Transcript Assessing public sector performance and efficiency: some

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.
1.
2.
3.
4.
Introduction and motivation
Measuring performance and efficiency
Methodology
Illustrative examples
•
•
•
•
Overall public sector
Education
Health
Social spending
5. Conclusions
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Introduction and motivation
“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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Introduction and motivation
Public finances efficiency and economic growth
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Introduction and motivation
• 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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Introduction and motivation
Total General Government spending (% of GDP)
Austria
Belgium
Germany
Denmark
Spain
Finland
France
Greece
Ireland
Italy
Luxembourg
Netherlands
Portugal
Sweeden
United Kingdom
Euro Area
EU 15
Japan
United States
1980
50.2
54.7
46.6
52.7
30.8
40.1
45.7
29.0
45.6
40.8
42.3
55.8
33.5
59.6
47.2
44.5
44.9
33.5
33.8
1995
56.0
51.9
48.3
59.3
44.4
61.6
54.4
46.6
41.1
52.5
39.7
51.6
43.4
65.2
43.9
50.6
50.3
36.9
35.4
2000
51.3
49.0
45.1
53.5
39.1
48.3
51.6
46.6
31.6
46.2
37.6
44.2
43.1
55.6
36.8
46.2
44.9
40.6
32.5
2007
48.0
48.8
43.9
50.6
38.8
47.4
52.6
43.1
36.4
48.5
37.5
45.9
45.7
52.5
43.6
46.3
46.1
38.2
35.6
Change
80 to 07
-2.1
-5.9
-2.7
-2.1
7.9
7.3
6.9
14.1
-9.2
7.8
-4.8
-9.9
12.2
-7.1
-3.6
1.8
1.2
4.8
1.8
• General
government
sector increased in the
euro area and in the
EU15 from 1980 to 1995
• In 2007, higher than
US and Japan
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.
A. Afonso
Performance and efficiency
Measuring public sector performance and efficiency
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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Performance and efficiency
Measuring performance and efficiency
• 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)
Key issues: methods and (homogeneous and “right”) data to
assess performance and efficiency.
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Methodology (1)
• 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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Methodology (2)
Examples of possible methods
Cost efficiency
Productivity
Technical efficiency
Total Factor
Productivity
Partial
Indicators
Frontier Analysis
Malmquist Indices
Parametric
Non-parametric
Deterministic
Stochastic
(COLS)
(SFA)
DEA
Extensions for Panel Data
FDH
Two-step
analysis
Tobit
Bootstrap
Fixed Effects
GLS
Random Effects
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Methodology (3)
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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Methodology – DEA
DEA
MIN
q , q
s. t o  y i  Y  0
qx i  X   0
n1'   1
0
y - column vector of outputs,
x - column vector of inputs,
X - input matrix,
Y - output matrix.
q - efficiency score (q<=1).
q < 1, inefficiency
q = 1, efficiency
Note: q 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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Methodology – DEA
DEA and FDH illustration
D’s output
inefficiency
A, C – efficient;
B, D – less efficient.
D’s input inefficiency
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Methodology – exogenous factors
Non-discretionary inputs and two-step procedure (1)
D’s environment
corrected output score=
d1c/(d1c+d2c)
D’s output score=
d1/(d1+d2)
1 > d1c/(d1c +d2c) > d1/(d1+d2), the environment corrected score is closer to the frontier.
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Methodology – exogenous factors
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).
Two-step approach:
Efficiency scores () are regressed on non-discretionary factor (z):
ˆi  zi    i
The efficiency scores are not higher than 1 (or always lower than
one according to the setup), which allows using a tobit regression
approach.
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Malmquist Productivity Index – MPI (constant returns to scale)
output
Methodology – MPI
• 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.
Efficiency change index
Technology change index
input
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Stochastic frontier analysis
ln yit  F ( X it ,  ) it   it
Coelli et al. (2005).
it  q zit
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;
it – 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;
q – set of efficiency parameters to be estimated;
A translog functional form for F(·) seems a sensible option.
 2
 2
    2
It is possible to produce a likelihood ratio statistic to test =0
If =0, there are no random inefficiency effects.
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Stochastic frontier
SFA production possibility frontier
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A. Afonso
Some literature
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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 crosscountry 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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Conclusions
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 (nondiscretionary 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
Source: Afonso, Schuknecht
and Tanzi (2005).
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A. Afonso
Country
Australia
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Greece
Iceland
Ireland
Italy
Japan
Luxembourg
Netherlands
New Zealand
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
United States
Average
EU15 average
Non-EU15 average
Small governments 1/
Medium governments 1/
Big governments 1/
EU 15 2/
Euro area 2/
A. Afonso
Input efficiency
Score
Rank
0.99
4
0.67
17
0.66
19
0.75
12
0.62
21
0.61
22
0.64
20
0.72
16
0.73
14
0.87
7
0.96
5
0.66
18
1.00
1
1.00
1
0.72
15
0.83
9
0.73
13
0.79
11
0.80
10
0.57
23
0.95
6
0.84
8
1.00
1
0.79
0.73
0.89
0.98
0.81
0.65
0.72
0.70
Output efficiency
Score
Rank
0.92
7
0.92
8
0.79
18
0.84
13
0.87
11
0.83
14
0.77
20
0.79
17
0.65
23
0.90
10
0.93
6
0.68
22
1.00
1
1.00
1
0.91
9
0.81
15
0.93
5
0.70
21
0.78
19
0.86
12
0.94
4
0.80
16
1.00
1
0.85
0.82
0.92
0.96
0.82
0.83
0.78
0.78
Public sector overall
efficiency, 2000
Source: Afonso, Schuknecht
and Tanzi (2005).
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Illustrative evidence on public sector performance and
efficiency (considering general government spending)
1.40
Public sector efficiency
Less effective
US
but efficient
IR
Effective &
efficient
CH
UK
CA
BE
1.00
AU
JP
GR
SP
PT
IT
Less effective &
NZ
FR
GE
Fl
AT
NL NO
DK
SW
less efficient
Effective but
less efficient
Public sector performance/effectiveness
Good performance (two right-hand side quadrants), include
lower efficiency/higher spending (Finland, Sweden, and Denmark) and
higher efficiency/lower spending (Austria, Japan, Ireland, US).
Source: Adapted from Afonso, Schuknecht and Tanzi (2005).
A. Afonso
1.40
1.00
0.60
0.60
General Government functional spending (% of GDP)
Health
Austria
Belgium
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Japan
Korea
Luxembourg
Netherlands
New Zealand
Poland
Portugal
Spain
Sweden
United Kingdom
United States
Euro Area
EU 15 (weighted)
2000
7.7
6.3
6.6
5.8
6.6
6.2
2.6
na
8.0
5.7
6.0
6.4
2.3
4.1
3.7
na
na
6.4
5.2
6.3
5.8
6.3
5.9
5.9
2005
7.0
7.1
6.9
6.8
7.3
6.2
3.7
5.5
na
7.5
na
7.1
3.6
5.3
4.3
6.6
4.5
7.2
5.7
7.0
7.1
7.5
5.2
5.6
Education
Change
00 to 05
-0.7
0.8
0.3
1.1
0.7
0.0
1.1
2000
5.9
5.7
8.0
5.8
6.3
4.2
2.6
0.7
1.2
1.2
0.6
6.2
4.0
4.9
4.1
4.1
4.3
4.7
0.8
0.4
0.7
1.3
1.2
-0.7
-0.3
6.7
4.4
6.8
4.9
6.0
5.0
5.1
1.8
2005
5.9
6.1
7.9
6.1
6.1
4.1
2.2
5.8
Social Protection
Change
00 to 05
0.1
0.4
0.0
0.2
-0.2
-0.1
-0.4
2000
20.9
16.8
21.8
20.3
21.2
21.5
15.7
4.3
0.3
3.9
4.9
4.9
5.1
7.4
6.2
7.4
4.4
7.3
5.8
6.2
4.1
4.6
-0.2
0.8
0.6
0.4
8.3
7.8
17.5
11.0
2.4
15.7
16.6
0.7
0.0
0.5
0.8
0.3
-0.9
-0.5
12.5
13.0
23.5
14.8
6.6
18.9
18.4
2005
20.8
17.9
22.6
21.2
22.6
21.9
15.5
17.0
Change
00 to 05
-0.2
1.0
0.8
0.9
1.4
0.4
-0.2
9.5
1.7
12.1
3.4
17.4
16.9
10.3
17.1
15.8
12.8
23.8
15.9
7.1
16.1
16.4
1.1
1.0
1.7
0.2
3.3
-0.2
0.3
1.1
0.5
-2.8
-2.0
Source: OECD.
A. Afonso
Table 1 – Public expenditure on education, 2001
(% of total expenditure in each level)
Pre-primary
education
Australia
Austria
Belgium
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Indonesia
Ireland
Italy
Japan
Korea
Mexico
Netherlands
Norway
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Thailand
Tunisia
Turkey
United Kingdom
United States
Uruguay
Mean
Median
Minimum
Maximum
Standard deviation
Observations
68.9
79.3
96.6
91.8
81.7
91.0
95.9
62.3
na
90.6
na
5.3
33.2
97.0
50.4
48.7
86.7
98.2
na
na
97.4
83.4
100.0
na
97.8
na
na
95.7
68.1
81.3
78.3
86.7
5.3
100.0
24.3
23
Primary and
secondary
education
84.4
96.3
95.0
92.1
98.0
99.1
93.0
81.1
91.4
93.1
95.3
76.3
95.3
98.0
91.5
76.2
87.2
95.1
na
99.9
98.5
93.3
99.9
84.8
na
100.0
na
87.2
93.0
93.5
92.2
93.3
76.2
100.0
6.8
27
Tertiary
education
All levels of
education
51.3
94.6
84.1
85.3
97.8
96.5
85.6
91.3
99.6
77.6
95.0
43.8
84.7
77.8
43.1
15.9
70.4
78.2
96.9
92.3
93.3
75.5
87.7
na
82.5
100.0
95.8
71.0
34.0
99.5
79.3
85.3
15.9
100.0
21.8
29
75.6
94.4
93.0
90.6
96.1
97.8
92.0
81.4
94.2
89.0
91.7
64.2
92.2
90.7
75.0
57.1
84.6
90.9
95.9
98.5
97.1
87.8
96.8
na
95.6
100.0
na
84.7
69.2
93.4
88.2
91.9
57.1
100.0
10.8
28
Source: OECD.
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26
Table 3 – Results for education efficiency (n=25)
2 inputs (teachers-students ratio, hours in school) and 1 output (PISA 2003 indicator)
Country
Australia
Austria
Belgium
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Indonesia
Ireland
Italy
Japan
Korea
Netherlands
New Zealand
Norway
Portugal
Slovak Republic
Spain
Sweden
Thailand
Turkey
Uruguay
Average
A. Afonso
DEA Output oriented
VRS TE
Rank
1.038
7
1.095
14
1.055
8
1.068
9
1.093
13
1.000
1
1.072
10
1.083
12
1.182
21
1.105
15
1.447
25
1.079
11
1.151
19
1.024
4
1.000
1
1.037
6
1.036
5
1.109
16
1.161
20
1.118
17
1.129
18
1.000
1
1.283
24
1.260
22
1.278
23
1.116
Peers
Finland
Finland
Finland
Finland
Finland
Finland
Finland
Finland, Korea
Finland
Finland
Finland, Korea
Finland, Korea
Finland
Finland, Korea
Korea
Finland, Korea
Finland, Korea
Finland
Finland
Finland
Finland
Sweden
Finland, Korea
Finland, Korea, Sweden
Finland, Korea
DEA results
Note: in this example
inefficient values are
higher than unity.
With the same inputs,
it would be possible
to increase the output.
27
Source: Afonso and St. Aubyn (2006).
Results from education tobit:
ˆi  0  1Yi  2 Ei   i
Table 4 – Censored normal Tobit results
(25 countries)
Constant
Y
Model 1
Model 2
Model 3
Model 1a
Model 3a
1.295024
(0.000)
-0.825e-5
(0.000)
1.342502
(0.000)
1.374361
(0.000)
-0.427e-5
(0.012)
2.614888
(0.000)
2.237114
(0.000)
-0.152062
(0.000)
-0.101269
(0.000)
-0.001903
(0.001)
0.051811
(0.000)
Log(Y)
E
ˆ 
0.081428
(0.000)
-0.003566
(0.000)
0.071752
(0.000)
-0.002574
(0.000)
0.062480
(0.000)
Notes: Y – GDP per capita; E – Parental educational attainment.
 P- values in brackets.
0.063324
(0.000)
ˆ 
– Estimated standard deviation of
Note: in this example inefficient scores () are higher than unity.
Y , E     efficiency
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Source: Afonso and St. Aubyn (2006).
Health
expenditure
OECD, 2003:
8.7 % of GDP, of
which 72.5% is
public spending.
Source: Afonso and St.
Aubyn (2007).
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Inputs
Outputs
Health inputs and outputs summary
Source: OECD.
Infant survival rate (ISR) = [1000-infant mortality rate]/[infant mortality rate]
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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
Note: in this example
inefficient values are
higher than unity.
With the same inputs,
on average, output
could increase.
Source: Afonso and St. Aubyn (2007).
A. Afonso
32
Results from 2nd step health Tobit
Source: Afonso and St. Aubyn (2007).
Note: in this example inefficient scores () are higher than unity.
Y , E     efficiency
O, T     efficiency
33
A. Afonso
Income distribution efficiency:
Production possibility frontier (1 input, 1 output)
85
DNK
80
FIN
SVK
LUX
NOR
100-Gini
75
CZR
JAP
NZ
ESP
65
USA
DEU
BEL FRA
HUN POL
AUS
IRL
AUT
SWZ
CAN
70
NLD
SWE
UK
ITA
GRC
PRT
60
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Social spending-to-GDP ratio (%)
Source: Afonso et al. (2008).
34
A. Afonso
DEA income distribution efficiency (1 input, public social expenditure;
2 outputs, Gini coefficient, income share of poorest 40%)
Source: Afonso et al. (2008).
A. Afonso
35
Production possibility frontier, CRS, 1 input (social spending-to-GDP),
2 outputs (income share of poorest 40%, Gini)
Output1/Input (Share 40%/Spending)
1.3
IRL
1.2
CAN
1.1
LUX
1.0
US
AUS
NOR
ESP
0.9
0.8
AT FIN
GRC PRT
DEU
UK
BELITASWZ
DNK
SWE
0.7
NZ
NDL
FRA
0.6
CRS PPF frontier
0.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Output2/Input (Gini/Spending)
Source: Afonso et al. (2008).
36
A. Afonso
References (1)
•
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 twostep and bootstrap analysis”, ISEG/UTL WP 33/2006/DE/UECE.
•
Afonso, A. and St. Aubyn, M. (2009). “Public and Private Inputs in Aggregate Production and
Growth: A Cross-country Efficiency Approach”, mimeo.
•
Afonso, A. and Scaglioni, C. (2007). “Efficiency in italian regional public utilities’ provision”, in
Servizi Publici: Nuove tendenze nella regolamentazione, nella produzione e nel finanziamento, pp.
397-418, eds. M. Marrelli, F. Padovano and I. Rizzo, 2007, FrancoAngeli, Milano, Italy. ISBN 97888-464-8786-5.
•
Afonso, A., Schuknecht. L. and Tanzi, V. (2005). "Public sector efficiency: An international
comparison," Public Choice, 123 (3), 321-347. [ECB WP 242, 2003]
37
A. Afonso
References (2)
•
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.
•
Afonso, A., Schuknecht, L. and Tanzi, V. (2008). “Income Distribution Determinants and Public
Spending Efficiency ”, ECB Working Paper n. 861.
•
Barrios, S., Pench, L. and Schaechter, A. (2009, eds.). “The quality of public finances and economic
growth: Proceedings to the annual Workshop on public finance”, European Economy - Occasional
Papers n. 45.
•
Barro, R. and Lee, J-W. (2001). “Schooling Quality in a Cross-Section of Countries.” Economica, 68,
465-488.
•
De Borger, B. and Kerstens, K. (1996). “Cost efficiency of Belgian local governments: A
comparative analysis of FDH, DEA, and econometric approaches”. Regional Science and Urban
Economics 26, 145-170.
•
Clements, B. (2002). “How Efficient is Education Spending in Europe?” European Review of
Economics and Finance, 1 (1), 3–26.
•
Coelli, T.; Rao, P. and Battese, G. (2005). An Introduction to Efficiency and Productivity Analysis. 2nd
ed., Kluwer, Boston.
•
EC (2007). The EU economy: 2007 review, Moving Europe's productivity frontier. November
•
EC (2008a). “Public Finances in EMU 2008”.
•
EC (2008b). “The quality of public finances: Findings of the Economic Policy Committee-Working
Group (2004-2007), Deroose, S. and Kastrop, C. (eds.). Occasional Papers 37, March.
38
A. Afonso
References (3)
•
ECB (2006). “The importance of public expenditure reform for economic growth and stability”, ECB
Monthly Bulletin, April, pp. 61-73.
•
Eugène, B. (2007). “The efficiency of the Belgian general government in an international
perspective”, mimeo, National Bank of Belgium.
•
Evans, D.; Tandon, A.; Murray, C. and Lauer, J. (2000). “The Comparative Efficiency of National
Health Systems in Producing Health: an Analysis of 191 Countries”, GPE Discussion Paper Series
29, Geneva, World Health Organisation.
•
Geys, B., Heinemann, F. and Kalb, A. (2008). “Voter Involvement, Fiscal Autonomy and Public
Sector Efficiency: Evidence from German Municipalities”, ZEW Discussion Paper 08-024.
•
Hanushek, E. and Luque, J. (2003). “Efficiency and equity in schools around the world”, Economics
of Education Review, 22, 481-502.
•
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.
39
A. Afonso
Quality and efficiency in the SGP
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 mediumterm 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)
* 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.
40
A. Afonso
Methodology – exogenous factors
Non-discretionary inputs and tobit two-step procedure (3)
Problems with tobit traditional procedure:
ˆi  zi    i
- 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.
Simar and Wilson (2007) propose alternative estimation and
inference procedures based on bootstrap methods. They assume:
 i   ( zi ,  )   i  1,
where εi is a left truncated normal random variable.
41
A. Afonso
Country
PISA (2003)
Australia
Austria
Belgium
Brazil
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Indonesia
Ireland
Italy
Japan
Korea
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Russian Federation
Slovak Republic
Spain
Sweden
Switzerland
Thailand
Tunisia
Turkey
United States
Uruguay
Mean
Minimum
Maximum
Standard deviation
Observations
1/
526.15
498.35
517.59
379.84
511.16
499.65
545.90
509.34
502.53
461.67
494.06
501.57
374.55
505.54
474.31
531.79
541.29
393.56
523.87
524.68
492.23
492.81
470.29
469.61
488.49
483.75
509.50
514.99
422.73
365.70
426.54
486.67
426.35
480.82
365.70
545.90
48.87
33
Hours per year Teachers per
GDP per
in school,
100 students, capita, 2003
2000-2002
2000-2002
(USD)
2/
3/
4/
1023.7
8.0
29143. 4
1072.5
10.0
29972. 5
1005.0
10.5
28396. 1
800.0
5.5
7767. 2
867.0
7.5
16448. 2
860.0
7.8
31630. 2
807.0
7.3
27252. 2
1037.0
8.1
27327. 2
886.0
6.6
27608. 8
1064.0
10.1
19973. 2
925.0
8.7
14572. 3
821.9
na
30657. 3
1274.0
5.5
3364. 5
896.3
7.0
36774. 8
1020.0
9.8
27049. 9
875.0
6.7
28162. 2
867.0
5.1
17908. 4
1166.9
3.3
9136. 2
1066.9
6.1
29411. 8
952.6
6.1
21176. 9
826.8
9.6
37063. 4
na
6.8
11622. 9
881.7
11.5
18443. 5
989.0
8.9
9195. 2
886.3
7.4
13468. 7
907.2
8.6
22264.
740.9
7.3
26655. 5
887.0
na
30186. 1
1167.0
5.6
7580. 3
890.0
4.6
7082. 9
841.3
5.7
6749. 3
na
6.5
37352. 1
913.0
6.9
8279. 9
942.5
7.4
21202.3
740.9
3.3
3364.5
1274.0
11.5
37352.1
122.0
1.9
10168.7
31
31
33
Parental
education
attainment,
2001-2002 5/
61.1
81.9
64.6
57.3
90.5
80.5
84.7
67.9
85.6
59.4
78.6
61.0
22.7
63.7
49.4
94.0
77.8
15.6
69.9
79.6
90.8
47.9
20.0
na
90.3
45.3
86.8
87.3
19.0
na
24.7
88.5
35.1
63.9
15.6
94.0
24.6
31
Public-to-total
expenditure
ratio 20012002 6/
84.6
96.0
94.4
91.9
97.9
99.3
93.0
80.8
91.6
92.9
95.2
76.4
95.7
97.9
91.6
78.5
86.7
94.8
na
99.2
na
99.9
na
98.1
93.1
99.9
86.9
97.8
100.0
na
91.5
93.5
92.8
76.4
100.0
6.5
28
Data for
education
analysis
Source: OECD.
42
Health analysis – 2nd step (bootstrap)
Source: Afonso and St. Aubyn (2007).
43
A. Afonso
Overall public sector
PSP
Source: Afonso, Schuknecht
and Tanzi (2005).
44
A. Afonso