Evaluating Efficiency in the Portuguese Health and Education Sectors

Evaluating efficiency in the Portuguese health and education sectors

Miguel St. Aubyn1 ISEG – UTL [email protected]

February 2002

1 The author wishes to thank the referees, and Prof. Manuela Arcanjo, Prof. Gouveia Pinto and Dr. Manuel Teixeira for their very useful suggestions. They are not in any way responsible for anything written in this paper. 2

1. Introduction

Portuguese public expenditure weight on GDP has grown recently and attained levels that are close to the European Union average. According to the European Commission AMECO database, these figures were, 46.2 and 46.5 percent, respectively, in 2001.

Growth in public expenditure since 1995 resulted, in a functional classification, from growth in the social functions. They grew 4.9 percent in real terms per year, the economic functions having declined (-4.4 percent per year). Among the social functions, the more important in 2001 were "education" and "health" (5.4 and 4.8 percent of GDP, respectively). These were precisely the items that grew at a higher rate in the last 6 years (5.5 and 4.8 percent, respectively)2.

Growth of expenditure on education and health has been accompanied by growth in public employment in those sectors. From 1997 to 2000, the percentage of new subscribers to the Caixa Geral de Aposentações related to these sectors varied between 44,1 and 53,6 percent3.

The quantities of public provision of health and education have a direct impact on welfare and are important for the prospects of growth of the Portuguese economy4. The efficiency in spending on health and education becomes a relevant topic because there is no necessary connection between spending levels and provision levels. Increased spending levels may lead to very little improvement in provision if inefficiency predominates. If there are important inefficiencies, higher provision is best attained by eliminating them.

This paper is a contribution to the evaluation of efficiency in the health and education sectors in Portugal. It is structured as follows. After this introduction, section 2 summarises some methods to be used in measuring efficiency. Section 3 reviews some recent trends in the health sector, provides some new results concerning efficiency, and establishes some policy implications for health. Section 4 is devoted to education and similar in structure to section 3. Even if both sections have their own conclusions and are independent from each other, the paper ends with some final remarks.

2 The author computed these figures from the Contas Gerais do Estado and from the last Orçamento Geral do Estado. Nominal values were deflated using the GDP deflator. 3 See Caixa Geral de Aposentações (1998, 1999, 2000, 2001). 3

2. Evaluating efficiency - methodology

Results presented in this paper concerning efficiency evaluation in education and health sectors are based in an estimation of efficiency frontiers. We follow a non-parametric method known as "free disposal hull analysis" (FDH). Some results from an alternative parametric method – corrected least squares (CLS) to health expenditures and outcomes are also included. Also, previous results from other authors and to whom reference is made here are based in similar methods. It is therefore important to have a grasp of this methodology before proceeding5.

Suppose that under efficient conditions, health or education status of a population i, measured by an indicator I i , the output, depends on health or education expenses per habitant, the input, and on other variables (controls), C1i , C2i ,..., Cni :

= I i F(Di ,C1i ,...,Cni ) .

< If I i F(Di ,C1i ,...,Cni ) , it is said that country i exhibits inefficiency. For observed expense level and controls, the actual output is smaller than the best attainable one. FDH and CLS are two different methods of estimating function F, the efficiency frontier.

In a simple example without controls, three different countries display the following values for indicator I and expense level D:

Table 1 Fictitious values for countries A, B and C Indicator Expenditure Country A 65 800 Country B 75 1000 Country C 70 1300

4 Most recent theoretical and empirical research on growth emphasise the importance of human capital. Temple (2001) reviews this literature. Bassanini, Scarpetta and Hemmings (2001) provide empirical evidence that low levels of human capital have hindered economic growth in Portugal in recent years. 5 The interested reader may refer to Fried, Lovell and Schmidt (1993), a book with several contributions on efficiency frontier techniques and applications. Gupta and Verhoeven (2001) apply FDH analysis to education and health spending in Africa. Clements (1999) applies it to Portuguese education. Evans, Tandon, Murray and Lauer (2000) include a discussion of different techniques and their application to health spending. 4

Expenditure is lower in country A (800), and health or education level is also the lowest (65). Country C exhibits the highest expenditure (1300), but it is country B that attains a better level of education or health (75).

Graph 1 FDH frontier

Country C may be considered inefficient, in the sense that it performs worse than country B. The latter achieves a better status with less expense. On the other hand, neither country A nor country C shows as inefficient using the same criterion.

In FDH analysis, both countries A and C are supposed to be located on the efficiency frontier. This frontier takes the following form in this example:

 65, 800 ≤ D <1000 I = F(D) =  75, 1000 ≤ D ≤1300

This function is represented in graph 1.

It is possible to measure country C in two different ways:

5 i) Inefficiency may be measured as the vertical distance between point C and the efficiency frontier. Here, one is evaluating the difference between the level of health or education that could have been achieved if all expense was applied in an efficient way, and the actual level of health or education. In this example, the efficiency loss equals 5 – country C should, at least, achieve the same indicator level as country B, under efficient conditions. ii) If one computes the horizontal distance to the frontier, the efficient loss is now 300, in units of expense. It can be said that efficiency losses in country C are about 24 percent (=300/1300) of total expense. To attain an indicator level of 70, it is necessary to spend no more than 1000, as shown by country B.

FDH analysis is a non-parametric method, as frontier F is not previously specified. Suppose now that, a priori, frontier F is considered to be linear and its parameters estimated in a second step. One possibility is to adjust a least squares line to points A, B and C. This line, depicted as a dotted line in graph 2, is not yet an efficient frontier, as it has necessarily a point above it. Nevertheless, it is possible to shift the line upwards, adding to it the symmetric of the smallest of the residuals. This method is known in the literature as "corrected least squares", also represented in graph 2. In this case, one country only is on the frontier (country B), and country A is now deemed inefficient. Vertical and horizontal distances to the border can again be computed with the same economic interpretation.

Graph 2 CLS frontier

As we do not have any particular reasonable assumption concerning the functional form of the frontier function, we apply the FDH analysis to health and education data. We also present some CLS results for health, for the sake of comparability.

3. Public expenditure with health

3. 1 Some recent trends in expenditure

Table 2 Public expenditure on health 1995 1996 1997 1998 1999 2000 2001 In 1000 euros6 34806,1 37759,0 40188,1 43131,1 49236,3 52715,0 57942,0

% of total public 9,6% 9,6% 9,7% 9,7% 10,3% 10,4% 10,3% expenditure

% of GDP 4,3% 4,4% 4,3% 4,3% 4,6% 4,6% 4,8%

Real change 5,3% 2,6% 3,3% 10,2% 4,4% 5,4%

Source: CGEs, OGE 2002.

Graph 3

Source: OECD (2001a).

As mentioned before, public expenditure with health has clearly increased, both as a percentage of GDP and as a percentage of total public expenditure. In 2001, health expenditure accounted already for a bit more than a tenth of public expenditure, and this amounted to 5 percent of GDP.

6 Does not include regional and local government expenditure. 8

Considering the last 6 years, expenditure on health grew at a real rate of 5,2 percent (table 2). Nevertheless, and despite its recent progress, Portuguese public expenditure on health is below the EU average as a percentage of GDP, as shown in graph 3.

Portuguese private expenditure on health is high in international terms. Namely, its weight on GDP is above EU average (graph 47). Private expenditure on health in Portugal amounted to approximately a third of total expenditures, compared to a figure close to a quarter in the EU.

Graph 4

Source: OECD (2001a).

Due to the recent increase in both private and public health expenditure, total expenditure on health as a percentage of GDP in Portugal was close to average values in the EU (7.7 and 7.9 percent, respectively). These two time series are plotted in graph 5.

7 The drop in Portuguese data in 1989 is probably due to a break in the series. 9

Graph 5

Source: OECD (2001a).

Since Portuguese GDP per capita measured in purchasing power parities is clearly below EU average, it results that total health expenditure in per capita terms and purchasing power parities is also below EU average values. This expenditure is depicted in graph 6. In less than 30 years, expenditure on health per capita grew from 27.1 percent of EU average to 67.9 percent in 1998.

Graph 6

Source: OECD (2001a)

3.2 Some recent trends in health indicators

As shown above, Portuguese health expenditure, both private and public, has been growing and its level is now closer to the EU average. This convergence trend in what concerns costs is mirrored by convergence in results – in general terms, health indicators show an approximation towards average EU values. Two indicators that display a similar qualitative time trend are plotted below – infant mortality and potential years of life lost8 (graph 7 and 8, respectively). Portuguese, EU average and best performing country levels are plotted in both figures.

8 The potential years of life lost potential years for all causes is the number of years of life lost when a person dies "prematurely", before age 70. 11

Graph 7

Source: OECD (2001a). In both cases there has been some convergence of Portuguese values towards European values, in the sense that the gap between the series is much smaller in recent years. However, the gap is still positive, meaning that Portugal is still one of the EU worst performing countries. Graph 8

Source: OECD (2001a). 12

3.3 Evaluating health expenditure efficiency

3.3.1 Previous results

The OECD health sector efficiency evaluation

The OECD 1997-98 report on Portugal includes a chapter where the health sector is analysed in terms of size and performance, some cost pressures are identified and some policy measures are recommended9.

In a graphical and relatively informal analysis, it is concluded that efficiency in this sector is low when compared to other OECD countries. The study rests on the use of two health output indicators, infant mortality and potential years of life lost, and one input variable, total health expenditure as a percentage of GDP.

Results from this study deserve some criticism. Not all countries that spend the same percentage of GDP on health spend the same amount of resources per habitant, as GDP per head varies. Portugal is a relatively poor country within the OECD, so its expenditure per habitant is lower. One could expect lower results even under efficient conditions10. Moreover, it could be the case that GDP per head is also important in determining health status, i.e., GDP per head could be a control variable. Therefore, results from OECD (1998) are not taken here as perfect evidence of Portuguese inefficiency in this sector.

The WHS evaluation of the comparative efficiency of national health systems in producing health

The World Health Organisation (WHO) published in 2000 an extensive report on the performance of health systems in 191 countries11. Portugal was well placed in the efficiency ranking. All

9 See OECD (1997). 10 In fact, in OECD (1998) all countries that spend about the same percentage of GDP on health have a higher GDP per head. These countries are Australia, Austria, Finland, Iceland, Italy, Japan, New Zealand, Netherlands, Norway and Spain. 11 See WHO (2000).

13 countries together, the Portuguese health system was the 13th more efficient. Table 3 presents the ranking for OECD countries13.

Table 3 Ranking for OECD countries in WHO (2000) WHO ranking France 3 Italy 4 Spain 6 Japan 9 Greece 11 Portugal 13 Austria 15 Norway 18 Netherlands 19 Sweden 21 United Kingdom 24 Switzerland 26 Iceland 27 Belgium 28 Luxembourg 31 Ireland 32 Turkey 33 Canada 35 Australia 39 Germany 41 Finland 44 Mexico 64 Denmark 65 USA 72 New Zealand 80 Czech Republic 81 Poland 89 Hungary 105 Korea 107

With these results, Portugal is the sixth more efficient country in producing health in the OECD, which runs counter the perception conveyed by this same organisation in the report mentioned before. To understand this result, it is important to have a grasp of the methodology in which it is based.

13 Note the probably unexpected US position. This is due to the very high US health expenditure per habitant. In fact, this country expended approximately 41 percent more than Switzerland, the 2nd country in the expenditure ranking. Moreover, health indicators in the US are below average (see table 4). 14

Evans, Tandon, Murray and Lauer (2000) describe the methods and results used in WHO (2000) in detail. The efficiency frontier was estimated by an extension of corrected least squares to panel data, as data from 1993 to 1997 were considered when available. In log form, it was considered that:

=α + α + α + α 2 ln DALE 1 2 ln D 3 ln S 4 (ln S) where DALE is the "disability-adjusted life expectancy", an output indicator, D is total health expenditure per head in purchasing power parity, and S a control variable, the average number of schooling in the population14. Countries were then ranked in accordance with the vertical distance to the efficient DALE.

There are several differences from OECD (1998) that can well explain different results: i) the sample is much larger, with 191 countries; ii) resources were measured in per head terms, and not as a percentage of GDP; iii) one control variable was considered. iv) an efficient frontier was formally estimated and efficiency was effectively measured.

The main criticisms one could point in what concerns the WHO study derive from the high number of countries considered and from the no presentation of results with other specifications for the efficiency frontier or with alternative ranking criteria.

Results could have been slightly different if sub-samples of more similar countries were considered, as for instance, the OECD subset. It would be interesting to show the ranking robustness to alternative ways of estimating the frontier. Moreover, and as explained in section 2, efficiency can also be measured by the horizontal distance to the frontier. Rankings with this other measure rarely coincide with vertical rankings.

14 "DALE is most easily understood as the expectation of life lived in equivalent full health." (in WHO (2000), p. 146). This reference includes a discussion on the advantages of using DALE and some technical information on how it is estimated. 15

3.3.1 New results

Table 4 Basic data for efficiency in health evaluation Health DALE Infant Medium Expen- DALE Inf. Educ. expen- Mortality or higher diture ranking Mort. ranking diture educa- ranking ranking per head. tion ppp (%) Australia 1601 73.2 5.3 57 16 2 12 20 Austria 1960 71.6 4.7 71 6 13 6 11 Belgium 1738 71.6 6 53 14 13 18 21 Canada 1836 72 5.5 76 10 9 14 7 Czech 640 68 5.9 84 25 24 16 2 Republic Denmark 1940 69.4 5.3 66 8 21 12 13 Finland 1539 70.5 3.9 67 17 17 3 12 France 2125 73.1 4.7 60 4 3 6 18 Germany 2365 70.4 4.8 81 3 18 8 4 Greece 964 72.5 6.4 44 23 7 21 23 Hungary 372 64.1 9.9 63 28 28 26 14 Iceland 1757 70.8 5.5 62 13 16 14 16 Ireland 1200 69.6 6.2 50 20 20 19 22 Italy 1824 72.7 6.2 38 11 6 20 24 Japan 1759 74.5 3.7 80 12 1 2 5 Korea 862 65 7.7 61 24 26 25 17 Luxembourg 1985 71.1 4.2 29 5 15 5 26 Mexico 421 65 16.4 21 26 26 28 27 Netherlands 1911 72 5 63 9 9 10 14 New Zealand 1393 69.2 6.8 60 18 23 23 18 Norway 1708 71.7 4.1 82 15 11 4 3 Poland 392 66.2 10.2 74 27 25 27 9 Portugal 1060 69.3 6.4 20 22 22 21 28 Spain 1211 72.8 5 30 19 5 10 25 Sweden 1943 73 3.6 74 7 4 1 10 Switzerland 2644 72.5 4.8 80 2 7 8 5 Turkey 231 62.9 39.5 17 29 29 29 29 United 1193 71.7 5.9 76 21 11 16 7 Kingdom USA 3724 70 7.2 86 1 19 24 1

Taking into account criticisms to the two studies on health production discussed previously, the analysis presented here is restricted to OECD countries. Also, we considered two alternative ways of uncovering the efficiency frontier (FDH and CLS) and present rankings based both on vertical and horizontal distances. Moreover, two different output indicators were considered (DALE and infant mortality). Health expenditure, the input variable, is measured as total health expenditure per head in purchasing power parities. In some specifications the percentage of the population without 16 higher secondary or tertiary education enters as a control variable. Data concerns 1997 and can be read from WHO (2001), except for education, where the source was OECD (2001a).

Basic data for this study is reproduced in table 4.

Portugal is one of the countries that spend less on health per habitant (22nd place). Also, it is one of the countries with worse results in health indicators (22nd place with DALE, 21st place with infant mortality). As far as education is concerned, only Turkey has a worse indicator than Portugal. This is a country were, in international terms, not much is spent on health, and where health is relatively poor.

Clearly, a more detailed analysis is required to evaluate efficiency, and to see to what point the same expense could buy better health, or the same health could be bought with less spent resources. We present detailed results from FDH results for DALE, followed by results for infant mortality. Results using a parametric approach (CLS) are only sketched in the end of this section, details being available from the author on request.

Health expenditure and DALE

Graph 9 and table 5 summarise results from FDH analysis to the relationship between health expenditure and DALE in 29 countries.

Graph 9

Countries are ordered by the percent value of expenditure inefficiency, a measure of the horizontal distance towards the efficiency frontier in graph 9. The first eight countries (Japan, Australia, Spain, Greece, Czech Republic, Poland, Hungary and Turkey) are efficiency cases. There is no country in the sample that achieves the same level of DALE attained by these countries with less expenditure.

Table 5 FDH analysis- DALE Expen- DALE Expenditure Efficient expen- DALE Efficient diture ranking losses diture losses DALE ranking (%) Japan 1 1 0.0% 1759 0 74.5 Australia 1 1 0.0% 1601 0 73.2 Spain 1 1 0.0% 1211 0 72.8 Greece 1 1 0.0% 964 0 72.5 Czech Republic 1 1 0.0% 640 0 68 Poland 1 1 0.0% 392 0 66.2 Hungary 1 1 0.0% 372 0 64.1 Turkey 1 1 0.0% 231 0 62.9 Italy 9 14 3.6% 1759 1.8 74.5 Canada 10 18 4.2% 1759 2.5 74.5 Norway 11 12 6.3% 1601 1.5 73.2 Mexico 12 10 6.9% 392 1.2 66.2 Belgium 13 13 7.9% 1601 1.6 73.2 Netherlands 14 18 8.0% 1759 2.5 74.5 Iceland 15 17 8.9% 1601 2.4 73.2 Portugal 16 23 9.1% 964 3.2 72.5 Denmark 17 28 9.3% 1759 5.1 74.5 Sweden 18 12 9.5% 1759 1.5 74.5 Austria 19 20 10.3% 1759 2.9 74.5 Luxembourg 20 24 11.4% 1759 3.4 74.5 New Zealand 21 25 13.1% 1211 3.6 72.8 France 22 11 17.2% 1759 1.4 74.5 United Kingdom 23 9 19.2% 964 0.8 72.5 Ireland 24 20 19.7% 964 2.9 72.5 Finland 25 16 21.3% 1211 2.3 72.8 Germany 26 26 25.6% 1759 4.1 74.5 Korea 27 22 25.8% 640 3 68 Switzerland 28 15 33.5% 1759 2 74.5 USA 29 27 52.8% 1759 4.5 74.5

Portugal comes in 16th place. 9.1% of the Portuguese expenditure is inefficient. Greece achieves a DALE of 72.5 years, with an expense that is lower in 9.1 percent. Portugal only attains a DALE of 69.3. Therefore, efficiency losses measured in DALE amount to 3.2 years (vertical distance, column 6). If the ranking was done based on the vertical distance, Portugal would come 23rd, and therefore as one of the countries where more years of life are lost.

Health expenditure and infant mortality

FDH analysis to the relationship between health expenditure and infant mortality is synthesised in table 6. As before, countries were ranked by relative efficiency losses in expenditure15. Table 6 FDH – Infant mortality

Expen- Infant Expen- Efficient Inf. Efficient diture morta- diture expen- mortality inf. ranking lity losses diture losses mortality ranking (%)

Sweden 1 1 0.0% 1943 0 3.6 Japan 1 1 0.0% 1759 0 3.7 Finland 1 1 0.0% 1539 0 3.9 Spain 1 1 0.0% 1211 0 5 Czech Republic 1 1 0.0% 640 0 5.9 Hungary 1 1 0.0% 372 0 9.9 Austria 7 14 0.9% 1943 1.1 3.6 Luxembourg 8 13 2.1% 1943 0.6 3.6 Italy 9 26 3.6% 1759 2.5 3.7 Australia 10 19 3.9% 1539 1.4 3.9 Canada 11 22 4.2% 1759 1.8 3.7 Poland 12 8 5.1% 372 0.3 9.9 Netherlands 13 18 8.0% 1759 1.3 3.7 France 14 14 8.6% 1943 1.1 3.6 Denmark 15 20 9.3% 1759 1.6 3.7 Norway 16 8 9.9% 1539 0.2 3.9 Belgium 17 25 11.4% 1539 2.1 3.9 Iceland 18 20 12.4% 1539 1.6 3.9 New Zealand 19 22 13.1% 1211 1.8 5 Germany 20 16 17.8% 1943 1.2 3.6 Korea 21 22 25.8% 640 1.8 5.9 Switzerland 22 16 26.5% 1943 1.2 3.6 Greece 23 11 33.6% 640 0.5 5.9 Portugal 24 11 39.6% 640 0.5 5.9 United Kingdom 25 1 46.4% 640 0 5.9 Ireland 26 10 46.7% 640 0.3 5.9 United States 27 27 47.8% 1943 3.6 3.6

It is interesting to note that, among the six countries that define the efficiency frontier, now with a different indicator, four of the previously DALE efficient countries are found (Japan, Spain, the Czech Republic and Hungary).

Portugal comes now in the 24th place, with an inefficient estimated expenditure of 39.6 percent. Under efficient conditions, Portuguese infant mortality should have been 5.9 per thousand, like in

15 Turkey and Mexico were excluded here, as they were outliers, especially with corrected least squares analysis. 20 the Czech Republic, where expense is clearly lower, and not 6.4 per thousand, as was observed. If countries are ranked by infant mortality losses (the vertical distance), Portugal comes 11th, now in the first half of the table.

Summary of results

Table 7 summarises Portuguese results, also with corrected least squares (CLS). Table 7 Results for Portugal – a synthesis FDH-DALE CLS-DALE FDH-Inf. mort. CLS – Inf. mort. Expenditure losses 9.1% 55.8% 39.6% 69.8% DALE losses 3.2 3.9 Inf. mort. losses 0.5 2.1

Ranking by expenditure 16th (in 29) 14th (in 29) 24th (in 27) 15th (in 27)

Ranking by DALE 23rd (in 29) 23rd (in 29) Ranking by inf. mortality 11th (in 27) 20th (in 27)

Portugal arises as an inefficient country in producing health, considering both indicators and both methods. It is almost always placed in the bottom half of the table, considering either vertical or horizontal distances. Estimated inefficient expenditure varies between 9.1 and 69.8 percent, depending on method and indicator used.

As total expenditure was used, inefficiency may arise either from public or from private sector performances. They may also be explained by variables not considered here, like different attitudes towards illness, or different levels of alcohol and drug abuse or AIDS across countries. Nevertheless, the robustness and magnitude of results authorises the serious consideration of inefficiency in the public sector, which is responsible by approximately two thirds of total health expenditure. This is the reason why we turn now into a more detailed quantitative analysis of public health expenditures.

3.4 A more detailed analysis

3.4.1 Resources in the Portuguese health sector – some international comparisons

The Eco-santé database (OECD (2001a)) allows an international comparison of physical and human resources allocated to the health sector in 30 countries. A comparative analysis of some indicators is done in this section, in order to characterise available resources is the Portuguese health system. As shown below, the number of physicians in Portugal is similar to the EU average, but there are relatively few general practitioners as compared to specialists. They tend to concentrate in the Lisboa e Vale do Tejo region. Nurses and hospital beds are relatively scarce.

Physicians Graph 10

Source: OECD (2001a).

The number of physicians in Portugal per habitant increased through time in a pattern very close to the EU average (3.2 physicians per 1000 habitants for both in 1999). Nevertheless, specialists predominate in Portugal (2.2 per 1000 habitants in Portugal vs. 1.4 in the EU in 1999). On the other 22 hand, the general practitioners are relatively scarce (0.9 in the EU, 0.6 in Portugal). The time series for these indicators are depicted in graphs 10, 11 and 1216. Graph 11

Source: OECD (2001a).

Graph 12

Source: OECD (2001a).

16 According to OECD (2001a), there was a break in the series in 1992. Before 1992 some specialists working in 23

National Health Service (or SNS – Serviço Nacional de Saúde) doctors tend to concentrate in the Lisboa e Vale do Tejo region, as the majority of central hospitals is located in Lisbon (see table 8).

Table 8 Geographical distribution of SNS doctors Total % Per 1000 habitants Norte 7 964 31.7% 2.54 Centro 4 909 19.5% 2.12 Lisboa e Vale do Tejo 10 567 42.0% 3.26 Alentejo 847 3.4% 1.90 Algarve 845 3.4% 2.42 Total 25 132 100.0% 2.65 Source: Departamento de Gestão Financeira (2001) Nurses

Graph 13

Source: OECD (2001a)

Nurses are scarce in Portugal in European terms, as shown in graph 13. In the EU there were 8.3 nurses per 1000 habitants in 1999. In Portugal, there were only 3.8. They were more evenly distributed than doctors (see table 9).

hospitals were not registered as specialists in the Medical Order. Since 1992 they have been included. 24

Table 9 Geographical distribution of SNS nurses Total % Per 1000 habitants Norte 10 506 29.9% 3.35 Centro 8 223 23.4% 3.54 Lisboa e Vale do Tejo 13 073 37.2% 4.04 Alentejo 1 943 5.5% 4.37 Algarve 1 427 4.1% 4.09 Total 35 172 100.0% 3.71 Source: Departamento de Gestão Financeira (2001).

Hospital beds

Graph 14

Source: OECD (2001a).

There is a tendency in the EU and also in Portugal for a decreasing number of hospital beds. Nevertheless, Portugal has had consistently much less beds than the EU average (see graph 14). In 1998, there were 4 beds per thousand Portuguese, as compared to 6.9 per thousand habitants in the EU.

3.4.2 National Health Service Costs

SNS is financed in about 90 percent by the state budget. Two cost items, labour costs and services and suppliers amount to more than 80 percent of expenses, about 4 percent of GDP (see table 10). Table 10 SNS costs 1998 1999 % of % of % of total % of nominal total GDP GDP change Purchases 14.3% 0.66% 14.9% 0.73% 18.3%

Services and suppliers 38.7% 1.78% 38.2% 1.87% 12.3%

Labour 45.0% 2.06% 44.7% 2.19% 13.2%

Other 2.0% 0.09% 2.3% 0.11% 33.3%

Total 100.0% 4.58% 100.0% 4.90% 14.0%

Source: Departamento de Gestão Financeira (2001)

Labour costs

Additional remuneration is quite important in labour costs. These result both from nurse and doctor labour costs (table 11).

Table 11 Labour costs breakdown, 1999 Wages, incl. holidays and Christmas 76.0%

Additional remuneration 14.9%

Other 9.1%

Total 100.0%

Source: Departamento de Gestão Financeira (2001)

Table 12 compares mean incomes of nurses, doctors and of all workers in the health sector to the mean income in the economy. Portuguese values are not much different from those of other EU countries.

Table 12 Ratio of mean incomes in the health sector to mean incomes of all employees 1999 (or 1998) Nurses Doctors Total health sector Austria na na 1.00 Belgium 3.99 na na Denmark 1.18 2.03 0.58 Finland 0.82 1.83 0.87 France 0.81 1.94 0.82 Greece na na 0.76 Ireland 1.15 na 0.97 Luxembourg na na 0.85 Netherlands na na 0.88 Portugal 0.99 1.57 0.85 United Kingdom 0.89 1.39 na Source: Departamento de Gestão Financeira (2001); European Commission: AMECO database; OECD (2001a).

Services and suppliers

This item includes essentially two expenditure items: ancillary diagnostic services and expenditure with pharmaceuticals (table 13).

Table 13 SNS external services and suppliers costs– 1999 % of total % of GDP Annual nominal change Ancillary diagnostic 24.9% 0.4% 16.9% services Chemists 53.1% 0.9% 11.4%

Other 22.1% 0.4% -29.0%

Total 100.0% 1.7% 0.0%

Source: Departamento de Gestão Financeira (2001)

Expenditure with ancillary diagnostic services, and more importantly, with pharmaceuticals, attain very high levels in international terms. In 1998, Portugal was the third EU country with higher public expenditure on pharmaceuticals per habitant and in purchasing power parities (see graph 15). 27

The Portuguese state spent more than 40 percent in pharmaceutical per habitant than the EU average17.

Graph 15

Source: OECD (2001a).

This high level of spending results from high state co-payments and from a very high consumption of pharmaceuticals in the country. Considering all countries with available data, Portugal came second in 1998 in what concerns sales of pharmaceuticals per habitant in purchasing power parities (see graph 16).

17 This average excludes Austria, for which there were no data available on this matter in OECD (2001a). 28

Graph 16

Source: OECD (2001a).

3.5 Health: conclusions and policy implications

Health public spending has grown significantly in recent years. It is an important item of the government budget and it amounts to nearly 5 percent of GDP. This is less than the EU average, but it is composed by high private expenditure. Total health expenditure in Portugal has been growing and is close to 8 percent of GDP. Increased resources allocated to the health sector have been accompanied by an improvement of Portuguese health status. Nevertheless, empirical evidence presented here favours the hypothesis that the sector displays some important inefficiencies. The same expenditure level could buy better health, or, alternatively, the same health status could be bought with less spent resources.

A more detailed analysis of the SNS showed that some resources are relatively scarce – general practioners, nurses or hospital beds. Moreover, they tend to be asymmetricaly distributed in geographical terms. This may well diminish efficiency in health care. On the cost side, it partly explains costs with extra remuneration for doctors and nurses.

Also, it results from international comparisons that public spending in pharmaceuticals and ancillary diagnostic services are excessively high in Portugal. Note that these expenditure items amounted to 1.3 percent of GDP in 1999. This spending area has been identified as one of the main sources of inefficiency in the Portuguese health sector in different studies18.

We turn next into some policy implications of the inefficiency findings. Most of these implications are shared by different authors on this subject, even if there is some disagreement when it comes to implementation issues19.

Promotion of cost effectiveness in the public provision of health. This includes the separation of provision from financing and regulation, more autonomous and flexibile management of institutions, the distribution of funds to hospitals based more on performance and therapy-based indicators and less on past history, and to regions based on health needs.

Better co-ordination and integration between hospitals and health centres. Better co-ordination between different health institutions should ensure a better rate of utilisation of installed capacity in the public sector.

Review of personnel management and payments policy. Staff remuneration, namely doctors', could be reviewed in order to reward performance and to provide incentives for an improved regional distribution.

Induce changes in the pharmaceutical market. Public policy should be designed in order to induce more consumption of generic drugs. Competition in this market would be reinforced by easing entry restrictions, by allowing the sale of some non-prescribed drugs in supermarkets and other outlets, and by abolishing the fixed margin on the sale of pharmaceuticals.

Induce changes in users behaviour. This includes incentives and educations of users in order to behave economically (e. g. in accepting and asking for generic drugs or in not overcrowding hospitals' urgencies).

18 For example, in Pereira, Campos, Ramos, Simões and Reis (1999) or in Pinto and Oliveira (2001). 19 See OECD (1998), Pereira, Campos, Ramos, Simões e Reis (1999), Pinto e Oliveira (2001) and Conselho de Reflexão Sobre a Saúde (1998). See also the interview of the minister of health to the newspaper "Vida Económica" (22-28 de Fevereiro de 2002) for an exposé of recent governmental policy and goals.

Formation policy. Education policy should take into account the relative scarcity of some health workers, namely nurses.

4. Public expenditure with education

4.1 Education expenditure – some data

As documented before, public expenditure with education in Portugal has been growing in the last decade20. Expenditure with education has become a more important item within total public expenditure. According to educational data from the OECD and presented in Table 14, expenditure with education in Portugal was 13.5 per cent of total public expenditure in 1998 (12.5 percent in 1995). Portuguese behaviour in this matter was not very different from OECD average behaviour. In fact, education expenditure was growing in the OECD area at a comparable rate and its weight on public expenditure was not much lower (12.9 percent).

Considering the structure by level, it is noticeable that about three quarters of public education expenditure is devoted to non-tertiary education in Portugal. In the OECD area, the weight of tertiary education is slightly higher (one third). The weight of public education expenditure on GDP is very similar in Portugal and in the OECD area, 5.7 and 5.4 percent, respectively, in 1998.

Table 15 presents some numbers concerning educational expenditure per student in purchasing power parity dollars, and therefore corrected for different price levels across countries. Also, they include both public and private expenditure, and are based in full-time equivalent students.

Portuguese expenditure per student is lower than the OECD average in real terms. The difference is more striking for lower levels of education. Educational expenditure with a pre-primary child is less than half of what is spent in other OECD countries. For a secondary student, the difference is much smaller: in Portugal it is spent 87,6 percent of the OECD average with this type of student. Some European Union countries spend less than Portugal with secondary students, namely Greece, Spain and Ireland.

20 Note that private financing of the Portuguese educational system is of residual nature. According to Branco (2000), this system works as "a quasi-monopoly of the public system, being financed almost exclusively by taxation" (p. 212, in Portuguese). 31

Table 14 Total public expenditure on education - OECD countries Direct public expenditure on educational institutions plus public subsidies to the private sector (including subsidies for living costs, and other private entities) as a percentage of GDP and as a percentage of total public expenditure, by level of education and year Public expenditure on education as a percentage Public expenditure1 on education as a percentage of total public expenditure of GDP 1998 1995 1998 1995 Primary, Tertiary All levels of All levels of Primary, Tertiary All levels of All levels of secondary education education education secondary education education education and post- combined combined and post- combined combined secondary secondary non-tertiary non-tertiary education education

Australia 10.2 3.6 13.9 13.4 3.5 1.2 4.8 5.0 Austria 7.8 3.2 12.2 12.0 4.0 1.6 6.3 6.5 Belgium 6.9 2.2 10.2 m 3.5 1.1 5.2 m Canada 8.2 3.9 12.6 12.9 3.7 1.8 5.7 6.5 Czech Republic 6.3 1.8 9.3 8.7 2.9 0.8 4.3 4.9 Denmark 8.8 3.9 14.8 13.1 4.9 2.2 8.3 7.7 Finland 7.6 4.0 12.4 12.1 3.8 2.0 6.2 6.9 France 7.9 2.0 11.3 11.1 4.2 1.0 6.0 6.0 Germany 6.3 2.3 9.8 8.6 3.0 1.1 4.6 4.7 Greece 4.6 2.1 6.9 5.2 2.3 1.1 3.5 2.9 Hungary 7.8 2.4 12.4 12.2 2.9 0.9 4.6 5.0 Iceland 10.8 5.6 17.8 m 4.3 2.2 7.1 m Ireland 9.9 3.5 13.5 13.0 3.3 1.1 4.5 5.1 Italy 7.1 1.6 10.0 8.7 3.5 0.8 4.9 4.6 Korea 12.7 1.8 16.5 m 3.1 0.4 4.1 m Mexico 16.2 4.5 22.4 22.4 3.0 0.8 4.2 4.6 Netherlands 6.8 3.0 10.6 9.1 3.1 1.4 4.9 5.0 Norway 9.7 4.2 16.1 18.4 4.6 2.0 7.7 9.1 Poland 7.8 2.7 12.2 11.5 3.5 1.2 5.4 5.5 Portugal 10.2 2.4 13.5 12.5 4.3 1.0 5.7 5.4 Spain 8.1 2.2 11.1 10.6 3.3 0.9 4.5 4.7 Sweden 9.1 3.6 13.7 m 5.3 2.1 8.0 m Switzerland 10.8 3.0 14.6 m 4.1 1.1 5.5 m United Kingdom 8.3 2.6 11.9 11.2 3.4 1.1 4.9 5.2

Average 8.7 3.0 12.9 11.9 3.7 1.3 5.5 5.5

1. Public expenditure presented in this table includes public subsidies to households for living costs, which are not spent on educational institutions. 2. Post-secondary non-tertiary is included in tertiary education and excluded from primary, secondary and post-secondary non- tertiary education. Source: OECD (2000). 32

Table 15 Expenditure per student (1998) Expenditure per student in US dollars converted using PPPs on public and private institutions, by level of education, based on full-time equivalents

Pre-primary Primary All secondary

OECD countries Australia m 3981 5830 Austria1 5029 6065 8163 Belgium2 2726 3743 5970 Belgium (Fl.) 2 2601 3799 6238 Canada 4535 m m Czech Republic 2231 1645 3182 Denmark 5664 6713 7200 Finland 3665 4641 5111 France 3609 3752 6605 Germany 4648 3531 6209 Greece2 m 2368 3287 Hungary 2160 2028 2140 Ireland 2555 2745 3934 Italy1 4730 5653 6458 Japan 3123 5075 5890 Korea 1287 2838 3544 Mexico 865 863 1586 Netherlands 3630 3795 5304 Norway1 7924 5761 7343 Poland 2747 1496 1438 Portugal 1717 3121 4636 Spain 2586 3267 4274 Sweden 3210 5579 5648 Switzerland1 2593 6470 9348 United Kingdom2 4910 3329 5230 United States 6441 6043 7764

Average 3549 3932 5293

1. Public institutions only. 2. Public and government-dependent private institutions only. Source: OECD (2001b).

If one examines the breakdown of educational expenditure by resource category (table 16), it is apparent that most of it is on compensation of staff, both for OECD countries in general and for Portugal. In Portugal, the weight of compensation of staff is considerably higher than average, especially in what concerns non-tertiary education – it amounts to almost 90 percent of total expenditure. 33

Table 16 Educational expenditure by resource category (1998) Distribution of total and current expenditure on educational institutions, by resource category and level of education Primary, secondary and Tertiary education post-secondary non-tertiary education Percentage of total expenditure Percentage of current Percentage of total Percentage of current expenditure expenditure expenditure

Current Capital Compen- Other Current Capital Compen- Other sation of all current sation of all current staff staff Portugal 95 5 94 6 84 16 70 30

OECD country 92 8 80 20 87 13 70 30 mean Source: OECD (2001b).

Table 17 provides an international comparison of statutory teachers' wages in the OECD area. It is noticeable that Portuguese teachers receive a wage that is lower than the OECD average, both at the start of a career and after 15 years of teaching. However, teachers at the top of the scale are among the best paid in the OECD. 34

Table 17 Annual statutory teachers' salaries in public institutions at the lower secondary level of education, in equivalent US dollars converted using PPPs (1998) Starting Salary Salary at Ratio of Ratio of Ratio of Years Percenta Salary salary after 15 top of starting salary salary from ge after 15 /minimum years' scale salary to after 15 after 15 starting additional years' training experienc /minimum GDP per years' years' to top bonus1 experienc e training capita experienc experienc salary e per /minimum e to GDP e to teaching training per starting hour capita salary

Australia 25,775 36,175 36,175 1.17 1.64 1.40 8 10 45 Austria 21,585 28,464 44,604 0.90 1.19 1.32 34 n 44 Belgium (Fl.) 19,472 27,932 34,262 0.80 1.15 1.43 27 n 40 Belgium (Fr.) 21,259 30,496 37,627 0.88 1.26 1.43 27 n 42 Czech 7,027 9,342 12,477 0.50 0.67 1.33 32 20 13 Republic Denmark 25,375 31,000 31,000 0.96 1.18 1.22 10 1 48 England 22,661 38,010 52,023 1.04 1.74 1.68 m m 48 Finland 20,660 27,942 29,127 0.93 1.25 1.35 20 20 58 France 22,579 29,615 42,697 1.01 1.32 1.31 34 12 47 Germany 32,769 38,640 43,156 1.43 1.68 1.18 28 n 53 Greece 19,871 24,337 29,165 1.35 1.65 1.22 33 n 39 Hungary 5,978 11,066 12,526 0.53 0.99 1.85 40 m 20 Ireland 23,303 36,151 40,708 0.99 1.53 1.55 22 n 49 Italy 21,108 25,773 31,546 0.951.16 1.22 35 m 42 Japan 21,899 41,201 52,867 0.91 1.72 1.88 31 31 m Korea 24,150 39,921 66,269 1.62 2.67 1.65 41 6 80 Mexico 12,774 14,708 26,496 1.51 1.74 1.15 11 n 18 Netherlands 25,515 31,380 38,988 1.10 1.35 1.23 24 n 34 Norway 19,565 23,879 25,702 0.71 0.87 1.22 28 3 39 New Zealand 19,863 32,260 32,260 1.12 1.81 1.62 8 11 33 Portugal 16,429 26,288 47,975 1.07 1.71 1.60 29 20 42 Scotland 19,658 32,679 32,679 0.90 1.50 1.66 11 m 36 Spain 27,506 32,144 40,806 1.56 1.82 1.17 42 m 59 Sweden 18,389 23,896 m 0.84 1.09 1.30 m m m Switzerland 38,143 51,361 59,133 1.44 1.93 1.35 23 n 60 Turkey m m m m m 1.17 20 m m United States 24,624 32,713 43,458 0.78 1.03 1.33 30 22 34 Country 21,459 29,899 37,749 1.04 1.45 1.40 26 8 43 mean 1. Percentage additional bonus is an average of two ratios: maximum bonus applicable to starting salary and maximum bonus applicable to salary at top of scale.

Source: OECD (2000).

4.2 Educational performance

When evaluating educational performance, we refer to two types of performance indicators. Short of a better designation, we call them "quantitative" and "qualitative" indicators.

Quantitative indicators, like enrolment rates, school expectancy and educational attainment, assess the current situation and progress in schooling. Here, one is concerned with the level of education attained by the population, and with the frequency of education by people in age groups at the expected age of participation. It is important to stress a flux versus stock interpretation. It is usual to use variables related to the educational attainment of the population as proxy variables to "human capital", the existing stock of knowledge and skills that exist in an economy. The educational system works mainly by a flux mechanism akin to investment - as the participation rates of young people augment through time, the existing human capital stock increases when these youth cohorts enter the labour force. As it will be shown below, Portugal has a comparatively low human capital stock, but an investment rate that has already converged to OECD average levels. With the passing of time, and maintaining this quantitative performance, it is to be expected that attainment levels will also converge to the more developed countries typical values.

Quantitative indicators of human capital stock and human capital formation have an important drawback. When making international comparisons, there is the implicit assumption that educational levels are equivalent across countries. More direct measures are possible, by testing individuals for a number of abilities, like literacy or numeracy. This is done both at the “stock” level, when adults are considered, and at the "formation" levels, when student performance is assessed and compared internationally. These are the indicators designated here by "qualitative". With this approach, and as documented below, Portuguese performance becomes much lower than when quantitative indicators only are considered.

Finally, and even if some characterisation is given on the stock side of the problem, it should be emphasised that the performance and efficiency of the Portuguese educational system will be evaluated considering the investment perspective. As in any other country, most of the education expense is done with young people not yet in the labour force. 36

Table 18 Educational attainment of the population (1999) Distribution of the population 25 to 64 years of age, by highest level of education attained

Pre-primary Lower Other and primary secondary education education

Australia X 43 57 Austria1 X 26 74 Belgium 20 23 57 Canada 7 13 79 Czech Republic X 14 86 Denmark n 20 80 Finland X 28 72 France 20 18 62 Germany 2 17 81 Greece 41 9 50 Hungary 4 29 67 Iceland 2 35 63 Ireland1 23 26 51 Italy 25 32 44 Japan X 19 81 Korea 18 16 66 Luxembourg 24 14 62 Mexico 59 21 20 Netherlands 12 23 65 New Zealand X 26 74 Norway1 n 15 85 Poland 1 X 22 78 Portugal 67 12 21 Spain 42 23 35 Sweden 11 12 77 Switzerland X 18 82 Turkey 68 10 22 United Kingdom X 18 82 United States 5 8 87

Country mean 16 20 64

X indicates that the data are included in the next column. 1. Year of reference 1998. Source: OECD (2001b).

Table 18 clearly shows that the stock of human capital as measured by the educational attainment of the population is much lower in Portugal than in most other OECD countries. In 1999, only 21 percent of the population aged between 25 and 64 had attained a level higher than lower secondary education, compared to a country mean of 64 percent. Portugal was clearly behind other countries with similar GDPs per head, like Spain or Greece, and at a level very similar to poorer countries, like Turkey and Mexico. As mentioned before, empirical studies have shown that the lower stock of Portuguese human capital have hindered economic growth in recent years21. Considering that the educational system is of paramount importance to human capital formation, this becomes one of the sectors where investment and efficiency will have more long-lasting effects. 37

Human capital formation measured in quantitative terms has clearly increased in Portugal in recent decades. Graph 17 depicts enrolment rates for selected years between 1986 and 1998. These enrolment rates are defined as the percentage of the population with a specific age that participates in the education system22.

Graph 17

Source: DAPP.

Progress in schooling among younger people is clearly noticeable as the curve shifts upwards through time. In 1986, a minority of children attended pre-primary education. Attainment between 6 and 12 years of age was universal, but there was a significant drop after 12, with less than half of young people aged 16 years of age attending school. Since then, significant progress has been made at both ends of the distribution: both pre-primary and upper-secondary and tertiary education attendance became clearly more common.

21 See Bassanini, Scarpetta and Hemmings (2001). 22 Theoretical rates should not exceed 100 percent. Empirical rates may exceed 100 percent due to measurement errors. According to DAPP, these measurement errors may result either from an underevaluation of the number of individuals in the 1991 Census or from incorrect information transmitted at the school level. According to the same source, schools may tend to inflate student numbers to justify tenure and teacher/student ratios and/or more favourable budgets (DAPP, p. 12-13, in Portuguese). 38

In fact, Portuguese enrolment rates have converged to the OECD average in recent years. From Table 19, one can notice that Portuguese values are not far from the OECD country mean for all age groups considered. Consequently, a Portuguese child aged 5 is expected to have almost 17 years of schooling under current conditions, the same as the average child in OECD countries (see Table 20). 39

Table 19

Enrolment rates (1999) Net enrolment rates by age group for full-time and part-time students in public and private institutions Students aged: 4 and under as 5 to 14 as a 15 to 19 as a 20 to 29 as a a percentage of percentage of percentage of percentage of the population the population the population the population aged 3 to 4 aged 5 to 14 aged 15 to 19 aged 20 to 29

Australia 33.8 97.7 80.3 27.3 Austria 56.2 98.7 76.7 18.2 Belgium 118.2 98.8 90.6 24.6 Canada 19.7 96.6 75.3 20.3 Czech Republic 66.9 99.3 74.8 12.9 Denmark 78.9 99.0 80.4 28.7

Finland 36.3 91.2 84.5 36.1 France 118.2 99.9 87.2 18.9 Germany 65.8 100.1 88.3 22.6 Greece 28.2 98.5 82.0 15.9 Hungary 78.6 99.8 78.1 17.2

Iceland 121.4 98.2 78.7 28.8 Ireland 27.8 99.9 79.8 15.0 Italy 98.0 99.2 70.7 16.9 Japan 76.3 101.2 m m Korea 16.2 91.8 81.2 21.9

Luxembourg 57.9 95.3 73.8 4.7 Mexico 35.0 94.0 39.3 8.7 Netherlands 49.7 99.4 87.7 22.0 New Zealand 85.4 98.8 72.5 20.4 Norway 73.6 97.4 86.1 27.5

Poland 28.4 93.5 83.0 22.7 Portugal 61.9 105.6 76.3 18.8 Spain 97.0 104.8 76.3 23.7 Sweden 66.9 98.5 86.2 33.7 Switzerland 19.3 98.2 83.6 18.6

Turkey m 76.9 30.5 7.9 United Kingdom 77.4 99.0 72.5 23.6 United States 47.2 100.7 78.1 20.4

Country mean 62.1 97.7 76.9 20.7 Source: OECD (2001b). 40

Table 20 School expectancy (1999) Expected years of schooling under current conditions in public and private institutions, excluding education for children under five years of age, all levels of education combined, full-time and part-time

Sweden 20.3 Australia 19.9 United Kingdom 18.9 Belgium 18.5 Finland 18.3 Norway 17.9 Denmark 17.7 Iceland 17.7 Spain 17.3 Germany 17.2 United States 17.2 New Zealand 17.2 Netherlands 17.1 Portugal 16.8 Canada 16.5 France 16.5 Switzerland 16.3 Austria 16.0 Ireland 16.0 Poland 16.0 Hungary 16.0 Korea 15.8 Italy 15.8 Greece 15.6 Czech Republic 15.1 Mexico 12.4 Turkey 10.6

Average 16.7 Source: OECD (2001b).

Evidence from direct measures of human capital formation is not so favourable to Portuguese performance. We refer here to two direct studies of student performance in an international context with Portuguese participation: the Third International Mathematics and Science Study (TIMMS), conducted in 1994-95, and the more recent PISA 2000 study23. In both cases students of about the same age from different countries were given the same set of tests. The TIMM Study included Mathematics and Science tests, but not literacy ones. The PISA study included scientific, mathematical and reading literacy. Results from both studies are summarised in Tables 21 and 22.

23 More details on this studies can be found in TIMMS (1996), and OECD (2001b). 41

Table 21 TIMSS results (1995) Mathematical Scientific Average literacy literacy

Japan 605 571 588 Korea 607 565 586 Czech Republic 564 574 569 Austria 539 558 549 Hungary 537 554 546 Australia 530 545 538 Switzerland 545 522 534 Ireland 527 538 533 England 506 552 529 Belgium* 546 511 528 Sweden 519 535 527 Germany 509 534 522 France 538 498 518 United States 500 534 517 Norway 503 527 515 Spain 487 517 502 Greece 484 497 491 Denmark 502 478 490 Portugal 454 480 467

Ranking 19/19 18/19 19/19 Portugal

Average 526.39 531.03 528.71 *Simple average of Flemish and French speaking students Source: TIMMS (1996).

Both studies included more countries than those presented in Tables 21 and 22. For the sake of comparability, non-OECD countries are not considered here. Also, TIMMS results are for 8th grade students, with an age close to those considered in the PISA study (15 years of age).24

Two main conclusions can be drawn from these results: i) Portuguese performance is consistently low across categories (reading, mathematics, and science) and in both studies. Portuguese students are the worse or among the worst performers in every dimension one considers. ii) Correlation between results is strong, in the sense that a country with a good performance in reading is a good performer in mathematics or science, and that a country that performed well in TIMMS also performed well in PISA. This last correlation is illustrated in Graph 18.

24 Note that Finland, Mexico, Poland and Sweden did not participate in the TIMM study. England, a participant in TIMMS, is a part of the United Kingdom, present in PISA. As Belgium is concerned, the average of performances of Flemish and French speaking students in TIMMS was computed by the author. 42

Note that the two best performers and the two worst ones are the same, with Portugal included in the latter group. Table 22 PISA results (2000) Reading literacy Scientific literacy Mathematical literacy Average

Japan 522 550 557 543 Korea 525 552 547 541 Finland 546 538 536 540 Australia 528 528 533 530 United Kingdom 523 532 529 528 Ireland 527 513 503 514 Austria 507 519 515 514 Sweden 516 512 510 513 Belgium 507 496 520 507 France 505 500 517 507 Switzerland 494 496 529 506 Norway 505 500 499 502 Czech Republic 492 511 498 500 United States 504 499 493 499 Denmark 497 481 514 497 Hungary 480 496 488 488 Germany 484 487 490 487 Spain 493 491 476 487 Poland 479 483 470 477 Italy 487 478 457 474 Portugal 470 459 454 461 Greece 474 461 447 460 Mexico 422 422 387 410

Ranking Portugal 22/23 22/23 21/23 21/23

Average 499.51 500.17 498.70 499.46 Source: OECD (2001c). 43

Graph 18

4.3 Evaluating efficiency in education

The analysis so far has not been made in terms of a direct comparison between inputs and outcomes in education. As with the health sector, some results based on efficiency frontier methods are presented next. We first refer to some previous research on the subject and then present some new results.

4.3.1 Previous results

Recent research by Clements (1999) applied FDH analysis to evaluate the efficiency of educational expenditure in Portugal. In this study, two output indicators were considered: (i) the ratio of secondary graduates to population at typical graduation age; (ii) the scores on eight-grade exams in TIMMS (1996). Different inputs were used, namely: (i) Spending per student in purchasing power parities; (ii) Educational expenditure to GDP, adjusted for population structure or for student enrolment as a share of the population. With different combinations of inputs and outputs, results were always in favour of an inefficient performance of the Portuguese educational sector. In the OECD context, Portugal was never in the 44 efficient frontier. Most of the times it was quite far from it, being placed in the second half of the ranking.

New results presented next may be interpreted as both an updating and a refinement of Clements (1999) analysis. On one hand, we use more recent data, including the new PISA (2001) study. On the other hand, we choose different input indicators. In fact, and as with health, the consideration of expenses as a share of GDP may tend to bias results, as Portugal is a poorer than average country. Also, it may be defended that spending per student is not a very good input when the output is expressed in per population terms. In our new results, spending was also expressed in population terms if the output is a graduation rate. From a qualitative point of view, Clements (1999) results proved to be robust to these changes – we also conclude clearly in favour of inefficiency.

4.3.2 New results

We apply here the techniques described in section 2 comparing inputs and outcomes in education. In applying FDH analysis, two input measures were chosen: cumulative expenditure per student and expenditure in primary and secondary education per habitant aged between 5 and 19, in both cases in US dollars converted using purchasing power parities. As the ultimate goal of education is successful learning, we have chosen two different measures related to it: the PISA results described above, and the graduation rates in upper secondary. The earlier is an international assessment, the latter being a national standard of success. Raw data for OECD countries used in this analysis is presented in Table 23.

The first evaluation was done comparing graduation rates and expenditure in primary and secondary education per habitant aged between 5 and 19. Graph 19 depicts the inferred efficiency frontier.

Graph 19

Portugal was the country where graduation rates were smaller. Two countries spending less achieved considerably higher rates – the Czech Republic and Greece. Consequently, Portugal was not in the efficient frontier. Numerical results for this analysis are presented in Table 24.

With the Portuguese level of expenditure, a graduation rate of 82.71 should have been achieved in efficient conditions. The vertical loss in graph 19 is therefore equal to 26.71, the higher in the sample. Expenditure loss is estimated as 13.24 % of actual expenditure – Portugal could have achieved this low graduation rate expending less (horizontal loss in the graph). Portugal comes 7th in 11 countries when efficiency is measured by expenditure loss. 46 Table 23 Raw data for efficiency analysis in education

Cumulative expenditure per Expenditure in primary PISA result, 2000 Upper Cumulative Expenditure PISA result, Graduation student (US$ converted using and secondary education secondary expenditure, per habitant, ranking rates, PPPs), 199825 per habitant aged 5-19 graduation ranking ranking ranking (US$ converted using rates, 199826 PPPs), 1998 Australia 44 623 na 529.70 na 12 na 4 na Austria 71 387 na 513.58 na 1 na 7 na Belgium 46 338 49 200 507.49 84.2 10 4 9 4 Czech Republic 21 384 23 426 500.19 80.0 20 11 13 11 Denmark 65 794 na 497.45 na 3 na 15 na Finland 45 363 na 540.12 na 11 na 3 na France 50 481 48 596 507.46 86.6 9 5 10 3 Germany 41 978 48 329 486.97 93.3 14 6 17 2 Greece 27 356 28 425 460.41 82.7 19 10 22 6 Hungary 20 277 na 488.03 na 21 na 16 na Ireland 31 015 na 514.32 na 17 na 6 na Italy 60 824 na 474.14 na 6 na 20 na Japan 53 255 43 634 543.08 96.0 8 7 1 1 Korea 30 844 na 541.24 na 18 na 2 na Mexico 11 239 na 410.26 na 23 na 23 na Norway 61 677 na 501.68 na 5 na 12 na Poland 16 154 na 477.45 na 22 na 19 na Portugal 36 521 na 460.96 56.0 16 9 21 11 Spain 36 699 37 715 486.60 67.1 15 8 18 10 Sweden 53 386 61 592 512.74 79.3 7 2 8 8 Switzerland 64 266 66 462 506.46 83.6 4 1 11 5 United Kingdom 42 793 na 528.22 na 13 na 5 na United States 67 313 52 412 499.01 73.5 2 3 14 9 Source: OECD (2000, 2001b, 2001c).

25 Cumulative expenditure per student corresponds to average spending per student from the beginning of primary school up to the age of 15. See OECD (2001c). 26 Ratio of upper secondary graduates to total population at typical age of graduation. 47

Table 24 FDH analysis Input: Educational expenditure per habitant aged 5-19 Outcome: Upper secondary graduation rates

Expenditure Graduation Expenditure Efficient Graduation Efficient loss ranking rate loss loss (%) expenditure rate loss graduation ranking (1000 US$ rate ppp) Japan 1 1 0.00% 43.63 0.00 95.99 Greece 1 1 0.00% 28.43 0.00 82.71 Czech 1 1 0.00% 23.43 0.00 80.04 Republic Germany 4 4 9.72% 43.63 2.71 95.99 France 5 5 10.21% 43.63 9.41 95.99 Belgium (fl.) 6 6 11.31% 43.63 11.77 95.99 Portugal 7 11 13.24% 28.43 26.71 82.71 United 8 10 16.75% 43.63 22.47 95.99 States Spain 9 8 24.63% 28.43 15.61 82.71 Sweden 10 9 29.16% 43.63 16.70 95.99 Switzerland 11 7 34.35% 43.63 12.43 95.99

Comparison of two other indicators allows having more countries in the sample, due to more data availability. In graph 20 we plot the efficiency frontier derived from the consideration of as an input and the average of PISA results as an outcome.

Graph 20

Again, it is apparent that Portugal is far from the efficient position. Poland, Hungary the Czech Republic, Ireland and Korea spend less than Portugal per student and get better results. It can be read from table 25 that expenditure loss (the vertical distance to the frontier) amounts to 15.5 percent of actual Portuguese expense. With the actual expense per student, a result 14.8 percent higher should be achieved in efficient conditions. Ranking countries by expenditure loss, Portugal comes 11th in 23. It comes last when the ranking is done by PISA results loss.

Table 25 FDH analysis Input: cumulative expenditure per student Outcome: Average of PISA results Expenditure PISA Expenditure Efficient PISA result Efficient loss ranking result loss (%) expenditure loss (%) PISA result loss (US$ ppp) ranking Japan 1 1 0.0% 53255 0.0% 543 Korea 1 1 0.0% 30844 0.0% 541 Czech 1 1 0.0% 21384 0.0% 500 Republic Hungary 1 1 0.0% 20277 0.0% 488 Poland 1 1 0.0% 16154 0.0% 477 Mexico 1 1 0.0% 11239 0.0% 410 Sweden 7 12 0.2% 53255 5.6% 543 Ireland 8 10 0.6% 30844 5.0% 541 Italy 9 22 12.4% 53255 12.7% 543 Norway 10 16 13.7% 53255 7.6% 543 Portugal 11 23 15.5% 30844 14.8% 541 Spain 12 21 16.0% 30844 10.1% 541 Switzerland 13 15 17.1% 53255 6.7% 543 b 14 19 19.1% 53255 8.4% 543 Denmark United 15 18 20.9% 53255 8.1% 543 States Greece 16 17 21.8% 21384 8.0% 500 Austria 17 11 25.4% 53255 5.4% 543 Germany 18 20 26.5% 30844 10.0% 541 United 19 9 27.9% 30844 2.4% 541 Kingdom Australia 20 8 30.9% 30844 2.1% 541 Finland 21 7 32.0% 30844 0.2% 541 Belgium 22 13 33.4% 30844 6.2% 541 France 23 14 38.9% 30844 6.2% 541

4.4 Education: conclusions and policy implications

Results from the previous sections on education can be summarised as following: i) Portugal is one of the OECD countries with less human capital, as measured by the educational attainment of the population; ii) There has been a very significant investment in education. This has allowed enrolment rates and school expectancy to rise and to converge to more developed countries levels. iii) Investment in education has been done at a cost to public finance that is comparable to other OECD countries, if one considers this cost in terms of its weight in total public expenditure or in GDP. Moreover, educational expenditure per student is not very high in Portugal in international terms. The weight of current expenditure, essentially staff compensation, is higher than in other OECD countries. iv) The Portuguese education system is not efficient if one takes into account the relationship between the level of spending and different success measures. Portuguese students perform badly in international exams, and upper secondary graduation rates are low, due to high failure rates at the end of secondary school.

Considering this state of affairs, it seems sensible to consider the following avenues in what concerns further research with strong policy implications27:

Careful examination and reassessment of teaching standards in secondary school, namely in key knowledge areas, e.g. the languages, sciences and mathematics. International student performance comparisons show that it is possible to better prepare students than it is currently done in Portugal. In this respect, international assessment should be pursued and deepened. The idea that course programmes, exams and classroom practices could be improved deserves some attention. Namely, achievements in previous levels that are too low in comparison to standards at the end of upper secondary may be one of the causes of the high failure rate.

A careful and open assessment of school performance. School assessment should be done carefully, independently and openly and not be confined to a simple comparison of student average results in

27 Some of the ideas proposed here are adapted or inspired in Carneiro (2000) and Clements (1999). 50 exams. Its main goal should be to identify best practices susceptible of further dissemination. The adoption of best practices should be encouraged by a well-designed system of incentives.

Review of personnel management and payments policy. Personnel management and pay policy could be reviewed in order to introduce adequate incentives so that human resources are allocated where they are most needed. Schools should not be either under or overstaffed, and a correct composition of teaching staff should be achieved at school level. Also, there seems to be scope to introduce some wage differentiation based on merit and individual achievement, and less on length of service.

Review of the breakdown of educational expenditures by resource category. The fact that in Portugal current expenditure is so much higher than capital expenditure deserves some more research and points to the hypothesis of some reallocation of resources.

Develop a life-long education program. As education attainment of the population is very low, convergence at a rewarding speed to more advanced international standards is only possible with the re-qualification of the adult population.

4. Final remarks

This paper provided empirical evidence for the existence of important inefficiencies in education and health spending in Portugal. Under the efficiency hypothesis, as the sector is below the efficiency frontier, there is an apparent room for Pareto optimal improvements – output can be expanded without increasing the cost. In practice, the implementation of policies, either in education or health, such as the ones suggested in sections 3.5 and 4.4 or any others, imply different and sometimes opposing choices that are ultimately the responsibility of policy-makers. This research tries to inform these choices and point towards some possible available options.

Some aspects, namely from a methodological point of view, deserve further research. Namely, it would be important to further test robustness of results to more specifications, different indicators or controls. Also, this author thinks this type of methods is rewarding and could be applied to other public spending areas, as justice or local government. They are also suitable to a more micro- oriented approach, and much could be learned from applications of efficiency frontier methods to, say, Portuguese schools or hospitals. 51

References

Banco de Portugal (2001), Relatório do Conselho de Administração – 2000.

Branco, F. (2000), Estudo Prospectivo sobre O Financiamento da Educação em Portugal, in Carneiro, Caraça and Pedro (2000), vol. 3.

Bassanini, A, S. Scarpetta and Ph. Hemmings (2001), Economic Growth: The Role of Polcies and Insitututions. Panel Data Evidence from OECD Countries, Working paper nº 283, OECD Economics Department.

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