Quality of public finances: some illustrations

Quality of public finances: some illustrations

António Afonso(European Central Bank; ISEG/UTL-Technical University of Lisbon;

UECE-Research Unit on Complexity and Economics )

Política fiscal y coordinación de políticas San Sebastian, 24 July 2009

These slides reflect the views of the author and do not necessarily reflect those of the ECB or the Eurosystem.

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1. Introduction and motivation

2. Measuring performance and efficiency

3. Methodology

4. Illustrative examples• Overall public sector

• Education

• Health

• Social spending

5. Conclusions

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“Public expenditure ratios have steadily increased in the euro area since the 1960s before peaking and, in some cases, declining in more recent years. Public expenditure is nevertheless much higher than in most other industrialised countries. According to many observers, it exceeds the levels required for the efficient provision of essential public services.”(ECB, Monthly Bulletin, April 2006, p. 73).

“The need to improve competitiveness, concerns about fiscal sustainability and growing demands by taxpayers to get more value for public money as well as the need to reconsider the scope for state intervention in the economy has prompted efforts to increase the focus of budgets on more growth-enhancing activities and gear the tax mix and the allocation of resources within the public sector towards better efficiency and effectiveness.” (EC, 2007, p. 9)

“The question we ask today is not whether our government is too big or too small, but whether it works (…). Where the answer is yes, we intend to move forward. Where the answer is no, programs will end. And those of us who manage the public's dollars will be held to account – to spend wisely, reform bad habits, and do our business in the light of day – because only then can we restore the vital trust between a people and their government.” (Barack Obama inaugural speech, 20 January 2009)

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Public finances efficiency and economic growth

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• Public finance developments, notably the growth in the size of the government, have increasingly been in the focus of policy debates.

• The existing fiscal framework in the EU has increased the awareness of the relevance of fiscal sound behaviour.

• The EC, the Lisbon Reform Agenda and the Stability and Growth Pact argue for assessing fiscal policy developments also by taking into account the quality of public finances, especially the efficiency and effectiveness of public spending.

• At the EU level the Working Group for the Quality of Public Finances was created in the Economic Policy Committee (in 2004).

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Total General Government spending (% of GDP)

Source: EC Ameco database and EC spring 2008 economic forecasts. DE, ES, GR, IE, SE, EA, EU15: values for 1980 are from the Ameco autumn 2006 database (old definition). For 1995, values reflect the euro area 13 whereas for 1980 values reflect the euro area 12 and West Germany respectively.

• General government sector increased in the euro area and in the EU15 from 1980 to 1995

• In 2007, higher than US and Japan

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on 1980 1995 2000 2007

Change 80 to 07

Austria 50.2 56.0 51.3 48.0 -2.1

Belgium 54.7 51.9 49.0 48.8 -5.9

Germany 46.6 48.3 45.1 43.9 -2.7

Denmark 52.7 59.3 53.5 50.6 -2.1

Spain 30.8 44.4 39.1 38.8 7.9

Finland 40.1 61.6 48.3 47.4 7.3

France 45.7 54.4 51.6 52.6 6.9

Greece 29.0 46.6 46.6 43.1 14.1

Ireland 45.6 41.1 31.6 36.4 -9.2

Italy 40.8 52.5 46.2 48.5 7.8

Luxembourg 42.3 39.7 37.6 37.5 -4.8

Netherlands 55.8 51.6 44.2 45.9 -9.9

Portugal 33.5 43.4 43.1 45.7 12.2

Sweeden 59.6 65.2 55.6 52.5 -7.1

United Kingdom 47.2 43.9 36.8 43.6 -3.6

Euro Area 44.5 50.6 46.2 46.3 1.8

EU 15 44.9 50.3 44.9 46.1 1.2

Japan 33.5 36.9 40.6 38.2 4.8

United States 33.8 35.4 32.5 35.6 1.8

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Main questions:– Are “public” services satisfactory considering the amount of resources allocated to its activity?

– Could one have better results using the same resources?

– Could we have the same results with lower expenses?

– Can we measure cross-country efficiency and determine benchmark countries?

– Can we explain measured inefficiency?– systemic component,

– environmental or non-discretionary component.

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Measuring public sector performance and efficiencyP

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• Public sector performance can be measured via output/outcome indicators:

– Health, education, infrastructure, income distribution…

=> need for good indicators

• Public sector efficiency relates outcomes to the resources used/inputs:

=> need for homogenous and matching data (heterogeneity is a limit)

Measuring performance and efficiency

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Key issues: methods and (homogeneous and “right”) data to assess performance and efficiency.

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• The common “production function” relates inputs (xi) to output (y):

y = F (x1,x2)

• Alternatively: F (x1, x2) is a production possibilities frontier

• Note that:

– typically there are several outputs, (y1, y2, ...)=F (x1,x2, ...);

– their joint production depends on several inputs– and on other “environment” variables.

• Non-parametric methods commonly used in the literature:

– FDH, DEA, both;

– Non-discretionary inputs should be considered;

– There are some examples of two-step (tobit/bootstrap) analysis.

• Parametric methods: stochastic frontier analysis.

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Frontier Analysis

Parametric

Deterministic

(COLS)

Stochastic

(SFA)

Extensions for Panel Data

Fixed Effects GLS Random Effects

Non-parametric

DEA FDH

Cost efficiency

Technical efficiency

Productivity

Total Factor Productivity

Partial Indicators

Malmquist Indices

Two-step analysis

Tobit

Bootstrap

Examples of possible methods

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One should be able to:

– i) estimate output efficiency scores for EU/OECD countries, taking into account the resources employed;

– ii) explain efficiency scores, controlling for environment factors (non-discretionary inputs).

Most used methodologies:• “raw” efficiency scores: DEA (data envelopment analysis);• stochastic frontier;• explaining inefficiency:

– tobit regression,– bootstrap technique

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y (3

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DEA

y - column vector of outputs, x - column vector of inputs, X - input matrix,

Y - output matrix.

- efficiency score (=1).

1, inefficiency = 1, efficiency

0

1'1

0

0 tos.

,

n

Xx

Yy

MIN

i

i

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Note: is the measure of efficiency, given by the ratio between the weighted average of the outputs (y) produced and the weighted average of the inputs (x) used. See Coelli et al. (1998) for more details.

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y –

DE

A

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DEA and FDH illustration

D’s output inefficiency

D’s input inefficiency

A, C – efficient;B, D – less efficient.

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DE

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D’s output score=d1/(d1+d2)

D’s environmentcorrected output score=d1c/(d1c+d2c)

1 > d1c/(d1c +d2c) > d1/(d1+d2), the environment corrected score is closer to the frontier.

Non-discretionary inputs and two-step procedure (1)

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Non-discretionary inputs and tobit two-step procedure (2)

Non-discretionary inputs:Socio-economic differences play a role in determining heterogeneity and influence outcomes (for either schools, hospitals, local governments or countries’ achievements in an international comparison).

The efficiency scores are not higher than 1 (or always lower than one according to the setup), which allows using a tobit regression approach.

iii z ˆ

Two-step approach:Efficiency scores () are regressed on non-discretionary factor (z):

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Malmquist Productivity Index – MPI (constant returns to scale)

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• The DMU produces less than feasible under each period’s production frontier.• The MPI indicates the potential rise in productivity as the frontier shifts from period t to t+1.

• The DMU at time t could produce output yp for input xt;• With the same input xt it could produce output yq at period t+1.

Met

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y –

MP

I

input

output

Efficiency change index

Technology change index

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ln ( , )it it it ity F X

it itz

i – country, t – time period; yit – output, GDP per worker;Xit – vector of inputs, private and public capital per worker and human capital; β – set of production function parameters to be estimated; t – normally distributed random error; it – non-negative efficiency effect, assumed to have a truncated normal distribution; zit – non-discretionary factors (the governance indicators) that explain inefficiency; – set of efficiency parameters to be estimated;A translog functional form for F(·) seems a sensible option.

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2 2

It is possible to produce a likelihood ratio statistic to test =0If =0, there are no random inefficiency effects.

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Coelli et al. (2005).

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SFA production possibility frontier

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• Van den Eeckhaut, Tulkens and Jamar (1993), efficiency in Belgian municipalities.• De Borger and Kerstens (1996), efficiency of Belgian local governments.• Evans, Tandon, Murray and Lauer (2000), efficiency of national health systems.• Gupta and Verhoeven (2001), education and health in Africa.• Clements (2002), education in Europe.• St. Aubyn (2003), education in the OECD. • Afonso, Schuknecht and Tanzi (2005, 2006), public sector in the OECD and in emerging

markets. • Afonso and St. Aubyn (2005a, b), health and education in OECD.• Afonso and St. Aubyn (2006, 2007), health and education in OECD using bootstrap

methods.• Afonso and Fernandes (2006, 2008), Portuguese municipalities.• Afonso and Scaglioni (2007), Italian regions.• Sutherland et al. (2007), education in OECD.• Eugene (2007), health, education, public order and safety and general public services in

EU15.• Afonso, Schuknecht and Tanzi (2008), social spending and income distribution in the

OECD.• St. Aubyn (2008), law and order efficiency measurement. • Geys, Heinemann, and Kalb (2008), German municipalities.• Afonso and St. Aubyn (2009), public and private inputs in aggregate production in OECD.

• Another strand: for instance, study of the determinants of (education) quality using cross-country regressions, Barro and Lee (2001), Hanushek and Luque (2003).

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Illustrative examples of public sector cross-country efficiency analysis

Overall public sector

Education

Health

Social spending

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1. Public spending policies are more useful when they• are limited to core/productive spending (including basic safety nets); • provide services in an efficient manner;

2. Cross-country, sector level analysis is important to highlight best practices; 3. Social protection, health, and education accounted for 64-65% of total

spending in the euro area/EU in 2006 (focus on these items);

4. DEA/tobit/bootstrap/stochastic frontier procedures have been recently used in the context of cross-country efficiency analysis;

5. Non-parametric analysis has the advantage that a priori conceptions about the shape of the production frontier are kept to a minimum;

6. Parametric analysis has the advantage of allowing for hypothesis testing;

7. Care is needed in selecting as homogeneous as possible data as well as the “right” data (physical vs. financial resources, etc.);

8. Countries far from the efficiency frontier: not necessarily inefficient (non-discretionary factors);

9. QPF indicators and efficiency assessments can help EU fiscal surveillance. SPs/CPs include a section on the quality of public finances;

10. An indirect cost of public sector provision inefficiency is the increase in the excess burden of taxation, (Afonso and Gaspar, 2007).

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PSP

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Source: Afonso, Schuknecht and Tanzi (2005).

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Public sector overall efficiency, 2000


Country Input efficiency Output efficiencyScore Rank Score Rank

Australia 0.99 4 0.92 7Austria 0.67 17 0.92 8Belgium 0.66 19 0.79 18Canada 0.75 12 0.84 13Denmark 0.62 21 0.87 11Finland 0.61 22 0.83 14France 0.64 20 0.77 20Germany 0.72 16 0.79 17Greece 0.73 14 0.65 23Iceland 0.87 7 0.90 10Ireland 0.96 5 0.93 6Italy 0.66 18 0.68 22Japan 1.00 1 1.00 1Luxembourg 1.00 1 1.00 1Netherlands 0.72 15 0.91 9New Zealand 0.83 9 0.81 15Norway 0.73 13 0.93 5Portugal 0.79 11 0.70 21Spain 0.80 10 0.78 19Sweden 0.57 23 0.86 12Switzerland 0.95 6 0.94 4United Kingdom 0.84 8 0.80 16United States 1.00 1 1.00 1Average 0.79 0.85EU15 average 0.73 0.82Non-EU15 average 0.89 0.92Small governments 1/ 0.98 0.96Medium governments 1/ 0.81 0.82Big governments 1/ 0.65 0.83EU 15 2/ 0.72 0.78Euro area 2/ 0.70 0.78

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Illustrative evidence on public sector performance and efficiency (considering general government spending)

NZ

IRAU

US

JP

NO

0.60

1.00

1.400.

60

1.00

1.40

Public sector performance/effectiveness

Public

sec

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effici

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Fl SW

DK

Effective &

efficientLess effective

but efficient

Effective but

less efficient

Less effective &

less efficient

GE

ITFR

ATBE

GR

CH

NL

PTSP

CAUK

Source: Adapted from Afonso, Schuknecht and Tanzi (2005).

Good performance (two right-hand side quadrants), includelower efficiency/higher spending (Finland, Sweden, and Denmark) andhigher efficiency/lower spending (Austria, Japan, Ireland, US).

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2000 2005Change00 to 05 2000 2005

Change00 to 05 2000 2005

Change00 to 05

Austria 7.7 7.0 -0.7 5.9 5.9 0.1 20.9 20.8 -0.2Belgium 6.3 7.1 0.8 5.7 6.1 0.4 16.8 17.9 1.0Denmark 6.6 6.9 0.3 8.0 7.9 0.0 21.8 22.6 0.8Finland 5.8 6.8 1.1 5.8 6.1 0.2 20.3 21.2 0.9France 6.6 7.3 0.7 6.3 6.1 -0.2 21.2 22.6 1.4Germany 6.2 6.2 0.0 4.2 4.1 -0.1 21.5 21.9 0.4Greece 2.6 3.7 1.1 2.6 2.2 -0.4 15.7 15.5 -0.2Hungary na 5.5 5.8 17.0Iceland 8.0 na 6.2 8.3Ireland 5.7 7.5 1.8 4.0 4.3 0.3 7.8 9.5 1.7Italy 6.0 na 4.9 17.5Japan 6.4 7.1 0.7 4.1 3.9 -0.2 11.0 12.1 1.1Korea 2.3 3.6 1.2 4.1 4.9 0.8 2.4 3.4 1.0Luxembourg 4.1 5.3 1.2 4.3 4.9 0.6 15.7 17.4 1.7Netherlands 3.7 4.3 0.6 4.7 5.1 0.4 16.6 16.9 0.2New Zealand na 6.6 7.4 10.3Poland na 4.5 6.2 17.1Portugal 6.4 7.2 0.8 6.7 7.4 0.7 12.5 15.8 3.3Spain 5.2 5.7 0.4 4.4 4.4 0.0 13.0 12.8 -0.2Sweden 6.3 7.0 0.7 6.8 7.3 0.5 23.5 23.8 0.3United Kingdom 5.8 7.1 1.3 4.9 5.8 0.8 14.8 15.9 1.1United States 6.3 7.5 1.2 6.0 6.2 0.3 6.6 7.1 0.5Euro Area 5.9 5.2 -0.7 5.0 4.1 -0.9 18.9 16.1 -2.8EU 15 (weighted) 5.9 5.6 -0.3 5.1 4.6 -0.5 18.4 16.4 -2.0

Health Education Social Protection

General Government functional spending (% of GDP)

Source: OECD.

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Table 1 – Public expenditure on education, 2001 (% of total expenditure in each level)

Pre-primary

education Primary and secondary education

Tertiary education

All levels of education

Australia 68.9 84.4 51.3 75.6 Austria 79.3 96.3 94.6 94.4 Belgium 96.6 95.0 84.1 93.0 Czech Republic 91.8 92.1 85.3 90.6 Denmark 81.7 98.0 97.8 96.1 Finland 91.0 99.1 96.5 97.8 France 95.9 93.0 85.6 92.0 Germany 62.3 81.1 91.3 81.4 Greece na 91.4 99.6 94.2 Hungary 90.6 93.1 77.6 89.0 Iceland na 95.3 95.0 91.7 Indonesia 5.3 76.3 43.8 64.2 Ireland 33.2 95.3 84.7 92.2 Italy 97.0 98.0 77.8 90.7 Japan 50.4 91.5 43.1 75.0 Korea 48.7 76.2 15.9 57.1 Mexico 86.7 87.2 70.4 84.6 Netherlands 98.2 95.1 78.2 90.9 Norway na na 96.9 95.9 Portugal na 99.9 92.3 98.5 Slovak Republic 97.4 98.5 93.3 97.1 Spain 83.4 93.3 75.5 87.8 Sweden 100.0 99.9 87.7 96.8 Switzerland na 84.8 na na Thailand 97.8 na 82.5 95.6 Tunisia na 100.0 100.0 100.0 Turkey na na 95.8 na United Kingdom 95.7 87.2 71.0 84.7 United States 68.1 93.0 34.0 69.2 Uruguay 81.3 93.5 99.5 93.4 Mean 78.3 92.2 79.3 88.2 Median 86.7 93.3 85.3 91.9 Minimum 5.3 76.2 15.9 57.1 Maximum 100.0 100.0 100.0 100.0 Standard deviation 24.3 6.8 21.8 10.8 Observations 23 27 29 28

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DEA results

Table 3 – Results for education efficiency (n=25) 2 inputs (teachers-students ratio, hours in school) and 1 output (PISA 2003 indicator)

DEA Output oriented

Country VRS TE Rank Peers

Australia 1.038 7 Finland Austria 1.095 14 Finland Belgium 1.055 8 Finland Czech Republic 1.068 9 Finland Denmark 1.093 13 Finland Finland 1.000 1 Finland France 1.072 10 Finland Germany 1.083 12 Finland, Korea Greece 1.182 21 Finland Hungary 1.105 15 Finland Indonesia 1.447 25 Finland, Korea Ireland 1.079 11 Finland, Korea Italy 1.151 19 Finland Japan 1.024 4 Finland, Korea Korea 1.000 1 Korea Netherlands 1.037 6 Finland, Korea New Zealand 1.036 5 Finland, Korea Norway 1.109 16 Finland Portugal 1.161 20 Finland Slovak Republic 1.118 17 Finland Spain 1.129 18 Finland Sweden 1.000 1 Sweden Thailand 1.283 24 Finland, Korea Turkey 1.260 22 Finland, Korea, Sweden Uruguay 1.278 23 Finland, Korea Average 1.116

With the same inputs, it would be possible to increase the output.

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Note: in this example inefficient values are higher than unity.

Source: Afonso and St. Aubyn (2006).

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Results from education tobit:

Table 4 – Censored normal Tobit results (25 countries)

Model 1

Model 2 Model 3 Model 1a Model 3a

Constant 1.295024 (0.000)

1.342502 (0.000)

1.374361 (0.000)

2.614888 (0.000)

2.237114 (0.000)

Y -0.825e-5 (0.000)

-0.427e-5 (0.012)

Log(Y) -0.152062 (0.000)

-0.101269 (0.000)

E -0.003566 (0.000)

-0.002574 (0.000)

-0.001903 (0.001)

0.081428 (0.000)

0.071752 (0.000)

0.062480 (0.000)

0.063324 (0.000)

0.051811 (0.000)

Notes: Y – GDP per capita; E – Parental educational attainment. – Estimated standard deviation of

P- values in brackets.

iiii EY 210ˆ

efficiency , EY

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Note: in this example inefficient scores () are higher than unity.


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Health expenditure

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OECD, 2003:8.7 % of GDP, of which 72.5% is public spending.


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Health inputs and outputs summary

Ou

tpu

tsIn

pu

ts

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Infant survival rate (ISR) = [1000-infant mortality rate]/[infant mortality rate]

Source: OECD.

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Principal component analysis (PCA) for health analysis

• PCA reduces the dimensionality of multivariate data

• Afonso and St. Aubyn (2007) in the case of health in OECD

- apply PCA to the 4 input variables;

- use the first 3 principal components as the 3 input measures (they explain around 88% of the variation);

- applied PCA to the three output variables;

- selected the 1st principal component (it accounts for around 84% of the variation);

• This reduces the problem to 1 output – 3 inputs (helpful since, as as a general rule of thumb, there should be at least 3 units for each input

and output)

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Health output efficiency results – DEA

With the same inputs, on average, output could increase.

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Note: in this example inefficient values are higher than unity.


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Results from 2nd step health Tobit

, efficiencyO T efficiency , EY

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Note: in this example inefficient scores () are higher than unity.


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Income distribution efficiency:Production possibility frontier (1 input, 1 output)

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NZ

UK

DNK

JAP

FRA

NLD

ESPIRL

CAN

ITA

SVKNOR

AUS

BEL

CZRAUT

PRT

POL

SWELUX

SWZ

HUN

DEU

FIN

GRC

USA

60

65

70

75

80

85

5.0 10.0 15.0 20.0 25.0 30.0 35.0

Social spending-to-GDP ratio (%)

10

0-G

ini

Source: Afonso et al. (2008).

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DEA income distribution efficiency (1 input, public social expenditure; 2 outputs, Gini coefficient, income share of poorest 40%)

A. AfonsoSource: Afonso et al. (2008).

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Production possibility frontier, CRS, 1 input (social spending-to-GDP), 2 outputs (income share of poorest 40%, Gini)

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BEL

FIN

UK

ITA

NDL

PRTGRC

SWZSWE

FRA

NZESP

NORLUX

US

IRL

DNK

CAN

DEU

AT

AUS

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

2.0 2.5 3.0 3.5 4.0 4.5 5.0

Output2/Input (Gini/Spending)

Ou

tpu

t1/I

np

ut

(Sh

are

40

%/S

pe

nd

ing

)

CRS PPF frontier

Source: Afonso et al. (2008).

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• Afonso, A. and Fernandes, S. (2006).“Measuring local government spending efficiency: Evidence for the Lisbon Region”, Regional Studies, 2006, 40 (1), 39-53.

• Afonso, A. and Fernandes, S. (2008). “Assessing and Explaining the Relative efficiency of Local Government”, Journal of Socio-Economics, 37 (5), 1946-1979.

• Afonso, A. and Gaspar, V. (2007). “Dupuit, Pigou and cost of inefficiency in public services provision”, Public Choice, 132 (3-4), 485-502.

• Afonso, A. and St. Aubyn, M. (2005a). “Non-parametric Approaches to Education and Health Efficiency in OECD Countries”, Journal of Applied Economics, 8 (2), 227-246.

• Afonso, A. and St. Aubyn, M. (2005b). “Assessing Education and Health Efficiency in OECD Countries using alternative Input Measures,” in Public Expenditure, 361-388. Banca d’ Itália.

• Afonso, A. and St. Aubyn, M. (2006). "Cross-country Efficiency of Secondary Education Provision: a Semi-parametric Analysis with Non-discretionary Inputs", Economic Modelling, 23 (3), 476-491. [ECB WP 494, 2005]

• Afonso, A. and St. Aubyn, M. (2007). “Assessing health efficiency across countries with a two-step and bootstrap analysis”, ISEG/UTL WP 33/2006/DE/UECE.

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• Afonso, A.; Schuknecht, L. and Tanzi, V. (2006). “Public Sector Efficiency: Evidence for New EU Member States and Emerging Markets”, ECB Working Paper n. 581, Applied Economics, forthcoming.

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• Simar, L. and Wilson, P. (2007). “Estimation and Inference in Two-Stage, Semi-Parametric Models of Production Processes”, Journal of Econometrics, 136 (1), 31-64.

• St. Aubyn, M. (2003). “Evaluating Efficiency in the Portuguese Education Sector”, Economia, 26, 25-51.”

• St. Aubyn, M. (2008). “Law and Order Efficiency Measurement – A Literature Review”, ISEG/UTL WP 19/2008/DE/UECE.

• Sutherland, D.; Price, R.; Joumard, I. and Nicq, C. (2007). “Performance indicators for public spending efficiency in primary and secondary education”, OECD Economics Department WP 546.

• Van den Eeckhaut, P., Tulkens, H., and Jamar, M.-A. (1993). “Cost-efficiency in Belgian municipalities,” in Fried, H.; Lovell, C. and Schmidt, S. (eds.), The Measurement of Productive Efficiency: Techniques and Applications. New York: Oxford Univ. Press.

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Corrective arm of the SGP *

Mentions that the Commission and the Council, when assessing and deciding upon the existence of an excessive deficit, shall take into account “developments in the medium-term budgetary position (in particular, fiscal consolidation efforts in ‘good times’, debt sustainability, public investment and the overall quality of public finances)”. (see also EC, 2008a)

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* Regulation of the European Council, N.º 1467/97 of 7 July 1997, modified by Regulation N.º 1056/2005 of 27 June 2005, on speeding up and clarifying the

implementation of the excessive deficit procedure.

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iii z ˆ

- Each efficiency score estimate depends on all observed inputs and outputs: εi is serially correlated..- The environmental variables are correlated with both inputs and outputs: εi is not independent from zi.

Problems with tobit traditional procedure:

Simar and Wilson (2007) propose alternative estimation and inference procedures based on bootstrap methods. They assume:

,1),( iii z

where εi is a left truncated normal random variable.

Non-discretionary inputs and tobit two-step procedure (3)

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Data for education analysis

Country

PISA (2003)

1/

Hours per year in school, 2000-2002

2/

Teachers per 100 students, 2000-2002

3/

GDP per capita, 2003

(USD) 4/

Parental education

attainment, 2001-2002 5/

Public-to-total expenditure ratio 2001-

2002 6/ Australia 526.15 1023.7 8.0 29143. 4 61.1 84.6 Austria 498.35 1072.5 10.0 29972. 5 81.9 96.0 Belgium 517.59 1005.0 10.5 28396. 1 64.6 94.4 Brazil 379.84 800.0 5.5 7767. 2 57.3 Czech Republic 511.16 867.0 7.5 16448. 2 90.5 91.9 Denmark 499.65 860.0 7.8 31630. 2 80.5 97.9 Finland 545.90 807.0 7.3 27252. 2 84.7 99.3 France 509.34 1037.0 8.1 27327. 2 67.9 93.0 Germany 502.53 886.0 6.6 27608. 8 85.6 80.8 Greece 461.67 1064.0 10.1 19973. 2 59.4 91.6 Hungary 494.06 925.0 8.7 14572. 3 78.6 92.9 Iceland 501.57 821.9 na 30657. 3 61.0 95.2 Indonesia 374.55 1274.0 5.5 3364. 5 22.7 76.4 Ireland 505.54 896.3 7.0 36774. 8 63.7 95.7 Italy 474.31 1020.0 9.8 27049. 9 49.4 97.9 Japan 531.79 875.0 6.7 28162. 2 94.0 91.6 Korea 541.29 867.0 5.1 17908. 4 77.8 78.5 Mexico 393.56 1166.9 3.3 9136. 2 15.6 86.7 Netherlands 523.87 1066.9 6.1 29411. 8 69.9 94.8 New Zealand 524.68 952.6 6.1 21176. 9 79.6 na Norway 492.23 826.8 9.6 37063. 4 90.8 99.2 Poland 492.81 na 6.8 11622. 9 47.9 na Portugal 470.29 881.7 11.5 18443. 5 20.0 99.9 Russian Federation 469.61 989.0 8.9 9195. 2 na na Slovak Republic 488.49 886.3 7.4 13468. 7 90.3 98.1 Spain 483.75 907.2 8.6 22264. 45.3 93.1 Sweden 509.50 740.9 7.3 26655. 5 86.8 99.9 Switzerland 514.99 887.0 na 30186. 1 87.3 86.9 Thailand 422.73 1167.0 5.6 7580. 3 19.0 97.8 Tunisia 365.70 890.0 4.6 7082. 9 na 100.0 Turkey 426.54 841.3 5.7 6749. 3 24.7 na United States 486.67 na 6.5 37352. 1 88.5 91.5 Uruguay 426.35 913.0 6.9 8279. 9 35.1 93.5 Mean 480.82 942.5 7.4 21202.3 63.9 92.8 Minimum 365.70 740.9 3.3 3364.5 15.6 76.4 Maximum 545.90 1274.0 11.5 37352.1 94.0 100.0 Standard deviation 48.87 122.0 1.9 10168.7 24.6 6.5 Observations 33 31 31 33 31 28

Source: OECD.

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Health analysis – 2nd step (bootstrap)

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Documents

Quality of public finances: some illustrations