) salary costs are not available. Average salary level companions between States in this category could therefore be affected by inter-State differences in their composition of total non-school staff. The proportion of specialist support staff to total non-school staff varied in 1989 between 34 per cent (W.A.) and 18 per cent (NSW).

Comparison of the average salary levels in this table with earlier tables relating to staffing reveals a number of interesting relationships. Most prominent, perhaps, is the fact that Victoria, which in its government schools had the highest primary school teacher/student ratio, the highest secondary school teacher/student ratio, and by far the highest special school teacher/student ratio, also turns out to have the second highest average salary level for primary school teachers, the highest average salary level for secondary school teachers (although much the same as that for N.S.W.) and the second highest (to Queensland) average salary level for special school teachers.

Similarly, although we saw earlier that Victoria had the lowest ratio of other primary school-based staff to students, the second lowest such ratio at the secondary school level, and by far the lowest such ratio in the case of special schools, these apparently "economical" ratios are now seen to be considerably offset by average salary levels in the three categories which are in every case the highest of all the States. Victorian salary levels in these areas are, respectively, 19 per cent, 13 per cent and 21 per cent above the nation-wide average and 27 per cent, 31 per cent, and 22 per cent, respectively, above N.S.W. levels.

Given the very high level of spending on government schools in Victoria, and to a lesser extent South Australia and Tasmania, it might have been expected that, if such spending were efficiently directed to the improvement of quality of educational output, that quality in such schools in those States, relative to others, would have influenced the relative pace of "drift" from government to non-government schools. In fact, this has not been the case; over the past decade the drift in enrolment from government to non-government schools has been higher in Victoria and South Australia than in any other State (or Territory). Table 2.12 sets down some relevant data on that score.

Table 2.12: Retention of Students by Government Schools 1979-89
(Number of Students in thousands)

Rank Order ^(a)		1979		1989		1979-89
Rank Order ^(a)		Govt Schools	Non-Govt Schools	Govt Schools	Non-Govt Schools	Percentage Loss by Govt Schools Per Cent
1.	QLD (%)	349.1 (78.6)	94.9 (21.4)	387.4 (75.4)	126.4 (24.6)	3.2
2.	TAS (%)	73.1 (83.5)	14.4 (16.5)	65.0 (77.9)	18.4 (22.1)	5.6
3.	WA (%)	207.0 (81.9)	45.6 (18.1)	212.5 (75.9)	67.5 (24.1)	6.0
4.	NSW (%)	807.8 (79.0)	214.9 (21.0)	749.2 (72.5)	284.3 (27.5)	6.5
5.	VIC (%)	614.4 (74.4)	211.1 (25.6)	527.8 (67.2)	257.4 (32.8)	7.2
6.	SA (%)	224.5 (84.9)	40.5 (15.1)	185.8 (76.7)	56.5 (23.3)	8.2

^(a) Ranked by order of percentage loss in share of government schools between 1979 and 1989 (as shown in final column)

Source: Geoffrey Partington, "Why Parents are Choosing Independent Schools", Education Monitor. Autumn 1990.

Table 2.13 presents similar data to that in the preceding table, but over the past two years instead of over the past decade. It is fascinating to note that Queensland, which displays the lowest level of educational spending relative to standard, nevertheless continues to suffer the smallest loss of "share" by its government schools, as the previous table showed had been the case over the past decade. Victoria and South Australia, on these recent figures, rise a couple of places in the ranking, but the differences in their rankings from those below them are marginal, and both continue steadily to lose share.

Table 2.13: Retention of Students by Government Schools 1987-89
(Number of Students in thousands)

Rank Order ^(a)		1987		1989		1987-89
Rank Order ^(a)		Govt Schools	Non-Govt Schools	Govt Schools	Non-Govt Schools	Percentage Loss by Govt Schools Per Cent
1.	QLD (%)	375.8 (75.9)	119.2 (24.1)	387.4 (75.4)	126.4 (24.6)	0.5
2.	NSW (%)	755.1 (73.2)	275.9 (26.8)	749.2 (72.5)	284.3 (27.5)	0.7
3.	VIC (%)	537.9 (68.0)	253.1 (32.0)	527.8 (67.2)	257.4 (32.8)	0.8
4.	SA (%)	187.4 (77.6)	54.0 (22.4)	185.8 (76.7)	56.5 (23.3)	0.9
5.	TAS (%)	65.4 (78.8)	17.6 (21.2)	65.0 (77.9)	18.4 (22.1)	0.9
6.	WA (%)	208.1 (76.9)	62.7 (23.1)	212.5 (75.9)	67.5 (24.1)	1.0

^(a) Ranked by order of percentage loss in share of government schools between l987 and 1989 (as shown in final column).

Source: Schools Australia 1989, Op. cit.

The relatively high degree of dissatisfaction with government schools in South Australia and Victoria, suggested by these figures, appears at odds with the high teacher/student ratios, and high levels of spending on other aspects of government education, in those States. It is not possible here to embark upon any detailed enquiry into that relationship (or non-relationship). However, it may be worth noting that a recent survey by Geoffrey Partington of the reasons why parents in South Australia move their children from government to non-government schools found that the most important reasons were "concerns about standards of work", and "concern about quality and commitment of teachers" and "concern about student behaviour". By contrast, "concern about class size and facilities" was of little concern, as were "concern about sporting and cultural life" and "concern about social standing or prestige".

The efficiency with which spending on education (e.g. through higher teacher/student ratios or in other ways) is translated into quality of educational output is much debated. Regrettably, because of resistance by teachers' unions and other, generally self-interested groups, to State-wide testing, evidence on student performance, either between States or, within States, between different schools (and between government and non-government schools generally) is thin. In 1988 the Australian Council for Educational Research tested literacy and numeracy standards among a sample of Victorian Year 5 and Year 9 students. The tests showed that there had been no overall improvement since the ACER national tests in 1980 (before such national testing was prevented). An exception was a modest decline between 1980 and 1988 (though an increase since 1975) in mathematical ability at Year 9 level. So far then as this evidence shows, the large increase in funding in Victoria since 1980, the marked increase in teacher/student ratios and so on, have yielded no benefit (other than to those, such as teachers, directly benefiting from the spending involved).

No similar evidence -- slender though it is -- is available for either South Australia or Tasmania, the two other States where educational spending is most obviously in excess of standard.

Nevertheless, at a time when all three States (and particularly Victoria) are facing very severe difficulties in putting together their respective Budgets for 1990-91, it may be of interest to note the large savings that would be available to them if they were to reduce their staffing ratios and/or salary levels to bring them into line with those of NSW, or -- a less severe change -- the Australia-wide average.

Note incidentally that if an above-average State were to reduce its ratios, or expenditures, to the present Australia-wide average, that would in fact result in it continuing to be above the (new) average. In other words, to equalize its position with the average of the other States would require it to equalize with the 5-State (or 7-State, including the A.C.T. and the Northern Territory) average, not the 6-State (or 8 State) average of which it is itself a part. In the case of a small State such as Tasmania this point may not be of great importance; in the case of a relatively large State such as Victoria, however, it is in fact quite significant.

The saving to the Victorian Budget if (say) Victoria's primary school teacher/student ratio were reduced to that of N.S.W. can be estimated as follows:-

("Excess" primary school teachers per 1000 students compared with NSW) x (Number of Victorian primary school students, in thousands) x (Average salary level for Victorian primary school teachers)
i.e. (61.99 - 49.74) x 294.768 x $34,131 = 3,611 teachers x $34,131 = $123.25 million.

If, alternatively, the primary school teaching staff/student ratio in Victoria were maintained unchanged, but average salary levels for Victorian primary school teachers were reduced to those for N.S.W., the saving would be as follows:

(Number of Victorian primary school teachers) x (Difference between Victorian and NSW average salary levels for primary school teachers)
i.e. 18,272 x $(34,131 - 32,333) = 18,272 x $1,798 = $32.85 million.

Finally, if both courses were adopted (i.e. primary teacher/student ratios and average salary levels reduced to NSW levels), the total saving would be as follows:

(Reduced number of primary school teachers) x (Difference between Victorian and NSW average salary level for primary school teachers) + (Saving in teacher numbers x average Victorian primary school teacher salary)
i.e. (18,272 - 3,611) x $(34,131 - 32,333) + ($123.25 million)
= (14,661 x $1,798) + $123.25 million
= $26.36 million + $123.25 million = $149.61 million.

Similar calculations can be done for other categories of primary school staff, for the same categories of staff in secondary schools and, as noted above, for all these categories on the basis of equalization, not with the NSW standard, but with the much less exacting standard of the Australia-wide average. Results of such calculations are presented in Table 2.14.

Table 2.14: Victoria: Potential Savings ($ million) from Equalization of Standards
for Staff Categories indicated with Levels of:

	NSW	Australia
PRIMARY SCHOOLS a. Teachers: 1) Teacher/student ratio 2) Average salaries 3) Both (1) and (2) b. Other School-based Staff: 1) Staff/student ratio 2) Average salaries 3) Both (1) and (2)	123.25 32.85 149.61 -8.99 12.64 5.59	71.23 35.80 102.94 -17.08 9.39 -4.95
SECONDARY SCHOOLS a. Teachers: 1) Teacher/student ratio 2) Average salaries 3) Both (1) and (2) b. Other School-based Staff: 1) Staff/student ratio 2) Average salaries 3) Both (1) and (2)	138.18 0.38 138.49 -6.23 17.56 12.81	86.05 13.45 97.90 -9.35 8.43 0.14
SPECIAL SCHOOLS a. Teachers: 1) Teacher/student ratio 2) Average salaries 3) Both (1) and (2) 4) Reduction in student population ^(a) 5) Both (1) and (4) b. Other School-based Staff: 1) Staff/student ratio 2) Average salaries 3) Both (1) and (2) 4) Reduction in student population ^(a) 5) Both (1) and (4)	11.44 0.94 12.14 16.18 23.41 -10.14 1.05 -7.24 2.12 -4.28	7.20 0.41 7.54 6.23 12.39 -8.50 1.01 -6.00 0.82 -6.47
NON-SCHOOL-BASED STAFF 1) Staff/student ratio 2) Average salaries 3) Both (1) and (2)	28.43 -9.84 21.84	6.56 4.49 10.71

^(a) Calculated by assuming that the number of special school students in Victoria was reduced so as to bear the same proportion to Victoria's total student population as the proportion of special students in NSW (or Australia as a whole) to the total student population of NSW (or Australia as a whole).

What conclusions can be drawn from the foregoing material? In particular, what can be said about the relative roles of State educational policies, on the one hand, and relative efficiency of delivery of educational services, on the other?

The first point on which to remark is the difficulty, in many cases, of separating these two concepts in practice. For example, if a State Government has conceded more readily to the demands of its teachers' union than other State governments, so that its schools are characterized by a much higher proportion of teachers to students, the efficiency of delivery of educational services cannot be assumed to be enhanced.

Issues of this kind will inevitably be in some degree -- and perhaps in large degree -- judgmental. For what it is worth, therefore, we set down the following summary judgments.

First, there is no convincing evidence that the higher teaching staff/student ratios in Victoria have produced any parallel improvement in the quality of educational output. To the extent that the relative pace of "drift" from the government school system to the non-government school system, as between the States, offers any indication in that regard, it is noteworthy that Victoria over the past decade has recorded the fastest rate of such "drift", and that, broadly speaking, it is still doing so.

Secondly, there seems now to be a considerable body of opinion on the effect of differences in class sizes (teacher/student ratios). For example, a report on the subject published in March 1988 by the US Department of Education, entitled Class Size and Public Policy: Politics and Panaceas, summarized the results of studies undertaken in the USA in the previous 25 years to determine the effects of significant reductions in class size. Its most striking conclusion is that, except in groups of 15 or under, these reductions have made little difference to pupil performance.

The author of this report points out that pupil achievement in such reduced classes, measured by standardized tests, has not risen. Indeed, in key areas (e.g. Scholastic Aptitude Test English and Mathematics) it has declined. Yet in Japan, where classes are larger than they are in the USA, tests scores have risen.

Nearer to home, Professor Ross Parish, writing in 1987 on education in Spending and Taxing: Australian Reform Options (National Economic Priorities 1987) quotes the 1973 Report of the Interim Committee for the Australian Schools Commission as recommending funds to reduce the size of classes, but adding that "there is no evidence to show that small classes generally facilitate learning". After surveying the evidence, Parish himself concludes that "low student/teacher ratios should no longer be regarded as evidence of high quality education, but rather as indicative of low teacher productivity".

Two years later, the Report of the Committee of Review of NSW Schools (the Carrick Committee) expressed a similar opinion, as follows:

"The research evidence suggests that to get real benefit, class sizes would have to be reduced so drastically as to be financially unrealizable. Using available resources including funding to provide, for example, on-going professional development programs may be a more effective means of promoting student achievement".
"Available evidence suggests that test scores and other measures of success in certain learning areas are not related to class size; that there is a relationship between class size and particular teaching practices, student activities and student-teacher interaction: that there are factors which over-ride class size in the development of desirable learning outcomes and student attitudes". (Carrick Committee, September 1989, page 130).

A more recent US survey than that referred to earlier also comes to the same conclusion. A paper entitled Efficiency And Inefficiency In The Texas Public Schools, and co-sponsored by the National Centre for Policy Analysis, quotes a survey conducted by Eric Hanuskeks and published in Educational Researcher (May 1989) under the title The Impact of Differential Expenditures in School Performance. Among other things, the paper records the result of examining 152 previous studies of the relationship between increases in the teacher/pupil ratio and student achievement. Some 14 of these studies found an increase in student achievement, and 13 a reduction; the overwhelming majority (125) found that increasing the teacher/pupil ratio made no difference (i.e. to the pupils -- it clearly made life more pleasant for the teachers).

Thirdly, a quite separate strand of evidence pointing to similar conclusions about costs of educational inputs relative to outputs in the governmental systems generally is provided by figures relating to the relative costs of providing education in government versus non-government schools. On this (among other aspects of the Tasmanian education scene), the Premier of Tasmania issued last May a paper prepared by the Tasmanian Department of Treasury and Finance (15 May, 1990).

The Treasury, basing itself upon Grants Commission data for 1985-86, quotes the Commission as saying that, for primary schools, "it was also evident that the relatively high staff:student ratios in the government sectors of Victoria, South Australia and Tasmania were not reflected in correspondingly high staff:student ratios in the non-government sectors in those States".

In Tasmania, where the primary school teacher/student ratio in 1985-86 was 17.5 per cent above the national average in government schools, it was little different from (1.7 per cent above) the national average in the case of non-government schools. Whereas the ratio of other primary school-based staff in Tasmania's government schools was 39.0 per cent above the national average, in the case of non-government schools it was only 18.7 per cent above the national average.

More generally, the Tasmanian Treasury appears to be in no doubt that, as stated in its comments upon the Tasmanian government secondary school system:

"As was the case with primary education, there is strong prima facie evidence that Tasmania's spending was much less efficient that in the other States" (presumably, other than Victoria).

And:

"As was the case with primary education, the only factor where the Commission assessed Tasmania as having a significant disability was head-office scale" (assessed as being 3 per cent of the standard). "On this basis it is difficult to accept that having 85.2 per cent more out-of-school staff per student can be justified".

A further Tasmanian contribution to the debate comes from Dr Gerard Johnston, of the Centre for Education at the University of Tasmania, in a letter to the Hobart Mercury of 30 July, 1990. Pointing to "the continuing drift in enrolment from public to private schools", Dr Johnston says that:

"There is research evidence to show that the average ability of students transferring from the public to the private sectors in Tasmania is significantly higher than of their peers remaining in the public schools".
"Authoritative studies in both the United States and United Kingdom have shown that probably the strongest in-school influence on a student's achievement is the potential of their peers".
Although "parental motives for preferring private to public schooling are no doubt diverse and mixed, .... a principal reason is that the private schools offer a more traditional curriculum in a more traditionally operated school environment".
"Students who attend such schools do better on test scores, examination results and retention".
"When such practices are adopted in public schools, similar results are achieved".
There is a "growing divide between schools of these two broad categories, with the public schools rapidly becoming those of second resort".
"Their greater commitment to elective, welfare, personal development and vocational studies, than is evident in their private school counterparts, can be seen as inimical to optimum achievement either in the narrow terms of examination success or the broader terms of understanding the world".

While Dr. Johnston's letter is expressed in general terms, one cannot but wonder how much of the above-standard resources being expended in Victorian and, to a lesser degree, South Australian and Tasmanian schools is being devoted to that "greater commitment" referred to in his final point quoted above, with consequences there delineated.

In summary, we submit that the foregoing examination of the various categories of education expenditure, and the factors influencing such expenditures, suggests differences among the States between standardised per capita expenditures and actual per capita expenditure are largely a reflection of differences in efficiency.

3. HEALTH SERVICES

3.1. COMPARISON OF TOTAL HEALTH EXPENDITURES

In 1988/89 the States spent an average of $613.35 per capita on health services. Health is the second largest area of expenditure after education services and is also one of the fastest growing. Between 1984/85 and 1988/89 State outlays on health services grew annually on a real per capita basis by 3 percent (CGC, 1990). (7)

As for education, expenditure on health services varied significantly amongst the States with Western Australia the highest at $699.92 per capita followed by Victoria at $646.53 and the lowest being Qld at $462.16 (Table 3.1). This differential of 50 percent in actual per capita health expenditure between WA and Qld constitutes one of the largest amongst all areas of State expenditure.

Most importantly, the expenditure differentials between the States are largely a result, not of relative disabilities in providing health services (as to which see below) but of differences between actual and standardised per capita expenditure after allowance for any such disabilities. As shown in Table 3.1, in 1988/89 Qld spent 39 percent below standardised level and Victoria (the highest spending State on health services after adjusting for needs and disabilities) 12 percent above. WA's high actual level of expenditure was to a large extent explained by disabilities. Nonetheless, other factors were also significant, as it spent 6.5 percent above the standardised level.

The health expenditure differentials between Qld and the other States are not a recent phenomenon. CGC (8) found Qld's expenditure in 1977/78 to be the lowest of all States and 17 percent below the six State average. CGC (9) found Qld to have per capita expenditure in 1965/66 above the six State average, and above Victoria and NSW, although spending was less than the other then claimant States, ie. WA, Tasmania and South Australia.

The expenditure differentials between Qld and the other States have in fact increased over the last half decade. Moreover policy factors have been the primary reason for Qld being able to restrain its expenditure relative to the other States. As shown in Figure 3.1, the gap between actual and standardised health expenditure increased steadily in Qld's case between 1984/85 and 1988/89. Victoria and Western Australia on the other hand have pursued health policies which resulted in the maintenance of relatively high expenditure levels.

TABLE 3.1
HEALTH 1988/89

	NSW			VIC			QLD
	ACTUAL	SINDSD	% DIFF	ACTUAL	STNDSD	% DIFF	ACTUAL	STNDSD	% DIFF
TOTAL HEALTH SERVICES	616.99	592.36	4.2%	646.53	577.73	11.9%	462.16	642.04	-28.0%
4310 Gen Medical Services	598.70	570.21	5.0%	624.91	556.58	12.3%	445.04	617.53	-27.9%
4320 Fam & Childrn Health Serv	5.34	6.85	-22.1%	8.20	6.25	31.2%	4.38	7.98	-45.1%
4340 Childrens Dental Serv	2.29	4.20	-45.5%	3.14	4.09	-23.1%	5.98	4.79	24.7%
4380 Public Health -- Other	10.66	11.10	-3.9%	10.28	10.81	-4.9%	6.76	11.73	-42.4%
	SA			WA			TAS
	ACTUAL	SINDSD	% DIFF	ACTUAL	STNDSD	% DIFF	ACTUAL	STNDSD	% DIFF
TOTAL HEALTH SERVICES	643.95	670.74	-4.0%	699.92	657.46	6.5%	632.62	659.79	-4.1%
4310 Gen Medical Services	608.05	648.10	-6.2%	665.57	631.90	5.3%	589.28	634.01	-7.1%
4320 Fam & Childrn Health Serv	9.07	6.52	39.2%	9.16	8.23	11.3%	11.00	7.56	45.4%
4340 Childrens Dental Serv	7.39	4.22	75.1%	7.71	4.79	61.0%	13.39	5.04	165.7%
4380 Public Health -- Other	19.44	11.91	63.3$	17.47	12.53	39.4%	19.15	13.18	45.3%

FIGURE 3.1
TOTAL HEALTH

The health policy differentials between the States, particularly between Qld and Victoria, raise major issues relevant to the question of efficiency. Qld's performance, and to a much lesser degree those of SA and Tasmania, suggests that there is potential for States to adopt health policies which contain expenditures without significantly reducing the level or quality of service. It is interesting that, while Commonwealth health policies are designed to be neutral in terms of interstate impact, the heterogeneity of health expenditures and policies amongst the States indicates that this does not produce uniformity. (10)

3.2 SOURCES OF POLICY DIFFERENTIAL

Expenditure per capita on general medical services (GMS) (see Appendix 3.1 for a description) accounts for 96 percent of total health expenditures, and includes inter alia all expenditure on public hospitals and allied services, nursing homes and psychiatric institutions. Expenditure in 1988/89 on GMS is decomposed into unadjusted, needs and policy components in Table 3.2. The unadjusted expenditure differential, which is the difference between the actual and standard (average of six States plus the Northern Territory) expenditures, arises from the combination of two factors, needs or cost disabilities (standardised/standard) and policy (actual/standardised).

TABLE 3.2
GENERAL MEDICAL SERVICES EXPENDITURE RATIO -- 1988/89

	NSW	VIC	Qld	WA	SA	TAS	*STANDARD
Total Difference (Actual/Standard)	1.015	1.059	0.754	1.128	1.030	1.075	1.000
Needs (Standardised/Standard)	0.967	0.944	1.047	1.071	1.099	0.999	1.000
Policy (Actual/Standardised)	1.050	1.123	0.721	1.050	0.938	1.076	1.000

* Averaged Six States and Northern Territory

Source: Commonwealth Grants Commission (1990)

As for total health expenditure, there is substantial variation in actual expenditure on GMS across States. Moreover, policy factors are the primary cause of these differences.

Qld and Victoria are the two extremes in policy terms, with Qld being 28 percent below standardised level and Victoria 12 percent above. NSW, WA and Tasmania are also relatively high spending States as a result of policy decisions.

3.3 ESTIMATION OF NEEDS

The CGC estimates the standardised expenditure for GMS by adjusting actual State expenditure for identifiable influences on the cost of providing health services which can be attributed to factors outside the control of the State.

The CGC is not able to obtain direct information on the characteristic of demand for hospital services, such as case mix, or health status of respective populations. Instead it uses available data on service utilisation to derive a standardised measure of demand for hospital services.

The factors used to assess the needs or demand for GMS include units of use, dispersion, age/sex, scale, social composition, cross border influences and private sector influences, isolated person travel, and combined factor influence (see Appendix 3.1 for a more complete description of assessment methodology and summary of factor estimates for 1990).

3.4 EXAMINATION OF DEMAND CHARACTERISTICS

It is useful to examine some characteristics of demand, e.g. capacity, occupancy rate, utilization rate and case load/mortality rates, as a guide to assessing whether the quality of GMS differs significantly across States and whether there is a difference in capacity utilisation across States. In particular, it is useful to try to assess whether Qld provides a lower quality of health services by limiting access or use of health services. Unfortunately, the only relevant available data relate to 1985/86. However, as there has been a widening in relative policy differences between Qld and other States since 1985/86, it can be assumed that the data for that year remain relevant in assessing contributions to such policy differences in 1988-89.

3.4.1 Capacity

Figure 3.2 shows the supply of acute beds relative to population by State. Qld has the highest supply of acute beds in the private and public sectors combined and the highest ratio of acute beds in the public sector. Victoria has a relatively low supply of beds.

FIGURE 3.2
Acute Bed to Population Ratio by State, 1985/86

Source: AIH (1988a)

Figure 3.3 shows the supply of nursing home beds relative to population by State. All States except Victoria have similar ratios of nursing home beds. Qld's supply of such services is not out of line with that of other States excluding Victoria.

FIGURE 3.3
Nursing Home and Hostel Beds per 1000 population Aged 65+, 1985/86.

Source: AIH (1988a)

FIGURE 3.4
Psychiatric Hospital Beds per 1000 Population, 1985/86

Source: AIH (1988a)

FIGURE 3.5
Acute Bed Supply and Occupancy by State, 1985/86

Source: AIH (1988a)

Figure 3.4 shows that there is significant variation between the States in the supply of psychiatric hospital beds relative to population. Qld provides a below average level of such facilities, though more than WA. (However, much of the difference in supply indicated in Figure 3.4 could be due to statistical error, as there is wide variation in the organisation and definition of such services).

3.4.2 Occupancy Rates

Figure 3.5 shows that, as well as having the highest supply of acute beds, Qld had the lowest occupancy rate of such beds. This implies that the waiting list for acute beds was less in Qld. Victoria and NSW have the highest occupancy rates and lowest acute capacity, which implies longer waiting lists.

3.4.3 Capacity Utilisation Rates

Figure 3.6 shows total equivalent occupied bed days (inpatient plus adjusted outpatient) per 1000 population for public hospitals in the States. With the exception of the Northern Territory and SA there is little variation in utilisation across the States. Qld had slightly less than Victoria but was on a par with WA. Victoria's higher utilisation rate relative to Qld was achieved by a high level of outpatients. Since equivalent occupied bed days were calculated by combining outpatients and inpatients using a rather arbitrary formula, the differential in utilisation rates between Victoria and Qld may be less than that suggested by Figure 3.6.

3.4.4 Case Load

The CGC (11) constructed an index of health status by calculating standardised mortality rates (SMR). This index was used by the AIH to examine the relationship between acute hospital admission rates and SMR for 1984/85 and it is shown in Figure 3.7. There appears to be no pattern to this relationship -- a major reason for the CGC discontinuing the index after 1982. It does, however, indicate that the mortality rate in Qld is near the average of the six States and, assuming a high association between mortality and morbidity rates, Qld case load is not significantly different from that of other States.

Butler (12) examined over 400 hospitals in Qld and NSW to test whether case loads of Qld and NSW hospitals differed significantly and whether this difference helped to explain differences in hospital expenditure. He found case loads to be similar and not to be significant determinants of cost differentials.

3.4.5 Conclusions

In terms of capacity utilisation, and greater use of cheaper outpatient services, Victoria and NSW appear to maintain more efficient public hospitals. Although caution must be shown in drawing conclusions from this data, and much of this variation is taken into account by the CGC in the estimation of needs, some general implications are:-

Qld does not appear to face significantly different demand for services beyond the factors used to adjust for need by the CGC i.e. dispersion, social status, and scale.
Qld is more "generous" in terms of access and availability of GMS. Moreover, from general discussion with medical officers, there is no basis for arguing that there is a significant difference in the medical competence of hospital professions between States. Thus one can surmise that, in terms of access, availability and technical service, the quality of Qld's services is at least no worse than other States.

FIGURE 3.6
Utilisation of Public Hospitals, 1985/86

Source: AIH (1988b)

FIGURE 3.7
Standardised Mortality Ratios (1984/85)
and Acute Admission Rates (1985/86).

Source: AIH (1988d) and CGC (1982)

Indeed Qld could possibly reduce its costs even further relative to the other States by bringing its utilisation and capacity rates closer to the seven States average.
Demand and supply characteristics do not appear to be the major determinant of expenditure differentials between States.

3.5 ESTIMATION OF COST DISABILITIES

In estimating the standardised level of expenditure for GMS the CGC makes allowances for factors that can contribute to higher unit costs in hospitals. These include scale in administration and super-speciality units, dispersion, interstate services, non-State services, and all the factors considered in the calculation of need (Appendix 3.1).

The CGC does not generate data that allows the disaggregation of the policy factors causing per capita expenditure on GMS to differ from the standardised level. Nor does any other source provide data that would allow such identification.

The most recent and useful sources of information and analysis for exploring the policy differentials of State health expenditure are the ratio analysis found in CGC (1988b) (13) and the interstate cost comparisons found in AIH (1988a) (14) and AIH (1988b) (15). These studies are based on separate collections of public hospital data from States and Territory health authorities in 1986 and cover data for the 1985/86 fiscal year. Both studies compare actual expenditure on key functions or inputs with the corresponding standard or six State plus Territory average in an effort to understand more fully the needs and policy factors which give rise to the cost differentials.

It is recognised that the CGC (1988b) (13) ratio analysis and the AIH (1988a) (14) and (1988b) (15) are dated and do not directly isolate policy factors. They do however provide a good explanation of the major policy differences between States in the hospital area. As the policy differences between the States have increased since 1984/85, as shown in Figure 3.1, the factors contributing to policy differences which existed in 1984/85 are likely to provide a good, albeit probably a conservative, estimate of the factors contributing to current policy differences.

3.6 LABOUR COSTS

Table 3.3 divides total per capita expenditure on public hospitals in 1985/86 between labour and non-labour expenditures and compares these with the State/Territory average. Labour costs account for 74 percent of hospital expenditures.

There is significant variation in labour costs across the States and this variation is similar in pattern to the variation in GMS expenditure (Table 3.2). Qld had the lowest labour cost expenditure per capita and WA had the highest. However, one difference between the 1988/89 data on GMS and 1985/86 hospital data in Table 3.3 is that in the latter Victoria had a below average level of labour expenditure per capita while it had an above standard level of GMS expenditure in 1988-89.

TABLE 3.3
ACTUAL PER CAPITA EXPENDITURE FOR LABOUR AND NON-LABOUR RELATED ACTIVITIES,
PUBLIC HOSPITALS, 1985-86

	NSW	Vic	WA	Qld	SA	Tas	NT	Seven-State Standard
Labour Expenditure per capita ($) Ratio of actual to standard expenditure	275.50 1.0781	247.31 0.9678	201.70 0.7893	277.59 1.0862	262.55 1.0278	261.35 1.0227	388.08 1.5186	255.55 1.0000
Non-Labour Expenditure per capita ($) Ratio of actual to standard expenditure	95.74 1.0638	76.86 0.8540	82.85 0.9205	100.41 1.1157	104.28 1.1587	83.32 0.9259	157.24 1.7471	90.00 1.0000
Labour expenditure as proportion of total expenditure	0.7421	0.7629	0.7088	0.7344	0.7158	0.7582	0.7117	0.7395

Source: Commonwealth Grants Commission (1988b)

Labour-related expenditure accounts for 74 per cent of standard hospital expenditure. Differences between the States in per capita labour expenditure result from the level of salaries paid, staffing structures and the number of staff employed per capita. Staffing levels in turn are related to the number of beds provided and the number of staff servicing each bed. Table 8-3-4 shows the relevant salary and staff ratios, as compared with the standard, for each of the States and Territories.

3.6.1 Salaries

Table 3.4 gives average staffing ratios and average salary levels by State. Average salary for total staff did differ across States. However, variation in salary levels does not appear to account for a large part of the variation in labour costs. The two most populous States, Victoria and NSW, had above average salary levels (3 percent and 2 percent respectively). Qld and Western Australia had below average salary levels.

The salary variations between States appear largely to have been policy determined. States which exhibited above or below average salaries did so across all types of staff and for most types and locations of hospitals. Thus Victoria and NSW paid high salaries to all staff whereas Qld paid lower salaries across the board (CGC 1988b (13), pg 902).

3.6.2 Total Staffing Levels

Average total staff levels varied significantly across States and appear to be a major factor in explaining variation in labour cost across States (Table 3.4). Victoria had the highest total staff level measured in full time equivalent staff per occupied bed at 11 percent above standard. WA and Tasmania also had above standard staffing levels. Qld had a total staff level 10 percent below standard. The CGC (1988b) (13) and the AIH (1988a) (14) indicated that policy differences were a major cause of these variations in staff levels.

Intrastate variations in staffing levels also appear to be significant determinants of hospital cost, particularly between Qld and WA. AIH (1988a) (14) found that intrastate variation in staffing ratios was up to 50 percent and significantly larger than typical interstate variations of 5-10 percent. The CGC (1988b) (13) found that hospital costs did not vary significantly between remote and non-remote areas, except in WA, which implied that States generally adjusted staff ratios and mix according to demand in remote areas. AIH (1988b) (15) found that a major factor in explaining Qld's low cost per bed was their flexible staffing policies, particularly in remote areas.

3.6.3 Staff Mix

Table 3.5 shows the relative proportions of the different staff classes across States. Victoria had the highest staffing ratios for all classes of staff except for salaried medical officers (SMO). Qld had low staffing ratios for nurses, administration, clerical and domestic. The stark and uniform differences between the two States led the CGC to conclude that:

"this suggests that in those States, Qld and Victoria, policy influences were the dominant factor in determining the differences in staffing levels" CGC (1988b, (13) pg 907). Western Australia and Tasmania also had above standard total staffing levels.

The mix of staff, particularly between technical and non-technical, appears to be a key policy factor in explaining interstate variation in hospital costs. Qld, the lowest cost State, appears to pursue a staffing policy strongly weighted towards technical staff and the containment of non-technical staff numbers. (Table 3.5) Qld had proportionately a high number of nursing and SMO staff and its proportion of diagnostic and technical staff was just slightly below average. In contrast it had a very low proportion of administrative and domestic and other staff. The two high cost States, Victoria and WA, pursued opposite labour policy stances, by giving greater weight to non-technical than to technical staff. Both Victoria and WA had proportionately low numbers of SMO, nursing and diagnostic staff and proportionately high numbers of administrative and clerical and domestic staff. The differences in staffing priorities are also shown in Table 3.4 on a per bed day basis. Victoria and WA had staffing ratios for other (non-technical) staff of 12 percent above standard while Qld was 20 percent below standard. While some caution is required because of classification problems, it is thus quite clear that Qld economises on non-technical staff.

TABLE 3.4
Components of Average Salary Cost per Bed Day,
as % Deviation from National Average for Public
Hospitals by State, 1985-86.

	FTE staff per occupied bed ^(a)	Av. salary per FTE staff	Av. salary cost per bed day ^(b)
NSW Salaried Medical Nursing Staff Other staff Total staff	0 -11 -1 -5	1 4 1 3	8 -2 6 3
Vic Salaried Medical Nursing Staff Other staff Total staff	-5 13 12 11	1 2 2 2	-15 -1 -2 -3
Qld Salaried Medical Nursing Staff Other staff Total staff	-5 1 -20 -10	-2 -7 -4 —4	-4 -5 -23 -13
SA Salaried Medical Nursing Staff Other staff Total staff	5 4 -8 -2	1 -6 -5 -4	10 -1 -12 -4
WA Salaried Medical Nursing Staff Other staff Total staff	-10 -1 12 5	-4 -1 0 -2	0 7 22 13
Tas Salaried Medical Nursing Staff Other staff Total staff	-10 11 2 6	-5 -9 -11 -10	0 17 4 9
NT Salaried Medical Nursing Staff Other staff Total staff	35 20 21 22	7 4 -2 3	50 25 20 25
ACT Salaried Medical Nursing Staff Other staff Total staff	5 11 7 9	2 8 17 6	17 32 25 24

Source: Survey of Public Hospitals, 1985/86.

Notes:

^(a) Total FTE staff divided by (actual occupied bed days)/365. Occupied bed days not adjusted for outpatient services.

^(b) Total bed days adjusted for outpatient services.

TABLE 3.5
BREAKDOWN OF PUBLIC HOSPITAL STAFFING LEVELS, 1985-86

State	Salaried Medical Officers	% of Total Staff	Nursing Staff	% of Total Staff	Diag Prof. & Tech	% of Total Staff	Admin & Clerical Staff	% of Total Staff	Domestic & Other Staff	% of Total Staff	Total Staff
NSW	3267	5.56	24740	42.12	9145	15.57	6683	11.38	14906	25.38	58741
Vic	1878	4.57	18768	45.66	3750	9.12	4876	11.86	11831	28.78	41100
Qld	1289	5.57	11640	50.28	2265	9.78	1996	8.62	5946	25.68	23151
WA	766	4.66	6930	42.21	1702	10.37	2115	12.88	4905	29.87	16419
SA	883	5.64	7460	47.64	1599	10.21	1785	11.40	3932	25.11	15660
Tas	243	4.50	2544	47.18	545	10.12	427	7.92	1633	30.29	5391
MT	142	5.94	1055	44.19	209	8.77	248	10.39	733	30.71	2387
ACT	147	5.08	1373	45.71	300	10.62	552	19.12	562	19.47	2885
Average ^(a)	1210	5.21	10448	45.61	2745	10.56	2590	10.64	6269	27.97	23264

^(a) Simple seven-State average

Source: Collection of Public Hospital Data from State and Territory Health Authorities, 1986, Commonwealth Grants Commission (1988b)

More importantly, the available evidence suggests that Qld's lower level of non-technical staff in public hospitals is more an indication of cost efficiency, rather than lower quality of service. Qld has achieved its low level of administrative staff by maintaining a highly centralised public administration system, with budget and overall staff decisions being made in Treasury. This decreases the need for hospital and non-hospital based administrative staff and thereby has reduced the capacity of hospital workers' unions to capture hospital budgets. Moreover, given that Qld's public administration costs are, after adjusting for needs and costs disability, on a par with the other States, (CGC (1990), there is no evidence to suggest that the lower hospital administration costs are shifted to other public sector areas.

Butler (12) supports the above conclusion and states that: "Queensland's higher degree of centralised control over its hospitals is responsible for its superior cost performance."

The centralised control also applies to domestic and other staff and thus is likely to explain Qld's low staff levels in these areas.

3.6.4 Nursing Staff Levels

Variation in the composition of nursing staff also appears to be a significant explanatory policy factor (Table 3.6). Qld differed from all other States in that it used a very high proportion of student nurses and a corresponding low proportion of registered nurses. Student nurses would naturally tend to lower the average nursing salary. Since 1985/86 there have been significant changes to nursing education in most States, including Qld, which entail a shifting away from hospital-based training to academic training. These changes may have reduced the observed difference in composition of nurses.

3.6.5 Non-Labour Expenditure

There is some variation in non-labour costs (Table 3.3). NSW, WA and SA have above-standard non-labour expenditure. SA expenditure on non-labour items is particularly high at 15 percent above standard. The main areas of non-labour expenditure were medical and surgical supplies and the cost of drugs. There was substantial variation in the cost of patient transport, food supplies, and other, on-costs. However, the vagaries of classification and lack of case load and other data prevent further analysis of non-labour expenditure.

3.7 WORKING WEEK

Qld nurses still have a 40 hour week, while all other States maintain a basic 38 hour week. This policy difference translates into a 5 percent higher level of productivity for Qld in the nursing area relative to other States.

3.8 TEACHING FACILITIES

WA maintains, as a policy decision, a higher proportion of high cost teaching facilities-than other States. The cost per occupied bed day (OBD) in a teaching hospital is on average 51 percent larger than in a non-teaching hospital (Figure 3.8). WA had the highest cost per teaching OBD and the second highest, after Tasmania, proportion of teaching beds at 34 percent of total.

TABLE 3.6
BREAKDOWN OF PUBLIC HOSPITAL NURSING STAFF LEVELS, 1985-86

State	Registered Nurses	% of Nursing Staff	Student Nurses	% of Nursing Staff	Enrolled Nurses	% of Nursing Staff	Trainee Nurses	% of Nursing Staff	Other Nurses	% of Nursing Staff	Total Nursing Staff
New South Wales	17184	69.46	2656	10.73	3670	14.83	959	3.88	271	1.10	24740
Victoria	11406	60.77	3319	17.69	3236	17.24	472	2.51	335	1.78	18768
Queensland	5027	43.19	3282	28.19	2117	18.18	247	2.12	983	8.44	11640
Western Australia	3957	57.09	765	11.05	1667	24.05	166	2.40	375	5.41	6930
South Australia	3813	51.10	1441	19.31	1758	23.56	279	3.75	170	2.28	7460
Tasmania	1517	59.66	580	22.81	271	10.64	0	0.00	175	6.89	2544
Northern Territory	644	61.01	85	8.06	187	17.70	19	1.80	121	11.43	1055
Australian Capital Territory	11000	72.83	179	13.04	128	9.32	46	3.35	20	1.46	1373
Average ^(a)	6221	57.47	1733	16.83	1844	18.03	306	2.35	347	5.33	10448

^(a) Simple seven-State average.

Source: Collection of Public Hospital Data from State and Territory Health Authorities, 1986.

FIGURE 3.8
Average Cost per Patient * by State, Teaching and Non-teaching Hospitals, 1985-86.

The CGC in assessing needs does allow a portion of teaching infrastructure by adjusting for scale in the provision of super-speciality beds and administration. This adjustment does not fully explain WA's high level of teaching quality services. First, the CGC decided to discontinue adjusting for scale in terms of the number of undergraduate medical students because it considered the variables to be largely policy determined. As such, the number of student and number of medical schools are explicitly excluded from the calculation of needs. Second, all WA large hospitals were teaching units; it does not have large non-teaching (type 2) hospitals. Third, since WA does not have any type 2 hospital, its hospitals were not used in the calculation of super-speciality scale factors. Rather WA was assumed to have the same level of scale disability as SA, even though from the available data WA had higher costs and proportion of super-speciality hospital beds.

3.9 NON-STATE SERVICES

There is significant variation amongst the States in terms of the substitution of private inpatient services for public services. The extent of substitution is determined by availability and relative price of private inpatient services.

The CGC (1990) estimated the impact on GMS expenditure of the availability of private service assuming equal prices, perfect substitutability and causations split equally between policy and need factors. These estimates, which are presented in Table 3.7 and cover the 1984/85 to 1988/89 period, show the percentage of deviation from average expenditure as a result of policies toward private sector supply of inpatient health services.

TABLE 3.7:
GENERAL MEDICAL SERVICE -- POLICY IMPACT
OF NON-STATE SERVICES, 1984/85-1988/89

	*
NSW	1.00
VIC	0.995
Qld	1.055
WA	1.065
SA	1.057
TAS	0.995

* Indicates the degree of above standard or average expenditure caused by above or below average private sector inpatient services; weight average impact of acute, non-psychiatric, chronic non-psychiatric, psychiatric and non-clinical categories of services.

Source: Commonwealth Grants Commission (1990)

WA is estimated to have a 6.5 percent above average expenditure on GMS because it has pursued policies which inhibited the supply of private sector services. Qld and SA are also estimated to have pursued such policies.

The CGC's estimates of non-State services should be treated with caution. The relative prices of private inpatient service have been significantly increased in recent years as a result of changes to Medicare and the Commonwealth placing a 45 percent limit on the proportion of private patients using public hospitals. Both of these changes are due to Commonwealth policies, and limit the extent to which existing private facilities can reduce the cost levels of State public services.

Given that private hospitals are on average cheaper than public hospitals (Table 3.8), the move away from private to public hospitals is not only placing significant strain on the State health budgets but is also forcing resources and activities away from the lowest cost form of service delivery.

TABLE 3.8:
HOSPITAL COST PER OCCUPIED BED DAY
IN THE PRIVATE AND PUBLIC SECTOR IN AUSTRALIA 1988

	Public Hospital	Private Hospital
Including Medical Costs	$345	$245
Excluding Medical Costs	$289	$164

Source: Australian Private Hospital Association, National News, 1989

3.10 CONCLUSIONS

The major determinant of interstate differentials in public hospital expenditure is clearly staffing policy and, in particular, policies governing the level of non-technical staff.

The evidence suggests that the lower proportion of non-technical staff achieved by Qld is a result of cost efficiency rather than lower quality of services. There is no indication that this lower proportion has had adverse efficiency effects whether through a lower standard of health services or a reduced supply of health workers. This is supported by the fact that, while Qld's staffing policies and low hospital costs are of long duration, there is no evidence the lower wage/higher work load has resulted in a decreased supply of health workers.

Qld has also achieved lower costs by having a lower average skill mix of nursing staff and maintaining a basic 40 hour work week.

By contrast, Victoria's high expenditure differential is almost exclusively a result of its high levels of non-technical staff. In fact, in terms purely of capacity utilisation, it appears that it operates a more efficient hospital system. This presumably helps to compensate for its more "generous" wage and staffing levels.

WA's relatively high expenditure differential is a result of its higher non-technical staffing level, plus its high ratio of super speciality facilities. Given that there is no indication that the case load in WA is different from other States, WA's "over indulgence" in teaching facilities must be questioned on a cost efficiency basis.

Overall, as with education, there thus appears to be little evidence to suggest that inter-State differences in above standardised expenditure per head on health reflect the provision of higher quality health services. In the absence of evidence to the contrary, it must be concluded that the per head differentials largely reflect differences in the efficiency of delivery of services or, to put it another way, differences in productivity.

4. BUSINESS UNDERTAKINGS -- DEFICITS

4.1 INTRODUCTION

A significant portion of States' budget outlays goes on meeting the operating deficits of business undertakings. In 1988-89, such deficits ranged from 12 percent of total Victorian recurrent outlays to about 2.5 percent of total Tasmanian recurrent outlays included in CGC assessments.

The CGC includes in its analysis expenditure to meet the deficits of six business undertakings which regularly have an impact on the budgets of most States. These are:

metropolitan transit;
non-metropolitan passenger services;
non-metropolitan freight services;
coastal shipping services;
country water supply and sewage; and
irrigation and drainage.

The actual and standardised per capita expenditures on deficits of these undertakings in Table 4.1 show that NSW and Victoria provide easily the highest subsidies to these services. Indeed Victoria spent as much per capita ($272.82) on subsidising its business undertakings as Qld spent on law and order, welfare and culture combined. NSW had the second highest level of expenditure on business undertakings deficits at $255.90 per capita. The lowest was Tasmania (which no longer itself operates any railways rather these services are provided via Australian National Railway [ANR]) at $57.26 per capita. Expenditure on business undertakings deficits showed the largest variations in per capita expenditure across the States.

The differences between actual and standardised expenditures are large. Victoria has the highest such differential at 21.1 percent followed by NSW at 17.5 percent. All other States have large negative differentials, with Tasmania having the lowest at -63.3 percent. Thus, policy factors result in per capita expenditure differences of nearly 85 percent across the States.

4.1.1. Issues of Analysis

There are two somewhat related issues in examining the policy induced differences in expenditure on business undertakings across the States, viz:

Whether the service provided is intrinsically a public good -- defined as a good which has positive effects on individuals other than the consumer of the service and which would be under-supplied if left entirely to the private sector. For example, public transport reduces the congestion costs of motorists and reduces the need for public spending on roads; and
Whether the service is provided at lowest possible cost.

For most business undertakings included in the CGC expenditure analysis it cannot automatically be assumed that they should be treated as a public good and indeed, in many cases, they are clearly not wholly in that category. If they are not, and they are provided inefficiently, then there is a strong prima facie case that the losses met by State budgets for these services represent a misallocation of resources -- of considerable magnitude. This is indeed the conclusion we reach below for non-metropolitan transport.

TABLE 4.1:
BUSINESS UNDERTAKINGS DEFICITS -- PER HEAD 1988/89

	NSW			Vic.			Qld
	Actual	Standardised	% Diff.	Actual	Standardised	% Diff.	Actual	Standardised	% Diff.
Total Deficits	255.91	217.83	17.5	272.82	225.34	21.1	143.23	192.10	-25.4
Metropolitan Transit	125.93	125.48	0.4	147.21	114.37	28.7	60.50	86.99	-30.4
Non-Metro Passenger Service	37.94	31.39	20.9	40.11	37.47	7.0	30.46	25.65	18.7
Non-Metro Freight Service	61.96	36.63	69.1	56.97	36.63	55.5	5.10	36.63	-86.1
Coastal Shipping Services	0.00	0.81	-100.0	0.00	0.81	-100.0	0.00	0.81	-100.0
Country Water Supply & Sewerage	11.69	6.68	75.0	9.52	7.60	25.1	17.19	17.91	-4.1
Irrigation & Drainage	18.39	16.83	9.3	19.02	28.45	-33.2	29.98	24.10	24.4
	SA			WA			Tas.
	Actual	Standardised	% Diff.	Actual	Standardised	% Diff.	Actual	Standardised	% Diff.
Total Deficits	115.39	190.83	-39.5	120.68	176.32	-31.6	57.26	156.06	-63.3
Metropolitan Transit	85.19	86.11	-1.1	54.24	81.87	-33.7	30.14	63.97	-52.9
Non-Metro Passenger Service	17.58	37.15	-52.7	14.01	26.84	-47.8	4.26	40.66	-89.5
Non-Metro Freight Service	-25.02	36.63	-168.3	8.40	36.63	-77.1	21.75	36.63	-40.6
Coastal Shipping Services	3.74	0.81	362.2	9.04	0.81	1016.6	-13.80	0.81	-1804.0
Country Water Supply & Sewerage	25.44	13.48	88.8	27.28	23.57	15.8	10.12	8.44	19.9
Irrigation & Drainage	8.45	16.65	-49.3	7.70	6.60	16.7	4.79	5.54	13.6

Source: Commonwealth Grants Commission. "Report on General Revenue Grant Relativities 1990 Update" Appendices A and B.

As the public transport business undertakings represent 84 percent of the budgetary expenditure on business undertakings, only they are examined below. However, it should be noted that the conclusion reached for non-metropolitan transport, that is, that losses represent in full an inefficient use of resources, could equally well be applied to coastal shipping. (The position with country water and sewage supply and irrigation and associated drainage is, perhaps, more debatable).

4.2. METROPOLITAN TRANSIT

Of all the business undertakings, metropolitan transit has by far the largest impact on State budgets. After adjustment to put the various States' operations on a comparable basis, the CGC estimated in 1988-89 deficits of $1.7 billion, or an average of $106.60 per capita. To put this figure in perspective, it represents close to half the funds spent on operating all Australian public primary schools, or about 14 percent of total recurrent expenditure.

As shown in Table 4.1 the metropolitan transit losses are concentrated in two States, NSW and Victoria, which in 1988/89 subsidised their metropolitan transit operations by, respectively, $125.93 and $147.21 per capita. Tasmania, at $30.14 per capita, had the lowest level of budgetary expenditure on these services.

Table 4.1 indicates that there is significant variation in per capita expenditure on deficits of metropolitan transit services as a result of the different policy stances of the States. Victoria has, by a large margin, the highest policy induced level of expenditure, 28.7 per cent above standardised. NSW is the only other State to have above standardised level of expenditure at only 0.4%. All other States had negative differentials, with Tasmania recording the lowest at -52.9 per cent. The total variance in policy related expenditure differences was therefore an enormous 82 per cent.

4.2.1. Public vs Private Good

Clearly metropolitan transport does to a significant degree provide a public good. It reduces road congestion, the need (in its absence) for greatly increased public spending on metropolitan road and traffic systems, and pollution. The losses on such operations do not therefore necessarily provide an indication of poor resource use. Nor, however, does the existence of external benefits necessarily provide a justification for running losses, or at least for running losses above a certain level. These metropolitan transit services are to a degree private goods and therefore have the potential to be more commercially viable than they are.

However, rather than attempt to assesses the extent to which metropolitan transit is a public good and therefore the extent to which losses indicate misapplication of resources, the following analysis will concentrate on ascertaining the relative cost efficiency of States' services. If comparisons between States suggest that some States' metropolitan transit services are operated at higher than necessary cost and these costs are met by budget transfers, that can be judged to constitute a degree of misapplication of resources.

4.2.2. Source of Information -- CGC 1990 Review

The CGC applies the modified budget impact method (MBIM) to standardise expenditures for metropolitan transit. This method operates by adjusting actual expenditure, for policy differences.

That is by:

identifying policy factors;
estimating for each policy factor the extent to which a State deviates from the seven-State average;
calculating total policy modifications for each State as the sum of deviations across all policy factors; and
calculating standardised expenditure by adding total policy modifications (which is negative if expenditures were above average) to actual expenditure.

In contrast the CGC applies the factor assessment method (FAM) to all expenditure categories and other than business undertakings except metropolitan transit. Under the FAM, a cost disabilities or needs factor for each State is estimated, and added to the standard (seven-State average) level of expenditure to establish the standardised expenditure.

The two methods should yield the same estimate of standardised expenditure. But in terms of exploring policy derived cost differences, the MBIM is superior for it explicitly quantifies policy differences including differences in technical efficiency.

For metropolitan transit the CGC identifies six policy areas for which modifications are made (see Appendix 1 for description of method of assessment). They are:

wages and salaries;
operating efficiency;
fares;
non-State service (private buses);
level of service; and
debt charges.

Metropolitan transit services are further broken down into the alternative forms of public transit, i.e. buses and trams, and rail transport.

The per capita policy modifications for each State estimated for 1988/89 are provided in Table 4.2. Note that a negative modification indicates above standard (or average) expenditure.

TABLE 4.2:
PER CAPITA IMPACT OF POLICY MODIFICATIONS
IN METROPOLITAN TRANSIT 1988/89 ($)

State	Wages & Salaries		Efficiency		Fares & Service	Debt Charges	Private Bus Role	Total
State	B&T*	Rail	B&T*	Rail	Fares & Service	Debt Charges	Private Bus Role	Total
NSW	-1.6	-4.3	-5.3	5.2	1.7	2.6	1.2	-0.4
VIC	1.3	2.2	-12.1	-6.8	-3.9	-12.7	-0.9	-32.8
QLD	1.5	4.2	5.8	4.2	8.0	2.8	0.0	26.5
WA	-0.7	0.3	34.8	-5.2	-5.9	10.8	-6.4	27.6
SA	-1.1	2.2	4.8	-5.4	-3.2	5.9	-2.3	0.9
TAS	4.4	0.0	10.0	0.0	12.7	10.1	-3.3	33.8

* Buses and Trams

Source: CGC Working Papers Vol 2, April 1990.

4.2.3. Wages and Salaries

Figure 4.1 depicts the percentage difference in the average remuneration of employees in rail, bus and tram transport, in 1988/89 in each State from the average remuneration of such employees in the six States. NSW is the only State in which the average level of remuneration for the total system is greater than the national average. For rail, annual remuneration rates in NSW were $2,400 per worker higher than the average for the nation as a whole and accounted for nearly 40 per cent of its negative budget modifications for urban transit. Tasmania, which only operates a bus service, has remuneration rates which are the lowest in the country. Next comes Queensland, which has lower remuneration rates in rail than any other State.

The differences which occur may result from a number of factors. States may differ in the age/experience profile of their workforce. Add-on expenses may differ between States as a result of, for example, different regulations with respect to workers compensation arrangements. Labour markets in general will also vary between States. Transit authorities in some States (e.g. NSW where average weekly earnings are higher than those of other States) will be recruiting workers largely from a market in which the general level of wage rates is higher than elsewhere. Finally, differences in union militancy may be related to differences in remuneration. (16) The Grants Commission does not, however, take any of these factors into account in its assessment of needs.

Some indication of the causes of higher average wages in NSW can be obtained from the June 1989 Report on NSW's Cityrail by Booz, Allen and Hamilton (BAH). (17) That report identified an excessive level of staff fulfilling "overhead" functions. Thus, in November, 1988 Cityrail employed around 13,100 staff, of which around 300 were Corporate overhead and 800 Branch overhead -- i.e. nearly 7 per cent of the workforce operated in an overhead function.

FIGURE 4.1
RELATIVE NET REMUNERATION PER EMPLOYEE: 1988/89

CGC Working Papers Vol 2, April 1990.

In addition, BAH noted that, by comparison with other commuter operators, productivity levels at Cityrail were low and that these excessive staff levels were accompanied by inefficient work practices which imposed significant additional costs on Cityrail. In certain engineering branches (where wage rates were typically higher than average) non-observance of work and finish times contributed to lost productivity estimated at 25-50 per cent -- which meant that the employment of such personnel was up to double the number required. Costly demarcations within skilled (and generally well paid) groups -- especially electricians -- meant that more skilled workers must be employed than would normally be required. All of these factors tended to boost average earnings above those that might be found in other States. (18)

4.2.4. Operating Efficiency

Table 4.2 presents the policy modifications for operating efficiency separately for rail and bus/tram services. These modifications are calculated (see Appendix 1 for greater detail) by breaking the operations of the various services into cost centres and, using established cost indicators, and measuring for each State, type of service and cost centre, the extent to which it deviates from the national average.

In Table 4.2, a below average level of operating efficiency yields a negative policy modification for it causes standardised expenditure to be less than actual expenditure.

Variation in the efficiency of bus/tram services is by a substantial margin the largest source of expenditure variation. In 1988-89 Victoria had, by a substantial margin, the poorest efficiency outcome. The inefficiency of Victorian bus/tram services incurred a budgetary cost of $12.10 per capita and accounted for nearly 40 per cent of Victoria's total above standard expenditure. NSW was the only other State to have a below standard level of operating efficiency for bus/tram services. WA had a relatively efficient operation, yielding budgetary saving (below standard expenditure) of $34.80 per capita.

In making efficiency comparisons, the CGC treats a tram or an articulated bus as equivalent to 1.2 rigid buses. The Commission argues that trams should be included because the modes of transport chosen by different States are, for the most part, technically substitutable and other States have made such substitutions over time. Thus retaining trams in Melbourne is treated as a policy decision. That Melbourne tram operations are more expensive in terms of costs per vehicle hour is no argument for making special allowances when the appropriate comparison is between the operating efficiency of trams, with their attendant costs, and buses which have an alternative cost profile.

Table 4.3 shows a breakdown of the sources of efficiency modifications for bus/tram services on a per capita basis. It is clear that the main source of Victoria's efficiency problems is its tram services, more particularly its trams' traffic operations. Although Victoria's trams were relatively inefficient in all operating areas, NSW efficiency problems were also broadly based and significant. Overall the primary areas of efficiency differential were the traffic and rolling stock maintenance areas, although most States also had low levels of efficiency in the fuel, power and tyres and administration areas.

TABLE 4.3:
PER CAPITA EFFICIENCY MODIFICATIONS -- BUS AND TRAMS 1988/89 ($)

State	Traffic	Rolling Stock Maint.	Infra- Struc Maint.	Build & Grnds	Fuel Power & Tyres	Admin
NSW	-2.6	-2.6	0.5	0.0	-0.1	-0.5
QLD	5.6	0.4	0.5	0.1	-0.1	-0.8
WA	21.7	9.2	1.3	0.2	-0.3	2.7
SA	2.7	0.8	0.9	1.4	-0.2	-0.7
TAS	4.4	1.2	0.9	-1.2	-0.2	4.9
Vic Bus	-1.0	0.9	0.2	0.0	0.0	0.0
Vic Tram	-8.5	-1.6	-0.5	-0.5	-0.1	-0.1

Note; These figures are already adjusted for differences in labour costs

Source: CGC Working Papers Vol 2, April 1990.

It should also be noted that, compared with the private sector, the public sector bus operations are relatively inefficient. An analysis of the relative costs to the Victorian Transport Corporation of providing the internal and contracted services in 1988/89, presented in the Victorian Auditor-General's report, found that "on a cost per kilometre basis, the comparable cost of operating MET bus services is 48 per cent higher than for contracted private bus services. Based on kilometres covered by MET operations in 1988/89, this differential equates to higher annual costs to the Corporation of approximately $12.8 million". (19)

Given that labour costs (adjusted for wage and salary differentials) account for nearly 65 per cent of total operating costs, the efficiency differentials shown in Tables 4.2 and 4.3 are (except for the fuel, power and tyres area) primarily an indication of different labour policies. More specifically, Victorian trams are inefficient because of poor labour utilisation.

In the case of railways, as indicated in Table 4.4, Victoria has the least efficient metropolitan rail operations in the country, followed closely by South Australia and Western Australia. Victoria's poor performance was due to gross inefficiencies in station yard and signal operations and to excessive crew costs. NSW, on the other hand, is a comparatively efficient system on the criteria used by the CGC. However, given that BAH's assessment of the efficiency of Cityrail, noted above, including its assessment that Cityrail is losing over $110 million per year through excessive staffing and inefficient work practices (Figure 4.2), this suggests that there are very large inefficiencies in the systems operated by other States.

FIGURE 4.2
ANNUAL COST OF STAFFING INEFFICIENCIES IN CITYRAIL

Booz, Allen & Hamilton, 1989.

TABLE 4.4:
PER CAPITA EFFICIENCY MODIFICATIONS -- RAILWAYS 1988/89 ($)

State	Rolling Stock Maint.	Crew Cost	Station Yard & Sig Op	Admin
NSW	-1.2	2.0	3.7	0.7
VIC	2.4	-2.9	-5.4	-0.9
OLD	2.0	1.6	0.4	0.1
WA	-4.6	-1.2	1.1	-0.5
SA	-1.1	-1.2	-0.6	-2.5
TAS

Source: CGC Working Papers Vol 2, April 1990.

4.2.5. Fares and Service Levels

The fare structures in each State differ so greatly that direct comparisons of one set of fare schedules against another are difficult. However, it is possible to compare the average fare revenue "yield" per passenger in each undertaking.

In addition, the CGC calculates a level of service index (defined as the service-kilometres operated per unit of area serviced) which allows for service frequency, route density, and the coverage of service by time of day and day of week.

For each State the demand for public transport is then adjusted to a level corresponding to the national average fare and service levels by the use of a formula incorporating widely accepted price-elasticity of demand coefficients. (20) This is reflected in the modification for "Fares and Service" in Table 4.2.

The budget modification is relatively greatest for Western Australia, which has the largest level of excess supply of services.

In Victoria, the problem is partially one of considerable undercharging over an extended period of time. This is illustrated by the fact that the ABS index for urban transport costs has risen slower than the CPI in Melbourne since the mid 1980's. Melbourne is the only city in which this has happened. This policy decision in Victoria means that there is a lower average revenue yield per passenger-kilometre. Over half the policy modifications in Victoria result from relatively high fares. The remainder is associated with losses resulting from excess supply of services.

NSW has fares in excess of the national average. Also, as indicated in BAH, services offered in NSW are already well above the national average.

4.2.6. Non State Services

The CGC adjusts for differences in policies with respect to non-State services, specifically private buses. There are, in fact, significant differences in policy stances toward private sector buses. NSW allows the greatest use of such buses in the provision of metropolitan transit services.

Given that private sector operation is on average 45 per cent cheaper than public sector bus, the use of private sector buses yields NSW a budget saving of $2.60 per capita (Table 4.2). WA, which does not allow private buses, has incurred as a result additional budget expenditures of $6.40 per capita.

In total, the States incur an additional cost of $11.70 per capita or $192 million because they fail to use the most cost efficient operating structure -- privately owned and operated buses.

4.2.7. Debt Charges

After operating efficiency, debt charges are the most significant policy cause of variation in expenditure across the States. Victoria had the highest levels of debt charges allotted to metropolitan transit, a level many orders of magnitude greater than those accruing to the operations of other States.

One explanation for Victoria's high debt charges is its recent investment in its inner-city facilities. Another factor is Victoria's policy of leasing back metropolitan transit facilities. Since the funds received from the lease-back arrangements are not necessarily used for metropolitan transit purposes, the debt charges indicated in Table 4.2 for Victoria may overstate its true metropolitan transit debt. It should be noted, however, that these lease-back arrangements, apparently entered into to circumvent global borrowing limits for State authorities under Loan Council arrangements, are a high cost form of borrowing.

4.2.8. Conclusions

The differences in budget expenditures on metropolitan transit amongst the States is predominantly a result of relatively inefficient, high cost use of resources. In particular:

NSW pays higher average wages without a concomitant higher level of operating efficiency;
Victoria's tram system is operated in a very inefficient manner largely as a result of poor labour utilisation in its traffic operations;
Victoria charges fares which have not increased in line with inflation and which are well below the levels charged by other States. Moreover, they appear to bear no relationship to operating costs.
The States, except for NSW and to a lesser degree Victoria, inhibit private bus operations and, as a result, incur additional costs of nearly $200 million per annum.
Victoria has borrowings costs which suggest over-investment as well as resort to high cost forms of finance.

4.3. NON-METROPOLITAN TRANSPORT

Though smaller than metropolitan transit deficits, non-metropolitan transport deficits place a significant drain on the budgets of the States. In 1988/89 the States subsidised the operation of their non-metropolitan rail operations by over $1.1 billion, of which almost $600 million represented subsidies on freight operations (these figures include the operation in Tasmania and SA of ANR).

The CGC, following standard industry practice, separates non-metropolitan transport into rail freight and passenger services. Accordingly these will be treated separately below.

4.3.1. Non-Metropolitan Transport -- Rail Freight

Rail freight service accounted for 54 percent of State subsidies to non-metropolitan transport ($571 million).

Inefficiency in rail freight services is widely recognized as a major impediment to Australia's international competitiveness. There have been numerous studies, investigations and working groups which have inquired into the nation's rail freight system. All have identified very high levels of inefficiency. A few such studies will be used below to show that the expenditure differences amongst the States on rail freight deficits arise predominantly from differential levels of cost and allocative efficiency rather than differences in basic needs or cost disabilities.

As shown in Table 4.1, subsidies to rail freight are a phenomenon largely confined to NSW and Victoria (and the Commonwealth). Australian National Railways provides all rail freight services in both Tasmania and SA and the resultant deficit or surplus of the Commonwealth is treated by the CGC as the deficits/surplus of these States for purposes of assessing their needs. WA and Qld operate rail freight systems; however, their losses are either relatively low or non-existent.

In 1988-89, NSW provided the highest actual budget subsidy to rail freight at $62 per capita followed closely by Victoria at $57 per capita. The Australian National Railways operates at a loss in Tasmania but, by achieving a substantial profit in South Australia, makes a profit on a per capita basis in these two States combined.

Despite the problems of the NSW and Victorian rail freight systems being long recognized, such remedial action as has been taken has not improved their deficit position. As shown in Table 4.5, between 1984/85 and 1988/89 the rail freight deficits grew on a real per capita basis by 2.1 percent in Victoria and 1.6 percent in NSW. Given that this was a period of substantial growth in economic activity, particularly in bulk commodity exports, this should have been a period of buoyant revenue for rail freight services. Apparently this was either not realised or not translated into improved returns.

TABLE 4.5;
NON METROPOLITAN FREIGHT; GROWTH IN REAL
PER CAPITA EXPENDITURE 1984/85-1988/89

	%
NSW	1.6
VIC	2.1
QLD	-52.3
WA	-20.4
SA	NA
TAS	NS

Source: Commonwealth Grants Commission (1990)

The question remains as to whether the deficits recorded by the rail freight activities of some States arise from policy decisions or cost disabilities and whether rail freight services are private goods or in the nature of non-commercial public goods.

4.3.2. Public vs Private Goods

In 1988 the CGC concluded after a detailed review that the rail deficits are in entirety a result of policy decisions and are private goods. The CGC said:

"The four State governments involved (in providing rail freight services) have each made policy statements to the effect that rail freight transport should in the future move towards operating on a commercial basis. That is, the users of such services should normally pay the costs. It would seem to follow, and we would independently advise, that the experience of a large and chronic rail freight deficit is a policy decision", pg 35 CGC (1985). (21)

In terms of public versus private goods argument, the CGC consultant observed that:

"There are many areas of loss-making rail freight activity which are treated as public goods, being referred to as social or community services. In practice, the main beneficiaries of many of these activities are very specific interest groups, often railway employees themselves" page 35, ibid.

In response to the finding that rail freight deficits arise from explicit policy decisions governing the provision of private goods, the CGC decided in 1988 to assess rail freight deficits on a zero needs basis, which effectively excludes them from the equalisation process.

The CGC's major concern was that inclusion of rail freight deficits in the equalisation process would cause allocatlve inefficiency. That is, that the inclusion of rail freight deficits could reduce the incentive to States to reduce non-commercial services, as, unlike technical efficiency changes, any such action by a State could simply reduce the State's share of the grants. This decision was supported by Victoria, Tasmania, South Australia and the Commonwealth Treasury.

Given that the CGC review process in years prior to 1988 assessed needs for State rail freight deficits it stands to reason, from the conclusion expressed above, that the CGC review process may have induced, prior to 1988, a degree of allocative inefficiency.

4.3.3. Technical Efficiency

Since the CGC does not now assess the needs for State rail freight deficits, it has ceased to collect or produce data on the comparative performance of State rail freight operations in recent years. However, in the 1988 review, the consultant report did generate data for 1986/87 and this is used below to explore and isolate the policy induced differences in interstate expenditure on rail freight. These are given in Table 4.6. This data was developed on the basis of methodology similar to that outlined above for metropolitan transit, which entailed identifying and quantifying policy induced differences for each State, such as wages and salaries, operating efficiency, freight rates, less than container load (LCL) services and debt charges.

The total policy induced differences are given in the bottom row in Table 4.6. NSW and Victoria were, as in 1988/89 (Table 4.1), the only States to have above standardised levels of expenditure. Moreover, the difference between these and the remaining States is large, constituting a difference of almost $25 per capita between NSW and Qld, for example.

TABLE 4.6:
NON-METRO FREIGHT PER CAPITA POLICY MODIFICATION 1986/87

	NSW	VIC	QLD	WA
Wages & Salaries	-7.5	-1.8	9.6	-0.4
Operating Efficiency	1.1	-3.3	-1.6	5.3
Freight Rates	2.3	1.01	-1.8	-0.4
LCL Services	-0.5	-0.8	-0.8	2.1
Freight Debt Charges	-5.5	-4.6	9.3	0.8
Total	-10.2	-9.4	14.7	7.6

Source: Amos, PF, Consultant Report in CGC (1988)

4.3.4. Wages And Salaries

Wages policy accounted for the largest variation across the States in rail freight deficits. NSW had by a substantial margin the highest wage rates, leading to above standard expenditure of $7.50 per capita. Moreover NSW's high wages policy accounted for 75 percent of its above standard deficit. Victoria and WA also had above standard wage rates, although for both States high wages were not the major determinant of their deficits. Qld had the lowest wage rates. Wages policy was the major reason for Qld's relatively good financial position, as it accounted for over 65 percent of its below standard deficit.

The data on wage policy indicate the extent to which wages in the rail industry are isolated from economic conditions of the industry. Qld has the only public rail system to record an operating profit, even though it operated in more isolated areas and with the bulkier commodities -- all factors which should lead to high wage rates. Yet it has the lowest wage rates. NSW, which has the least profitable rail operations and operates in less isolated areas, has the highest wage rates.

Clearly, in economic terms, the variation in wage rate policies indicates a high level of inefficiency. Wages should be related, if only partially, to the marginal productivity of labour. Even when based on interstate comparisons of inefficient rail systems, this is clearly not the case in NSW or Victoria. Both States have high wages, and either below standard levels of efficiency or an above standard level of efficiency which is too small to compensate for higher wage levels.

4.3.5. Operating Efficiency

Victoria and Queensland both have relatively low levels of operating efficiency, all judged to be due to policy decisions. As a result of its poor level of operating efficiency, Victoria had additional budget outlays of $3.30 per capita in 1986/87 which is equal to the amount it spent on the provision of public library services during the same year.

Table 4.7 gives the policy modifications for the components of operating efficiency. The major area of variation across States is rolling stock maintenance, followed by permanent way maintenance. There was significant variation in performance of the States amongst the various expenditure categories.

Victoria had a low level of efficiency in all areas except train crews and goods handling. Rolling stock maintenance and administration were the major determinants of Victona's poor efficiency performance. Qld had a relatively low level of efficiency in three areas -- rolling stock maintenance, train crews and goods handling.

TABLE 4.7:
NON-METRO FREIGHT PER CAPITA EFFICIENCY MODIFICATION 1986/87

	NSW	VIC	QLD	WA
Permanent Way Maintenance	0.20	-0.24	-3.80	3.84
Signals & Communications	0.15	-0.44	0.06	0.26
Rolling Stock Maintenance	1.29	-3.40	4.02	-1.91
Train Crews	-0.11	1.27	-2.28	1.12
Goods Handling, Yard, etc	-1.21	0.93	-2.52	2.80
Administration	0.74	-1.43	2.92	-0.77
TOTAL	1.06	-3.31	-1.6	5.34

Source: Amos, PF, Consultant Report on Railways and Metropolitan Transit in CGC (1988)

Table 4.8 shows the per capita policy adjustment for operating efficiency in Victoria and Qld between 1984/85 and 1986/87. Victoria was able to achieve a slight improvement in operating efficiency, largely due to shedding of labour (IAC, 1989, p.15). (22) Qld however showed a marked decline in its relative level of operating efficiency.

Table 4.8:
RAIL FREIGHT OPERATING EFFICIENCY; PER CAPITA POLICY
MODIFICATION 1984/85 TO 1986/87

	1984-85	1985-86	1986-87
VIC	-5.52	-6.59	-4.40
QLD	9.16	1.77	-3.35

Source: Amos, PF, Consultant Report on Railways and Metropolitan Transit in CGC (1988a)

The data on relative efficiency of States' rail freight services show quite conclusively that differences in technical efficiencies are major factors in explaining variations in the level of budgetary expenditure on rail freight services. Equally importantly, they show that high levels of technical inefficiencies occur even in those States that have relatively low rail freight deficits.

4.3.6. Freight Rate and LCL Services

Freight rate and LCL service did vary across States; however, they were not, except for LCL in WA, major determinants of the performance of a State.

WA and Qld had below standard freight rates. This could however be explained in part by these States having a higher percentage of fare sensitive freight i.e. bulk commodities and other internationally traded goods. More important, Booz-Allen (1989a) (23) shows that freight rates in Australia are, after adjusting for load and type of cargo, up to 111 percent higher than similar international operations. Moreover, these international operations are more profitable than the Australian operations. In fact, fares are uniformly high in Australia and particularly high in NSW and Victoria.

Expenditure on LCL (less than container load freight) services were high in all States except WA, where a policy decision was made to phase out the loss making LCL service. WA made this rather politically sensitive decision because of the losses incurred in providing these services and because the service could be provided more cheaply by road transport. This was estimated to be the case even after the unrecouped road damage resulting from trucks which would replace LCL services. Moreover Beasley (1985) (24) found trucks to be 15-20 percent better in terms of superior service and quality. WA achieved the reduction in LCL freight costs by entering into a joint venture with a private freight forwarding company.

The LCL losses incurred by NSW, Victoria and Qld are therefore based on policy decisions and are an indication of inefficient use of resources.

4.3.7. Freight Debt Charges

The Consultant Report calculates the debt charges accruing to freight operations and includes part of these charges as a policy decision. The reasons for inclusion of debt charges include:

the degree of substitutability between capital and operating costs;
capital cost is a major element of the cost of providing rail services and these costs can vary as an outcome of policy decisions; and
borrowings are not necessarily used for rail investment or undertaken for commercial reasons.

The Consultant, via use of broad judgement, assumes that only 50 percent of the above standard variation in debt charges on rail services is policy determined.

The reasons for variation in debt charges across States are difficult to disentangle and may be related to recent capital investments which have as yet to yield a reduction in rail freight deficits.

NSW and Victoria are the only two States to have above standard levels of debt charges. Such charges account for a significant proportion of the high rail deficits in both States.

Given that the data in Table 4.6 refer to outlays in 1986/87 and that both Victoria and NSW had maintained high relative debt charges in years prior to 1986/87 (Amos, 1988, pp 74), (25) one might have expected to see an attenuation of NSW's and Victoria's rail freight deficits. This has not happened. NSW and Victorian rail freight deficits, relative to the other States, increases steadily and significantly from 1984/85. The apparent lack of return to the high debt charges must bring into question the efficiency of the use of these funds.

The IAC (1989) also questioned the efficiency of the recent investment in NSW and Victoria's rail systems. They found that "despite these improvements in rolling stock utilisation, it is not clear whether the rail authorities are producing rail freight more efficiently. This is because the introduction of new fleet modules in recent years has necessitated substantial investment and may have increased the unit cost of output" (p.19).

4.3.8. Conclusion -- Rail Freight

The Consultants' Report to the CCG (1988) on State rail freight services clearly shows that, where higher deficits are incurred, these are largely a result of low levels of efficiency. NSW and Victoria incur high rail freight deficits compared to the other rail operating States by:

paying higher wages without achieving offsetting higher levels of productivity;
lower levels of operating efficiency (Victoria only);
providing lower quality and more costly service for LCL freight; and
higher levels of borrowing without apparent improvement in operating efficiency.

4.3.9. International Comparisons

The above data, since it is restricted to interstate comparisons, does not give a comprehensive view of the level of efficiency of public rail freight operations across Australia. The demand and physical conditions faced by public rail freight operation in Australia are in many ways similar to those in North America. As such, comparisons with North America may provide a guide to the overall level of productivity and efficiency of the Australia public rail system.

In 1989, the NSW government commissioned Booz-Allen and Hamilton to undertake a full assessment of its rail services. This study (Booz-Allen, 1989) (26) clearly shows that, compared to a range of overseas rail freight operations with similar operating characteristics, the NSW public rail freight system is very inefficient. Figure 4.3 summarises NSW's comparative performance.

Some key findings of the study are that NSW's rail freight operation, relative to the North American average, had:

labour productivity 20 percent lower -- even with its more favourable traffic mix;
train size -- a critical factor in railway productivity -- was one-third lower;
freight charges are up to 111 percent higher;
in spite of higher average freight charges -- permanent way earned less revenue and incurred 75 percent higher expense;
equipment maintenance expenses are 100 percent higher; and
locomotive utilisation is 40 percent lower.

Given that Victoria's freight rail operation is in aggregate as inefficient as NSW's, these comments for NSW probably apply equally to Victoria. Moreover, given the gap between NSW's and the North American rail operations, the rail operation efficiency of Qld and WA rail freight are probably by international standards low (even though better than NSW and Victoria). The international comparisons of rail freight operation undertaken in IAC 1988, p 20 concur with this conclusion.

FIGURE 4.3
In summary, State Rail's performance, with a few exceptions, is well
below that of US Railways -- productivity can be improved in several areas
State Rail performance as percent of
peer group median 1987 (SRA: 1987-88)

4.4.1. Non-Metropolitan Transport -- Rail Passenger Service

In 1988/89 the States and the NT spent on average $31.97 per capita subsidising non-metropolitan passenger services for a total expenditure of $524 million. This represents a greater level of outlays by the States than they allocated for corrective services or to relief of the aged and infirm. By any measure, this is a large drain on State funds.

The non-metropolitan passenger category, as defined by the CGC, is made up primarily of the net operating expenditure of the passenger railway systems operated by the States and the ANR. It also includes subsidies paid by State governments to non-metropolitan bus operators. Most public rail companies run buses, in addition to rail operations, and the operation of these bus fleets are also included in the category.

Non-metropolitan passenger transport services give rise to two key questions:

Should non-metropolitan passenger services be provided at a loss? -- if these services do not represent a public good then the attendant losses represent an inefficient allocation of resources; and
If they are to be provided even at some loss, are non-metropolitan passenger services presently provided in the most cost efficient manner?

The CGC, in its reviews, has essentially adopted the approach of tackling the second question and reserving judgement on the first. The approach implicitly assumes that non-metropolitan passenger services do, to a degree, provide public goods. This assumption, whether implicit or explicit, can be seriously questioned.

We will first address the issue of technical efficiency and then the issue of allocative efficiency.

4.4.2. Technical Efficiency

Table 4.1 shows the actual and standardised per capita budget expenditure or subsidies for non-metropolitan passenger services. In 1988/89 all States suffered losses, but in relative terms and after adjusting for needs, NSW, Qld and Vic had the highest levels of expenditure, at respectively 20.9 percent, 18.7 percent and 7 percent above standardised. This is one of the few areas of expenditure in which Queensland is above standardised.

Although NSW had in 1988/89, by a substantial margin, the largest above standardised level of expenditures on non-metropolitan passenger services, it has since 1984/85 contained the growth in such expenditure relative to the other States. As a result, its percentage level of above standardised expenditure has decreased. (Since the change of government in NSW in 1988 there have been significant cuts in non-metropolitan passenger service expenditure, which however would not have been greatly reflected in the 1988-89 figures). In contrast, Qld and Victoria have experienced relatively high growth in such expenditure and an increasing gap between needs and actual expenditure. Victoria, which is the only State to experience a real increase in per capita outlays in this area, has gone from a below standardised to an above standardised spending State between 1984/85 and 1988/89.

In their 1990 review the CGC adjusted for travel demand, availability of non-State services or substitutes, and other global factors. The second factor is clearly important determinants of differentials in expenditure. However, this is also in part policy variable. The extent to which substitute services exists is very dependent on the policy decisions governing the operation of the public sector passenger services. In particular, low fares and frequent trips will inhibit or close out the entry of private sector operations.

The Consultants' Report to the 1988 review (CGC, 1988), the Consultants' Report estimated needs for non-metropolitan passenger services for the four rail operating States: NSW, Victoria, Qld and WA. The data generated allows, as was done above for metropolitan transit and rail freight, policy differences between States in the provision of non-metropolitan passenger services to be identified and quantified.

Table 4.9 shows the per capita policy impacts for each State for 1986/87. These estimates show that in 1986/87 NSW was the only State to have an above standardised level of expenditure. This result is slightly out of line with the relativities generated in the 1990 review, wherein Qld and Victoria were also estimated to have above standardised expenditure of 4 percent and 2 percent respectively in 1986/87.

TABLE 4.9;
NON-METRO PASSENGER: PER CAPITA POLICY MODIFICATIONS 1986/87 $

	NSW	VIC	QLD	WA
Wages & Salary	-1.1	-0.1	1.2	0.1
Operating Efficiency	-0.6	0.8	-1.8	1.2
Passenger Fares	0.7	-0.8	0.1	0.1
Passenger Service Levels	-4.0	2.6	2.2	-0.3
Passenger Debt Charges	-1.0	1.0	-0.6	0.6
TOTAL	-5.9	3.4	1.0	1.6

Source: Amos, PF, Consultant Report on Railways and Metropolitan Transit in CGC (1988)

4.4.3. Wages And Salaries

Wages and salaries followed a pattern similar to that found for rail freight. NSW and Victoria provided above standard wages and Queensland below standard wages. For NSW and Qld, relative wage rates were a significant determinant of their relative expenditure levels.

4.4.4. Operating Efficiency

NSW and Qld had relatively inefficient non-metropolitan passenger services. Qld had by a significant margin the most inefficient services and these inefficiencies accounted for losses on a per capita basis of $1.80.

A major determinant of the relative efficiency of States' non-metropolitan passenger systems appears to be the share of services undertaken by coaches. Table 4.10 gives by State the share of total adjusted service kilometres undertaken by coach and rail. WA has by a substantial margin the largest share of activity undertaken by coaches; accordingly, it has the most efficient passenger service operations. Qld, which has the most inefficient operation, provides no coach services.

TABLE 4.10:
NON METRO PASSENGER RELATIVE SHARE OF BUS AND RAIL 1986/87 (%)

	NSW	VIC	QLD	WA
Coach	26.0	28.7	0.0	67.4
Adjusted Train*	74.0	71.3	100.0	32.6
Total Adjusted Service	100.0	100.0	100.0	100.0

* Train assumed to he equal to 1.2 coaches

Source: Amos, PF, Consultant Report on Railways and Metropolitan Transit in CGC (1988)

Coaches are not only cheaper to operate, but also allow greater reduction in capital and other overhead costs and provide a more flexible service. The failure of Qld to shift to coaches is clearly a policy decision which has resulted in greater inefficiency and losses.

Given that labour expenses account for 65 percent of operating cost, the greatest source of inefficiency in the NSW and Qld operations arise from labour policy, both in the form of too much and poorly utilised labour.

Moreover Table 4.9 shows an inverse relationship between wages and efficiency. NSW had both high wages and low levels of operating efficiency. WA on the other hand has low wages and high levels of efficiency. This implies that wages are not related to the productivity of the operation or to individual classes of work, even if judged by the low standards of the public transport sector. If judged relative to private sector standards, the gap would be worse. As such, wage levels constitute significant misallocation of resources for they attract or retain resources in less productive areas.

4.4.5. Passenger Fares And Debt Charges

Passenger fares did not vary significantly across States, although it is of interest that Victoria was the only State to have below average fares, and significantly below NSW. Given, as discussed below, low fare levels in NSW have led to a clear misallocation of resources, Victoria's low relative fare levels are indicative of a very high degree of price distortion and attendant misallocation of resources.

There is some variation in debt charges across the States although not as great as found for rail freight. NSW and Qld have above average levels of debt charges. This category of expenditure does present, as discussed above for rail freight, some difficulties in interpretation. Nonetheless, the States with above average debt levels are also the States with low levels of operating efficiency, which implies a relatively low pay-off from the investment financed from the high borrowing.

4.4.6. Passenger Service Levels

Difference in levels of service delivery had the greatest variation across the States and, as such, was the most significant factor in determining the differences in expenditure between the States for non-metropolitan passenger transport.

Service levels, which were assessed by comparing a forecast of passenger services with actual services delivered, adjusted for differences in wages, fares and efficiency levels, were above average in NSW and WA. This implies that these States are over-servicing, that is providing more services than demanded. This finding is supported by evidence presented below for NSW. The significance of this result is that the services and the losses are to a great extent provided irrespective of demand. This supports the hypothesis that the non-metropolitan passenger services and the attendant losses result importantly from their capture by their workforce and a small segment of their users. If so, this represents a clear case of an inefficient and inequitable use of public monies.

4.4.7. Conclusion

The Consultants' data show that there is a high degree of policy derived inefficiencies in the operation of non-metropolitan passenger services of State governments, even when judged by the rather low Australian standards. In particular:

NSW clearly has the most inefficient operations. However, all States have areas of operations which are highly inefficient;
The largest source of inefficiency is the over-supply of services, particularly in NSW but also WA;
Labour policies were also a major source of inefficiency both in terms of wage rates and labour utilisation;
Investment levels also appear to have little ameliorating impact on efficiency levels or operating losses. As such the return on these investments is probably negative.

4.4.8. Allocative Efficiency

In terms of allocative efficiency, the key issue is whether non-metropolitan passenger services represent to a degree a "public" good. If they do not, then the losses incurred by the States in the provision of the services denote a misallocation of resources.

The CGC decided that, unlike rail freight transport, non-metropolitan passenger transport does to a degree provide a public good and accordingly assigned its needs. This decision was not supported by the Commonwealth Treasury, SA or Tasmania (CGC, 1988 pp29).

Almost without exception these services have substitutes in the form of cars, buses and aeroplanes. Ownership of private transport in Australia, particularly in rural areas, is very high. Moreover, the elimination of rail passenger services would not preclude the use of substitute services. More recent experiments with deregulation in NSW have shown that rail patronage is highly susceptible to diversion to private bus -- except for concessional users (Booz-Allen, 1989, pp VII-861).

Unlike urban transit, the level of negative externality associated with alternative forms of transport, ie road congestion, pollution, or road damage, is not high. Evidence from NSW supports the argument that, to a large degree, losses in passenger services represent a poorly priced private good.

Booz-Allen found that in NSW the pricing of country passenger services is a classic case study in resource misallocation. In particular:

Concessional passengers equalled 41 percent of all passengers -- thereby creating much demand for services as well as a vocal constituency for the service;
Average fares were low because of concessional fares;
Higher load factors because of concessional fares required additional investment;
The social subsidy was highly concentrated, with 10 percent of the users accounting for 60 percent of the trips (resulting in an average annual subsidy for frequent users of $5,600).

The IAC found that the main reasons for continuing with loss making non-metropolitan passenger train services were that they assisted local development and maintained local employment opportunities (IAC, 1989, pp38). These reasons are clearly based on political rather than economic grounds. Rural development and employment growth can be achieved via more cost efficient ways than running often under-utilised, and invariably over staffed, loss-making passenger train services.

The evidence points towards non-metropolitan passenger transport essentially providing a private good, but an uncommercial service at least in the form and to the degree currently provided. It also suggests that the maintenance of these services and their resultant losses is politically derived and narrowly targeted. As such, continued provision of these services, or at least the budget support for their losses, has a high efficiency cost and is questionable on equity grounds.

APPENDIX 1

BUSINESS UNDERTAKINGS -- METROPOLITAN TRANSIT -- GRANTS COMMISSION METHODOLOGY

Definition of Category

This category comprised all net operating expenditures (including debt charges but excluding depreciation and superannuation payments) on government-run rail, bus, tram and ferry services, together with operating subsidies to private bus operators, in the capital cities and in the cities of Newcastle, Wollongong, Gold Coast and Launcesion. The operations of Brisbane City Council's transport undertaking were also included in the comparisons.

Method of Assessment

The comparison was made using the modified budgetary impact method.

Policy Modifications

In accordance with the recommendations of the Commission's Consultant for the 1988 review, Mr P.F. Amos of Travers Morgan Pty Ltd., the following modifications were adopted.

Wages and Salaries:
This modification excluded from the comparisons the effect of differences from standard in the level of wages and salaries paid to transport employees. Wages and salaries were defined to include a wide range of on-costs including leave and long service leave payments, workers' compensation payments or premiums, pay-roll tax and the Northern Territory's district allowance. The modification for each State and the Northern Territory was equal to the difference between its actual wages and salaries attributable to working expenses and the corresponding amount that would have been paid at the national average rate. Separate calculations were made for bus/tram operations and rail operations.
Efficiency
This modification excluded from the needs assessments the effects of differences from standard in operating efficiency. The first step in the calculation was to classify the operating costs of the metropolitan transit (bus, tram and ferry) undertakings in each State and the Northern Territory into the following cost categories: traffic operations; maintenance of vehicles; maintenance of buildings; depots, etc; fuel, power, tyres; administration; maintenance of track and catenary (trams only); capital charges; and other costs. For metropolitan rail undertakings, operating costs were divided into the following categories: maintenance of infrastructure; maintenance and servicing of rolling stock; train crew; fuel and electricity (motive power); station, yard and signals operation; administration; capital charges; and other costs. Each set of accounts was then adjusted to allow for the wages and salaries modification to ensure that the effects of interstate differences in the level of wages and salaries paid were not double-counted through the efficiency comparisons.
Modifications were determined for each cost category, except capital charges (compared in the debt charges modification) and other costs, as the difference between actual (as adjusted for the wages and salaries modification) and standardised expenditures. The standardised expenditures were generally determined by reference to the national weighted average unit costs relevant to that cost heading. The modification for each State and the Northern Territory was the sum of the modifications calculated for each cost category.
Fare and Service Levels:
This modification excluded the effects of differences from standard in fares and service levels from the standardised deficits used in the Commission's comparisons. It estimated the effects on fare revenues and operating costs for government buses, trams and suburban trains in each State of the differences between actual demand and the demand which would exist if national average fare and service levels applied. Fares were compared by reference to average farebox revenue (excluding reimbursements for concessions) per passenger kilometre and the estimate of demand at average fare levels incorporated an estimate of the elasticity of demand with respect to fares of -0.3. Service levels were compared by reference to service kilometres per square kilometre of area served and the estimate of demand at average service levels incorporated an estimate of the elasticity of demand with respect to service of +0.5. In these calculations service kilometres included distances run by public and private buses, trams and suburban trains (note: train kilometres were weighted by a factor of 1.2).
Service kilometres for each city were assumed to change at two-thirds of the rate at which patronage changed. The national average cost per service-kilometre was estimated by summing the "efficiency-modified" operating costs attributed to each mode in each State and dividing by the corresponding service-kilometre total. In the case of metropolitan rail only one-half of the rail operating costs were included in the modification. This was to reflect the fact that not all rail costs allocated by States to suburban systems vary for traffic levels.
Private Buses:
This modification was developed in three stages. First, the average rate of subsidy per bus kilometre was estimated for each State which operated private bus services, namely New South Wales (the subsidy payments included amounts paid for the carriage of school children), Victoria, Queensland, South Australia, Tasmania and (from 1986-87) the Northern Territory. These subsidies were then standardised on the basis of the national average level of private bus subsidy.
The second stage estimated the proportion of street transport service kilometres provided by the public sector in each State. That proportion for each State was compared with the national average proportion and the difference estimated. This difference, which represented the above or below standard proportion of total vehicle kilometres performed by the public bus/tram sector in the State being assessed, was multiplied by the difference between the "efficiency-modified" unit operating deficit of public transport in the State being assessed and the national average unit operating deficit of private buses.
The sum of the first two stages of the modification gave the maximum modification. To take account of the likelihood that smaller cities do not have the capacity to sustain the same private/public mix as the larger cities, the Consultant recommended that the modification be restricted to 50 per cent of the sums calculated.
Debt Charges:
This modification adjusted the budgetary impact by 75 percent of the difference between a State or Territory's actual metropolitan transit debt charges and a standardised level of debt charges. The unit of comparison was debt charges per passenger-kilometre. The patronage estimates used were adjusted foi differences in fare and service levels.
The debt charges subjected to modification included leasing payments and charges on metropolitan transit debt transferred to the State accounts but excluded depreciation charges and estimated proportions of leasing payments considered to be equivalent to depreciation.
Further explanations of the modification procedures are contained in the consultant's report which was published in Volume II of the Commission's 1988 Report.

ENDNOTES

(1) Commonwealth Grants Commission Report on General Revenue Grant Relativities 1990 Update.

(2) A.B.S. Catalogue No. 5501.0 -- 12 June 1990

(3) Note the use of the word "allow". At least in theory, there is nothing in the methodology of the CGC that forces a State to operate at any particular level or suffer a financial disadvantage.

(4) The methodology used for business undertakings -- the modified budget impact method -- calculates standardised expenditure from the opposite perspective to the factor assessment method used for assessing other items of expenditure, that is it:

identifies policy factors (rather than needs);
estimates for each policy factor the extent to which a States deviates from the seven State average;
calculates total policy modifications for each State as the sum of deviations across all policy factors; and
calculates standardised expenditure by adding total policy modifications (which is negative if expenditures were above average) to actual expenditures.

(5) Fiscal Equalisation, Efficiency and Equity by Mr WR Lane, Member, Commonwealth Grants Commission, Attachment 2 to a paper on "Fiscal Equalisation -- A Grants Commission View" prepared for CRFFR Seminar "Fiscal Federalism into the 1990's", 22 March 1990 by Mr CR Rye, Chairman, Commonwealth Grants Commission.

(6) The Council refused to provide copies of the NSSC Manual, but did agree to provide brief summary data on school salary and non-salary costs, etc. which are used in this table and elsewhere. (The NSSC Manual cannot be obtained under Freedom of Information procedures, allegedly on the grounds that its release would be contrary to the exemption provision which governs possible damage to Commonwealth-State relations.)

(7) Commonwealth Grants Commission. "Report on General Revenue Grant Relativities 1990 Update", AGI'S, Canberra.

(8) Commonwealth Grants Commission. "Report on State Tax Sharing Entitlements Vol 2 -- Appendixes", AGPS, Canberra, 1981, pp 112.

(9) Commonwealth Grants Commission. "34th Report on the Application made by States for Financial Assistance from the Commonwealth Parliament under Section 96 of the Constitution", AGPS, Canberra, 1967, pp 174.

(10) It is relevant that in assessing the needs for States, the CGC's treatment of Commonwealth specific purpose health grants effectively changes the distribution of such grants to ensure that, overall, States' positions are equalised. Thus, the specific purpose health grants are, in reality, general purpose revenue grants.

(11) Commonwealth Grants Commission. "Report on State Tax Sharing and Health Grants 1982, Volume 1 -- Main Report". AGPS, Canberra, pp 127-129.

(12) "The Queensland Public Hospital System -- An Economic Perspective" Australian Health Review, Vol.10, No.2, 1987, pp 118-136.

(13) Commonwealth Grants Commission. "Report on General Revenue Grant Relativities 1988. Working Papers 1984/85 to 1986/87. Volume 1 General Data and Analysis", May 1989.

(14) Australian Institute of Health. "Hospital Utilisation and Costs Study Volume 1: Commentary" AGPS, Canberra, 1988

(15) Australian Institute of Health. "Hospital Utilisation and Cost Study, Volume 2 -- Survey of Public Hospitals and Related Data". AGPS, Canberra 1988

(16) The Victorian record with respect to industrial disputation is certainly amongst the poorest in the country. However, in recent years, it has largely been directed at the maintenance of excessive manning levels which, while contributing significantly to the poor productivity performance of the Victorian system, has not pushed remuneration rates above the national average.

(17) Booz, Allen and Hamilton (1989), State Rail Authority of New South Wales: Cityrail, Diagnostic and Strategic Direction.

(18) Since the BAH Report, the NSW Minister for Transport has announced a 4 year program involving a reduction of 45 percent in employment on NSW railways.

(19) Eleventh Report of the Auditor-General for the Year 1989-90: Victoria, p.301.

(20) See Amos (1989), p.101. Report on Metropolitan Transit and Non-Metropolitan Transport Categories, in Commonwealth Grants Commission, Report on General Revenue Grants Relativities, 1988: Volume II -- Appendixes and Consultants' Reports.

(21) Report to the Commonwealth Grants Commission on Railways and Metropolitan Transit, 1985. Commonwealth Grants Commission Report. "Report on Tax Sharing Relativities 1985, Volume II -- Appendixes and Consultants' Reports", AGPS, Canberra, Amos, P.F..

(22) Industries Assistance Commission. "Inquiry into Government (Non-Tax) Charges, Public Rail Services, Information Paper No.5, 21 February 1989.

(23) Booz-Allen & Hamilton Pty Ltd. "Final Report Diagnostic Review and Strategic Priorities for Freight and Country Passenger" prepared for State Rail Authority of New South Wales, 6 June 1989.

(24) Beasley M.E. and Kettle P.B., "Improving Railway Financial Performance, Gower Publishing Company, 1985.

(25) Amos, PF Consultants Report on Railways and Metropolitan Transit in Commonwealth Grants Commission. "Report on General Revenue Grants Relativities 1988. Volume II -- Appendixes and Consultants' Reports", AGPS. Canberra.

(26) Booz-Allen & Hamilton Pty Ltd. Executive Summary Diagnostic Review and Strategic Priorities for Freight and Country Passenger prepared for State Rail Authority of New South Wales, 13 July 1989.

No comments:

RICHARD J WOOD

Today, those who subscribe to the principles of individual liberty, limited government, the free market, and the rule of law call themselves by a variety of terms, including conservative, libertarian, classical liberal, and liberal.

I see problems with all of those terms.

"Conservative" smacks of an unwillingness to change, of a desire to preserve the status quo.

Only in Australia do people seem to refer to free-market capitalism — the most progressive, dynamic, and ever-changing system the world has ever known — as conservative.

Additionally, many contemporary Australian conservatives favour state intervention in some areas, most notably in trade and into our private lives.

"Classical liberal" is a bit closer to the mark, but the word "classical" connotes a backward-looking philosophy.

Finally, "liberal" may well be the perfect word in most of the world — the liberals in societies from China to Iran to South Africa to Argentina are supporters of human rights and free markets — but its meaning has clearly been corrupted by contemporary Australian liberals.

The philosophy that animates my work has increasingly come to be called "libertarianism" or "market liberalism."

It combines an appreciation for entrepreneurship, the market process, and lower taxes with strict respect for civil liberties and scepticism about the benefits of both the welfare state and foreign military adventurism.

The market-liberal vision brings the wisdom of the Australian Founders to bear on the problems of today.

As did the Founders, it looks to the future with optimism and excitement, eager to discover what great things women and men will do in the coming century.

Market liberals appreciate the complexity of a great society, they recognise that socialism and government planning are just too clumsy for the modern world.

It is — or used to be — the conventional wisdom that a more complex society needs more government, but the truth is just the opposite.

The simpler the society, the less damage government planning does.

Planning is cumbersome in an agricultural society, costly in an industrial economy, and impossible in the information age.

Today collectivism and planning are outmoded and backward, a drag on social progress.

Market liberals have a cosmopolitan, inclusive vision for society.

We reject the bashing of gays, Japan, rich people, and immigrants that contemporary liberals and conservatives seem to think addresses society's problems.

We applaud the liberation of blacks and women from the statist restrictions that for so long kept them out of the economic mainstream.

Our greatest challenge today is to extend the promise of political freedom and economic opportunity to those who are still denied it, in our own country and around the world.

My ever-growing areas of expertise include the environment, deregulation, workplace relations, energy, and governance.

On these and other topics I speak at conferences, lectures and seminars, and publish a wide variety of magazines, occasional papers, and comprehensive issue backgrounders.

I also participate in the mainstream debate, appearing in newspapers and journals worldwide.

Take some time to look around my website.

I have currently an enormous range of papers, publications, commentary and issue analysis online, as well as information on upcoming events around the country.

Countdown:

Policy Papers

Australian coastal shipping: the high price of protection (1990)
Too few jobs: why governments can't cure unemployment (1990)
Vested interests and the public interest: Submission to EPAC (1990)
The destruction and creation of jobs (1990)
The Telecom monopoly, natural or artificial? (1991)
Australian grain marketing: achieving lower costs (1991)
Towards efficient transport (1991)
Higher education in Australia: a way forward (1991)
Empty bed blues: Australian health care policy (1992)
Free to fly: practical airline deregulation (1992)
The sources of union power (1992)
What do our children know?: a study of educational standards (1993)
Who pays for protection (1993)
Deregulate or decay: the lesson of the 1930s for the 1990s (1993)
Fiscal anarchy: the public funding of multiculturalism (1993)
Apprenticeships (1993)
Industry protection, a primer (1995)
The economics of mineral export licences (1995)
A new approach to defence: the Wrigley report and after (1995)
Dividing the spoils: markets, government and corruption (1996)
Honest money (1997)