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Proceedings of the 1st International Conference
Fiscal Dialog 2017
Fiscal Decentralization and Effectiveness
of Regional and Local Authorities in the EU
College of Regional Development and Banking Institute – AMBIS
Prague, November 10th, 2017
Conference organizers: Media partners:
2
Proceedings of the 1st International Conference
Fiscal Dialog 2017
Fiscal decentralization and effectiveness
of regional and local authorities in the EU
College of Regional Development and Banking Institute - AMBIS
Prague, March 2018
3
Proceedings of the 1st International Conference Fiscal Dialog 2017
Fiscal decentralization and effectiveness of regional and local authorities in the EU
Scientific Committee:
Bojka Hamerníková, College of Regional Development and Banking Institute - AMBIS,
Prague, Czech Republic
Agniezska Alinska, Warsaw School of Economics, Poland
John Hudson, University of Bath, United Kingdom
Klára Major, HETFA, Research Institute and Center for Economic and Social Analysis in
Budapest, Hungary
Marta Orviská, Matej Bel University, Slovak Republic
Juraj Nemec, Masaryk University, Brno, Czech Republic
Lucie Sedmihradská, University of Economics in Prague, Czech Republic
Romana Provazníková, University of Pardubice, Czech Republic
René Wokoun, College of Regional Development and Banking Institute - AMBIS, Prague,
Czech Republic
Reviewers: prof. Bojka Hamerníková, College of Regional Development and Banking
Institute - AMBIS, Czech Republic
All papers were peer reviewed by two reviewers.
Editor: Bojka Hamerníková, College of Regional Development and Banking Institute -
AMBIS, Czech Republic
Technical Editor: Jana Juzová, College of Regional Development and Banking Institute -
AMBIS, Czech Republic
Publication was not subject to language check.
ISBN: 978-80-7265-233-4
Publisher: College of Regional Development and Banking Institute - AMBIS
Published on March 2018.
© Vysoká škola regionálního rozvoje a Bankovní institut - AMBIS, a.s.
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CONTENTS
Fiscal Attitudes, Preferences and Policies across the Regions of the EU ......................................... 6
Marta Orviska, John Hudson
A Comparison between Decentralization in Spain and Colombia .................................................. 21
Helmuth Yesid Arias Gómez, Gabriela Antosova
Does Municipal Size Impact Municipal Performance?.................................................................... 34
Juraj Nemec, Lenka Matějová, Jana Soukopová, Daniel Klimovský
The Impact of Education on the Social and Economic Development of the Country ................... 45
Zuzana Hirková, Helena Kuvíková, Jana Štrangfeldová, Štefan Hronec, Nikola Štefanišinová
Common Provision of Local Public Services by Inter-municipal Cooperation as a Tool of
Efficient Management ......................................................................................................................... 69
Marek Jetmar
Economic Geography and Fiscal Decentralization in the European Union ................................... 77
Ivana Mandysová
Public-Private Partnership Projects in Transport Infrastructure in the Slovak Republic –
Opportunities and Threats ................................................................................................................. 84
Beáta Mikušová Meričková, Nikoleta Muthová, Marián Holúbek
Fiscal Decentralization and Waste Management in Slovakia ......................................................... 96
Katarína Orságová, Mária Horehájová
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PROLOGUE
In November 2017, the College of Regional Development and Banking Institute – AMBIS
organized the 1st International Conference from the cycle Fiscal Dialog with around 100
participants.
The topic of this conference was “Fiscal decentralization and effectiveness of regional and local
authorities in the EU”. The conference was held under the auspices of the Ministry of Regional
Development of the Czech Republic. The conference was attended not only by academics but
also practitioners and policy makers.
Among the keynote speakers were prof. John Hudson (University of Bath, United Kingdom),
prof. Marta Orviská (Matej Bel University, Slovak Republic), prof. Arias Gómez (University
of Seville, Spain), Ms. Věra Kameníčková (Analyst in Czech Credit Bureau), and
representatives from the Ministry of Interior, Ministry of Finance and Union of Towns and
Municipalities of the Czech Republic.
The papers presented during the conference showed various aspects of public finances and laid
conditions for active participation of domestic and foreign attendees.
Conference details are available at the web site of the conference at www.fidi.cz.
Bojka Hamerníková
College of Regional Development
and Banking Institute - AMBIS
Prague, Czech Republic
6
FISCAL ATTITUDES, PREFERENCES AND POLICIES ACROSS THE
REGIONS OF THE EU
Marta Orviska, John Hudson
Abstract
We examine whether there is evidence for preference differences between regions to support
the concept of fiscal federalism. We do this by using Eurobarometer data to specifically
examine the heterogeneity of fiscal preferences and policy concerns in different regions within
the EU, with a specific focus on the Czech and Slovak Republics. We find no evidence to
support the Tiebout mechanism. However, we do find that there are preference differences
between regions. The data also supports the hypothesis that regions are more homogenous than
countries in terms of their policy preferences. In addition, regional characteristics, such as the
regional level education, unemployment and poverty tend to influence everyone’s attitudes in
a region. All of this provides a rational for fiscal federalism. However, there are also very
substantial differences within regions and fiscal federalism is largely irrelevant for this. We
have the rich versus the poor, the city dweller versus the village dweller and, in particular and
increasingly, the old versus the young. Ideally we would want fiscal federalism based not on
spatial considerations, but on socio-demographic ones, with each identifiable socio-economic
group having its own government. That of course is not possible.
This work was supported by the Slovak Research and Development Agency under the contract
No. APVV 15-0322.
Keywords: Fiscal preferences, fiscal federalism, Tiebout hypothesis, age divide
JEL Classification: H31, E61, J18
INTRODUCTION
In this paper we focus, not on the supply side rational for giving power to the regions, but the
demand side rationale. The supply side rationale is based on the hypothesis that the closer a
government is to the firms and citizens in the region, the more efficiently it can deliver goods
and services to meet those needs. The demand side is based on the idea that if the people in
different regions are different, then a regional or local government can best meet their specific
preferences. Thus Oates (1999) wrote that decentralized levels of government have their raison
d'etre in the provision of goods and services whose consumption is limited to their own
jurisdictions. The basic argument is that the efficient level of output of a "local" public good is
likely to vary across jurisdictions as a result of both differences in preferences and cost
differentials. To maximize overall social welfare thus requires that local outputs vary
accordingly. Hence an important part of the rationale for fiscal federalism is this heterogeneity
of preferences between different regions.
We examine whether there is evidence for preference differences between regions to back up
this argument for fiscal federalism. We are also looking for evidence for the Tiebout (1956)
mechanism. We do this specifically by using Eurobarometer data to specifically examine the
heterogeneity of fiscal preferences and policy concerns in different regions within the EU.
Using regression analysis, we also analyse the relative impact of regional variables and
7
individual socio-economic characteristics in influencing people's policy preferences and
concerns. In doing this we look at both the EU as a whole as well as the Czech Republic and
the Slovak Republic. As far as we are aware there are relatively few precedents for this type of
analysis.
The paper proceeds as follows. In the next section we analyse certain general fiscal issues in
the context of fiscal federalism and the Tiebout hypothesis. We then turn to more specific
concerns. In a regression analysis we then look at the determinants of such attitudes and
concerns focusing on the relative importance of individual and regional characteristics. Finally,
we conclude the paper.
1. THEORY OF FISCAL FEDERALISM
The theory of fiscal federalism was originally developed by German-born American economist
Richard Musgrave in 1959. He argued that federal government systems have the ability to solve
many of the issues local governments face (Musgrave, 1959). Musgrave further argued that
federal governments should give money to states, who can distribute it locally as needed and as
they deem best. The United States government relies on fiscal federalism. In the United States,
there exists a complex and highly bureaucratic relationship between states and the federal
government to fund roads, schools, and health care. Regional governments may also raise their
own taxes. The countries of the EU vary in the degree to which fiscal federalism is practiced.
In Germany the federal fiscal system allows a substantial redistribution of income between
states and is also a mechanism to stabilise asymmetric shocks to state incomes (Hepp and
Hagen, 2011).
Part of the rational for fiscal federalism is that different regions differ in what they want and
resources they have. Regional governments are in the best position to meet these differing
needs. In a related argument, Tiebout (1956) argued that if there are differences in the policies
of different regions, people will move to one that has policies which are most in line with their
own preferences. The two processes reinforce each other. Fiscal federalism allows regional
governments to follow different policies based on the needs of their regions. The Tiebout
hypothesis then supposes people move to those regions whose policies most closely align with
their own views. Thus an initial small difference in policy preferences will become accentuated
over time and policy differences between different regions will become more pronounced.
In this paper we will examine the case for both fiscal federalism and the Tiebout hypothesis.
We will examine the evidence for two hypotheses. Firstly, that policy preferences differ
between regions and secondly that the attitudes of older people are more homogenous than
those of younger people within specific reasons. If the Tiebout hypothesis is true, then we would
expect to see such reduced heterogeneity amongst older people within different regions as they
will have had more time to move to their preferred location than younger people.
2. HETEROGENEITY OF POLICY PREFERENCES
We use Eurobarometer 87.3 Data. This is based on a survey carried out in May 2017 of
approximately 1000 people in each EU country. The description and the coding of all the
independent variables can be found in the Appendix. The variables include socio-economic-
demographic variables. They include gender, age, education, location and personal prosperity.
In addition to variables pertaining to the individual, we will also be including variables
pertaining, in general, to the NUTS2 region in which the individual lives. Included in these are
8
regional prosperity, unemployment and education levels. To begin with, we focus on the
responses to the following attitudinal questions:
(i) Measures to reduce the public deficit and debt (in our country) cannot be delayed, (ii)
Measures to reduce the public deficit and debt in are not a priority in our country, (iii) The
private sector is better placed than the public sector to create new jobs and (iv) Public money
should be used to stimulate private sector investment in the EU. These are general questions
and not specifically related to regions, but they allow us to examine how attitudes in regions
compare to those in the country as a whole. For fiscal federalism to be valid, attitudes should
vary between regions. For the Tiebout hypothesis to be valid they need to be more homogenous
within regions than the country as a whole, and to be more homogenous for the old within a
region than the young.
The basic responses to these questions are shown in table 1. They show that a majority of people
are of the view that reducing the debt cannot be delayed, but somewhat paradoxically are more
evenly divided on whether it is a current priority. Most also support the capitalist view that the
private sector is better at stimulating jobs, but again that public money should be used to
stimulate private investment. People in the Czech and Slovak Republics tend to follow broadly
similar views as to the rest of the EU. However, they tend less to the view that reducing the
debt is a current priority and more to the view that the private sector is better at stimulating
jobs. On the latter, of course, both countries have somewhat lower public deficits than some
other countries.
Table 1 – Basic data on Attitudes to Fiscal Matters
Reducing public debt not to
be delayed
Reducing public debt not a
priority now
All
EU Czech R Slovak R
All
EU Czech R Slovak R
% % % % % %
Totally agree 31.33 33.33 28.26 14.76 9.5 10.83
Tend to agree 40.82 46.35 44.47 32.14 26.93 28.05
Tend to disagree 11.83 11.24 8.1 25.82 36.83 23.21
Totally disagree 4.21 2.76 3.36 14.52 17.62 16.25
Don’t Know 11.8 6.31 15.81 12.76 9.11 21.66
Private sector better to
create jobs
Public money should be used
to stimulate private investment
Totally agree 22.84 33.33 28.26 18.63 10.08 15.93
Tend to agree 41.52 46.35 44.47 39.95 41.5 38.81
Tend to disagree 17.52 11.24 8.1 19.05 29.94 19.16
Totally disagree 5.74 2.76 3.36 8.62 8.1 6.35
Don’t Know 12.38 6.31 15.81 14 10.38 19.75
Source: Derived from Eurobarometer 87.3 (2017)
The data also supports the hypothesis that regions are more homogenous than countries in terms
of their views on these issues. Thus on delaying the debt, for 62% of regions the average
standard deviation in the region was less than in the country as a whole. For the regions, the
average standard deviation was 0.766. In the countries as a whole the average standard deviation
9
was 0.806. This suggests that on the deficit there is more agreement within the regions of a
country than within the country as a whole. This is consistent with a demand side rationale for
fiscal federalism. Figure 1 further illustrates this by showing for all regions the difference
between the region’s standard deviation and that of the region’s country. A negative value
indicates that the regional standard deviation is less than the country standard deviation. A
positive value indicates the opposite. Most values are negative, but there are a few very large
positive ones indicating that, that particular region has a very large standard deviation and hence
substantial differences in policy attitudes. Table 2 summarizes the standard deviations for all
four questions. In every case the average regional standard deviation is less than that for the
country as a whole, and this is also a case for a majority of regions.
Figure 1 – The difference between regional and country standard deviations on delaying
public debt
0.5
11.5
22.5
De
nsity
-.5 0 .5 1 1.5Difference
The difference between regional and country standard deviations
10
Table 2 – Comparing regional and National Standard deviations (SDs) on Attitudinal
Questions
Average
Regional SD
Average
Country SD
% of regions where SD
smaller than in country
Public debt
reduce now
0.766 0.806 62.0%
Public debt not a
priority
0.897 0.942 62.4%
Private sector
best for creating
jobs
0.800 0.832 59.2%
Government
should stimulate
investment
0.817 0.864 62.4%
Source: Derived from Eurobarometer 87.3 (2017)
But not only is there more agreement within regions, there is agreement around different means
as can be seen in Table 3. We focus on the regions of the Czech and Slovak Republics. For the
first issue the highest average response is for Prague. A value of 2.067 is an average response
between tend to agree that the debt reduction should not be delayed and tend to disagree, but
much nearer the first option. The other regions are more in agreement that debt reduction should
not be delayed. In Slovakia it is again the capital, Bratislava, which is most sceptical about the
need for debt reduction. Most in favour is Eastern Slovakia. However, on other issues, other
regions are outliers. People in different regions have different preferences and hence once more
there is a case for regional governance.
11
Table 3 – Regional Attitudes in the Czech and Slovak Republics
Delay reduction public
debt
Public debt not a priority Private sector Investment
for jobs
Public money stimulate
Investment
Czech Republic Mean Std. dev Obs Mean Std. dev Obs Mean Std. dev Obs Mean Std. dev Obs
Praha 2.067 0.751 45 2.552 0.862 58 2.079 0.796 101 2.297 0.769 101
Stredni Cechy 1.875 0.833 56 2.814 0.824 43 2.253 0.800 99 2.394 0.753 99
Jihozapad 1.948 0.926 58 3.020 0.812 51 2.234 0.886 107 2.485 0.873 103
Severozapad 1.746 0.682 67 2.757 0.919 74 2.163 0.755 135 2.353 0.821 136
Severovychod 1.680 0.587 50 2.345 0.985 55 2.090 0.866 100 2.175 0.785 103
Jihovychod 1.852 0.635 81 2.779 0.803 86 2.360 0.771 161 2.391 0.750 156
Stredni Morava 1.600 0.639 50 2.625 0.952 40 2.167 0.916 84 2.412 0.863 85
Moravskoslezsko 1.824 0.845 68 2.577 0.977 52 2.355 0.788 124 2.677 0.771 124
Czech Republic 1.823 0.751 475 2.688 0.902 459 2.225 0.819 911 2.402 0.804 907
Slovak Republic
Bratislavsky kraj 2.081 0.836 62 2.614 0.901 57 2.164 0.830 128 2.446 0.894 121
Zapadne Slovensko 1.915 0.846 142 2.638 0.960 149 2.133 0.831 293 2.143 0.808 280
Stredne Slovensko 1.852 0.653 108 2.762 0.904 105 2.153 0.773 215 2.263 0.786 209
Vychodne
Slovensko
1.605 0.604 114 2.234 1.020 94 2.072 0.852 235 2.066 0.892 211
Slovak Republic 1.840 0.753 426 2.573 0.969 405 2.126 0.822 871 2.199 0.846 821
Source: Derived from Eurobarometer 87.3 (2017)
12
Thus there is demand side evidence for fiscal federalism. Is there also evidence for the Tiebout
Hypothesis? If this is to be valid then the views of older people within regions should show
much less variation than those of the young. Older people are supposed to have moved to areas
which are more in line with their own views. Hence they should be broadly in agreement with
other older people in the same region. The young may not yet have moved in this way. However
Table 4 shows little evidence for this. On no issue are the old substantially more in agreement
within regions than are the young. There is little sign of Tiebout’s hypothesis working and
perhaps we should not be surprised at that. People choose where to live partly out of path
dependence, they live and carry on living where they were born, or because of reasons linked
to employment, or the quality of the environment, e.g. close to mountains or the sea.
These are all issues linked to fiscal policy at the national level, rather than fiscal and other
policies at the regional level. It may be that if we were to examine attitudes more related to
local issues we would find more evidence in favour of Tiebout. Nonetheless, we would still
imagine fiscal conservatives to move to areas where the regional government is fiscally
conservative if there is truth in the Tiebout hypothesis, and hence to show up in our analysis.
Table 4 – Attitude Heterogeneity amongst the Old and the Young
All population Over 50 years
Average
Regional SD
Average
Country SD
Average
Regional SD
Average
Country SD
Public debt reduce now 0.766 0.806 0.754 0.799
Public debt not a priority 0.897 0.942 0.885 0.946
Private sector best for
creating jobs 0.8 0.832 0.797 0.833
Government should
stimulate investment 0.817 0.864 0.831 0.875
Source: Derived from Eurobarometer 87.3 (2017)
3. POLICY PRIORITIES
We now turn to policies and issues, at least some of which, are more closely decided at the
regional level. We focus on the perceived most important current policy issues. The question
asked ‘personally what are the two most important issues facing you at the moment?’ The
options included (i) crime, (ii) the country’s economic position, (iii) rising prices/inflation/the
cost of living, (iv) taxation, (v) unemployment, (vi) terrorism, (vii) housing, (viii) their
household’s financial position, (ix) immigration, (x) health and social security, (xi) the
education system, (xii) the environment, climate and energy issues, (xiii) pensions, (xiv)
working conditions and (xv) living conditions. There were also options for ‘other’, which were
not recorded, ‘none’ and ‘don’t knows’. On average within a region the most important issue
was agreed upon by 37.7% of the respondents. Within the country, the figure was less at 33.8%.
In 64.4% of regions this proportion in the region was higher than that in the country. This
indicates more agreement on the most important issue within the average region than the
country as a whole, and once more provides support for fiscal federalism.
13
In Figure 2 we show the difference between a region and its country on the most important
issue. Hence if in the region 38% agree on the most important issue and in the country it is 35%
then this figure is +3% (or 0.03). Hence a positive value indicates more agreement on the most
important issue in the region than the country; a negative value indicates the reverse. For
example, in the country the most important issue may be price (0.40) and in a particular region
it may be unemployment (0.35). This is then the difference (0.35-0.40) we analyse. Note, as
above, in general there is agreement between the region and the country on the most important
issue, e.g. crime. But this does not have to be the case. It can be seen in Figure 2 that in most
regions the agreement level is higher than in the country. Once more this provides support for
fiscal federalism.
Figure 2 - The difference between regions and their country on the most important issue
In Table 5 we once more focus on the regions in the Czech and Slovak Republics. There is
general agreement that rising prices/inflation is the most important issue. But more so in Prague,
the Northeast and Central Bohemia than the rest of the country. Thus unusually in the Czech
Republic agreement on the most important issue is less in most regions than in the country as a
whole. This is not so in most countries and in Slovakia there is approximately an even split.
People can also be divided along socio-economic characteristics. In Table 6 we show these
differences. They are substantial. Women are much more concerned about health than men.
And the poor are much more concerned about unemployment than the rich. But the biggest
divide is between the young and the old. The former are more concerned with working and
living conditions than the old, and the old are much more concerned with health and pensions
than the young.
01
23
45
De
nsity
-.2 0 .2 .4 .6Difference
The difference between regional and country most important issues
14
Table 5 – Most Important Issues in the Regions of the Czech and Slovak Republics
Czech Rep.
Taxation Crime Unemployment Inflation Economy Housing Finan-
ces
Immi-
gration
Health Education Environment Pensions Working
conditions
Living
conditions
Praha 0.116 0.071 0.036 0.482 0.027 0.107 0.259 0.071 0.125 0.071 0.299 0.143 0.107 0.098
Stredni Cechy 0.070 0.080 0.030 0.460 0.100 0.120 0.150 0.060 0.170 0.070 0.080 0.130 0.130 0.080
Jihozapad 0.102 0.076 0.042 0.373 0.059 0.085 0.153 0.085 0.161 0.102 0.025 0.102 0.102 0.042
Severozapad 0.054 0.014 0.041 0.351 0.041 0.088 0.236 0.034 0.277 0.054 0.014 0.216 0.054 0.101
Severovychod 0.104 0.017 0.043 0.487 0.017 0.078 0.157 0.035 0.183 0.078 0.026 0.104 0.070 0.061
Jihovychod 0.054 0.048 0.016 0.409 0.027 0.129 0.188 0.032 0.215 0.054 0.048 0.215 0.113 0.097
Stredni Morava 0.085 0.009 0.028 0.340 0.085 0.085 0.142 0.047 0.160 0.047 0.085 0.160 0.094 0.085
Moravskoslezsko
0.055 0.047 0.063 0.378 0.024 0.142 0.150 0.071 0.134 0.031 0.071 0.205 0.055 0.165
All Country 0.077 0.044 0.037 0.407 0.044 0.106 0.182 0.052 0.184 0.062 0.053 0.166 0.090 0.093
Slovak Rep.
Bratislavsky kraj 0.082 0.015 0.030 0.537 0.164 0.045 0.209 0.037 0.201 0.045 0.015 0.164 0.127 0.090
Zapadne
Slovensko
0.056 0.051 0.068 0.352 0.039 0.051 0.141 0.023 0.242 0.079 0.045 0.203 0.093 0.093
Stredne
Slovensko
0.042 0.030 0.101 0.506 0.051 0.042 0.152 0.025 0.228 0.042 0.055 0.169 0.089 0.068
Vychodne
Slovensko
0.051 0.057 0.131 0.330 0.040 0.067 0.182 0.013 0.279 0.030 0.020 0.226 0.104 0.064
All Country 0.055 0.043 0.089 0.406 0.059 0.053 0.164 0.022 0.244 0.052 0.036 0.196 0.100 0.078
Source: Derived from Eurobarometer 87.3 (2017), all views apart from terrorism which was not a major concern.
15
Table 6 – Most Important Issues across Socio-Economic Characteristics
Issue Villag
e
Tow
n
City Unemploy
ed
Rich Poor Mal
e
Femal
e
Youn
g
Middl
e
Aged
Old
Crime 0.046 0.05
6
0.05
7
0.031 0.06
1
0.03
2
0.05
8
0.049 0.044 0.047 0.06
2
Prices 0.318 0.29
3
0.28
3
0.25 0.27
2
0.33
7
0.28
2
0.311 0.304 0.324 0.27
8
Economy 0.08 0.08
4
0.10
5
0.073 0.08
4
0.07
7
0.09
8
0.08 0.092 0.104 0.07
5
Unemployme
nt
0.101 0.1 0.1 0.552 0.06
4
0.24
9
0.1 0.1 0.135 0.123 0.06
8
Terrorism 0.037 0.04
7
0.03
4
0.023 0.04
8
0.01
7
0.04
3
0.038 0.039 0.038 0.04
2
Housing 0.049 0.05
6
0.08
2
0.07 0.05
7
0.05
3
0.06
3
0.059 0.114 0.064 0.03
3
Finances 0.154 0.15
4
0.17 0.283 0.09
7
0.37
7
0.15 0.165 0.155 0.194 0.13
4
Immigration 0.051 0.05
2
0.05 0.032 0.05
9
0.02 0.05
9
0.045 0.049 0.048 0.05
5
Health 0.215 0.21
5
0.21
3
0.128 0.23
8
0.15
9
0.18
9
0.234 0.111 0.176 0.29
Education 0.084 0.07
4
0.09
3
0.038 0.09
2
0.04
1
0.07
8
0.086 0.166 0.1 0.03
1
Environment 0.066 0.06
8
0.07 0.025 0.08
8
0.01
7
0.07
3
0.064 0.069 0.067 0.06
8
Pensions 0.178 0.17
3
0.14
9
0.052 0.17
3
0.17
4
0.15
8
0.176 0.027 0.064 0.30
8
Working
Conditions
0.093 0.07
6
0.08
9
0.103 0.07
4
0.10
7
0.08
7
0.084 0.133 0.122 0.03
6
Living
Conditions
0.096 0.08
4
0.09
8
0.117 0.07
8
0.12
1
0.09
3
0.091 0.114 0.098 0.07
7
Source: Derived from Eurobarometer 87.3 (2017)
16
4. REGRESSION ANALYSIS
Table 7 – Regression results for the Attitudinal Analysis
Delay debt Debt
priority
Gov
stimulate
Investment
Delay
debt
Debt
priority
Gov
stimulate
Investment
Old -0.01601
(0.42)
-0.1015**
(2.82)
-0.02842
(1.08)
0.007602
(0.20)
-0.1085**
(2.96)
-0.02177
(0.82)
Young 0.05109
(1.76)
-0.0288
(1.05)
0.004808
(0.24)
0.0562
(1.92)
-0.03618
(1.29)
0.006078
(0.31)
Male 0.000729
(0.03)
0.0313
(1.47)
-0.1021**
(6.61)
0.001589
(0.07)
0.04059
(1.87)
-0.1027**
(6.58)
Village -0.1161**
(4.02)
0.08405**
(3.09)
0.05304**
(2.61)
-0.05982
(1.79)
0.08916**
(2.80)
0.04814*
(2.06)
Town -0.06908*
(2.51)
0.01733
(0.66)
0.01155
(0.61)
-0.01593
(0.51)
0.01967
(0.66)
0.02027
(0.94)
Log of
education
-0.07448
(1.60)
-0.04351
(0.97)
0.06551*
(2.00)
-0.06031
(1.26)
-0.0128
(0.28)
0.06438
(1.95)
Professional
management
0.02587
(0.74)
-0.02497
(0.74)
-0.01394
(0.57)
0.02897
(0.81)
-0.0281
(0.82)
-0.01046
(0.42)
semi-skilled -0.09868*
(2.45)
-0.1118**
(2.88)
-0.009931
(0.35)
-0.09337*
(2.26)
-0.1046**
(2.66)
0.01542
(0.54)
unskilled -0.104
(1.65)
0.03142
(0.50)
0.02574
(0.60)
-0.1101
(1.73)
0.03324
(0.52)
0.02558
(0.59)
Farmer 0.2642
(1.65)
0.01028
(0.07)
-0.1329
(1.29)
0.2561
(1.55)
0.001265
(0.01)
-0.06636
(0.64)
Houseperson -0.0582
(1.05)
-0.00653
(0.13)
0.01562
(0.41)
-0.05505
(0.98)
-0.00896
(0.18)
0.01999
(0.52)
Unemployed -0.03334
(0.66)
-0.04947
(1.07)
-0.006852
(0.21)
-0.02366
(0.47)
-0.04711
(1.01)
-0.004847
(0.15)
Retired -0.05829
(1.39)
0.04943
(1.22)
0.07124*
(2.43)
-0.06853
(1.61)
0.05287
(1.28)
0.06981*
(2.36)
Prosperity -0.131**
(5.18)
0.02372
(0.98)
-0.07889**
(4.50)
-0.1406**
(5.48)
0.0144
(0.59)
-0.07923**
(4.49)
Regional Variables
Education 0.05731
(0.87)
-0.162**
(2.59)
0.2421**
(5.23)
Unemployment -1.098**
(3.22)
-1.328**
(4.08)
-0.1202
(0.53)
Prosperity 0.1664
(1.93)
-0.3125**
(3.65)
0.2187**
(3.75)
Observations 10785 10857 21293 10785 10857 21293
Log Likelhd. -11985 -14133 -26027 -11751 -13870 -25650
X2 429.7 593.5 1424 880.5 1215 2237
Note: Regressions estimated by ordered probit, with standard errors corrected for heteroscedasticity. **/* denotes
significance at the 1%/5% level of significance. Country dummy variables included in the regression but not
shown.
17
We begin the regression analysis by once more focusing on general fiscal attitudes. We include
both regional variables and socio-economics-demographic characteristics. Are people’s
attitudes determined solely by their own personal situation or do regional factors influence their
attitudes? If the latter, then once more it emphasises the importance of regional factors in
influencing attitudes and provides a further rationale for fiscal federalism. Table 7 shows the
results, focusing on the three attitudes most closely related to fiscal issues. People in villages
tend to be more of the view that debt is a priority, whilst semi-skilled workers are less of this
view. People in villages tend to be relatively hostile to governments stimulating the economy.
The old are not that different to the young on these issues. Regional variables are important.
Highly educated regions are more sceptical of governments stimulating the investment, but tend
to think paying the debt is less of a priority than others. The latter is also true for poor regions
and regions with high unemployment. The regional variables are calculated directly from the
data, as we know which region each person comes from and hence we can identify the views
of others in the region. The final three columns allow for each region to be unique by including
regional dummy variables, but still the socio-economic variables are significant.
However, when we look at the most important issue in the second set of regressions, this
changes a little. The results, for selected issues are shown in Table 8. Age groups are very
important in determining attitudes to the most important issues, particularly health, finances,
pensions and education. This is true even if we include a dummy variable for each region – i.e.
allowing for each region to be different. Other variables which affect attitudes include education
– educated people prioritise education as an issue and are less concerned with pensions - being
unemployed and prosperity. There are also some differences with respect to location with
people outside the large towns and cities, particularly in rural areas, more concerned with
inflation and the cost of living. Again regionally defined variables are significant, although
slightly less so than before.
Thus both socio economic characteristics and regional characteristics impact on attitudes to
general questions such as the public debt and on policies more relevant to the individual such
as crime, pensions and health. The significance of the latter indicates that two people with
identical characteristics will have different fiscal preferences and policy concerns if they live
in different regions with substantially different regional characteristics. Once more this
provides a justification for fiscal federalism.
However, in many respects today the big divide is between the different groups of society rather
than different regions within a country. This has probably always been the case, but the
divisions between the age groups, and particularly the old versus the rest and the old versus the
young, are particularly important now. This is because the old make up a large and increasing
proportion of the population. That an increasingly elderly population tends to soak up resources
without contributing to current GDP has long been realised. But the potential for policy conflict
between old and young has received less attention. And this conflict becomes potentially
stronger and more important as the old become a more important part of the population.
18
Table 8 – Regression results for the Most Important Policy Issues
Crime Health Unempl. Prices Finances Pension Education
Old 0.0584
(1.29)
0.1841**
(5.81)
-0.2907**
(6.22)
-0.09809**
(3.27)
-0.2181**
(5.99)
0.6477**
(18.83)
-0.3976**
(8.53)
Young -0.06249
(1.56)
-0.2881**
(10.20)
0.05133
(1.62)
-0.00792
(0.33)
-0.1338**
(4.89)
-0.4685**
(11.40)
0.2811**
(9.58)
Male 0.05001
(1.77)
-0.1823**
(9.42)
0.03549
(1.37)
-0.04671**
(2.58)
-0.01428
(0.68)
-0.03637
(1.68)
-0.09794**
(3.73)
Village -0.09506*
(2.50)
-0.00249
(0.10)
-0.03655
(1.08)
0.1288**
(5.45)
-0.03471
(1.26)
0.05999*
(2.10)
-0.0051
(0.15)
Town -0.04315
(1.27)
-0.02937
(1.24)
0.01257
(0.40)
0.07634**
(3.41)
-0.01882
(0.74)
0.01904
(0.71)
-0.08237**
(2.58)
Log of
education
-0.07856
(1.39)
-0.03963
(1.04)
-0.02891
(0.53)
-0.07415*
(2.02)
-0.1004*
(2.35)
-0.2554**
(6.09)
0.4025**
(6.73)
Professional
management
-0.0428
(0.91)
-0.02764
(0.85)
-0.2325**
(4.72)
-0.1504**
(5.05)
-0.04929
(1.40)
0.1356**
(3.36)
0.1832**
(5.35)
semi-skilled 0.03459
(0.65)
-0.03868
(1.03)
0.01873
(0.39)
0.07643*
(2.35)
-0.04082
(1.07)
-0.02677
(0.58)
-0.2712**
(5.47)
unskilled 0.1108
(1.36)
-0.06352
(1.11)
0.2962**
(4.61)
-0.09452
(1.84)
0.1391*
(2.52)
-0.03521
(0.50)
-0.2297**
(2.99)
Farmer -0.1953
(0.88)
0.01349
(0.11)
0.3771**
(2.75)
-0.05754
(0.51)
-0.01329
(0.10)
-0.05757
(0.40)
-0.2972
(1.40)
Houseperson 0.1128
(1.63)
0.01491
(0.31)
0.3873**
(6.88)
-0.03286
(0.76)
0.1224*
(2.46)
0.06823
(1.24)
-0.1212*
(1.96)
Unemployed -0.1084
(1.59)
-0.168**
(3.82)
1.497**
(37.55)
-0.3342**
(8.69)
0.2661**
(6.80)
-0.2336**
(4.08)
-0.4819**
(7.83)
Retired 0.03747
(0.74)
0.1956**
(5.51)
0.06586
(1.26)
-0.07206*
(2.14)
-0.01142
(0.28)
0.4161**
(10.64)
-0.3071**
(6.02)
Prosperity 0.1691**
(4.90)
0.09528**
(4.20)
-0.2294**
(8.00)
-0.08964**
(4.41)
-0.5871**
(25.25)
-0.08187**
(3.32)
0.1026**
(3.37)
Regional Variables
Education 0.01735
(0.19)
-0.186**
(3.06)
-0.117
(1.51)
0.01074
(0.20)
-0.00643
(0.10)
-0.1377*
(2.05)
-0.2192**
(2.68)
Unemployme
nt
0.9548*
(2.22)
0.291
(0.98)
1.672**
(4.62)
0.03648
(0.14)
0.1937
(0.63)
-0.08245
(0.25)
0.5614
(1.40)
Prosperity -0.3665**
(3.24)
-0.0147
(0.19)
0.165
(1.69)
-0.2517**
(3.70)
0.03004
(0.38)
0.09451
(1.09)
0.01473
(0.14)
Observations 24598 24598 24598 24598 24598 24598 24598
Log Likelhd. -4841 -11926 -6096 -13972 -9806 -9358 -5910
X2 436.6 1985 3107 1864 1818 3135 1284
44 44 44 44 44 44 44
9772 23942 12281 28033 19701 18807 11910
Note: Regressions estimated by probit, with standard errors corrected for heteroscedasticity. **/* denotes
significance at the 1%/5% level of significance. Country dummy variables included in the regression but not
shown.
19
CONCLUSIONS
The results show little support for the Tiebout hypothesis. But there are differences between
regions and there is potential for fiscal federalism to result in better policy making. Regional
characteristics such as the regional level education, unemployment and poverty tend to
influence everyone’s attitudes in a region. This could be because regional characteristics impact
on regional preferences, as perhaps with a region’s average education level, or because these
characteristics reflect a region’s problems, as with regional unemployment. But regardless of
the reason these differences provide a rational for fiscal federalism.
However, there are also very substantial differences within regions and fiscal federalism is
largely irrelevant for this. We have the rich versus the poor, the city dweller versus the village
dweller and, in particular, the old versus the young (Fishman, 2010). The key is to reconcile the
different interest groups within countries and within regions. Ideally we would want fiscal
federalism based not on spatial considerations, but on socio-demographic ones, with each
identifiable socio-economic group having its own government. That is not possible. When the
economy is prosperous these divisions are relatively easy to manage. The cake is getting bigger,
everyone can have a bit more. But when it is less prosperous, the battle between the different
sections of society becomes more difficult to reconcile. The risk is then that society becomes
more fractured. This is a key problem which both national and regional governments must focus
upon.
Of course there are limitations to our analysis. Firstly, the regions we have analysed do not
necessarily correspond to areas of governance. Nonetheless we would expect an overlap, and it
is this overlap which makes our search for evidence for the Tiebout hypothesis valid. Secondly,
even if there are differences between regional jurisdictions and the regions used in this paper,
the differences in regional preferences we have found provide a justification for fiscal
federalism. But we must remember it is a justification, but not a full justification. That depends
upon supply side factors. That is the relative ability of regional and national governments to
efficiently deliver public goods to their citizens and that is a trade-off between the advantages
of being close to those citizens and economies of scale. We have added a piece to the jigsaw,
but there are other pieces to consider before we get the full picture.
References:
1. Fishman, Ted. Shock of Gray: The Aging of the World's Population and How it Pits Young
Against Old, Child Against Parent, Worker Against Boss, Company Against Rival, And
Nation Against Nation. New York: Simon and Schuster, 2010.
2. Hepp, R., & Von Hagen, J. (2011). Fiscal federalism in Germany: Stabilization and
redistribution before and after unification. Publius: The Journal of Federalism, 42(2), 234-
259.
3. Musgrave, R. A. (1959) The Theory of Public Finance. New York: McGraw Hill.
4. Oates, W. E. (1972) Fiscal Federalism. New York: Harcourt Brace Jovanovich.
5. Oates, W. E. (1999). An essay on fiscal federalism. Journal of Economic Literature, 37(3),
1120-1149.
6. Tiebout, C. M. (1956). A pure theory of local expenditures. Journal of Political
Economy, 64(5), 416-424.
20
Appendix 1
Independent variables
Age The respondent’s age in years
Male The gender of the respondent: Male = 1; Female = 0
Education Age at which the individual finished full time education
Village Coded 1 if the respondent lives in a rural area or village, otherwise 0
Town Coded 1 if the respondent lives in a small sized town, otherwise 0
Professional/ Senior Respondents current occupation: 1 if employed professional or senior
Manager manager, otherwise 0
Middle management Respondents current occupation: 1 if middle manager, otherwise 0
Skilled manual Respondents current occupation: 1 if skilled manual worker, otherwise
0
Unskilled manual Respondents current occupation: 1 if unskilled manual worker,
otherwise 0
Farmer Respondents current occupation: 1 if farmer, otherwise 0
Driver Respondents current occupation: 1 if involves travelling, e.g. driver or
salesperson, otherwise 0
House person Respondents current occupation: 1 if house person, otherwise 0
Unemployed Respondents current occupation: 1 if unemployed, otherwise 0
Retired Respondents current occupation: 1 if retired, otherwise 0
Prosperity Difficulties to pay bills at the end of the month during the last twelve
months.
Dependent variables defined in the text.
Source: Derived from Eurobarometer 87.3, November-December 2014
Contact information
Prof. Marta Orviska
Matej Bel University
Banska Bystrica, Slovakia
Prof. John Hudson
University of Bath
United Kingdom
21
A COMPARISON BETWEEN DECENTRALIZATION IN SPAIN AND
COLOMBIA
Helmuth Yesid Arias Gómez, Gabriela Antosova
Abstract
This analysis aims to make a comparison between the process of devolution of competences in
Colombia and Spain, focusing on the fiscal aspects of them. Regarding the first country we
describe the institutional mechanism that rules the Spanish system of regionalization, his quasi
federal nature and his relationship with the political process and particularly some mechanism
in a very complex system of equalization funds. In the case of a unitary country as Colombia,
we make a description of financial rules that dictate the functioning of transfer system (SGP)
and we stress the huge centralized nature of Colombian process.
Keywords: Federal Federalism, Devolution of Competences, Decentralization.
JEL Classification: H73, H71
INTRODUCTION
Either in unitary and federal schemes, the systems of decentralization pursue the equalization
of basic services for all citizen irrespective of the place they live, emphasizing tenets of equality
and justice (Buchanan 1950). Nevertheless, deep inequalities across regions obstruct identical
treatment for citizen living at different location of the same country.
But the posture of central government can diverge depending of unitary or federal framework.
In the former case, a bankruptcy or territories moves the central government to bail out it, and
in the latter one, the government may press territories in order to serve the public debt (von
Hagen & Eichengreen 1996). In any case, the role of central government is in practice, an
insurer that protects against territorial shocks (Sala i Martin & Sachs 1991)
According to this, our analysis compares two specific cases of devolution of competences: one
European country member of EU and full member of OCDE: Spain and by the other hand, a
Latin American country: Colombia. In the first example, in spite that constitution doesn’t
declare explicitly a federal state, Spain has a highly decentralized structure, while in the second
case the system of decentralization operates fully around transference from central government
to regions (departments).
In terms of decentralization a key aspect is the issue of the distribution of tax revenues between
levels. A greater regulatory capacity in tax matters could generate a process of competition
across regions in order to retain the factors of production in regions that offer better conditions.
That is a natural process derived from the regional divergences in terms of productivity
(Buchanan 1950). But in regard to sharing of taxes and more concretely, of devolution of
tranches in national taxes, the great constraint is the unequal economic structure of the regions.
From that point of view, to undertake a territorial tax policy will always be problematic in
schemes with acute regional inequalities and in such circumstances, mechanism of equalization
and redistribution must be available.
Any initiative in this area goes through the problem of concentrating additional fiscal income
in dynamic regions. In fact, these efforts of devolution of taxes to territories in these conditions,
22
do not provide interregional solidarity to the scheme, but on the contrary, tend to increase the
tax revenue of the rich regions.
1. THE CASE OF SPAIN
Map 1 – Spain: autonomous communities (CC.AA.)
Source: own elaboration
In the case of Spain regional inequalities are always present and differences in GDP per capita
in 17 autonomous communities (A.C) are evident. The origin of such inequalities can be found
in productive specialization, the specific location of manufacturing activity and differences in
productivity. Higher standard of living is exhibited by more industrialized regions as Catalonia,
Madrid and Basque Country. More lagged regions in GDP indicators are Extremadura and
Andalusia. In addition, two autonomous cities must be included in the system: Ceuta and
Melilla. Moreover, the fact of having archipelagos as Baleares Islands and Canarias Islands
entails for the transfer system an additional factor pressing the needs and the expenditures: the
insularity. In those cases, the geographical situation claims for additional funds in modulation
of autonomic system.
23
Map 2 – Spain: regional GDP per capita 2015 (euro)
Source: Eurostat, own elaboration.
Spain is a fairly regionalized country as a feature related to the necessity of political cohesion
linked to its regional heterogeneity. For the sake of illustration, the GDP per capita of the
Basque Country roughly doubles that of Extremadura.
Constitution of 1978 has arranged a State of Autonomies, reckoning multiple idiosyncrasies
and different dialects in its regions, so the first regional scale is constituted by Autonomous
Communities (C.A.) (NUTS 2). Several reforms have been carried on in order to manage the
resources for funding the autonomic State.
Spain designed an Autonomic Financial Model that suffered subsequent reforms as the results
of political agreements between Government and C.A.s. In all cases regions try to defend an
“ordinal” or status quo tenet that points out that situation of regions cannot be worsened when
the system suffers any modification. In such situation Central Government has been forced to
mobilize additional quantities of money into the model.
In addition, in Spanish system coexist two parallel regimes: Common Regimen that includes
15 C.A., and Foral Regime. The last one consist in a privileged regimen that allows to Basque
Country and Navarra to collect its taxes, manage its expenses and to give to Central Government
a contribution for defense expenditure.
The existence of Foral Regime conveys inequalities due that such regions enjoy a high degree
of autonomy and their population enjoys roughly twice the quantities per inhabitant respect to
average of CC.AA.s.
The actual system of funding pursues two principles that not always are attainable: territoriality
and equality. Territoriality means that the resources perceived by a region relates with its
capacity to collect taxes. Equality means, as before has been defined, that all regions receive
the same adjusted resources per capita. But in fact, rich and principal contributors of the system
receive less resources and has argument for complaining (Zubiri 2006).
24
The Common Regime is designed to receive funds from three sources, (Vilalta, 2014):
Tax mix: Includes taxes with revenues fully destined to C.A. and those shared with
Central Government (50 % of IRPF, 50 % of VAT, 58% of duties levied to tobacco,
alcohol and some hydrocarbon fuels. On that taxes have been allowed some regulatory
control. This taxes correspond to 83, 9% of resources funding the Model, but if are
included only taxes that allow decision capacity percentage falls to 47,5% and to 13%
if are considered those taxes actually managed by C.A.
Equalization Mechanism: For this mechanism was designed the “Guarantee Fund for
basic public services”. This fund has the purpose to guarantee that all CC.AA. have the
same resources per capita in order to provide the basic services (education, health and
social services)
Three Adjustment Funds represented by a Sufficiency fund, a Competitiveness Fund
and the Cooperation Funds. Those are funds included with the purpose to concede
greater resources to some CC.AA. The sufficient Fund gives additional resources to
CC.AA when a new criteria of necessity are applied. The competitiveness Fund is
assigned only to those CC.AAs with per capita resources lower than the mean. Finally
the Cooperation Fund is exclusive for poor CC.AAs with two features: low population
growth and low population density.
In theoretical terms when the equality tenet doesn’t predominate, a system of transfers must be
designed to allow lagged regions to provide equal services in comparison with others
(Buchanan 1950).
Map 3 – Spain: Income per capita in each C.A. coming from autonomic financial model 2017.
(euro per cápita)
Source: Generalitat Valenciana.
This kind of arrangement has attracted a broad strain of criticism from different analysts (Zubiri
2016, Vilalta 2016). Critics focus on the fact that equal CC.AA receive different quantities per
25
capita and that richer regions contribute with high quantities of taxes and the system returns
them less resources. This fact may attempt against the quid pro quo tenet (Buchanan 1950)
defined in terms of that richer regions normally perform higher expenditure. Additional
complaints come from Catalonia who asserts that, as the richer region, confronts higher prices
levels in the provision of services.
The equalization mechanism is guided by a principle of equity because its resources are
distributed according to principle of necessity in each CC.AA.
Meanwhile the system applies the principle of territoriality allocating to each CC.AA. a
percentage of 25% of quantities collected by ceded (transferred) taxes. So in practice, the
mechanism of equalization is funded by the 75% of collection of ceded taxes and by
contribution of Central Government.
1.1 Macroeconomic Consistence
Table 1 – Spain- Financial capacity (+) or necessity (-) public administration
Level 2004 2005 2006 2007 200
8 2009 2010 2011 2012 2013 2014 2015 2016
Central Administration
-0,9 0,5 0,9 1,3 -2,9 -9,1 -4,8 -3,6 -7,9 -4,8 -3,7 -2,8 -2,7
Autonomous Communities (CCAA)
-0,1 -0,3 -0,1 -0,3 -1,7 -2 -3,7 -5,1 -1,9 -1,6 -1,8 -1,7 -0,8
Local Entities
0,0 -0,1 0,1 -0,3 -0,5 -0,5 -0,7 -0,8 0,3 0,6 0,5 0,4 0,6
Social Security
1,0 1,1 1,3 1,3 0,7 0,7 -0,2 -0,1 -1,0 -1,1 -1,0 -1,2 -1,6
Total -0,0 1,2 2,2 1,9 -4,4 -11 -9,4 -9,6 -10,5 -7 -6 -5,3 -4,5
Source: Banco de Espana.
NOTE: surplus in terms of National Accounts
In recent years, fiscal stances in all levels of government show the direct effect of economic
crises. We observe an evident cyclical increase in public deficit in particular, in the central
administration. From the beginning of the financial crises deficit evolved to 9,1% of GDP
during 2009, maintaining high levels in subsequent years. In 2015 and 2016 the disequilibrium
has been corrected. Fiscal deterioration has affected sub regional levels also, because deficit in
CC.AA soared in 2011 to 5,1% of GDP, showing a correction in more recent years.
Some authors (Viver and Martin, 2012) see a tendency to recentralize economic decisions in
the assignation of recent fiscal adjustment dictated by Europe. The subscription of fiscal
adjustment dictated form Brussels, can be as a cut of the financial autonomy of Spanish regions.
In fact, the period imposed to apply the fiscal adjustment at overall levels of public
administration was defined since 2009 to 2013, and the commitments arranged pointed out a
reduction of public administration deficit in 8,5 points of GDP in a very short period.
For recent years a new act (Ley 2/2012) settled new objectives of deficit, reserving to central
government the higher part of deficit, letting to territorial authorities the bigger fiscal effort
(Viver and Martin, 2012). In percentage terms the required adjustment asked to CC.AA implies
the accomplishment of deficit relative to GDP of -0,7 % in 2013 to superavit of 0,2% in 2015,
so regional governments are object of harder conditions of adjustment. Likewise, the
distribution of the limit to indebtedness (60% of GDP) has been distributed allowing the larger
part of debt to central government (44% of GDP).
26
However from the theoretical point of view, von Hagen & Eichengreen (1996) defend the right
of central government of impose constraint on regional deficit and debt, adducing the
predominance of macroeconomic stability in the context of monetary union.
2. THE CASE OF COLOMBIA
Map 3 – Departments of Colombia
Source: Instituto Geográfico Agustin Codazzi. Own elaboration.
Colombia has been a unitary country with deep centralist roots. Along roughly 100 years a very
centralist constitution promulgated in 1886, guided the institutional life of country but with the
punctual application of sporadic reforms during XXth century. Only in 1991 an outright new
constitution was arranged between diverse political sectors, and there was included a system of
transfers of money to territories complemented with competences in public expenditure.
Nonetheless, few years later the expenditure associated to reforms turned out in deep fiscal
imbalances, not only originated in the new framework of decentralization but in new public
expenditures destined to judicial institutions, security forces, etc. Facing this problem,
subsequent constitutional amendments restrained the growth in public expenditure related to
decentralization scheme, as will be explained further.
27
Map 4 – Colombia: GDP per capita 2016 (millions of pesos)
Source of data: Departamento Administrativo Nacional de Estadística. Own elaboration.
The distribution of wealth across departments of country is also unequal, ranging the GDP per
capita from 5,4 to 32 million of pesos in 2016. Leading the best indicators of wellbeing we find
Bogota, Antioquia and Valle del Cauca, as three regions with an important role in
manufacturing and services. In addition, two main oil producers appears with high indicator
also: Meta and Casanare. In these cases the importance of oil production and low population
press the indicator to higher levels. Although as Auriol (2006) points out, the permanent effect
of extractive industries in territories is rather scarce, due to lack of links to local and regional
economy.
2.1 Macroeconomic Consistence
In 1991 Colombia changed its rigidly centralist constitution dating from 1886 and promulgated
a new Constitution that in the area of decentralization granted a merely administrative power to
subnational levels and a scheme of regional social expenditure was designed around a strongly
centralized Government transfer system, known as General System of Participation (GSP).
Discussions on decentralization in Colombia within the framework of GSP, have a marked
fiscal connotation, ignoring the integrality of the problem and overlooking the need to expand
the autonomy scheme of the subnational levels with the object of promoting their own economic
dynamics.
The original text of Constitution linked the evolution of decentralized resources with the growth
of current revenues of Central Government (CRG) which, as time passed, worried strongly to
central government. In these conditions all additional resources that government got from tax
reforms had partially a compulsory destination to decentralization framework. In those terms,
the consequent reforms of government proposed to divert the evolution of decentralization
28
system from the evolution of current revenue of government. The formula proposed by
government defined an evolution of the resources to territories according to some additional
point to inflation, in opposite way to original constitutional formula.
Table 2 – Colombia - Fiscal stance of consolidated public sector (% GDP)
2008 2009 2010 2011 2012 2013 2014 2015 2016
Central Government
-2,3 -4,1 -3,9 -2,8 -2,3 -2,3 -2,4 -3,0 -4,0
Decentralized Sector
2,4 1,4 0,8 1,0 2,8 1,4 1,0 -0,4 1,6
Social Security 1,1 1,0 1,0 1,1 1,4 0,3 0,5 0,4 0,8
National Level Enterprises 1/ 0,2 0,0 0,0 -0,1 -0,3 -0,1 0,0 0,0
-0,2 -0,1
Local Level Enterprises
0,0 0,0 -0,1 0,0 0,1 0,0
0,1 -0,1 -0,1
Regional and Local Goverments 1,1 0,4 -0,1 -0,1 1,5 1,2 0,4 -0,5 0,3
Central Bank (B. de la República) 0,3 0,1
0,0 0,0 -0,1 -0,1 -0,1 0,0 0,1
FOGAFIN (Fund of Guarantee of Deposit) 0,1 0,2 0,1 0,0 0,1 0,1 0,1 0,1 0,1
Discrepance -0,2 -0,2 -0,2 0,1 0,1 -0,1 0,1
CONSOLIDATED PUBLIC SECTOR -0,1 -2,7 -3,3 -0,2 0,3 -0,9 -1,4 -3,4 -2,2
Source: CONFIS – Cierre Fiscal Anual.
1/ Ecopetrol, FAEP, Energy Sector.
If we go back to the times of promulgation of new Colombian constitution, from 1991 the
Central National Government (CNG) deficit worsened continuously. During the first decade of
present century, a set of reforms run in order to constrain the public expenditure. The problem
of the rapid growth of public debt, particularly CNG’s debt, was pointed out, given the quick
evolution of domestic debt linked to the public expenditure and the disappearance of monetary
funding from the Central Bank (strictly limited in the new Constitution). Later, the fiscal stance
improved thanks to better collection of taxes, and in recent years the public deficit evolved
according to economic cycle of economy, which has been affected by prices of raw materials,
in particular oil.
Assertions about macroeconomic consistency predominate in the Colombian decentralization
discussion because the high correlation between decentralized transfer system and the
macroeconomic stability. So the issue of the need for fiscal adjustment has always put the
discussion in terms of a negotiation of resources for subnational entities, which relegates the
fundamental problems of model of State and the affirmation of the regional fact.
Another aspect of the Colombian process is that the solutions embodied in the different
constitutional amendments have been transitory formulas. So, at the end of the transition period
of each amendment, the government has promoted the current formula, evolving the resources
according to points to the caused inflation and diverting the financial behavior of
decentralization from the Current Revenues of Government.
In such cases, for the sake of macroeconomic convenience, the government did not accept the
original constitutional formula of tie-up the transfer system regarding Current Revenues of
Government. But, nor regions could accept any formula that could entail cuts in expected
resources. So, the best solution was a comprehensive formula that distributed adequately the
risks of system and that could balance macroeconomic stability and regional development.
Such political discussion should be the opportunity to carry out an in-depth debate on the nature
of decentralization process, on the tax autonomy, on the creation of inter territorial leveling
funds and on the tools for reinforce the institutional capacity of subnational territories.
29
Table 3 – Colombia: Central Government tax collection. %PIB
2010 2011 2012 2013 2014 2015 2016
Internal taxes 9,4 10,6 11,7 12,0 12,1 12,2 11,5
Income tax 1,6 2,0 3,2 2,9 1,6 1,3 1,2
VAT 2,7 2,8 2,7 2,8 3,0 2,9 2,8
Retention VAT and Income 4,1 4,3 4,3 3,9 3,9 4,1 4,0
Timbre 0,1 0,0 0,0 0,0 0,0 0,0 0,0
Bank Debit Tax 0,6 0,8 0,8 0,8 0,9 0,8 0,8
Patrimony/wealth 0,4 0,7 0,6 0,6 0,5 0,7 0,5
Consumption N.A N.A 0,0 0,2 0,2 0,2 0,2
Hidrocarbon fuels N.A N.A 0,0 0,4 0,4 0,4 0,4
CREE N.A N.A 0,0 0,4 1,6 1,3 1,1
CREE surtax N.A N.A 0,0 0,4 0,0 0,5 0,5
External Taxes 0,9 2,6 2,3 2,1 2,2 2,3 2,2
Import tariff 0,9 0,7 0,5 0,5 0,5 0,6 0,5
External VAT 1,7 1,9 1,8 1,6 1,6 1,7 1,6
Total 12,3 13,2 14,3 14,1 14,3 14,5 13,6
Source: DIAN.
In Colombia the lion´s share of tax collection goes to Central Government, which maintains the
resources of more dynamic bases and higher yields: VAT and revenue taxes. In the opposite,
departments (regions) manage static taxes with unstable basis and with no normative capacity
over rates of taxes. The list of regional taxes is as follows: beer, liquor, registration, tobacco
and cigarettes, stamps, vehicles, fuels, etc. Despite the upward trend of the collection, there is
no margin to increase the yield of such departmental taxes, since these are indirect taxes.
The Colombian centralism in tax matters has led to a rather weak regional and local tax
structure, with very weak dynamics and reduced taxes, which in the end, leads to a high
dependence on transfers. On the other hand, the Spanish experience, although critical, proposed
a scheme of greater regional participation in taxes such as VAT and has established an
autonomous section, with some degree of regulatory power, in the Income Tax of Individuals.
With regard to the destination of Colombian regional taxes, some of them already have specific
destinations, which in turn make them very inflexible to be redirected to investment or other
different purposes. So such fiscal weakness in territories conveys a high dependence from
central government’s transfers.
This argumentation can drive to a perverse circle. Admittedly, in theoretical terms, this high
dependence from transfers doesn´t induce territorial governments to tackle an effort to
strengthen the yield of own taxes. Oats (1999) suggested three points for fiscal reform in
developing countries: 1) avoid perverse incentives coming from high dependence form
transfers; 2) Enhancing the access to own revenues for improve deficit. 3) Restraint the access
to debt instruments for regions.
30
2.2 Colombia: SGP, Reforms and Financial Scenarios.
Constitution amendment (Legislative Act 01)
The Government has always shown its concern about the fact of having a tax system of
decentralization tied to the Current Revenues of Nation. In the words of official officials this
situation generated a very inflexible and rigid public expenditure scheme and made difficult to
undertake a fiscal adjustment process cutting expenditures that were constitutional and legally
predetermined.
So the Government presented and discussed before parliament Act (Acto Legislativo) 01 of
2001 that established a real growth in the transfers system according to evolution of caused
inflation, starting from a value of 10.96 billion pesos in 2001.
At that time the political discussion was contextualized in an economic environment marked
by the economic downturn of 1999 (-4.2%). In this period, the decline affected the Current
Revenues of nation, and in consequence the amount of resources transferred, because a drastic
reduction in government tax collection.
Table 4 – Colombia: scenarios of evolution in transfer system.
Constitutional Amendment (AL 04/ 07)
2008 2009 2010 2011 … 2016 2017 … 2022
Former system of transfer linked to Current Revenue of Government (CRG) 1/
Inflation + 2,5
Average growth of Current Revenues (CRG ) in the last 4 years
Constitutional Amendment (Acto Legislativo 04 de 2007). Evolution according to inflation
Inflation + 4,0 Inflation +3,5 Inflation+3,0 Average growth of Current Revenues of Government (CRG ) in the last 4 years
Points to education: 1,3
Points to education:1,6
Points to education: 1,8 --
Source: Own elaboration based on: Ministerio de Hacienda y Crédito Público (2006).
1/ GDP growth above 4%, means an equivalent growth in the resources to system
As can be observed in chart 4, central government succeed to run a constitutional amendment
in which resources of transfers evolved according to inflation plus additional points. This
strategy lightened the central government fiscal stance and permitted to it to capture the
resources collected by subsequent tax reforms and from efforts to combat tax evasion and
elusion. Lozano et al. (2007) estimated in 1,8% of GDP during the period 2002-2005 and 4,2%
of GDP during the period 2006-2008. In these terms, the accrued fiscal saving channeled by the
reform to transfer system was roughly 6 points of GDP.
CONCLUSION
In European countries either in unitary and federal systems, the role of region is highly
recognized. Spain is a clear example, either for its own regional vocation or for being part of a
more general trend predominant in Europe.
In the opposite, the financial tax and management organization in Colombia remains very
centralized as a result of a system dependent of national decisions, and on the other hand, by
the insufficient institutional development in territories. In any case, a more aggressive
decentralized process is necessary to promote balanced regional development.
In Colombia the bulk of taxation (income tax and VAT) is jealously retained by the National
Government, meanwhile weaker taxes that yield precarious revenues are collected by sub-
31
national levels. In this context, the transfers contribute to rectify the vertical imbalances that
arise from the tax distribution scheme and to reach out a pristine equity tenet (Buchanan 1950).
Spain as a more decentralized country has advanced in this direction, giving to the autonomous
treasures the collection of some tranches of the Income Tax for Individuals and the assignment
of a percentage of VAT.
On the other hand, in terms of funding competences of expenditure, the Colombian General
System of Shares (SGP) has no explicit inter territorial funds that can channel resources
between regions. However, there is an implicit tool of allocation in favor of lagged regions, if
we could unravel the formula of allocation that includes criteria as poverty, population to be
served and coverage deficits. These types of funds gain importance in the regionalization
process, when the starting point is an asymmetric set of regions, taking for granted that this
circumstance obstructs a balanced regional model.
In fact, our analysis demonstrated the highly negative effects that external factors have had on
fiscal stance of countries, either developed or developing. In Spain economic crises obligated
to assimilate a deep adjustment dictated from Brussels, and carried out across all scales of public
sector. In Colombia and other developing countries, the drop of oil prices has direct and indirect
effect on fiscal stance.
Reactions and tools used to act in case of economic crisis diverge between federal and unitary
states. In federal systems, territories are forced to attend the financial market by funding their
necessities, meanwhile in cases of unitary countries central government must bestow money to
bill out territorial debts or deficit. So centralized schemes could instigate a behavior of moral
hazard in territorial governments, when are based on high dependence from central government.
From the outset, the distribution of tax revenues between levels in Spain, and even more in
Colombia, has turned out very unequal and has originated huge vertical imbalances. In fact, the
most powerful taxation (income, VAT, etc.) has been retained by the central administrations,
while the regions and localities administer anachronistic and static taxes and in the case of
Colombia, without normative capacity.
• Spain has taken some additional steps in favor of subnational financial autonomy, by
defining autonomic tranches in the Personal Income Tax and the assignment of a percentage
of VAT, among other examples. However, the regional fiscal problem is exacerbated by
growing spending needs arising from immigration, aging, insularity, the existence of
regional languages, etc., all of which are the direct and daily responsibility of governments
regional and local levels.
• Despite the declining trend of the Colombian Central National Government deficit, the
Central Level is reluctant establish a fairer vertical tax framework.
• In general, transfer systems attempt to compensate for imbalances arising from the
asymmetric distribution of fiscal revenues between levels (Buchanan 1950). The GSP
(SGP) responds more to the typical "Income Shares" scheme, with its usual limitation
associated with its inability to generate a complete financial autonomy in the sense of
transferring very little regulatory autonomy over departmental and municipal taxes.
• At the end of the transitional period of the formula defined by Colombian Legislative Act
04 of 2007, the discussion on the degree of fiscal and financial autonomy of departments
and municipalities may once again be discussed. There we find an opportunity to open a
comprehensive debate on the structure of revenues between levels that can contribute to
boost regional development.
• Unlike Spain and other cases, Colombia's transfer system does not explicitly have a regional
redistribution fund from rich to poor regions. With the exception of the modulations implicit
in the formulas, which correspond to the criteria of poverty, coverage deficit, population to
32
be served, etc., there is no coherent mechanism that fulfills a redistributive function that can
reduce the huge horizontal imbalances between regions.
In Spain during the discussion of funding mechanisms, the last instance for fulfill the aspiration
of regions for more equity and for maintain the status quo situation has been the intervention of
central government with additional resources, as a result of political bargain.
Central levels should be aware that, in case of not promoting a harmonious development of the
regions, the most lagged of them will continue to demand resources from the Central State to
meet financial sufficiency criteria and, in the end, will continue to depend extremely from the
General Budget of the Nation. So a centralized and regional asymmetric development model
will have a significant negative impact on macroeconomic and fiscal management and the
precariousness of regional development. This assertion has been pointed out by Von Hagen &
Eichengreen (1996) in the sense that constraint imposed to regional budget press the demands
for more central borrowing and ultimately weaken the central government fiscal stance.
References:
1. Auriol, C. (2006). “Regiones y Descentralización en Europa y América Latina”. en:
Restrepo, D. (ED), Historias de Descentralización, Universidad Nacional de Colombia,
Facultad de Ciencias Económicas.
2. Buchanan, J. (1950). Federalism and Fiscal Equity. The American Economic Review. Vol.
40. No 4. pp 583-599.
3. CONFIS, Cierre Fiscal Anual, (several issues). Ministerio de Hacienda y Crédito Público,
Bogotá. www.minhacienda.gov.co.
4. Lozano, I, Ramos J. & Rincón, H. (2007), Implicaciones Fiscales y Sectoriales de la reforma
a las Transferencias Territoriales en Colombia, Borradores de Economía, Banco de la
República. http://www.banrep.gov.co/es/borrador-437
5. Ministerio de Hacienda y Crédito Público (2006), Exposición de Motivos al Proyecto de
Acto Legislativo por medio del cual se modifican los artículos 356 y 357 de la Constitución
Política, Bogotá.
6. Oats, W. (1999). An essay on fiscal federalism. Journal of Economic Literature, Vol 37,
No 3, pp. 1120-1149.
7. Sala i Martin, X., & Sachs, J. (2004). Fiscal Federalism and Optimum Currency Areas:
Evidence for Europe from the United States. NBER, Working Paper. No. 3855.
http://www.nber.org/papers/w3855.pdf
8. Vilalta M. (2014). La reforma de la financiación autonómica. In: “Informe IEB sobre
federalismo fiscal 2012”. Institut d’Economia de Barcelona”. Universidad de Barcelona.
Barcelona.http://www.ieb.ub.edu/phocadownload/informe-anual/es/InformeIEB2012_Castellano.pdf
9. Viver C., & Martin G. (2012). El proceso de recentralización del Estado de las autonomías.
In: IEB. “Informe IEB sobre federalismo fiscal 2012”. Institut d’Economia de Barcelona”.
Universidad de Barcelona. Barcelona. http://www.ieb.ub.edu/phocadownload/informe-
anual/es/InformeIEB2012_Castellano.pdf
10. Von Hagen, J. & Eichengreen, B. (1996). Fiscal Restraint and European Monetary Union.
The American Economic Review. Vol. 86. No 2. Papers and Proceedings of the Hundredth
and Eight Annual Meeting of American Economic Association. pp 134-138.
11. Zubiri, I. (2016). El sistema de financiación de las comunidades autónomas. Problemas y
propuestas de solución. En: Mediterráneo Económico No 30. Publicaciones CAJAMAR.
http://www.publicacionescajamar.es/publicaciones-periodicas/mediterraneo-
economico/mediterraneo-economico-30-financiacion-autonomica-problemas-del-modelo-
y-propuestas-de-reforma/749/
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Contact information
Mgr. Helmuth Yesid Arias Gómez, Ph.D.
College of Regional development and Banking institute - AMBIS
Nárožní 2600/9, Prague, Czech Republic
Ing. Gabriela Antosova, Ph.D.
College of Regional development and Banking institute - AMBIS
Nárožní 2600/9, Prague, Czech Republic
34
DOES MUNICIPAL SIZE IMPACT MUNICIPAL PERFORMANCE?
Juraj Nemec, Lenka Matejova, Jana Soukopova, Daniel Klimovsky
Abstract
This paper has two goals. The first one (literature review part) is to summarise the arguments
for and against a fragmented territorial structure on the local level. The second one (analytical
part) is to assess the reality of the existence of “economies of scale” on the level of local self-
governments - to examine whether local government expenditures increase or decrease with
population size on the base of the Czech data. The results from the literature review indicate
that the territorial fragmentation has many supporters and detractors, however, the results from
all existing analyses are inconclusive. The decision on the size of the municipality seems to be
also more a political issue than an economic one. The results of the analysis seem to confirm
two core facts, established by most previous studies – the cost curves have different shapes for
different local services and functions, with different minimums and the fact that not all local
public services and functions can be connected with economies of scale. However, the fact that
cost curves are “inconclusive” does not mean that the existence of many too small
municipalities (like in the Czech Republic) should not be somehow reflected.
Keywords: local self-government, fragmentation, economies of scale, optimum size
JEL Classification: H77
INTRODUCTION
Local government is a fundamental part of the public administration of a democratic state. The
territorial, political, and administrative organization of local governments have different
characteristics in each country, whereas they share a common goal: to provide public services
for the quality of life of their inhabitants. After World War II, local governments were the object
of a series of reforms. These reforms were thorough, covering many aspects of the local
government system (Blom-Hansen, 2009). One of issues tackled were territorial changes. The
main aim of these changes was to make local governments larger. These reforms reflected the
enduring belief that “bigger is better” and that local governments are more cost efficient.
Opponents argued that smaller local governments were more responsive to citizens. This
dispute continues today.
The issue of fragmentation versus amalgamation represents one of the most frequently
discussed issues in the theory and practice of public administration. The core problems are the
potential lower efficiency of use of the available financial resources, lacking capacities and
knowledge, the inability to manage local public affairs, a lack of finance as well as employment
opportunities for inhabitants, and a lack of technical infrastructure etc. On the other hand,
smaller may mean better local democracy, more direct public control, better participation, etc.
The goal of this paper is to summarise the arguments for and against a fragmented territorial
structure on the local level and to add to the bulk of knowledge about reality of the existence of
“economies of scale” on the level of local self-governments (examining whether local
government expenditures increase or decrease with population size – Czech data).
35
1. CZECH REPUBLIC AND SLOVAKIA: EXAMPLES OF THE REALLY
FRAGMENTED TERRITORIAL STRUCTURE
On January 1st, 1993 as at the result of the friendly split of the former Czechoslovakia two
independent states – the Czech Republic and the Slovak Republic – were created. Both of them
are members of the European Union since May 1st, 2004.
Local government reform in the former Czechoslovakia started immediately after the 1989
regime change. Today, local and regional governments function well in both counties, but there
is still some space for future improvement to be sure.
The fundamental question for a future Czech and Slovak local government changes is
amalgamation. Graphs 1 – 3 characterise the situation (Graphs 2 and 3 use only Slovak data).
Graph 1 – Average population per local government entity in the European Union
Source: EU data
36
Graph 2 – Spatial distribution of small municipalities (up to 1,000 inhabitants) in Slovakia
Source: Klimovsky, 2014
Graph 3 – Spatial distribution of the micro-municipalities in Slovakia (up to 500 inhabitants)
Source: Klimovsky, 2014
After 1990, the terms decentralization and a paradigm of local autonomy were often understood
in a way that gave the right to become a separate local government to almost each settlement
unit, even if that unit was a tiny village. Attempts to create or maintain larger territorial
37
jurisdictions (as in the previous decade) were seen as a violation of local autonomy. But
according to Swianiewicz (2010) it quickly became apparent that territorial fragmentation was
one of the major barriers to the decentralization and effective functioning of the local
government system.
Since 2001, the total number of municipalities in the Czech Republic has stabilized at about
6,250, with a slight movement in this figure since then. The settlement structure is dense,
consisting of a large number of villages, townships and small towns. But there are relatively
few medium and large cities. According to the data from the Czech Statistical Office (2013),
an absolute majority of municipalities are the villages with a very small population size: 77.6%
consisted of municipalities with less than 1,000 inhabitants and almost 24% of the
municipalities have even fewer than 200 inhabitants. The average size of the villages is 1,482
inhabitants (excluding the capital city) and the median size is only 421 inhabitants. From 6,250
municipalities only 597 have a city status. There are only 20 cities, which have more than
50,000 inhabitants. The distribution of the population looks different, with more than 63% of
the population (without Prague) living in the city.
Nowadays, there are 2,890 municipalities in Slovakia. The average municipality population size
in Slovakia is only 1,870 inhabitants and the average Slovak municipality has approximately
17 km². Only two cities, the capital city Bratislava and Košice have a population size over
100,000 inhabitants (approx. 430,000 in Bratislava and 250,000 in Košice). According to the
last general census (2011), only seven other towns/cities have a population over 50,000
inhabitants. Almost 70% of all Slovak municipalities have less than 1,000 inhabitants and only
slightly more than 16% of the total population of Slovakia live in them. Furthermore, several
years ago, the smallest municipality, Príkra, had only seven inhabitants, (nowadays it has 12)
but according to the relevant legal provisions it has the same competence as the largest Slovak
municipalities/towns.
2. ARE ECONOMIES OF SCALE A REAL ARGUMENT FOR AMALGAMATION?
Analyses that deal with the question of the advantages and disadvantages of larger
municipalities have become quite common in the last twenty to thirty years, see e.g. Dahl and
Tufte (1973), Nielsen (1981), King (1984), Mouritzen (1989), Newton (1992), Bours (1993),
Sharpe (1995), Hampl and Müller (1998) Goldsmith and Rose (2000), Denters (2002), Rose
(2002), Swianiewicz (2002), Baldersheim and Rose (2010) and Faulk and Hicks (2011).
Keating (1995) summarized the results of the previous analyses in his work. He divided the
advantages and disadvantages of larger municipalities into four groups according to the terms
of efficiency, local democracy, distributive justice and the development perspective. According
to the terms of economic efficiency, the relative costs of local government performance and the
public services provided decrease with the size of the municipality, so these services will be
cheaper. The performance of local government can be more efficient and qualified because
municipal authorities and elected bodies provide greater specialization, the bureaucracy is more
professional and better equipped technically.
The term local democracy means that, in the municipality, the system is composed of many
individuals along with their different opinions, mutual competition, control, and balances of
system elements. In a small town, the local policy lies mainly on the level of personal
relationships. There is a higher “supply” of competent candidates for elected functions and
because as the size of the municipality increases, so does the prestige of these functions, and a
greater interest of qualified individuals in them can be simultaneously assumed (Illner, 2006).
The term distributive justice helps to compensate the unjustified differences in the availability,
scope, quality and the price of services, which are provided, within a larger municipality after
territorial consolidation.
38
The last term, development perspective, means that large municipalities can better design their
economic, social and territorial development, and they are less sensitive to changes in external
and internal conditions (Keating, 1995), such as a change in the price level, taxes revenue, the
funding rules for the municipality or the problem of being the largest employer in the area, etc.
2.1 Arguments Supporting Territorial Fragmentation
The most essential arguments for territorial fragmentation are primarily based on democracy-
related arguments. They include both the idea of localism (Jones, Stewart, 1983) and the idea
of public choice (Swianiewicz, 2002a). Although they are based on very different theoretical
assumptions, both theories come to a very similar conclusion that “small is beautiful”.
Denters (2002) found that contacts between councilors and citizens are much closer in small
municipalities, the flow of information is easier, and politicians are more accountable to their
local communities. However, the studies by Hajnal (2001) and Borecky and Prudky (2001) on
Hungary and the Czech Republic show that this rule does not apply to tiny municipalities with
fewer than 1,000 citizens. In such cases, perhaps, the low functional capacity of the local
government overshadows the socio-logical beauty of small municipalities and negatively
influences popular perceptions of local government performance (Swianiewicz, 2010a).
According to the classical Tiebout model (Tiebout, 1956) people migrate to local governments,
in which the ratio of taxes versus services is closest to their personal preferences, i.e. in small
municipalities citizens can vote “with their feet”. Thus, territorial fragmentation decreases the
costs of migration and increases the chances of reducing the gap between implemented public
policies and the individual preferences of citizens (Ostrom, Tiebout and Warren, 1961).
Swianiewicz (2002a) concluded that fragmentation supports experimentation and innovation.
However, it is interesting to note that the most well-known programme, which focused on the
stimulation of innovations and experiments in local governments, was introduced in the Nordic
countries, where the territorial system is consolidated rather than fragmented (Baldersheim,
1994).
The last argument states that small local governments are less bureaucratic (Swianiewicz
2002a).
2.2 Arguments Supporting Territorial Consolidation
The most important arguments for territorial consolidation are connected with economic
theories. The most serious problems of small municipalities include a lack of finances and
employment opportunities for their inhabitants. A lack of technical infrastructure, difficult
access to basic services and a small population can be included among the more moderate
problems.
Swianiewicz (2002) found that small, local governments’ budgets are mainly expended by
administrative spending, where in some extreme cases not much is left for any other purposes.
In small municipalities, the number of services provided is much lower than in bigger cities and
the unit costs of public services are higher. The paradox is that for example in 2009, total
revenues per capita in small municipalities amounted to almost 79% of the average of all
municipalities. Surprisingly, municipalities with less than 200 inhabitants almost approached
the average (97%), although the smallest local governments do not provide - in comparison
with larger communities - many public services, such as public transport, theatres, museums or
libraries (Kameníčková, 2011).
The most frequently discussed economic problem, which is associated with the problem of
municipal consolidation, is the existence of economies of scale that can be achieved after
amalgamation.
Scale economies exist in the private sector when a firm that optimizes its production costs in
the face of some fixed costs and enjoys lower per unit production costs as the production grows.
39
From a production point of view, municipalities can be seen as production units where the
production function and economies of scale are the decisive factors (Houlberg, 2010). The
municipalities have to be large enough to minimize average costs and there must be forces
working to ensure an efficient exploitation of these factors.
Potential economies of scale at the municipal level are primarily related to administration and
the costs of political representation. The costs per capita of having a local council may decrease
as the number of inhabitants increases, as well as the costs for having a Chief Executive Officer,
in addition to other administrative personnel. Every municipality will need a minimum amount
of personnel, buildings, and machinery to even start production, and this also includes having
a minimum of administration (Houlberg, 2010).
On the other hand, after a certain level of production, diseconomies of scale may begin to
emerge and unit costs may rise (Boyne, 1995). Thus, marginal costs are larger than average
costs. The personnel can be so specialized that they can only focus on their own narrow field,
no longer capable of being flexible, with their potentials not being optimally used (Scherer and
Ross, 1990).
At the theoretical level, potential economies of scale may be replaced by diseconomies of scale
at a certain level of production. The average cost of production therefore is U-shaped. In a
multipurpose municipality, the U-shape could mean that there are different optimal sizes in
different service areas.
Municipal economies of scale have, over the years, been the basis for many studies. Most of
them have used expenditure models with per-capita expenditure as the dependent variable.
However, it is difficult to compare these analyses of municipalities among different countries
because of differences in institutional settings, tasks, local autonomy, etc. (Houlberg, 2010).
Nevertheless, it is worth looking at the results and see if they point in the same direction, despite
the country-specific differences.
Many analyses were done in the United States. As Holzer et al (2009) show, even this discussion
of the U-shaped nature of the relationship between size and economies of scale has variations.
The consensus among researchers who have studied consolidation efforts is that nearly 80% of
municipal services and activities do not possess economies of scale beyond a population of
approximately 20,000 inhabitants (Katsuyama, 2003). Gabler (1971) uses a threshold of 25,000
inhabitants and results of his study suggest that large cities tend to employ and spend more per
capita than smaller municipalities and that this tendency is attributable to the effects of city size.
Appelbaum and Follet (1978) founded no effects of size when monitor various test factors.
(Newton, 1978) examined several European countries and concluded that the reforms of local
governments in these countries resulted in larger units of government, though there is not much
evidence to support that larger units are more effective and efficient than smaller ones.
Bodkin and Conklin (1971) looked at local service costs and municipality size in Canada by
examining eight functions and a variety of variables beside government characteristics, such as
the income of population of municipality, to determine both determinants of expenditures and
scale effects. The study concluded that different functions respond very differently to a scale,
that there are economies of scale for municipalities with populations of up to 140,000 for water
supply and 180,000 for public works. But in six other categories – fire, police, sanitation and
waste removal, health, recreation and general government – the minimum costs are achieved in
municipalities with populations of 5,000 to 10,000 (Bish, 2001).
3. ECONOMIES OF SCALE: DATA FROM THE CZECH REPUBLIC
In this part we provide few selected calculations from our research about the economies of scale
in the Czech Republic. Areas covered are education, schooling and waste management.
40
3.1 Education
Czech municipalities are responsible for pre-school and elementary education. There were
5,085 kindergartens and 4,095 primary schools in 2014 in the Czech Republic. From these,
4,707 kindergartens and 3,948 primary schools were established by municipalities and had a
legal form of contributory organizations. Municipalities finance educational expenditures from
targeted grants (formula based), their own financial resources as well as often using
contributions from parents (especially in pre-school education and in school catering).
Our analysis examining expenditures per capita of municipalities on preschool and basic
education is based on data for 2005-2012. The authors use regression functions – hyperbolic
regression (1) and quadratic regression (2) similarly to (The Council of Europe survey, 1995;
Holzer et al, 2009; Faulk and Hicks, 2011, Matejová et al., 2014). As the distribution of
expenditures on pre-school and basic education is specific in the Czech Republic, it was also
necessary to include the best regression function (3) where the quadratic regression was
adjusted by hyperbole:
𝐸𝑖 = 𝑓(1 𝑃𝑖⁄ , 𝜀𝑖) (1)
𝐸𝑖 = 𝑓(𝑃𝑖, 𝑃𝑖2, 𝜀𝑖) (2)
𝐸𝑖 = 𝑓(𝑃𝑖, 𝑃𝑖2, 1 𝑃𝑖, 𝜀𝑖⁄ ) (3)
where Ei is the expenditure per capita on education in municipality i. P is population in
municipality i and the random error term εi captures an unexplained variation.
The optimal size of the municipality represents the local minimum of functions (the method of
bisection interval was used). The authors feel that third regression function explains the cost
development best. The curve for this function is U-shaped as the theory of scale economies
predicts. The optimal size of a municipality calculated by our methodology is 233 606
inhabitants. These results must be interpreted with regard to limitations which analysis suffers.
The main limitation is the using cash principle in the reporting of the public sector expenditures
in the Czech Republic until 2012. It means that the exact results cannot be accomplished,
because fixed expenditures, which do not change with the number of inhabitants, cannot be
determined from the analysed data.
The resulting optimal size of the municipality means de facto that kindergartens and primary
schools would be established only in municipalities with large populations. However, such a
solution is impossible: the issue is only about possible amalgamation for this service – one
school serving more small villages and not about the full concentration, which would cause too
many problems, especially for parents. So, the results should be used mainly for calibrating
current formula based model of financing of primary education from state budget.
3.2 Maintenance of intangible property
For the evaluation of the scale economies in this area the authors use the same methodology as
for educational expenditures (Ei is expenditure per capita on the repair and maintenance of
intangible property in a municipality i. in this case). All regression functions describe the
analysing data quite well, but do not clearly confirm the existence of an expected U-curve (again
research limitations such as those described for educational services) may play a role. The
results of the regression functions propose that the optimal size of a municipality for this type
of expenditures lies in the interval from 15,339 to 80,143 inhabitants. Such a large range of an
interval limits the chance for deriving any conclusions.
41
3.3 Waste management
To analyze this service, research was performed with respect to data collected for a five-year
period from 2008 to 2012. The analysis was based on a sample of 1300 municipalities in the
Czech Republic, reflecting the general structure of municipalities in the Czech Republic by the
number of inhabitants. Table 1 shows the descriptive statistics of the municipalities and their
waste management expenditures per capita in 2008-2012 by population size.
Table 1 – Descriptive statistics of the groups for the 2008-2012 periods
Population size Sample
size Mean
Standard
deviation Min Max
less than 500 564 606.80 190.39 96.27 1,703.10
501 … 1,000 259 540.06 126.79 159.19 1,221.01
1,001 … 4,000 215 551.94 154.52 71.39 1,451.,38
4,001 … 10,000 81 790.66 197.69 207.14 1,416.61
10,001 … 20,000 56 783.28 222.09 128.41 1,373.74
20,000 … 50,000 40 795.08 237.86 112.39 1,287.09
50,001 …100,000 16 805.95 160.70 223.98 1599.82
100,001…500,000 4 683.44 238.24 303.81 953.39
more than 1 million 1 1,030.68
Total 1,236 612.58 195.15 67.17 1,738.47
The average expenditures related to municipal waste management operations in the Czech
Republic were 612.58 ± 195.15 CZK/capita for 2008-2012, with municipalities with
populations under 4000 achieving lower than average expenditures. It is apparent that the
distribution of expenditures by population size is not in full accordance with the theory of
economies of scale. The data show that the average expenditures of municipalities in the
population size category from 4000 to 100,000 (without extreme values – the authors excluded
Plzen with average expenditures slightly over 300 CZK/capita from this calculation) are nearly
invariable; this is not in accordance with the U-shaped curve. The research sample is fully
significant: the authors need to admit that classic economies of scale are not visible in the area
of the Czech waste management. Surprisingly, the results suggest that in terms of the average
waste management expenses, the optimal population of a small municipality is 1000 to 2000 –
such findings do not correspond to the outcomes of existing studies.
CONCLUSIONS
The results of the analysis seem to confirm two core facts, established by most previous studies
(see, for example, Byrnes and Dollery 2002):
a. cost curves have different shapes for different local services and functions, with
different minimums,
b. not all local public services and functions can be connected with economies of scale.
Territorial fragmentation has many supporters and detractors, however, the results from all
existing analyses are inconclusive. The decision on the size of the municipality is also more a
political issue than an economic one.
However, the existence of many small municipalities should be somehow reflected according
to the opinion of authors. From the possible alternatives - structural and functional integration
(Illner, 2006), the authors prefer the second option – a less radical form that does not affect the
42
autonomous identity of municipalities and thus it is more politically acceptable. Functional
integration already exists in the Czech Republic and Slovakia in two forms – in the area of
delegated responsibilities and as voluntary inter-municipal cooperation.
In the Czech Republic from the point of view of the delegated competences (competencies that
municipalities exercise on behalf of the state) three categories of municipalities exist. The first
type is the so-called basic municipality, which performs a few delegated competences only
within its own territory. The second level is the municipality with a commissioned municipal
office – such a municipality performs a defined scale of delegated competences for its
inhabitants and in addition, serves neighbouring local governments with the status of basic
municipality (delivering services not provided by the lowest level). Finally, the third type is a
municipality with extended powers, which is responsible for the full scale of delegated
competences and serves the entire surrounding region. This is much better solution than the
Slovak reality, where municipalities are “equal” also for delegated responsibilities.
The Municipal Acts in both countries provide municipalities with several options to cooperate
– probably the most frequent option is voluntary partnership based on the public-law agreement.
Municipalities create associations of municipalities – legal bodies with their property,
institutions and a financial budget (like voluntary union of municipalities, micro-region, region
or the associations of municipalities).
Acknowledgements
This research was completed with support from the research project APVV-15- 0306:
Collaboration activities of the local self-governments and measuring their effectiveness and
efficiency.
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Contact information
Juraj Nemec
Department of Finance and Accounting, Faculty of Economics, Matej Bel University
Tajovského 10, Banska Bystrica, Slovakia
Lenka Matějová
Department of Public Economics, Faculty of Economics and Administration, Masaryk
University Brno, Czech Republic
Lipová 41a, Brno, Czech Republic
Jana Soukopová
Department of Public Economics, Faculty of Economics and Administration, Masaryk
University Brno, Czech Republic
Lipová 41a, Brno, Czech Republic
Daniel Klimovský
Department of Political Science, Faculty of Arts, Comenius University, Bratislava, Slovakia
Gondova 2, Bratislava, Slovakia
45
THE IMPACT OF EDUCATION ON THE SOCIAL AND ECONOMIC
DEVELOPMENT OF THE COUNTRY
Zuzana Hirkova, Helena Kuvikova, Jana Strangfeldova, Stefan Hronec, Nikola
Stefanisinova
Abstract
The growing importance of human capital in terms of social and economic development
encourages government society to develop it especially through formal education, through
which they can influence the quality and quantity. The aim of this article is to quantitatively
analyse and confirm the existence of a relationship between direct and indirect dependence of
educational structure and selected indicators of economic performance. The object of the
quantitative analysis is the Slovak Republic and selected EU countries. In line with the aims of
the study and formulated research presumption the subject of the research was defined, namely
the correlation between educational structure and selected indicators of economic performance.
We grouped the countries on certain homogeneous groups in which we expect common features
such as: approximately similar spending on education, comparable performance of the economy
as well as comparable educational structure of the population. In many countries a very strong
linear relationship was demonstrated. The survey showed that there is a dependence (taking into
account a certain degree of abstraction) between the educational structure of the population and
performance of the economy in terms of GDP growth rate and GDP per capita.
Keywords: Education. Human capital. Lifelong learning. Socio-economic development
JEL Classification: H52
INTRODUCTION
According to the neoclassical model education is currently one of the key determinants of
economic growth and productivity. The basis of productivity is a quality workforce, in other
words capable human capital that would not exist without a successful educational process.
Education, qualifications or knowledge become a production force and businesses are aware to
make substantial investments in their training (their professional growth). The opposite also
applies if a worker wishes to compete in the labour market, they must constantly educate
themselves and comply with the requirements on the side of demand. Through implementation
of knowledge management companies acquire intellectual capital.
Changes in the market economy are a constant phenomenon, in some periods there is rising
output whereas in others falling. During the global economic crisis, the greatest fall in GDP
was witnessed, when the productivity of goods and services slumped, which was associated
with a subsequent increase in unemployment. Growth rate is ensured by the market
environment, high rates of savings and investment, free trade and government, which provides
for certain conditions. Growth in the economy is ensured through the creation of new jobs, on
the basis of which, better living standards through higher household incomes and government
are provided for. Great importance is placed on investments in education and health, because
only a healthy and educated society has the opportunity to improve the conditions for
sustainable development of the country.
46
As mentioned, the growing importance of human capital in terms of social and economic
development encourages government and society to develop it especially through formal
education, through which they can affect the quality and quantity. Flexibility, in terms of the
labour market, plays an important role due to the strong impact of technological progress.
The result of education and experience are the knowledge and skills embodied in the labour
force, otherwise also known as human capital. This term has appeared in economic theory since
the 1920s to 30s of the last century alongside the concept of human resources. Understanding
of human capital is based on the complexity of education, values, motivation and
entrepreneurial spirit which creates new objectives in the field of business policy of a company.
Through the development and use of human capital and consequent development and utilization
of human resources of a company it is possible to strengthen competitiveness. Munich (2000)
defines human capital as the component of human resources that can be economically defined
and emphasizes that it is above all about the knowledge, skills and abilities, with which an
individual is equipped and that these characteristics have a bearing on economic activity.
"The conclusions on the role of human capital are identical in terms of the positive impact on
growth. According to one group of authors (Krueger - Lindh, 1999 Bassanini - Scarpetta, 2001
Sianesi - van Reenen, 2002) it has a positive effect on the growth rate of income per capita by
an increase in education. According to a second group (Azariadis - Drazen, 1990 Kalaitzidakis,
2001) high social returns are generated only after exceeding a certain threshold level of human
capital, and therefore the key is the average level of human capital (Barro - Sala-i-Martin, 1995;
Mankiw - Romer - Weil, 1992; Benhabib - Spiegel, 1994). According to a third group the
growth rate is an important combination of both, accordingly at the level and increase in human
capital (Krueger - Lindh, 2001, Gemmell, 1996) (Tiruneh et al, 2011, p. 16)."
In order for us to determine how much influence education has on socio-economic
development, it is necessary to identify possible ways of measuring it. Among the first findings,
through which later research began to examine the influence of the levels of education on socio-
economic development, was evidence that the level of the quality of the labour force is a guiding
factor in economic growth.
The economist Barro (1996) deals with the examination of economic growth in a number of
studies. He examined it during the second half of the 20th century and the beginning of the new
millennium. In a study for the OECD in 2003 he dealt with the theme of education and economic
growth. His study considers human capital as a determinant of economic growth and explores
the relationship between human capital and education. The effects of education are influenced
by several factors such as compulsory education and the quality of the education system.
According to Barro (2001) the quality of education is measured by student performance in
international competitions of science, mathematics and reading. The best results in science were
achieved by students from more developed countries. Students from poorer countries had worse
results in all areas.
From the viewpoint of Dudová (2009) there is sustainable economic growth and socio-
economic development only if human capital is still developing. Human capital is an essential
element in the production of new ideas. This mechanism confirms the argument that education
is the main determinant affecting the degree of growth in the long term. According to this
investigation it was observed that educated human capital is a determinant of economic growth.
Dudová (2009) also examined the variation in the levels of study and levels of economic growth
in many countries. From the causal analysis of growth, it suggests that in those countries that
have achieved economic growth the percentage of graduates also increased. According to
regression analyses there is a correlation between economic growth and level of education. In
countries that have invested in the development of the quality of human capital the gross
47
domestic product increased by several percent. According Ramcharan (2002), no country has
achieved significant economic growth without investing in education, which means that
education plays a major role in economic development. All stages of education have a role in
society. A "bad" type of education can have negative or no effects on economic growth. In those
countries where there is a little secondary educated workforce the economic indicators are
automatically worse.
Jarecki (2009) in his study examined the effects of higher education on society. Based on his
examination he deduced that in those countries where they invested more in education,
economic indicators were better. In countries with educated populations wages are generally
higher, tax payments are higher and poverty is lower. Lee's study (2010) also shows that
economic growth is linked to the accumulation of human capital. World Bank (1993) stressed
that increased investment in education can have a positive impact on the economic situation of
the relevant country.
According to the neoclassical growth model of Mankiw, Romer and Weil (1992), human capital
has a positive effect on earnings. It extended the thinking on the meaning and nature of capital
in the production function of human capital. On this basis, if the productivity of human capital
increases, there is also an increase in its share in the gross domestic product per capita at the
same time. In doing so, if there is an assumption of constant returns from human capital, it
ensures the countries that have higher levels of human capital will achieve higher rates of
economic growth. According to Blakemore (2010) the development of real GDP per person
employed has a major impact on improving the standard of living and is associated with the
development of real wages. It follows that without productivity the standard of living does not
improve.
In the United States, some states are technologically advanced, precisely because of the
universities located in them. At these universities quality research is carried out and investment
in research returns in the form of economic growth and productivity. It is obvious that high
levels of qualification are a condition for carrying out work in science and research.
"It is particularly important that human capital significantly influences research and
development more than in other sectors of the economy. From this it was discovered that the
costs relating to investment and adaptation of new technologies decrease due to the increase in
the accumulation of human capital. We can therefore conclude that countries with high levels
of human capital have a much better standard of living than those with lower levels of human
capital (Tiruneh et al, 2011, p. 38)."
The aim of this article is to quantitatively analyse and confirm the existence of a relationship
between direct and indirect dependence of educational structure and selected indicators of
economic performance. The object of the quantitative analysis is the Slovak Republic and
selected EU countries. We grouped the countries on certain homogeneous groups in which we
expect common features such as: approximately similar spending on education, comparable
performance of the economy as well as comparable educational structure of the population.
The article is divided into several parts. In the first part of the article we will discuss the
theoretical definition of the selected issues, then present the investigation methodology; the
results and discussion part is devoted to the analysis of individual data by correlation and
regression analysis, and finally we present our conclusions and recommendations.
48
1. THEORETICAL RESULTS OF RESEARCH INTO THE PROBLEM
The theoretical source was the works of domestic and foreign authors (many mentioned in the
theoretical background) who have dealt with the issue of education, human capital and lifelong
learning: Abbott, Doucouliagos (2003), Alexy, Antalová (2003), Armstrong (2002, 2007),
Becker (1994), Benčo (1992, 1998, 2000), Benčo, Kamoďa, Hronec, Slačka (2005), Cenker
(2014), Colley, Hodkison, Malcolm (2003), Čaplánová (1999), Dewey (1966), Dobrotková (
2008), Goulliová (1998), Hamerníková (1998), Hronec (2008), Hvizdová (2011), Kamiač
(1971) Kampová (2001), Kempkes Pohl (2006), Koróny, Hronec (2012), Kulčár (2005, 2008),
Kuvíková (1992), Liptáková (2008), Mikušová Meričková (2007), Nemec (2000), Nemec,
Wright (1997), which inter alia, addressed the positive and negative externalities and
quantitation; further Pastorová, Svobodová (2010), Peková (2002), Peková, Pilný (2002), Pilný,
Pěšta (2000), Staneková (1998), Stiglitz (1997, 2000), Strecková, Malý (1998), who studied the
specifics of the public sector and can be considered the founders of the theory of public
economy in the Czech Republic and Slovakia, Tallman, Wang (1994), Vodák, Kucharčíková
(2011), Uramová, Valach (2004), Vomáčková (2007), Zdeněk (2002), Žižková, Jelínková, Volf
( 1989), etc.
Social and economic development are linked with both social and economic objectives. We are
talking about a strong cohesion between individual regions and their mutual influence. "In the
conditions of a pluralistic society, education is a part of and a fundamental determinant of
economic development. Education as the final effect of education is the driving force for the
development of every society (Benčo, et al., 2005, p. 4)."
According to Žižková (1989) education initially had a relatively narrow base and had at its
disposal only a very limited circle of people. The motivation to be educated was particularly
one of social status. Education, in the process of development, expanded and became the germ
of further human development in all areas of life.
Economic development is not possible without a quality education system and can therefore be
considered as its integral part, as proposed by Benčo (2005) in his publication where he states
that the economic and material conditions in which we live represent the basic direction of
human life and society. Under the conditions of a pluralistic society, education and science do
not operate outside the system of a market economy, but are an integral part and a basic
determinant of the development of each society. The level of qualification of the labour force
directly affects productivity, hence the efficiency and intensity of economic growth.
Uramová and Valach (2004) consider education as a conditioning factor of the ability of the
workforce to adapt to changing conditions. Changing the conditions of the application of the
workforce in the labour market is, among other things, a result of the macroeconomic and
microeconomic changes in the structure of the economy which alter the nature of many types
of work.
Education has an impact on many factors and thus performs several functions. Žižková et al
(1989) argue that its effects are seen not only in the economic field, but are also an important
tool in the creation of the social fabric of society, affecting not only economic but also social
development, and also significantly affects the political and moral character of individuals and
society as a whole. The functions of education are the following:
• economic function,
• socio-cultural function.
Economic function, according to Žižková et al (1989), is a given interrelationship between the
economy and education and these relationships can be formulated in two ways. One, that
49
economic development is an essential resource for the development of education or, two, that
education is not only an effect of economic growth, but is also simultaneously its necessary
condition, which confirms that lifelong learning has an impact on the socio-economic
development of the country. Socio-cultural function is a complex and very diverse range of
relationships and links between educational development and a range of non-economic areas of
social life. Education and its effects influence the human personality as a phenomenon, are
involved in shaping the overall cultural and spiritual horizon of people, are involved in the
cultivation of human abilities and needs, and affects the selection and creation of the way of
living.
Lifelong learning or education in general have a significant impact on the development of
science. Žižková (1989) argues that through science, which is a proximate production force,
education also becomes a moment for productive forces and a factor in their development.
Development of science, technology and culture is linked to the development of the entire
education system, particularly at secondary and high schools. Their mission and status is a
priority in every developed country for scientific discoveries, inventions, patents, technology,
and in the creation and interpretation of works of art.
Through education we receive two types of benefits: benefits for the individual and benefits to
society - social. Individual benefit brings added value to the school graduates for whom there
is a likelihood of higher income - salary or other non-monetary added value, but that is subject
to each individual. As declared by Hronec (2008) education provides individuals with a
complete spectrum of benefits, their size is however difficult to measure. The benefits of
education for society as a whole are understood as the positive externalities of education
(increase of national income, stimulation of economic growth). We can observe the situation in
more detail in the following figure.
Figure 1 – Positive externalities arising from the needs of educational services
Source: Nemec, 2000. p. 46.
Where: MEB – marginal external benefits from the production of externalities
MPB – marginal personal benefits from the production of externalities
MSB – marginal social benefits from the production of externalities
MC – marginal costs
R1 – individual equilibrium output
R2 – social equilibrium output
50
Nemec (2000) illustrates the situation of how from the education of an individual results the
marginal external benefit expressed by the MEB curve. Given that a graduate as a producer of
externalities is not directly compensated by the market as an external benefit, resulting in a
socially inefficient state expressed by a deficiency of production of externalities, which is
expressed by axis d. This results in deadweight loss, which is expressed by the triangle abc. We
can say that positive externalities arising from education is less in society than the economic
optimum condition, point a, required.
The most important macroeconomic indicators include gross domestic product GDP,
employment rate, unemployment rate, inflation and foreign direct investment. Human capital
and lifelong learning have a positive effect on the individual components of GDP as well as
other factors of economic growth and we therefore consider them important to define.
The basic indicator of economic performance of a state is gross domestic product. In general,
GDP is considered as the sum of the monetary value of all final goods and services produced
in an economy during a given period, usually one year.
Several authors who deal with the relationship of education and economic growth equate human
capital with school education (Gould, Ruffin, 1995 Gundlach, 1995 Benhabib, Spiegel, 1994).
Mazouch and Fischer (2011) reported that at present we can assess the level of human capital
on the basis of determining the level of education. Education and its highest achievable level
should ideally be one of the possibilities for measurement of the level of human capital.
Education in its various individual levels fulfils two functions, namely selectivity and
productivity. The selective function separates individuals who have the required level of human
capital from those individuals who do not. Productive function is mainly engaged in developing
and enhancing this level. From a subjective point of view, human capital is also influenced by
its degree of depreciation. Knowledge held by individuals over time becomes obsolete and
needs to be renewed, updated, and in particular developed, just as skills and qualifications are.
As reported by Čepelová (1997), learning and education are important factors in economic
growth. Education can be defined as the process of obtaining professional, theoretical and
practical knowledge in the course of the educational process in the school system. Purposeful
acquisition of knowledge is understood in terms of labour market requirements and the future
application of it.
Authors who have dealt with the influence of the level of education to socio-economic
development used various research methodologies to calculate it. Among the most frequently
used methods feature: Regression and correlation analysis, Ordinary least squares, Extreme
Bounds Analysis, Regression Trees, Three-stage least squares, Semiparametric estimation,
Instrumental Variables, Two-stage least squares, Pooled Mean Group, Arellano-Bond Dynamic
Data panel estimators, Feasible Generalized Least Squares, Hierarchical Linear Modelling,
Generalized Method of Moments and Vector autoregressive technique.
The most used method by our selected authors was Ordinary least squares.
Authors like Romer (1989) and Azariadis & Drazen (1990), in their research by the Ordinary
least squares method and the method of Instrumental Variables, show that literacy has a positive
impact on economic growth. Barro (1991) using the same method came to realize that the
growth of GDP per capita is positively related to the number enrolled and the literacy rate and
is negatively related to the ratio of students to teachers (the number of students per one teacher).
Murphy, Shleifer and Vishnu (1991), using this method, demonstrated the positive impact of
student enrollment on economic growth, while the number of enrolled students in the fields of
engineering and law have a negative impact on economic growth.
51
Levine and Renelt (1992), using the method of Extreme Bounds Analysis also showed the
positive impact of student enrollment growth of GDP per capita, while Mankiw, Romer and
Weil (1992) have confirmed the same impact in terms of the percentage of the working-age
population who are in the second stage of education.
Using Regression tree Durlauf and Johnson (1995) showed that the proportion of working-age
population who currently are enrolled in the second level of study has a positive impact on GDP
growth only in countries with middle-income and underdeveloped human capital and in
countries with high income.
Lee (1995), using the Ordinary least squares and Instrumental Variables methods also
demonstrated the positive impact of test results (marks) on the growth of GDP per worker,
however, that is not valid for literacy, the number of enrolled students or student-teacher ratio,
i.e. no effect on GDP was confirmed for these factors.
Using 3SLS (Three-stage least squares), Gemmel (1996) came to the conclusion that the growth
rate of GDP per capita is positively associated with the number of enrolled students, while
Collins and Bosworth (1996) found the same relationship to GDP growth and length of
schooling again using the Ordinary least squares method.
According to Ramos, Surinach and Artís (2009) there are a large number of educated people in
the European Union. The supply of highly educated workers does not correspond to that of
demand. It follows that education is not only a positive effect on economic growth, in this case
this is due to the geographical distribution of the workforce. When they are unable to find
employment in their own region, they move to another region. Many studies and research
confirm the clear impact of human capital or education on the socio-economic development of
a country.
Many authors, in addition to examining the relationship between educational structure and
economic growth, deal with the relationship between economic growth and length of study.
Hanushek and Kimka (2000), by the Ordinary least squares method, show that the length of
schooling and test scores have a strong positive result on the growth of GDP, while Bils and
Klenow (2000) reported the same impact in terms of the number of enrolled students and the
length of schooling. Using LSM, Ranis, Stewart and Ramirez (2000) found a positive impact
of literacy on economic growth, while Krueger and Lindahl (2001) pointed out that the change
in the length of schooling has little effect on economic growth, while the growth equation was
estimated with a difference in attendance of five years; a strong positive effect occurred only
when using a period of ten or twenty years. Using Semiparametric estimation, Kalaitzidakis et
al. (2001) found a non-linear relationship between economic growth and the length of
attendance, but there was no relationship with the number of enrolled students.
Pritchett (2001), using the Ordinary least squares and Instrumental Variables methods, proved
negative impact of education on economic growth. Moreover, Knowles et al. (2002) using LSM
and 2SLS (Two-stage least squares) show that there is a difference in impact on GDP growth
due to the length of education between men and women. Bosworth and Collins (2003) found a
strong positive correlation between economic growth and the initial level of length of education;
the same can be said of positive correlation of growth and test results (marks) using the NS
method. Panel data analysis is used often as a cross-sector analysis mainly due to the availability
of more complete data sets. From this perspective, Barro (1996) and Bassanini and Scarpetta
(2001), using 3SLS and Pooled Mean Group (PMG) estimators, have shown a positive
relationship between the growth rate of GDP per capita and the length of schooling.
Gyimah-Brempong et al. (2006), using the Arellano-Bond Dynamic Data panel estimators,
found that the length of schooling has a positive effect on the growth of GDP per capita. By
52
means of the Pooled Least Squares (PLS), Keller (2006) shows that the number of enrolled
students and expenditures on basic education contribute very significantly to the growth of GDP
per capita. Using Feasible Generalized Least Squares (FGLS) Siddiqui (2006) concluded that
the length of attendance has a negligible impact on economic growth, while the difference in
education between men and women has a significant impact on GDP growth. Hanushek et al.
(2007) using the HLM (Hierarchical Linear Modelling) algorithm show that the length of
attendance (length of education) has a strong positive effect on economic growth. This influence
was substantially reduced when the quality of education (the test results) were taken into
account. Using LSDV, FGLS, 2SLS and GMM (generalized method of moments), Baldacci el
al (2008) found that the number of enrolled students are positively associated with economic
growth. Benos and Karagiannis (2010) using GLS (generalized least squares) and GMM show
that the number of enrolled students has a positive effect on the growth of GDP per capita, while
the ratio of students per teacher has a negative impact.
The least utilized type of analysis is the analysis of time series, because the data from the field
of education are rarely found in long time series. Musil and Belassi (2004) using LSM showed
the positive impact of expenditure on education to economic growth. Ndiyo (2007) using the
vector autoregressive (VAR) technique proved a negative correlation between these variables.
Through the use of the Error Correction Model using a "one step" procedure, Odit et al. (2010)
demonstrated a positive effect of the length of schooling (of education) on the growth of GDP
per capita. As mentioned above, there are many studies and research that demonstrate a clear
effect of education on the socio-economic development of the country through the use of
numerous methods.
2. METHODOLOGY OF EXAMINING EDUCATIONAL IMPACTS
The aim of this article is to quantitatively analyse and confirm the existence of a relationship
between direct and indirect dependence of educational structure and selected indicators of
economic performance. The complexity of the object of study in the area of the world economy
implies a high degree of abstraction in the research of a secondary nature. Secondary collection
of information from the available statistics from the Statistical Office regional databases and
the Eurostat databases is realized through constructive methods of scientific observation. The
information obtained is processed and evaluated by means of statistical methods with emphasis
on correlation and regression analysis. The research sample was 19 EU countries. We made the
selection according to the complexity of the data over the entire time period. The essential
factors among which we investigated dependence are the proportion of the population having
completed secondary and higher education expressed in %. The shown indicator represented an
independent variable. Dependent variables were the rate of growth in GDP and GDP per capita
expressed in €.
When examining the impact of variables, most authors use the method of correlation and
regression analysis to confirm or refute the contrary effect of the independent variable, in this
case education. Which is the reason why we also chose this method of measurement. It is
important to note that the calculation is based on the use of the Ordinary least squares method,
therefore it was necessary to observe the rules of this method.
The strength of the linear relationship between two variables in the base set is given by the
coefficient of correlation rXY, which can take only the values of (-1; 1). The strength of mutual
linear dependence of variables X and Y measured by the coefficient of correlation of the rXY
type is defined as:
53
Regressive coeficient - its calculation is based on the equation of the regression line x to x
depends on the true relationship:
constant b is in the form:
x to y depends on the true relationship:
The object of quantitative analysis is the Slovak Republic and selected EU countries. We
grouped the countries on certain homogeneous groups in which we expect common features
such as: approximately similar spending on education, comparable performance of the economy
as well as comparable educational structure of the population. The key methods of scientific
research are the methods of classification analysis, comparison and abstraction in the creation
of a theoretical and methodological framework for solving problems; methods of quantitative
analysis using statistical methods of processing and evaluation of information and methods of
synthesis and partial induction in drawing research conclusions.
In line with the aims of the study and formulation of research presumption a subject of research
is defined, namely the correlation between educational structure and selected indicators of
economic performance.
3. RESULTS AND DISCUSSION
For processing the analysis of dependence, data of the dependent and independent variables in
the Slovak Republic in the time frame from 2003 to 2013 was available. In examining the
dependence, we used data on the development of selected macroeconomic indicators. Other
economic indicators entered in the analysis were data on the standard of education in the
selected countries. The following results present the development of dependence between GDP
growth and the standard of education of the population. V4 countries demonstrated a slight
indirect linear dependence. This means that with an increase in the standard of education the
level of GDP growth decreases at, however, a slower pace. The aforementioned may be related
to the broader impact of the economic crisis on the economies of the V4 countries. The
economic crisis has reversed the positive impact of education on the economy to a greater extent
than was the case for the large and less open Western economies. The Western economies have
a larger share of services sector than the V4 countries. V4 countries are characterized by
,
(1)
(2)
, (3)
,
(4)
54
industry and therefore a significant secondary sector, which represents a larger share of GDP
(about 40%). Slovakia is focused mainly on the automotive industry which recorded a
significant decline in the previous period, which was also reflected on the impact on GDP and
that is the reason for the indirect linear dependence.
Table 1 – Dependence of GDP growth on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Czech
Republic - 1.000 0.990 0.985 0.840 0.177 -0.480 -0.463 -0.480 -0.573 -0.630
Hungary - 1.000 0.126 -0.254 -0.722 -0.802 -0.779 -0.695 -0.614 -0.655 -0.608
Poland - 1.000 -0.142 0.527 0.711 0.568 -0.134 -0.195 -0.178 -0.360 -0.486
Slovakia - 1.000 0.995 0.998 0.967 0.555 -0.433 -0.403 -0.428 -0.476 -0.527
Average - 1.000 0.49 0.56 0.45 0.12 -0.46 -0.44 -0.43 -0.52 -0.56
Source: Own processing on the basis of Eurostat, 2015.
Heterogeneous results in tracking dependence were observed in the case of the Nordic
countries. A medium direct linear relationship was observed in the case of Denmark and
Norway. In the case of most countries this dependence was, however, either weak linear, or
weak nonlinear.
Table 2 – Dependence of GDP growth on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Denmark - 1.000 0.948 0.967 0.332 0.664 0.638 0.584 0.574 0.567 0.565
Estonia - -1.000 0.136 0.092 -0.101 0.173 -0.082 -0.067 0.007 0.024 -0.032
Finland - 1.000 0.500 0.714 0.835 0.010 -0.518 -0.342 -0.249 -0.324 -0.388
Sweden - 1.000 0.507 -0.418 -0.296 0.146 0.154 0.146 0.151 0.108 0.077
Norway - 1.000 0.586 0.586 0.031 0.394 0.508 0.530 0.523 0.473 0.473
Switzerland - 1.000 0.932 0.843 0.849 0.602 -0.056 -0.010 -0.016 -0.058 -0.053
Average - 0.67 0.60 0.46 0.28 0.33 0.11 0.14 0.17 0.13 0.11
Source: Own processing on the basis of Eurostat, 2015.
The dependence for developed Western economies was comparable with V4 countries. Almost
all countries have been identified as having weak indirect linear dependence and hence there
was no proof of a positive relationship between education standards and GDP growth. This may
be due to the fact that overall growth is driven mainly by developments in the global markets.
Table 3 – Dependence of GDP growth on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Germany - 1.000 0.305 -0.278 0.278 0.030 -0.527 -0.183 -0.006 -0.037 -0.071
France - 1.000 0.529 0.681 0.605 -0.343 -0.662 -0.478 -0.310 -0.368 -0.380
Netherlands - 1.000 0.903 0.938 0.962 0.750 -0.032 -0.031 -0.035 -0.144 -0.276
Austria - 1.000 0.939 0.793 0.712 0.258 -0.588 -0.416 -0.264 -0.286 -0.337
United
Kingdom - -1.000 -0.741 -0.874 -0.534 -0.575 -0.755 -0.547 -0.487 -0.471 -0.386
Average - 0.60 0.39 0.25 0.40 0.02 -0.51 -0.33 -0.22 -0.26 -0.29
Source: Own processing on the basis of Eurostat, 2015.
55
A moderate direct linear dependence was observed only in the case of Malta. The positive effect
may be due to the fact that this country has seen the most significant positive leap in the standard
of education. In other cases, a medium indirect linear relationship was recorded. The most
negative result was observed in the case of Greece, where the dependency value reached - 879,
meaning a strong indirect linear dependence.
Table 4 – Dependence of GDP growth on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Greece - -1.000 -0.923 -0.714 -0.747 -0.802 -0.800 -0.858 -0.912 -0.930 -0.879
Spain - 1.000 0.997 0.936 0.758 -0.249 -0.477 -0.542 -0.570 -0.642 -0.678
Italy - 1.000 0.618 0.802 0.770 -0.077 -0.517 -0.309 -0.257 -0.378 -0.436
Malta - -1.000 0.537 0.615 0.708 0.760 -0.117 0.140 0.059 -0.022 0.061
Average - 0.00 0.31 0.41 0.37 -0.09 -0.48 -0.39 -0.42 -0.49 -0.48
Source: Own processing on the basis of Eurostat, 2015.
The economic crisis significantly affected the positive effects of education on economic
performance. A moderately strong direct linear dependence was demonstrated only in the case
of Denmark and Norway, which are on the contrary characterized by a reduction in the share
of the population with secondary and university education. The only country with a strong
indirect linearity was Greece. With an increasing number of educated population, economic
performance decreased rapidly. The aforementioned is the result of a misconfigured state
economic policy that led the country to the brink of bankruptcy. Negative growth rate,
constantly increasing deficits, high unemployment rates are major factors of a negative
relationship between education and performance. In the case of the research into education and
GDP per capita, the results are slightly different. In the case of V4 countries a strong direct
linear dependence was recorded in each. The highest dependency was the case of Hungary. On
the contrary, the lowest was seen in the Czech Republic. The average dependence greatly
exceeded the EU average. Positive effects of education, therefore, in this group have the most
impact.
Table 5 – Dependence of GDP per capita on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Czech Republic - 1.000 0.990 0.988 0.945 0.956 0.891 0.852 0.857 0.873 0.877
Hungary - 1.000 1.000 0.996 0.995 0.994 0.958 0.968 0.969 0.973 0.976
Poland - 1.000 0.998 0.996 0.957 0.970 0.974 0.979 0.975 0.978 0.981
Slovakia - 1.000 0.986 0.996 0.968 0.982 0.927 0.940 0.952 0.960 0.966
Average - 1.000 0.994 0.994 0.966 0.976 0.938 0.935 0.938 0.946 0.950
Source: Own processing on the basis of Eurostat, 2015.
The dependence results in the Nordic countries are highly heterogeneous. A strong direct linear
dependence was observed especially the case of Finland and Estonia. A relatively strong
indirect linear dependence was observed in the case of Denmark and Norway.
56
Table 6 – Dependence of GDP per capita on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Denmark - 1.000 0.838 0.936 -0.649 -0.782 -0.738 -0.753 -0.722 -0.647 -0.584
Estonia - 1.000 0.975 0.537 0.716 0.508 0.506 0.517 0.570 0.673 0.732
Finland - 1.000 0.980 0.987 0.961 0.973 0.830 0.787 0.812 0.829 0.800
Sweden - 1.000 0.885 -0.646 -0.742 -0.756 -0.744 -0.701 -0.579 -0.377 -0.150
Norway - 1.000 0.993 0.993 -0.733 -0.814 -0.789 -0.802 -0.799 -0.741 -0.705
Switzerland - 1.000 0.999 0.994 0.974 0.983 0.969 0.940 0.881 0.863 0.881
Average - 1.000 0.945 0.634 0.088 0.019 0.006 -0.002 0.027 0.100 0.162
Source: Own processing on the basis of Eurostat, 2015.
Results from developed Western economies are comparable to the UK. Most other countries
had strong direct linear dependence. The negative results from the United Kingdom may have
been affected by a high proportion of labour migration. In addition to Eastern Bloc countries,
migration is affected mainly by the former colonies of the UK, from where workers with little
or no education come.
Table 7 – Dependence of GDP per capita on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Germany - 1.000 -0.476 -0.592 0.391 0.641 0.531 0.644 0.754 0.806 0.835
France - 1.000 0.998 0.998 0.999 0.962 0.827 0.843 0.878 0.901 0.888
Netherlands - 1.000 0.976 0.952 0.955 0.959 0.922 0.914 0.892 0.898 0.814
Austria - 1.000 0.999 0.725 0.525 0.677 0.548 0.630 0.728 0.802 0.840
United
Kingdom - 1.000 0.937 0.970 0.976 0.948 0.447 0.100 -0.054 -0.145 -0.132
Average - 1.000 0.687 0.611 0.769 0.837 0.655 0.626 0.640 0.652 0.649
Source: Own processing on the basis of Eurostat, 2015.
The last group in the study is countries in the south of the EU. Indirect linear dependence was
observed only in the case of Greece, which reached only -0283. Strong direct linear dependence
was observed in the other countries. The strongest direct linear dependence was observed for
Malta.
Table 8 – Dependence of GDP per capita on the standard of education of the population in
selected EU countries
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Greece - 1.000 0.989 0.707 0.738 0.821 0.829 0.731 0.375 0.036 -0.283
Spain - 1.000 0.982 0.937 0.936 0.950 0.893 0.819 0.758 0.717 0.688
Italy - 1.000 0.889 0.869 0.886 0.923 0.758 0.745 0.765 0.778 0.746
Malta - 1.000 0.845 0.893 0.839 0.867 0.862 0.915 0.937 0.949 0.959
Average - 1.000 0.926 0.852 0.850 0.890 0.836 0.803 0.709 0.620 0.528
Source: Own processing on the basis of Eurostat, 2015.
In many countries very strong linear dependence was demonstrated. The countries with the
highest value include Hungary, Slovakia, Poland and Malta. The survey illustrated that there is
a dependence (taking into account a certain degree of abstraction) between the educational
structure of the population and performance of the economy in terms of GDP growth rate and
57
GDP per capita. However, the results showed that the positive effects of education are
suppressed by significant influences such as the global economic crisis. Since 2008, the impact
of education on economic growth has weakened or it did not have any significant impact.
Since the correlation results were not always clear in all cases, we then conducted a regression
analysis that in some cases confirmed and in others refuted the results of correlation analysis.
The following table presents the basic parameters of regression analysis in the case of the V4
countries. The highest level of confidence was recorded in the Czech Republic for GDP growth,
while in the case of GDP per capita the value of reliability was the highest.
Table 9 – Basic parameters of regression analysis of V4 countries -% GDP growth and
GDP/capita
% GDP
Multiplied by R Reliability value Mean error Significance
Czech Republic 0.695943 0.484336 2.866504 0.025403
Hungary 0.608008 0.369673 2.766278 0.047195
Poland 0.486124 0.236316 1.635087 0.129495
Slovakia 0.527364 0.278113 3.664481 0.095497
Average 0.594098 0.352952 2.499290 0.053941
GDP/capita
Czech Republic 0.811692 0.658845 801.096735 0.004353
Hungary 0.975923 0.952426 325.057889 0.000000
Poland 0.981418 0.963181 510.393715 0.000000
Slovakia 0.965626 0.932434 791.063320 0.000001
Average 0.980572 0.961521 430.827552 0.000000
Source: Author´s.
The results of the regression analysis are presented in the following table. In the case of the
relationship of % GDP growth in each country and the education structure, results were
obtained with high variability. The P indicator in three countries exceeded the target value of
0.05 and thus cannot be incorporated into the % of GDP model as a dependent variable. This
relationship was confirmed in the case of the Czech Republic and Hungary. When examining
the relationship of education and GDP per capita, the value of P in all cases was less than 0.05,
thus examining the relationship of these variables makes sense. The highest value reached was
the coefficient in the case of Slovakia where a 1% increase in the education structure of middle
to university educated population should increase GDP per capita by € 1,484.96. The smallest
increase would occur in the case of Hungary.
Table 10 – Regression coefficient of relationship % of GDP to education and GDP / capita to
education in the V4 countries
Reg. coef. % GDP Reg. coef. GDP/capita Value P % GDP Value P GDP/capita
Czech Republic -2.141414 858.140226 0.025403 0.0043529
Hungary -0.697810 479.078076 0.047195 0.0000003
Poland -0.342975 984.359291 0.129495 0.0000001
Slovakia -1.149335 1,484.963376 0.095497 0.0000014
Average -0.813262 948.850045 0.053941 0.0000001
Source: Author´s.
The linear function for regression relationship between % GDP growth (country average) and
the educational structure has the form: ŷ = 73.50 to 0.813 * x. Given the high value of P this
58
model is ignored. In the case of the relationship between educational structure and GDP per
capita, the function has the form: ŷ = -66,014.9 + 948.85 * x.
Figure 2 – Values of regressive coeficients in V4 countries
Source: Author´s.
The previous figures present the value of regression coefficients for the V4 countries.
4. NORDIC COUNTRIES
In the case of the Nordic countries, the highest reliability value was in the cases of Denmark
and Switzerland, whereas the lowest mean error was in Norway and Finland. The lowest
reliability was found for Estonia.
Reg. koef. % HDP
-2,141414
-0,697810
-0,342975
-1,149335
-0,813262
-2,500000
-2,000000
-1,500000
-1,000000
-0,500000
0,000000
Česká republika Maďarsko Poľsko Slov ensko PriemerČeská republika
Maďarsko
Poľsko
Slov ensko
Priemer
Reg. koef. HDP/ob.
858,140226
479,078076
984,359291
1484,963376
948,850045
0,000000
500,000000
1000,000000
1500,000000
2000,000000
Česká
republika
Maďarsko Poľsko Slovensko Priemer
Česká republika
Maďarsko
Poľsko
Slovensko
Priemer
59
Table 11 – Basic parameters of regression analysis of the Nordic countries -% GDP growth
and GDP / capita
% GDP
Multiplied by R Reliability value Mean error Significance
Denmark 0.564663 0.318844 2.105375 0.070326
Estonia 0.031908 0.001018 7.550161 0.925799
Finland 0.388029 0.150566 3.797316 0.238310
Sweden 0.077480 0.006003 3.190852 0.820867
Norway 0.367008 0.134695 1.555597 0.266883
Switzerland 0.053207 0.002831 1.770007 0.876532
Average 0.138692 0.019236 3.204134 0.684238
GDP/capita
Denmark 0.583946 0.340993 1,861.177374 0.059261
Estonia 0.731969 0.535779 1,743.544487 0.010440
Finland 0.800312 0.640499 1,313.428660 0.003090
Sweden 0.255950 0.065511 8,332.552845 0.447453
Norway 0.664514 0.441579 4,365.487580 0.025717
Switzerland 0.880708 0.775647 2,061.346133 0.000344
Average 0.090784 0.008242 3,198.624127 0.790655
Source: Author´s.
In the case of the relationship of % GDP growth in each country and the education structure,
both positive and negative results of variability were obtained. The P indicator in all countries
exceeded the target value of 0.05 and thus cannot be incorporated into the %model of GDP as
a dependent variable. When examining the relationship of education and GDP per capita, the
value of P in 4 cases was less than 0.05, thus examining the relationship of these variables in
the countries Estonia, Finland, Norway and Switzerland makes sense. The coefficient reached
with the highest value was in the case of Estonia, where a 1% increase in the education structure
of middle and university educated population should increase GDP per capita by € 2,357.44.
The smallest increase would occur in the case of Finland. In the case of Norway, the coefficient
reached a negative value which means that in the event of an increase in educational structure
there should eventually be a decline in the absolute level of GDP per capita. In practice, this
may lead to a development in an oversaturation on the labour market of university graduates
and a reduction in labour costs due to the high supply of a highly skilled workforce.
Table 12 – Regression coefficient of relationship % of GDP to education and GDP / capita to
education in the Nordic countries
Reg. coef. % GDP Reg. coef. GDP/capita Value P % GDP Value P GDP/capita
Denmark 0.464125 -431.374400 0.070326 0.059261
Estonia -0.303360 2,357.440000 0.925799 0.010440
Finland -0.494700 542.477465 0.238310 0.003090
Sweden 0.150089 -1,335.331557 0.820867 0.447453
Norway 0.170617 -1,079.168813 0.266883 0.025717
Switzerland -0.047933 1,948.048220 0.876532 0.000344
Average 0.430700 279.876233 0.684238 0.790655
Source: Author´s.
The linear function for regression relationship between % GDP growth (country average) and
the educational structure has the form: ŷ = -130756 + 1,948.048 * x. Given the high value of P
this model is ignored. In the case of the relationship of educational structure and GDP per capita,
the function has the form: ŷ = 6,968.35 + 279.87 * x. Given the high value of P, this model is
taken into account.
60
Figure 3 – Values of regressive coeficients in Nordic countries
Source: Author´s.
The previous figures present the values of regression coefficients for the Nordic countries. In
the regression model the highest value was achieved by Estonia and the lowest by Finland.
5. WESTERN EUROPEAN COUNTRIES
The following tables present the results of regression analysis in the group of Western European
countries. The highest values of reliability were recorded in the case of the UK and France; the
lowest mean error was recorded in the case of France. The lowest reliability was observed for
Germany and the UK (GDP %).
Table 13 – Basic parameters of regression analysis of Western European countries -% GDP
growth and GDP / capita
% GDP
Multiplied by R Reliability value Mean error Significance
Germany 0.070905 0.005028 2.707366 0.835883
France 0.380231 0.144576 1.630826 0.248694
Netherlands 0.276292 0.076337 2.222403 0.410832
Austria 0.336799 0.113434 2.075658 0.311159
United Kingdom 0.385677 0.148746 2.546668 0.241416
Average 0.342379 0.117223 2.057361 0.302699
GDP/capita
Germany 0.834709 0.696739 1,537.519594 0.001391
France 0.887829 0.788240 785.256534 0.000263
Netherlands 0.814426 0.663290 1,350.436364 0.002271
Austria 0.650987 0.423785 2,837.378533 0.030051
United Kingdom 0.131869 0.017390 1,320.337036 0.699128
Average 0.852825 0.727310 982.894320 0.000848
Source: Author´s.
Reg. koef. % HDP
0,464125
-0,303360
-0,494700
0,150089 0,170617
-0,047933
0,430700
-0,600000
-0,400000
-0,200000
0,000000
0,200000
0,400000
0,600000
Dánsko Estónsko Fínsko Šv édsko Nórsko Šv ajčiarsko Priemer
Dánsko
Estónsko
Fínsko
Šv édsko
Nórsko
Šv ajčiarsko
Priemer
Reg. koef. HDP/ob.
-431,374400
2357,440000
542,477465
-1335,331557-1079,168813
1948,048220
279,876233
-2000,000000
-1000,000000
0,000000
1000,000000
2000,000000
3000,000000
Dánsko Estónsko Fínsko Šv édsko Nórsko Šv ajčiarsko Priemer
Dánsko
Estónsko
Fínsko
Šv édsko
Nórsko
Šv ajčiarsko
Priemer
61
In the case of the relationship of % GDP growth in each country and the education structure,
results with low negative variability were obtained. The P indicator in all countries exceeded
the target value of 0.05 and thus cannot be incorporated into the % of GDP model as a dependent
variable. When examining the relationship of education and GDP per capita, the value of P in
one case was greater than 0.05, thus examining the relationship of these variables in the case of
the UK does not make sense. The coefficient with the highest value was achieved in the case of
Germany and Austria, where a 1% increase in the education structure of middle and university
educated population should increase GDP per capita by € 1,719 and € 1,664 respectively. The
smallest increase would occur in the case of France. In these countries, therefore, what is most
economically worthwhile is increasing the educational structure of the population. The average
value reached the sum of € 791.
Table 14 – Regression coefficient of relationship % of GDP to education and GDP / capita to
education in Western European countries
Reg. coef. % GDP Reg. coef. GDP/capita Value P % GDP Value P GDP/capita
Germany -0.141954 1,719.004177 0.835883 0.001391
France -0.209720 473.907371 0.248694 0.000263
Netherlands -0.364527 1,081.415231 0.410832 0.002271
Austria -0.507796 1,664.241164 0.311159 0.030051
United Kingdom -0.362898 -59.876514 0.241416 0.699128
Average -0.369526 791.200000 0.302699 0.000848
Source: Author´s.
The linear function for regression relationship between % GDP growth (country average) and
the educational structure has the form: ŷ = 29,44 - 0,369 * x. Given the high value of P this
model is ignored. In the case of the relationship of educational structure and GDP per capita,
the function has the form: ŷ = - 31,927.4 + 791.2 * x. In this model the P value achieved
0.000848 and is therefore taken into account.
Figure 4 – Values of regressive coeficients in Western European countries
Reg. koef. % HDP
-0,141954
-0,209720
-0,364527
-0,507796
-0,362898 -0,369526
-0,600000
-0,500000
-0,400000
-0,300000
-0,200000
-0,100000
0,000000
Nemecko Francúzsko Holandsko Rakúsko V.Británia PriemerNemecko
Francúzsko
Holandsko
Rakúsko
V.Británia
Priemer
62
Source: Author´s.
The previous figures present the values of regression coefficients for the Western European
countries. Germany achieved the highest value and France the lowest in the linear regression
model: education - GDP / capita.
6. SOUTHERN EUROPEAN COUNTRIES
The following tables present the results of regression analysis in the group of Southern
European countries. The highest values of reliability were recorded for Greece and Malta, while
the lowest mean error was recorded in Malta. The lowest reliability was found in the case of
Malta and Greece.
Table 15 – Basic parameters of regression analysis of Southern European countries -% GDP
growth and GDP / capita
% GDP
Multiplied by R Reliability value Mean error Significance
Greece 0.878613 0.771961 2.508337 0.000371
Spain 0.678294 0.460082 2.036928 0.021777
Italy 0.435948 0.190051 2.225121 0.180127
Malta 0.061396 0.003769 2.310016 0.857684
Average 0.714670 0.510753 1.824629 0.013457
GDP /capita
Greece 0.283033 0.080107 1,566.398527 0.399031
Spain 0.688328 0.473795 1,206.490889 0.019193
Italy 0.745749 0.556142 770.747945 0.008415
Malta 0.959045 0.919767 587.713127 0.000003
Average 0.670303 0.449307 951.355314 0.024005
Source: Author´s.
The P indicator in two countries, Italy and Malta, exceeded the target value of 0.05 and thus
cannot be incorporated into the % of GDP model as a dependent variable. When examining the
relationship of education and GDP per capita, the value of P in one case was greater than 0.05,
thus examining the relationship of these variables in Greece does not make sense. The
coefficient with the highest value was achieved in the case of Spain and Malta, where a 1%
increase in the education structure of middle and university educated population should increase
GDP per capita by € 292. On average, the value of these countries was well below the EU
average. In the case of Greece, the regression coefficient relationship of education structure and
GDP per capita achieved a negative value.
Reg. koef. HDP/ob.
1719,004177
473,907371
1081,415231
1664,241164
791,200000
-59,876514
-500,000000
0,000000
500,000000
1000,000000
1500,000000
2000,000000
Nemecko Francúzsko Holandsko Rakúsko V.Británia Priemer
Nemecko
Francúzsko
Holandsko
Rakúsko
V.Británia
Priemer
63
Table 16 – Regression coefficient of relationship % of GDP to education and GDP / capita to
education in Southern European countries
Reg. coef. % GDP Reg. coef. GDP/capita Value P % GDP Value P GDP/capita
Greece -1.311610 -131.369829 0.000371 0.399031
Spain -0.481162 292.957020 0.021777 0.019193
Italy -0.278291 222.752677 0.180127 0.008415
Malta 0.020909 292.807433 0.857684 0.000003
Average -0.416805 192.121659 0.013457 0.024005
Source: Author´s.
The linear function for regression relationship between % GDP growth (country average) and
the educational structure has the form: ŷ = 20,93 - 0,416 * x. Given a suitable value of P this
model is taken into account. In the case of the relationship of educational structure and GDP
per capita, the function has the form: ŷ = 1,2991.59 + 192.12 * x. In this model the P value
achieved 0.024005 and is therefore taken into account.
Figure 5 – Values of regressive coeficients in Southern European countries
Source: Author´s.
The previous figures present the values of regression coefficients for Southern European
countries. The highest value in the linear regression model: education - GDP / capita was
achieved by Spain and Italy the lowest. In the case of Greece, it was of a negative value, but
due to the low P value we did not take this model into account.
Reg. koef. % HDP
-1,311610
-0,481162
-0,278291
0,020909
-0,416805
-1,400000
-1,200000
-1,000000
-0,800000
-0,600000
-0,400000
-0,200000
0,000000
0,200000
Grécko Španielsko Taliansko Malta Priemer Grécko
Španielsko
Taliansko
Malta
Priemer
Reg. koef. HDP/ob.
-131,369829
292,957020
222,752677
292,807433
192,121659
-200,000000
-100,000000
0,000000
100,000000
200,000000
300,000000
400,000000
Grécko Španielsko Taliansko Malta Priemer
Grécko
Španielsko
Taliansko
Malta
Priemer
64
CONCLUSION
The aim of this article was to quantitatively analyse and confirm the existence of a relationship
between direct and indirect dependence of educational structure and selected indicators of
economic performance. The object of the quantitative analysis was the Slovak Republic and
selected EU countries. In line with the aims of the study and formulated research presumption
the subject of the research was defined, namely the correlation between educational structure
and selected indicators of economic performance. The countries were grouped on certain
homogeneous groups in which we expected common features such as: approximately similar
spending on education, comparable performance of the economy as well as comparable
educational structure of the population.
The complexity of the object of study in the field of the world economy presupposed a high
degree of abstraction in the research of secondary nature. The secondary collection of
information from available statistics, regional Statistical Office databases and the databases of
Eurostat has been implemented through constructive methods of scientific observation. The
information obtained was processed and evaluated by means of statistical methods with
emphasis on correlation and regression analysis. The research sample was 19 EU countries. The
selection we made according to the complexity of the data over the entire time period. The
essential factors from among which we investigated dependence is the proportion of the
population having completed secondary and higher education expressed in %. The illustrated
figures presented independent variables. Dependent variables were the rate of growth in GDP
and GDP per capita expressed in €.
When examining the impact of variables, most authors use the method of correlation and
regression analysis to confirm or refute any contrary effect of the independent variable, in our
case education. Which is why we also chose this method of measurement. It is important to
note that the calculation is based on using the Ordinary least squares method, therefore it was
necessary to observe the rules of this method.
The key methods of scientific investigation were: classification analysis, comparison and
abstraction in the development of theoretical and methodological framework in the solving of
problems; methods of quantitative analysis using statistical methods of processing and
evaluation of information and methods of synthesis and partial induction in drawing research
conclusions.
A very strong linear relationship was demonstrated in many countries through correlation
analysis. Hungary, Slovakia, Poland and Malta were among those countries with the highest.
The survey showed that there is a dependence (taking into account a certain degree of
abstraction) between the educational structure of the population and performance of the
economy in terms of GDP growth rate and GDP per capita. However, the results showed that
the positive effects of education were suppressed by significant influences such as the global
economic crisis. Since 2008, the impact of education on economic growth weakened or had no
significant impact.
Since the correlation results were not always clear, we then conducted a regression analysis that
in some cases confirmed while in others refuted the results of correlation analysis. The highest
level of confidence in the V4 countries was recorded for the Czech Republic in GDP growth,
whereas in the case of GDP per capita, the reliability value was the highest. In the case of the
relationship of % GDP growth in each country and education structure, the results obtained
showed high variability. In the cases of Czech Republic and Hungary this relationship was
confirmed. The highest coefficient value achieved was in the case of Slovakia, where a 1%
increase in the education structure of middle and university educated population should increase
GDP per capita by € 1,484.96. The smallest increase would occur in the case of Hungary.
65
In the case of the Nordic countries, Denmark and Switzerland achieved the highest reliability
value while Norway and Finland achieved the lowest mean error value. The lowest reliability
value was found for Estonia. When examining the relationship of education and GDP per capita,
the value of P in four cases was less than 0.05, thus examining the relationship of these variables
in Estonia, Finland, Norway and Switzerland makes sense. The highest coefficient value
achieved was in the case of Estonia, where a 1% increase in the education structure of middle
and university educated population should increase GDP per capita by € 2,357.44. The smallest
growth would occur in the case of Finland. In the case of Norway, the coefficient reached a
negative value which means that in the event of an increase in educational structure there should
eventually be a decline in the absolute level of GDP per capita. In practice, this may lead to a
development in an oversaturation on the labour market of university graduates and a reduction
in labour costs due to the high supply of a highly skilled workforce.
The highest values of reliability in Western countries were recorded in the cases of the UK and
France; the lowest mean error value was recorded in France. The lowest reliability was observed
for Germany and the UK (GDP / capita). When examining the relationship of education and
GDP per capita, the value of P in one case was greater than 0.05, thus examining the relationship
of these variables in the UK does not make sense. The highest coefficient value was achieved
in the cases of Germany and Austria, where a 1% increase in the education structure of middle
and university educated population should increase GDP per capita by € 1,719 and € 1,664
respectively. The smallest increase would occur in the case of France. In these countries,
therefore, what is most economically worthwhile is increasing the educational structure of the
population. The average value reached the sum of € 791.
The highest values of reliability in the Southern European countries were recorded in Greece
and Malta, while the lowest mean error value was recorded in Malta. The lowest reliability
value was found in the cases of Malta and Greece. When examining the relationship of
education and GDP per capita, the value of P in one case was greater than 0.05, thus examining
the relationship of these variables in Greece does not make sense. The coefficient with the
highest value was achieved in the case of Spain and Malta, where a 1% increase in the education
structure of middle and university educated population should increase GDP per capita by €
292. On average, the value of these countries was well below the EU average. In the case of
Greece, the regression coefficient relationship of education structure and GDP per capita
achieved a negative value.
Acknowledgements
The article is co-financed by the project VEGA 1/0405/15.
Publication of the declaration
No conflicts of interest between the authors are likely to occur within the present study.
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Contact information
Ing. Zuzana Hirková, PhD.
Faculty of Economics, Matej Bel University
Tajovského 10, 975 90 Banska Bystrica, Slovakia
prof. Ing. Helena Kuvíková, PhD.
Faculty of Economics, Matej Bel University
68
Tajovského 10, 975 90 Banska Bystrica, Slovakia
doc. Ing. Jana Štrangfeldová, PhD.
Faculty of Economics, Matej Bel University
Tajovského 10, 975 90 Banska Bystrica, Slovakia
doc. Štefan Hronec, PhD.
Faculty of Economics, Matej Bel University
Tajovského 10, 975 90 Banska Bystrica, Slovakia
Ing. Nikola Štefanišinová
Faculty of Economics, Matej Bel University
Tajovského 10, 975 90 Banska Bystrica, Slovakia
69
COMMON PROVISION OF LOCAL PUBLIC SERVICES BY INTER-
MUNICIPAL COOPERATION AS A TOOL OF EFFICIENT
MANAGEMENT
Marek Jetmar
Abstract
The issue of public debate and government policy in the Czech Republic is to increase the
efficiency of the public sector. The article focuses on the potential for inter-municipal
cooperation as a mechanism for efficient provision of public services at the municipal level. It
is highlighted a possibility of ensuring joint funding of internal support services in addition to
the common provision of selected public services al local level.
Keywords: public services, communities and municipalities, inter-municipal cooperation, fund-
ing of municipalities
JEL Classification: H2, H7
INTRODUCTION AND POLITICAL FRAMEWORK
The issue of ensuring efficient public administration and public services (Peková, J., 2011) from
the point of view of public finances (Maaytová, A., Hamerníková, B. et al., 2010) is discussed
extensively among professionals and academic community. It became the object of interest of
government policy too. In accordance with Czech Government Resolution No. 680 of 27
August 2014 and subsequently Czech Government Resolution No. 21 dated January 14, 2015
was approved basic conceptual document for the purpose of modernization and development
of public administration - STRATEGIC FRAMEWORK FOR THE DEVELOPMENT OF
PUBLIC ADMINISTRATION OF THE CZECH REPUBLIC FOR THE PERIOD 2014-2020.
The document stresses the need to improve the quality, effectiveness and transparency of public
administration in its global objectives. Specific Objective 1.3 - Extension of quality methods in
public administration covers the systemic measures framing application of methods such as
Common Assessment Framework (CAF), benchmarking or bench learning, Balanced Scorecard
(Ochrana, F., Půček, M., 2012), Local Agenda 21, etc. Another supported priority is extension
of cooperation between municipalities.
This strategy also opened a debate on the appropriate form and method of funding the activities
of common interest at local level. This contains an agenda which is associated with the primary
function of communities and municipalities (independent competence), but potentially also
delegated powers. It deals with the level of public service provision (ie municipal,
supramunicipal/ microregional, regional) and how to ensure their funding (Peková, J., Pilný, J.,
Jetmar, M., 2012). This article is a contribution to this debate and focuses on communities
preferences in joint funding.
70
1. REASONS FOR COOPERATION AMONG MUNICIPALITIES
1.1 Settlement structure, number of municipalities and efficiency
International experience has shown that administration units with a population less than 5,000
face difficulties when coping with conditions and duties resulting from legal regulations. There
are many small communities and municipalities in the Czech Republic which confirms the
above information.
Some European countries (Germany, specifically the federal states Saxony and, earlier, also
Bavaria, the Netherlands or Denmark, for instance) decided to merge municipalities. Such a
merging means the establishment of a new municipality, provided that all the powers of the two
or more original municipalities are transferred to the new one. This will be achieved either
through the merging of several municipalities or by the attachment of a municipality to another
one (usually a bigger one to a smaller one). Such merger may be voluntary or forced. In both
cases, the legality (adherence to the constitution) of the solution and the motivation of
municipalities (primarily financial motivation) plays a principal role.
A high number of municipalities and the high level of fragmentation of the performance of
public administration may be actually seen as a problem from the economic, organizational and
performance quality point of view. On the other hand, this fragmentation also has its positives.
This character of public administration is al-ready a matter of history on the territory (responds
to a historically shaped settlement structure), and the stability of the system is its great
advantage. This is also connected with the knowledge of the local situation, which is important
for a number of municipalities' agendas (eg. social affairs, education and regional
development). Other positive aspects to be mentioned include a significantly higher level of
local democracy or the enhanced possibility of democratic participation in the administration
of public affairs, the proximity of the regional self-governing administration to the citizens and
the resulting higher potential of interest of people in local affairs and municipality development
and consequently the higher level of public control.
Foreign experience shows that voluntary cooperation through the sharing of power in a separate
agendas can receive savings while maintain the independence of individual municipalities. In
this context is possible to refer to the experience of France and various German federal states
(Länders) (Calza, P., 2014 Schnabel, F., 2014). Inter-municipal cooperation, supported by
government, led to increase of efficiency and economy provision of local public services and
ultimately resulted into decentralization of decision from national and regional to supra-
municipal level.
Due to the fragmentation of the settlement structure and the large number of communities (6258
in 2016), the Czech Republic has gone through two different ways of effectively ensuring local
public administration performance. 1) As part of the so-called delegated competence, it
concentrates its performance on the level of 205 municipalities of the so-called third type
(municipalities with extended competence), and then retains a minor importance in the
municipalities with a delegated municipal authority (municipalities of the second type). The
performance of state administration by the remaining municipalities is marginal. 2) In the field
of autonomous competence, the aim is to develop inter-municipal cooperation.
In addition to the above arguments, the decision to follow this trend is based on the fears of
representatives of small municipalities that they would lose their local identity (the
identification of inhabitants with the municipality is the strongest among all geographic units
in the Czech Republic) and the weakening of the influence on local decision-making. As the
decision-making powers are not fully delegated to another entity, municipalities will keep at
71
least some indirect control over decisions. Given the above, the inter-municipal cooperation
may be defined as any agreement between two or more municipalities or, as the case may be,
the jointly implemented and organized execution of services. Compared to municipality
mergers, this form is much less radical as it is focused on purely functional integration, free of
any intervention in the self-governing identity of the municipality.
1.2 Inter-municipal cooperation in the Czech Republic
A key element in the Czech environment is the voluntary nature of the cooperation system.
Generally, each municipality uses cooperation in its informal form on the local level.
Nevertheless, certain rules have to be set for its quality performance, in particular from the point
of view of public administration services.
The cooperation of municipalities is currently governed by the Act on Municipalities as a
voluntary association of municipalities. It is a public corporation (a legal entity of public sector
established in accordance with §§ 46, 49 and 50 of Act No. 128/2000 Coll., on Municipalities)
that may solely be composed of municipalities. A voluntary association of municipalities
(VAM) comes into effect upon its entry to the Register of Municipalities maintained by the
respective regional authority. According to the law, the foundation of such association is subject
to a municipal association foundation agreement, that has to be adopted by the council of each
of the member municipalities. An obligatory component necessary for the foundation of the
association is the statute that defines its organizational structure and describe the intended
activities. The activities of the association are fully dependent on the will of the member
municipalities that can invest the property if they wish to do so (however, they keep their title
to such property).
The subject-matter of the activities of the association may particularly include activities
entrusted to municipalities as self-governance (education, tourism, culture, transport services,
waste management, technical amenities of municipalities and others). The citizens of the
member municipalities have the right to participate in the meeting of the bodies of the
association, to submit written proposals and to comment the draft of budget. This ensures a
sufficient level of public participation.
2. OUTPUTS OF PROJECT SYSTEMIC SUPPORT THE DEVELOPMENT OF
COOPERATION BETWEEN MUNICIPALITIES
2.1 Purpose and objectives of the Project
The issue of the Project “Systemic support the development of cooperation between
municipalities in the Czech Republic within the area of districts of municipalities with extended
powers” (the Project), was to strengthen inter-municipal cooperation within the framework
defined by the public law (JETMAR, M., 2013). The purpose was to test the possibility of
cooperation in micro-regions defined by the administrative district of the third-class
municipality. The guarantor and project solver was Union of the Town and the Municipalities
of the Czech Republic. This Project implemented STRATEGIC FRAMEWORK FOR THE
DEVELOPMENT OF PUBLIC ADMINISTRATION OF THE CZECH REPUBLIC FOR THE
PERIOD 2014-2020 directly.
The Project involved 186 territories of 204 districts created by municipalities with extended
power. It represents more than 5,000 municipalities. During the course, there were implemented
72
several surveys mapping existing experience with municipal cooperation, with concurrent
adjustment, allowing the collection of examples of good practice. The Project was focused on
inter-municipal cooperation in the area of self-government only.
Map no. 1 – Districts involved in the Project
The Project was focused primarily on determination the potential of inter-municipal
cooperation in traditional areas. It is a sphere of basic and pre-school education, waste
management, social services etc., but municipalities as a subject of inter-municipal cooperation
also chosen security, business and employment, social entrepreneurship, tourism, transport
accessibility and services.
2.2 Shared services centers
One of the surprising outputs of the debate with the mayors of communities and small
municipalities was the demand for centers, which could together provide administrative
services for municipalities. These centers should help in solving problems of small
municipalities without inadequate personal and professional background – lack of capacity and
capability.
Number of municipalities require to create common environment where individual
municipalities could have easy access to administrative facilities according to their current
Participating districts
Non-participating districts
Non-supported area
(Prague)
73
needs. The joint provision of these services should contribute to bigger efficiency (are achieved
economies of scale and specialization) and ensure quality of services.
In reaction to these suggestions was organized a survey of mayors’ potential interest to provide
services in the form of a guided interview. The outputs of this interviews were recorded in the
standardized form (Recorder) to enable a creation of statistical analysis. The results were
identified following areas of services:
Legal support (preparation of contracts, legal opinions, municipal legislative action,
decision support of municipalities),
Economic Agenda (bookkeeping, accounting statements, tax issues, preparation of the
budget and budgetary changes, etc.),
Grant Management (preparation of projects co-funded from external sources),
Public Procurement,
IT support (enabling communication with other public institutions and other
government agencies, businesses and NGOs, internal systems for controlling the
operation of the municipality, the tools of strategic management),
Technical support and Construction (building agenda, investment preparation),
Community Development (including strategic planning also).
Followed by a question how these services will be provided, respectively, form and scope of
performance through shared service centers and ways of funding these services. There are a
number of options to ensure the provision of administrative services. At present, there are
situations where services are provided particularly by own staffs. If it is a voluntary activity of
municipalities and the municipality has limited funds (or small capacity) to provide them, they
do not have to offered, even in a situation where most people find it desirable.
Municipalities therefore seek ways to strengthen their own capacities (to obtain additional
resources or acquire experts). One of them is the transfer of the performance of services to
another municipality (under contract) or joint provision through a voluntary association of
municipalities. Some part of the activities can be solved by contract with private entity
(company or NGO).
Apart the availability, however, municipalities also solve the problem quality of local services.
Municipal executive bodies require to provide advice, expert guidance or supervision of their
activities. Demand is after training, sharing examples of good practice, innovations,
communicating news in the field etc.
For this reason, the Union of Towns of Municipalities carried out surveys among the
municipalities involved in the Project. Collection of information and format of the records have
been adjusted by using the same methodology.
74
Chart no. 1: The preferred method of providing the agendas
Source: Preliminary results of the survey, Association of Towns and Municipalities
The possibility of using VAM as a direct public service provider is reflected in all monitored
areas. In individual cases, however, the preference of using this mechanism differs. The chart
shows the greatest interest in joint provision of services in grant management and public
procurement. Contrary, individually and through own employees should be ensured economic
agenda.
What is regarding the extent of the service, there was determined preference for 1) a single
methodological support, 2) systematic methodological support, 3) continuous consultation on
individual cases. All these variants presupposes the existence capacity of municipalities and
ensuring comprehensive services. The 4th option assume complete providing by external entity
(private, public, VAM).
As illustrated in the following chart, the largest scope of the joint provision of services is
indicated in public procurement and grant management. In the first case it is the complexity and
opacity of these agendas for the management of small municipalities and a high risk of negative
impacts on the functioning of the municipality and its budget in the event of failure. The issue
of public procurement is very complex and confusing for municipalities. The prepared and
newly introduced law on public procurements (Act No.134/2016 Coll., on Public Procurement)
and the changes of other regulations have led to a number of municipalities being worsened.
Risk of failure of the municipality in the role of the contracting authority, complications in the
selection process, possibilities of appeal of the participants and legal actions was a reason why
representatives of municipalities tried to move the implementation of the process to private
entities, often legal firms.
The complexity of the agenda, but also problematic experiences with the services offered on a
commercial basis, can be identified as factors that lead municipalities to ensure a common
preference for grant management.
75
Chart no. 2: Preferences of extent (complexity) of services
Source: Preliminary results of the survey, Association of Towns and Municipalities
An approach to financing jointly provided services was also examined. Municipalities have
different payment setting preferences (per action, flat rate, combination). However, it is also
preferable to find solutions at national level (reimbursement of activities of shared services
centers by tax revenues, subsidies), or funding of these services directly by the state.
What is concerning legal services (including public procurement) and grant consulting/
management the municipalities favor payment for each completed transaction (the prices are
calculated by VAM or set by municipalities). However, if there were other sources of VAM
funding (as was mentioned above), they would certainly have preferred them.
CONCLUSION
The results of the Project showed that municipalities are interested in focusing on general
cooperation not only on the treatment of public services consumed directly by citizens but also
on the support and operation of local government as such.
The real possibility of joint provision of these services is influenced, among other things, by
existing legislation in force governing the forms of inter-municipal cooperation. The challenge
is to find a mechanism that would balance the interests of municipalities and towns within the
association and ensure its functionality.
There is also a need to adapt the status of the association so that it can, in agreement with the
participating communities and municipalities, bind citizens of members as it is set up in France,
Germany, Austria, etc. According to Fritz Schnabel: "Shared management is the most complex
manifestation of metropolitan cooperation, in the strongest form it allows the transfer of public
services ".
Although this is a very complicated problem, the solution would mean significant legislative
changes in the status of municipalities, voluntary associations of municipalities and public
finance settings. It is clear that, as in other countries with a similar settlement structure, the best
way to ensure high quality public services at local level is to support intensive cooperation
between municipalities.
76
References
1. Calzat, P. (2014). Vývoj meziobecní spolupráce v Německu. SBORNÍK MEZINÁRODNÍ
KONFERENCE K MEZIOBECNÍ SPOLUPRÁCI. Praha. SMO ČR. p.14-15. ISBN 978-
80-906042-0-9, http://www.obcesobe.cz/mezinarodni-konference/
2. Jetmar, M. Význam územního obvodu ORP pro regionální rozvoj a možnosti jeho využití
při společném řešení úkolů v samostatné působnosti obcí, XVI. mezinárodní kolokvium o
regionálních vědách. Sborník příspěvků, Valtice. Masarykova univerzita 2013. ISBN 978-
80-210-6257-3
3. Maaytová, A., Hamerníková, B. a kol. (2010). Veřejné finance, 2. aktualizované vydání,
Praha, Wolters Kluwer, ISBN 978-80-7357-497-0
4. Ochrana, F, Půček, M. (2012). Dosahování úspor a odstraňování plýtvání ve veřejné
správě. Praha, Wolters Kluwer, ISBN 978-80-7357-909-8
5. Peková, J. (2011) Finance územní samosprávy - teorie a praxe v ČR, Praha, Wolters
Kluwer, ISBN 978-80-7357-614-1
6. Peková, J., Pilný, J., Jetmar,M. (2012) Veřejný sektor - řízení a financování, Praha, Wolters
Kluwer, ISBN 978-80-7357-936-4
7. Schnabel, F. (2014). Vývoj meziobecní spolupráce v Německu. SBORNÍK
MEZINÁRODNÍ KONFERENCE K MEZIOBECNÍ SPOLUPRÁCI. Praha. SMO ČR.
p.11-13. ISBN 978-80-906042-0-9, http://www.obcesobe.cz/mezinarodni-konference/
Contact information
Ing. Marek Jetmar, Ph.D.
College of Regional Development and Banking Insitute – AMBIS
Nárožní 2600/9, Praha 158 00
77
ECONOMIC GEOGRAPHY AND FISCAL DECENTRALIZATION IN
THE EUROPEAN UNION
Ivana Mandysova
Abstract
Economic geography is determinant of fiscal decentralization. The main factors of fiscal
decentralization stated in the article are of special interest in the role of economic geography.
The geographical territories like European Union facing regional economic divergences will be
more decentralized in fiscal policy. Article uses specifications of economic geography to
examine the factors of fiscal decentralization and its effects of development factors which can
be GDP or institutional factors like sub-national expenditures, legislation, politics,
unemployment, safety or other social factors. We find positive effects of geographical factors
on fiscal decentralization. High levels of geographical disparities are significantly associated
with higher levels of fiscal decentralization.
Keywords: economic geography, fiscal decentralization, tax competition, European Union
JEL Classification: F15, R1, H3
INTRODUCTION
The current fiscal impact assessment theories do not incorporate location. The spatial pattern in
which an area develops will affect the government financial condition and the cost of public
services. Economic growth inside the core region has a significantly better fiscal effect than a
periphery region. Taxes on income and on capital are deemed to include all taxes, irrespective
of the manner in which they are levied, imposed on total income, on total capital, or on elements
of income or of capital, including taxes on gains from the disposal of movable or immovable
property, taxes on the amounts of wages or salaries paid by enterprises, as well as taxes on
capital appreciation.
1. THEORETICAL BACKGROUND
In new economic geography space is studied as an important subject. Early economists lacked
a model embracing both increasing returns and imperfect competition, the two basic ingredients
of the formation of the economic landscape. Agglomeration was introduced by Weber (1929)
though he is mainly known for his work on the location of the industrial firm. Our interests are
agglomerated cities and spatial distribution of industries among larger spatial regions or states,
as shown by the pioneering work of Isard (1956).
The general competitive equilibrium is the benchmark used by economists in order to study the
market properties of an economic issue. In the neoclassical theory of international trade the
space is not homogeneous and trade costs occur because the geographic variety of resources
distribution. For long time literature has been dominated by the competitive theories stating that
space is neglected, which is not what we see in reality. The competitive equilibrium exists in a
homogeneous spatial economy where no transportation can occur; hence, regions do not
specialize and agglomerations are not formed. Geographical integration and agglomeration of
economic activity with divergent incomes leads to mobile tax base and spatial tax competition.
78
Theoretical background on spatial tax competition with authors like Wilson (1999), Wildasin
(1988), predicts that competition among governments over geographical space lowers taxes and
public spending to suboptimal levels.
New economic geography introduces agglomeration forces linked to the increasing returns and
the trade cost of goods. This issue is pioneered by Krugman (1991). As there exist differences
in taxation, geographical integration may increase relocation of economic activities. Fujita,
Krugman and Venables, (1999) explain the formation of a large variety of economic activities
concentration in geographical sense. Krugman´s equilibrium of mobile factors results in
opposing forces concentrating and dispersing respectively. Firms try to minimize trade costs
and they prefer to concentrate in one single location. Firms prefer the spatial agglomeration of
activity into a „core“ regions rather than “periphery” regions. Pattern emerges when
governments have access to taxes level and public goods supply that impacts location of
economic activity. Like this there comes competition among governments using tax policies to
attract investment location. Firms focus on various factors in economies like agglomeration
economies. Growing geographical integration, growing agglomeration leads to decrease in tax
competition.
1.1 Tax competition with location effect
We consider tax competition when κ(τ)>λ, the labor-demand schedule is steeper than the human
resource supply schedule, and thus the only stable outcomes are the concentrated equilibrium
which produce a core–periphery pattern. This means that, in equilibrium, one country (the core)
will have all of the manufacturing workers and all of the tax revenue, while the other country
(the periphery) has no revenue and must import all of its manufactures.
The concentrated case also produces similar results in terms of the relationship between taxes
and trade costs in that reductions in the trade cost may increase taxes (or reduce subsidies).
Indeed, under certain assumptions, we show an even stronger result. If integration causes the
human resource demand schedule to become steeper, then it must increase taxes. Because of
agglomeration effects, the core region can impose a higher tax than the periphery.
We can solve this maximum tax differential by setting θ (0) = v (0) of spatial equilibrium by
setting three possibilities, where (t2−t1) is tax differential. This yields the following three
possibilities:
there is a unique location equilibrium concentrated in country 1.
there is a unique location equilibrium concentrated in country 2.
concentration in either country is a location equilibrium.
Now we have determined what location equilibrium can arise from different tax rates. (Ludema,
2000). Domestic sales generate more revenue than foreign sales on average. At constant goods’
If t2−t1≥κ(τ)−λ, (1)
If t1−t2≥κ(τ)−λ, (2)
If ∣t1−t2∣<κ(τ)−λ, (3)
79
prices, a country’s manufacturing wage increases as workers immigrate, because immigration
increases the country’s domestic market size and decreases the size of the foreign
market. Krugman (1993b) has defined the ‘home market effect.’ However, if we allow prices
to change, there emerges another, possibly countervailing, effect. As workers immigrate,
existing domestic firms will face more competitors in their domestic market and fewer in the
foreign market. The domestic price must fall and the foreign price must rise. The impact of this
‘competition effect’ (to continue using Krugman’s terminology) on domestic wages depends
on the relative market sizes, but for equal market sizes the effect is negative.
If λ>κ(τ), human resource supply is steeper than human resource demand, then there is
generically a unique equilibrium, with manufacturing production diversified across countries.
If λ<κ(τ), human resource demand is the steeper of the two, and there will typically be two
stable equilibrium, with production concentrated in either one country or the other.
1.2 Location and agglomeration economies
The location of industry is determined by the complex interaction of many factors. Model of
geography based on Krugman (1991) exhibits the agglomerative forces described earlier and
produces a relationship between the after-tax real profit and the allocation of human resources
across the geographical space, which we call the human resource-demand schedule. Krugman
(1993a) says that tax competition can be globally beneficial for high trade barriers and
detrimental otherwise. Agglomeration economies push firm to concentrate its production in one
location. Firms accept to bear a higher tax rate in order to benefit from agglomeration
economies and from local public goods.
Human resources concentrate in a core region and agglomerative incentives or human resources
mobility incentives only make them stay where they are. Integration makes human resources
more responsive to tax differentials only when agglomerative forces are too weak or human
resources are insufficiently mobile, the core-periphery pattern as an equilibrium cannot emerge.
As a result, economic integration may reduce the intensity for tax competition.
Human resources as well as consumers tend to concentrate, like this. Krugman specifies “core”
and “periphery” and “backward” and “forward” linkages. He remarks that there are immobile
agricultural factors left behind in periphery. Economic activities want to be close to consumers
or cooperating firms to satisfy a large demand, while consumers tend to be close to producers
to benefit from more variable production without sustaining transport costs. Krugman
demonstrates cumulativity of agglomeration process depending on the values of transport costs,
on the magnitude of the preference for diversified goods and on the share of the monopolistic
competition sector. Capital mobility is not the only factor impacting tax competition on tax
rates. Trade unification and agglomeration impact location of economic activities but also tax
rate equilibrium, when governments engage in tax competition.
Firms take advantage of international differences in taxation. In these terms they choose optimal
solutions. Economic geographers find it suitable to employ existing location theory and pay
attention to environmental stimulus and behavioral response. Existing location theory is
preoccupied with profit maximization or transport costs minimization. This provides only weak
insight into economic geography. Location of firms is the product of both economic and
noneconomic forces. Such theory takes into account non-optimal behavior, imperfect
knowledge and other variables.
About the only case in which economic integration intensifies tax competition is that when
production is diversified and integration takes the form of increased factor mobility. Most of
the literature on tax competition is focused around the case in which one factor, usually capital,
80
is perfectly mobile. By broadening the scope to include core–periphery equilibrium or to
examine trade liberalization, it becomes more typical to observe a reduction in the intensity of
tax competition.
Capital as mobile factor would eliminate the home-market effect. As the home market effect is
one of the agglomerative forces, its absence would make concentrated equilibrium less likely,
and the diversified case would become the norm. However, there would be no change in the
relationship between taxes and trade costs in either case.
When the integration takes the form of a reduction in trade costs, this result holds across of
equilibrium. If human resources are quite immobile, then the agglomerative forces may be
insufficient to produce a core–periphery pattern. Nevertheless, the presence of those forces in
the background produces a U-shaped relationship between taxes and trade costs. The other case
is where agglomerative forces are sufficient to produce core–periphery pattern. In that case, the
negative relationship between taxes and trade costs is even more robust. Fujita and Krugman
(2000) have both argued that geography models are less applicable to multi-country regions
like the European Union than to multiregional countries like the United States, because of the
difference in labor mobility.
2. TAXATION AND FISCAL DECENTRALIZATION IN THE EUROPEAN UNION
Mutual assistance by member states in the field of direct taxation to combat international tax
evasion and avoidance the European Union is strengthening collaboration between the member
states' tax administrations and facilitate the exchange of information which appears relevant for
the correct assessment of taxes on income and on capital. Council Directive 77/799/EEC of 19
December 1977 concerns mutual assistance by the competent authorities of the member states
in the field of direct taxation.
Under this Directive, member states' competent authorities are required to exchange any
information which appears relevant for the correct assessment of taxes on income and on capital
and the assessment of indirect taxes:
value added tax;
excise duty on alcohol and alcoholic beverages:
excise duty on manufactured tobacco.
The integration process in Europe makes it ideal for demonstration of the core periphery model.
There is a systematic policy aimed at improving integration of national markets, dropping of
tariff barriers and reducing of nontariff barriers, trade costs have dramatically decreased inside
the European Single market. Recent empirical works seem to confirm the basic result of the
core – periphery theory. Increase in the geographical concentration of industrial sectors between
eighties and nineties is visible and from 1968 to 1990, when there were observed both an
increase in the geographical concentration of economic activities across European region and,
for a vast majority of sectors, an agglomeration tendency. Cumulative causation appears in the
sense that agglomeration of production and agglomeration of expenditure influence each other.
The most important determinant in the European geography is the location and size of demand.
81
3. ASSESSMENT OF FISCAL POLICY COORDINATION AND TAX
COMPETITION IN THE EUROPEAN UNION
Fiscal rules may be necessary to correct macroeconomic spillovers. It occurs when public debt
accumulation may exert an upward effect on the long term interest rates. Short term interest
rates are touched when monetary policy aims at inflation stabilization and fiscal policy impacts
price level. In this case national fiscal policy may fail taking this into consideration. Hence,
long term interest rates tend to grow and fiscal policy needs amendments. There is no reason to
focus on the excessive deficit-interest rate possibility only. Other possibilities of
interdependence through goods market linkages, the common exchange rate and the common
payment balance, or the average inflation rate, can be of significance. It is important to
introduce a rule that prevents excessive public deficits and gets government into debts.
Maastricht convergence criteria explicitly spell out that Eurozone members as well as other
countries that intend to accept Euro in future, should not expect any form of bail out. Any
default on public debt by the state could constrain the policy of the European central bank. If
there is a risk of financial crisis, the central bank could be forced to refrain from raising interest
rates. In the Eurozone members there is no automatic control of the risk of fiscal profligacy.
Governments tend to do populist rhetoric and run excessive public deficits. There comes the
threat of political failure and currency crises or inefficiency of fiscal reflation. This emphasizes
the threat to monetary stability that European Central Bank aims to.
We come to result that economic integration reduces trade costs as well as tax competition. Tax
competition gives governments chance to change their taxation system and competition can be
viewed on tax rates when government decides to change tax rates in order to attract investments.
There is a trend of providing tax exemptions, tax deductions from tax base, etc.
The importance of fiscal harmonization in the European Union has been growing.
Macroeconomic considerations relate to monetary union, the microeconomic case for
harmonization has also been discussed. Economic integration increases regional disparities, this
suggests that tax competition across European Union is obvious process and further
harmonization will be called for in the future.
European Union member states as independent national bodies have responsibility of fiscal
policy coordination. It is the responsibility of member states to organize their fiscal relations
across different levels and sectors of government so as to ensure that they can meet the
budgetary requirements set down in the Maastricht Treaty. (Provazníková, 2003) On the other
hand there exist European legislation requirements imposed on states like Maastricht
convergence criteria or Stability and Growth Pact and budgetary commitments given by central
institutions.
Economic integration may reduce the intensity of tax competition, which means that future
fiscal policy must search for the balance and fiscal harmonization. Tax competition will
continue and cannot be abolished but it should not obstruct the Single market and economic
development of European Union as whole. Tax lowering in order to coordinate can be risky and
unbalancing at the level of national budgets. Transparency in fiscal sphere and less distortion
for the economy to function fluently under open and fair competition are required.
Fiscal policy viewed from point of political economy results at political failure excessive
government debts. It should be addressed through common rules rather than reforming national
institutions. This failure can be partly corrected through European disciplines when
governments behave in less responsible manner. In Eurozone the main reason for fiscal
discipline is that excessive borrowing accumulation with negative consequences on other
member states must be avoided.
82
The significance of moral hazard raised preparing Maastricht criteria and emphasizing debt
sustainability issues. As the matter of fact debt ratio of member states has exceeded 100 % of
GDP in the nineties, debt had to be put aside as a practical criterion to assess the ability of
member states to participate in Eurozone. Consequently, the Stability and Growth pact
overlooks the debt criterion and fiscal discipline has so far been emphasized on the side of
deficit rather on the side of indebtedness.
CONCLUSION
The article amends current theoretical background on fiscal decentralization by considering a
very important measure that aims to capture geographical divergences and agglomeration
factors. Economic geography matters in development progress and strong correlation between
geographical factors and fiscal decentralization could be used for correcting future research
where fiscal decentralization uses geographic divergences measures as an instrument of fiscal
decentralization. The use of economic geography as a measure for decentralization is limited to
estimation models as they do not include time changes. (Pacione, 2001)
Economic geography and concentration of economic activities causing decrease of
agglomerative forces such as reduction of trade costs, intensifies tax competition which may
lead to lower equilibrium taxes. Whereas stronger agglomeration and economic integration
increases tax competition which means higher equilibrium taxes.
Economic integration is likely to be a politically charged issue where taxation on factors is used
by local government to produce a local public good. Production of the public good constitutes
a new agglomeration forces and governments with more mobile factors produce more public
goods and attract more mobile factors.
Trade barrier reductions are focus of the economic integration efforts of governments as well
as other policies that can influence location of economic activities, such as public goods
provision, subsidies, entrepreneurial support, administration reduction, etc. Here we come to
competition among national governments public policies competing to attract the location of
economic activity.
The theories on tax competition do not deal with economic geography taking in consideration
integration in economic sphere. Investments are mobile and are distributed across the countries.
Foreign direct investments tend to pay domestic corporate tax so this issue is not so acute for
them. Capital investments are responsive to tax incentives, and integration intensifies tax
competition. Tax system is given at the outset and does not go through optimalization process
of the government.
Government inside integrated regions gets incentives to exchange information about foreign
investment with each other. This issue is important especially when designing the optimal
generally accepted tax system.
Integration means firstly reducing of trade costs and secondly increases human resource
mobility. Like this human resources react actively to tax differentials between the two regions.
Responsiveness of human resources to tax system is visible only when their mobility is
insufficient or agglomerative incentives are low. The reason has to do with consumer price
effect of emigration, as human resource – people can leave a region due to a tax increase, for
example, domestic production in the region falls, foreign production rises, and domestic
consumers become more reliant on imports which raise the domestic consumer prices.
Researchers should incorporate a geographic approach to better estimate fiscal impact. It
depends on many different factors. A geographic approach is necessary to identify
83
developments that can be classified as fiscally undesirable. Geographic criteria for periphery
include low density and fragmentation of developments. To promote economic development
while avoiding periphery use patterns, planners should emphasize infill development. Without
examining the underlying geography, an analyst would not be able to identify the extent to
which taxation is affected by agglomeration.
References:
1. Directive 77/799/EEC of 19 December 1977 concerning mutual assistance by the competent
authorities of the Member States in the field of direct taxation and taxation of insurance
premiums at http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=LEGISSUM:l33029
2. Fujita, M., & Krugman, P. (2000). A Monopolistic Competition Model of Urban Systems
and Trade. In Economics of Cities. Theoretical Perspectives, edited by Thisse J. F., Huriot
J. M., 167–216. Cambridge: Cambridge University Press.
doi/abs/10.1177/0160017612456399
3. Fujita, M., Krugman P., & Venables A. J. (1999). The Spatial Economy. Cities, Regions,
and International Trade. Cambridge, MA: The M.I.T. Press.
4. Isard, W., (1956). Methods of regional analysis: an introduction to regional science.
Cambridge: The M.I.T. Press.
5. Krugman P. (1991). Increasing Returns and Economic Geography. Journal of Political
Economy 99:483–99. /doi/abs/10.1086/261763
6. Krugman P. (1993a). On the Number and Location of Cities. European Economic Review
37, 293–298. doi/10.1111/j.1467-9396
7. Krugman P. (1993b). First Nature, Second Nature, and Metropolitan Location. Journal of
Regional Science. 33, 129–44. doi/abs/10.1080/0042098993231
8. Ludema, R. D., & Wooton, I. (2000). Economic Geography And The Fiscal Effects Of
Regional Integration. Journal of International Economics, 52, 331-357. 10.1016/S0022-
1996(99)00050-1 9. Pacione, M., (2001). Geography and public finance: planning for fiscal equity in a
metropolitan region. Progress in planning. 56, 1-59. 10.1016/S0305-9006(01)00011-3
Provaznikova, R. (2003). Fiscal decentralization in the EU and its interaction with EU´s
fiscal rules. Scientific Papers of University of Pardubice, Series D, 8.
10. Weber, A., (1929). Theory of Industrial Location. Chicago: University of Chicago Press.
11. Wildasin, D., (1988). Nash equilibria in models of fiscal competition. Journal of Public
Economics, 52, 331-357. 0.1007/s10797-008-9093-9
12. Wilson, J., (1999). Theories of tax competition, National Tax Journal, 52, 269-304. doi
1023/A:1023381705984
Contact information
Ivana Mandysova, Ph.D.
University of Pardubice, Faculty of Economics and Administration
Studentská 84, Pardubice
84
PUBLIC-PRIVATE PARTNERSHIP PROJECTS IN TRANSPORT
INFRASTRUCTURE IN THE SLOVAK REPUBLIC – OPPORTUNITIES
AND THREATS
Beata Mikusova Merickova, Nikoleta Muthova, Marian Holubek
Abstract
The public-private partnerships became part of the life of modern economics as the tool which
enables the state to carry their competences in a time that is ambitious to increase public need
and decrease public expenditure. The goal of our paper is to present a qualitative analysis of
public private partnership public-private partnerships projects in transport infrastructure in
Slovakia and demonstrate possible opportunities and threats of PPP projects in Slovak Republic
conditions. Study uses a qualitative approach to investigate the research question and analyzes
the secondary collected survey data from realised/prepared public-private partnerships projects
in transport infrastructure in Slovak Republic. The analysis does not allow drawing normative
conclusions about the desirability of PPP as a procurement method as it does not quantify PPP
impact on life-cycle costs and benefits of transport infrastructure projects. However, analysis
outcomes demonstrate mainly the possible threats of PPP projects in Slovak Republic in
legislative regulation and transparency of public procurement.
Keywords: Public-private partnership projects, Transport infrastructure, Slovak Republic
JEL Classification: H54, R42, R53
INTRODUCTION
The issue of the relations between the ownership form of an organisation and its performance
was investigated by many authors (Cullis & Jones, 1992; Knapp & Missiakoulis, 1982; Kay &
Thompson, 1986; Stiglitz, 1997; Weisbrod, 1988; Yarrow & Jasinski, 1996). Their studies had
theoretical, empirical or mixed character and their results suggested that no simple and clear
answers existed—for example, Cullis and Jones (1992, p. 169) stated that not the ownership,
but the level of competitiveness was the most important determinant of performance. The works
by Cullis and Jones (1992, 1992) are crucial for the theories of privatisation in the public sector.
According to them, privatization in the public sector shall be assessed only by complex methods
and it shall fully respect all specific conditions, determining the performance of economic
bodies in the public sector conditions. According to them, any change of public sector delivery
form and public infrastructure project implementation arrangement (ownerships, financing
sources) improving efficiency and effectiveness can be understood as privatization in the public
sector. And the most important, any decision on change of public service delivery and public
infrastructure project implementation arrangements shall be based on careful evaluation of
concrete socio-economic conditions and not on the base of subjective ideas and wants and done
on the case by case principle (Grafenauer & Klarič, 2011).
Considering this fact the design of an efficient PPP project depends crucially on the basic
underlying economic environment in which it operates. Therefore, it would be inappropriate to
prescribe a model arrangement between the public entity and the private entity in a PPP project.
However, there is a widespread consensus among economists (Grossman and Hart, 1986; Hart
and Moore, 1990; and Hart, 1995), that transparency is crucial in the case of PPPs.
85
PPP projects come under a variety of forms. The most common forms are some variant or
another of design-build-finance-operate (DBFO), in which a concessionaire from the private
sector designs, builds, and finances a certain facility (e.g., an airport) and then operates it as
well, or build-operate-transfer (BOT), in which a concessionaire finances and builds a
facility,operates it, and transfers it to the government at the end of the concession period. The
build-operate (BO) combination features in all of these arrangements.
Public infrastructure projects in the form of public-private partnerships are a legal, economic
and personnel-intensive process. Recent international evaluations of experience with public
private partnership (Lane 2000; Grafenauer & Klarič, 2011, Hood et al. 2004; Pollitt and
Bouckaert 2000) indicate that the conditions for a successful realization of this partnership have
to be created: an appropriate legal environment for public-private partnership development,
citizen participation in a transparent public decision-making process, measuring performance
in the public sector, a modern form of public service delivery and public infrastructure project
management, functional market mechanism. If these condition are met the change of traditional
public procurement form to public private partnership in public infrastructure projects should
improve efficiency and effectiveness.
The goal of our paper is to present a qualitative analysis of public private partnership public-
private partnerships projects in transport infrastructure in Slovakia and demonstrate possible
opportunities and threats of PPP projects in Slovak Republic conditions.
1. RESULTS AND DISCUSSION
In 2006, the government of the Slovak Republic undertook in its programme statement that "...
it will determine the rules and actively support the creation of public-private partnerships in the
field of management and public goods creation and provision of public services" (Programme
Statement of the government of the Slovak Republic, 2006, p. 9). Although this general
statement covers a broad framework for the use of PPP projects in various areas of public
infrastructure, transport infrastructure is dominant. One of the main priorities of the Slovak
Republic government is "... acceleration of the pace of construction and modernization of the
transport infrastructure in order to link the above-mentioned transport infrastructure to the
Trans-European Transport Network and to improve the accessibility of all regions of Slovakia
to the above-mentioned transport infrastructure" (Programme Statement of the government of
the Slovak Republic, 2006, p. 14). On the basis of the programme declaration, the government
of the Slovak Republic, # 704 from 2007 approved this objective albeit that some selected
sections of this infrastructure would be implemented in the form of PPPs. For the
implementation of road transport infrastructure in the form of PPP projects, parts of the D1
motorway and the R1 dual carriageway, to a total length of approximately 150 km, were to be,
from a transport, technical, geographic and financial point of view, divided into three packages
- see Table 1. In addition to these three packages, the government of the Slovak Republic by
resolution # 22 (2514 KOP) from 2015 decided to launch a public procurement process for the
concessionaire of the public-private partnership project concerning the D4 motorway (Jarovce
- Rača) and R7 dual carriageway (Bratislava Prievoz - Holice) (Table 1).
86
Table 1 - PPP packages # 1 – 3 and the Bratislava by-pass
Package # 1 – D1
motorway (Dubná
Skala – Ivachnová,
D1 Jánovce –
Jablonov, D1
Fričovce – Svinia)
Package # 2 – R1 dual
carriageway (Nitra západ –
Selenec, Selenec – Beladice,
Beladice – Tekovské Nemce,
Banská Bystrica northern by-
pass)
Package # 3 – D1
motorway (Hričovské
Podhradie – Dubná
Skala)
Bratislava by-pass -
realization of
sections of the D4
motorway Jarovce –
Rača and R7 dual
carriageway
Bratislava Prievoz –
Holice
Total length (km) 75 52 29 59
Investment value of
the project (mld. €
excl. VAT)
2.39 0.903 1.99 0.997
Total amount paid to
the concessionaire
for a period of 30
years (mld. € excl.
VAT)
approx. 6.6 3.465 approx. 4 approx. 1.7
Date and publication
number of the
concessionaire notice
in the EU Journal
17.11.07 19.12.07 28.4.08 30.1.2015
(#. 2007/S 223-
271152) (#. 2007/S 244-297131) (#. 2008/S 80-108302)
(#. 2015/S 021 –
033433)
Offer deadline /
number of candidates 30.1.2009/2 12. 11. 2008/4 11.05.2009/1 27.03.2015/9
Winning consortium Bouygues Travaux
Publics SA
Vinci Concessions a ABN
Amro Highway
Hochtief PPP Solutions
GmbH
Cintra
Infraestructuras S.A.
The date of
conclusion of the
concessionaire
contract
15.4.2009 23.3.2009 21.1.2010 20.5.2016
Concessionaire Slovenské diaľnice
a.s. GRANVIA, a. s.
Žilinská diaľnica, s. r.
o.
Zero By-pass
Limited "Obchvat
nula"
Type of concession /
duration (years) DBFO(M)/30 DBFO(M)/30 DBFO(M)/30 DBFO(M)/30
Deadline for
financial closure plan - 15. Apríl 2010 27.8.09 plan – 1 half of 2010 Plan 22.6.2016
Commencement of
construction 16.10.2009 16.10.2009 5.2.2010 24.10.2016
Expected initial end
date (transfer) of the
construction work
individual sections
from October 2011
to July 2013
- first and second sections,
1st half of 2011
- first and second
sections – spring 2013
2.11.2020 - third section, 2nd half of
2011
- third and fourth
sections – autumn 2014
- fourth section, first half of
2012
Actual state package cancelled in
2010
the operation of the project
was launched in October
2010
package cancelled in
December 2010,
renewal planned by
selection of
concessionaire in 2013
and commencement of
construction in 2014
construction
Source: authors’ own
Following the change of the government coalition in July 2010, all concluded concession
contracts were also reviewed. Construction of the R1 dual carriageway within the second
planned PPP package was triggered by the declared EBRD loan of € 250 million and the support
of 17 commercial banks. 46 km of the PR1BINA dual carriageway, the operation of which was
launched on October 28, 2010, was built as part of the project. In comparison with the estimated
daily use of 5 to 7 thousand vehicles, the real use represents more than 12 thousand vehicles
87
per day. The construction of the R1 dual carriageway was beneficial not only from an economic
but also from an environmental point of view, especially for the Nitra region.
In September 2010, the then Minister of Transport, due to the failure to secure the financial
closure of the project (the financial closure of the project, which had been postponed several
times, also prevented the European Commission's approval in the environmental field - the
previous government likewise counted on the priority loans from the European Bank for
Reconstruction and Development (EBRD) of up to € 250 million and € 1 billion from the
European Investment Bank (EIB) subject to the successful conclusion of negotiations on
environmental, technical and financial conditions) decided not to extend the deadline for the
first PPP project package resulting in the concession contract between the State and the
concessionaire losing its validity. Withdrawal from the contract should have originally cost the
Slovak Republic € 81 million, the latest information mentions a sum of “only” € 51.4 million.
The then government, however, argued that the contract would be disadvantageous for the state,
and that PPP projects would represent a more expensive alternative to the traditional method,
namely to the sum of € 545 million.
The third package of PPP projects should have included the demanding tunnel sections on the
D1 motorway around Žilina. Although the consortium led by the German company Hochtief
PPP Solutions offered the government a 30 percent reduction in the agreed annual payment, the
decision of the coalition partners of the then government in December 2010 to implement the
third package of PPP projects in Slovakia was halted. The government decided to build a
motorway between Bratislava and Košice with the help of the euro-funds and the state budget,
and their completion was set for 2017.
The following table (Table 2) compares the estimated construction costs of the eight D1
motorway sections that were originally to be implemented as PPP projects, but were ultimately
implemented in the traditional form. However, it is important to note that this comparison is
not complete as we do not know the costs for 30 years of operation and maintenance of these
sections.
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Table 2 - Comparison of construction costs for sections of the D1 motorway implemented
through PPP projects and in traditional form
Section name
1.
Hričovské
Podhradie -
Lietavská
Lúčka
2.
Lietavská
Lúčka -
Višňové -
Dubná
Skala
3.
Dubná
Skala -
Turany
4.
Turany -
Hubová
5.
Hubová -
Ivachnová
6.
Jánovc
e -
Jablono
v, 1
section
7.
Jánovce
-
Jablonov,
2 section
8.
Fričovce
- Svinia
Together
without
section 4
Section length
in km 11.3 13.5 16.5 13.5 15.3 9 9.5 11.2 86.3
of which
tunnels account
for
3.1 7.5 - 4.6 2 - 0.6 - 13.2
Cost for
construction
in PPP1 (€ mil.) 712 1090 335 758 541 165 385 284 3513
new contract 2
(€ mil.) 427 410 138 - 227 60 126 115 1503
Reality3 (€
mil.) - - 137 - - 70 124 124 1519
Cost per 1
km
in PPP1 (€ mil.) 63 81 20 56 35 18 41 25 41
new contract 2
(€ mil.) 38 30 8 - 15 7 13 10 17
Reality 3 (€
mil.) - - 8 - - 8 13 11 18
% of cost
from state
expertise
in PPP1 (%) 158 122 125 110 108 148 148 142 131
new contract2
(%) 95 46 51 - 45 54 49 57 56
Reality 3 (%) - - 51 - - 63 48 62 57
Saving against
PPP (€ mil.)
285 680 198 - 314 95 261 160 1993
Source: Ineko, 2016, Central register of contracts, 2017
1 in accordance with the signed 2010 concession contract (construction only, without the costs of financing,
operation and maintenance)
2 new construction price - under new contracts with contractors of individual sections
3 actual following additions and instructions for change – in accordance with Ministry of Transport data of
November 2015, only for sections already in premature use
Legend: • under construction, • put into use in 2015, in preparation
Four of the eight sections (Dubná Skala - Turany, Jánovce - Jablonov 1st and 2nd sections,
Fričovce - Svinia) were put into operation in 2015; in comparison to the projected construction
cost through the PPP project (€ 1,166 billion) the final cost of building the 46.2 km of the
motorway was € 439 mil., which is 2.6 times less than the original estimated costs if the
construction of the D1 motorway had been implemented through the PPP project. For other
sections, the construction costs are as yet only indicative, as individual sections are still under
construction, respectively, are in preparation (Turany - Hubová). For this section, it is assumed
that the procurement process will not be launched until 2021.
The change in government change in 2012 once again changed the state's attitude towards PPP
projects. The current government has declared the renewal of PPP projects in its programme
statement, where the continuation of the construction of the PPP transport network is one of the
above-mentioned priorities. The main priority was the completion of the D1 motorway between
Bratislava and Košice by 2017 and the R2 dual carriageway between Zvolen and Rimavská
Sobota. However, despite this government statement, the then leadership of the Ministry of
Transport, Regional Development and Construction envisaged PPP projects as a secondary or
tertiary form of financing the development of transport infrastructure.
89
The following figure (Figure 1) shows the current situation in the construction of motorways
and dual carriageways in Slovakia.
Figure 1 Construction sections of D1 motorway from parcels # 1 and 3
Source: National Motorway Company, 2017
Legend: planned motorway and dual carriageway projects, • motorways and dual carriageways in operation, •
motorways and dual carriageways under construction
Due to the lack of finances in the state budget for the construction of transport infrastructure,
the government proceeded to consider the renewal of PPP projects. The possibility of
implementing PPP projects in the construction of transport infrastructure was also discussed in
connection with the construction of the R7 and D4 dual carriageways. An international tender
for the selection of a concessionaire that would implement the construction and operation of
both roads began at the turn of 2014 and 2015, with the planned start of construction in 2016.
Nine interested parties participated in the international tender, whereby four candidates who
met the participation conditions and reached the highest number of points based on criteria
evaluation (VI.2.15 Notices) being invited to participate in the tender dialogue. On 27 January
2016, in accordance with the rules set out in the final evaluation document, the tender of the
Zero Bypass Limited ("Obchvat nula") consortium of Cintra SA, Macquarie Capital and PORR
AG was evaluated as the most economically advantageous tender. The benefits of the
interconnection of the motorway D4 in the motorway network are: relieving the Bratislava
traffic system from transit traffic; speeding up traffic connections to the motorway network
(D4, D1 and D2); partially relieving the traffic of Bratislava's catchment area by interconnecting
the R7 dual carriageway and the D4 and D1 motorways; improving the traffic service of the
affected area; improving the impact on the environment, in particular by diverting heavy traffic
(Ministry of Transport and Construction of the Slovak Republic, 2017). The above-mentioned
D4R7 PPP project also received the award for Best Transaction of the Year in Europe, for well-
managed cooperation between the public and private sectors in construction, due to the rapid
and convenient way of funding transport infrastructure. This acts as a combination of financial
instruments from the European Investment and Structural Funds through Slovak Investment
Holding (bridging funding up to € 50 million), using the European Investment Fund of Strategic
90
Investment (Juncker Plan) (EIB = € 426 million) and the EBRD (€ 148.5 million). The
construction of the D4R7 project started on October 24, 2016 (Ministry of Transport and
Construction of the SR, 2017) and should be completed in November 2020, whereby it is
assumed that some sections will be put into use from March 2020.
A prerequisite for the implementation of PPP projects in the field of motorway infrastructure
construction was the implementation of an electronic toll project, which should partly cover
payments to the concessionaire in the construction and operation of motorways.
The electronic toll project, in operation since January 2010, has the form of the DBFO (T)
(Design - Build - Finance - Operate - Transfer) PPP model. The legal basis for the introduction
and operation of the system of electronic toll collection was created by Act No. 25/2007 Coll.
on electronic toll collection for the use of defined sections of the road network. The sections of
the roads where tolls are collected are set out in the Decree of the Ministry of Transport,
Construction and Regional Development of the Slovak Republic No. 147/2012 Coll. With this
Decree, the original list of sections of 2009 was extended by 25 new sections with effect from
1 July 2012.
Electronic toll collection is applied in the Slovak Republic on highways, dual carriageways and
the majority of first-class roads. Since January 1 2014, toll satellite technology covers almost
17,770 km, of which approximately 660 km are defined sections of motorways and dual
carriageways, 3,630 km of defined sections of first class roads, 3,640 km of defined sections of
2nd class roads, and more than 9,840 km of defined sections of 3rd class roads. Satellite
technology, as a way of collecting tolls, was selected to make it possible to collect real-cost
payments and replace the existing way of charging in the form of motorway vignette stickers
(only for vehicles over 3.5 t). After initial problems, roads with tolls were divided into 1,006
sections, none of which exceeds 5 km. The fee for traversing 1 km of a paid section ranges from
€ 0.020 to € 0.232 - depending on the emission category, the number of axles and the vehicle
type. If the carrier does not traverse the entire section, they do not pay for the section. After
carrier protests, since 1 April 2010, sections have been shortened to less than 700 meters. The
satellite toll system used in the Slovak Republic is already technologically ready for
interoperability with the surrounding countries, is fully in line with the requirements of the
future European Electronic Toll Service which is based on the principles of "one contract - one
onboard unit - multiple toll systems".
The toll collection system in the Slovak Republic is SkyToll, a. s., founded by members of the
consortium Ibertax-Santoll which is the winner of a tender for a comprehensive toll collection
service that includes the construction and operation of the system. The National Motorway
Company, a.s. is the toll collection administrator. The contract for operating the system was
concluded for 13 years with the possibility of an extension of 5 years. According to the research
institute of transport in Žilina, during this period toll up to € 4 billion can be collected, from
which the operator will receive the amount of € 852 mil. The share of the repayable amount on
the toll collected should gradually decrease over the duration of the contract from almost 40%
to 12%
CONCLUSION
A comprehensive and stable legal framework is a prerequisite for the successful creation and
development of public-private partnerships, guaranteeing the protection of the rights of both
parties involved. The Slovak Republic, as a member state of the European Union, when creating
91
a legislative framework for public-private cooperation, should discharge its duties based on the
legal regulation established by the Community in this area.1
Forms of public-private partnership can be subdivided according to EU legislation into
contractual and institutional ones. Contractual forms of partnership are based on public
contracts or concessions, including the public sector's obligation to pay to the private sector for
the provision of a certain public service. Accordingly, the contracts in question fall within the
category of "public contracts" and must be subject to the arrangements for their being awarded.
The main objective of the European Union legislation is to open up the public procurement
market between individual member states to ensure the functioning of the single market, i.e. the
free movement of products and services. The basic principles of this regulation are zero
discrimination at the place of realization of public procurement, along with transparency and
preventing corruption. Competition in awarding public contracts not only between entities of
different ownership relationships but also within the EU should lead to an increase in the quality
of public services provided and the efficiency of the allocation of public resources.
The aim of the EU is to harmonize the national public procurement legislation of the member
states by applying a number of principles: public procurement contracts above a certain
financial limit throughout the Community; a ban on the technical specification of a public
contract that would discriminate against other bidders; the need to apply objective criteria when
assessing public contracts.
For this purpose, in 2006, the reform of European public procurement law occurred in the form
of Directives 2004/18 / EC and 2004/17 / EC. The directives also implicitly regulate the area
of public-private partnership, in particular in the section concerning concessions. It is possible
to positively assess the fact that Slovakia was one of the first eight EU member states to
incorporate European legislation into its own legislation (Act No. 25/2006 Coll. On Public
Procurement), including those sections concerning concessions that are the most important
from the view of PPP projects. Act No. 25/2006 Coll. of the National Council of the Slovak
Republic defines the concept of concession for civil engineering work and service concessions
(§ 15) for public procurers by removing those activities for which concession rules cannot be
applied. Concessions for civil engineering work are regulated in the third chapter of the new
Public Procurement Act in Sections 66 to 71 for the award of oversubscriptions and in Sections
97 and 98 for subcontracting. The Act also defines the procedure in public procurement -
competitive dialogue (§ 24 paragraph 7) and its progress (§ 60 to 63), which can be used only
by the contracting authorities in the implementation of particularly complex projects where no
competition or restricted competition may be implemented. It may involve the implementation
of important integrated transport infrastructure projects, large computer networks or projects
that require comprehensive and structured funding, and their financial and legal composition
cannot be defined in advance. There should be a flexible procedure that preserves not only
financial competition between financial operators, but also the need for public procurement
authorities to discuss all aspects of the contract with each bidder.
However, the risk in this area is a certain freedom of the public procurement authority in the
approach to competitive dialogue, seen as changing the essential aspects of the tenders or by
setting what are essentially new requirements for the successful bidder or by accepting any
other bidder such as one whose tender has been selected as the most economically advantageous
tender. In such cases, there is a limitation to or distortion of the financial competition.
A frequently debated issue in relation to the implementation of different forms of public-private
partnership in professional circles is the need to create a specific legal rule regulating the area
1 Directives and case-law of the European Court of Justice.
92
of public-private cooperation. If such a rule actually arises, then it is doubtful whether it should
cover all possible forms of public-private partnerships and determine their content and precise
procedures for selecting a private partner. Experts from several countries have yet to come up
with a clear answer to questions about the need for a specific legal rule governing public-private
cooperation and its scope. Some countries (Ireland, Portugal and Belgium) have legislated this
area with specific legal standards, others (the UK and France), on the contrary, do not have
specific legal arrangements for public-private partnerships, and yet many successful partnership
projects between the public and private sectors exist.
The Slovak Republic does not prefer regulation of the aforementioned area by a specific legal
norm. The issue of public-private partnerships is governed by a number of regulations
governing public procurement, fiscal supervision, the competencies of individual ministries,
the competence of regional self-governing units, and the protection of creditors, etc. The
question is whether it is easier to make adjustments to all of these legal norms, the scope of
which could be affected by the various forms of partnership, or to consolidate all legislation
into a cross-sectional legal standard. In our opinion, however, the minimum concession issue
will require specific legal regulation (at present, the concession arrangement is part of the Act
of the National Council of the Slovak Republic No. 25/2006 Coll. On Public Procurement).
Another contentious issue is the legal definition of public-private partnerships as well as their
content. There is no general characteristic or classification of public-private partnerships, and
it would be extremely difficult (perhaps to some extent restrictive) to introduce a precise legal
definition of this area (here, to a certain degree, we identify with the view expressed by the
United Kingdom). Any modification of the relevant legal standards falling within the scope of
individual forms of public and private sector cooperation should include certain criteria for
identifying such forms (e.g. any contractual relationship between the public sector as the
contracting entity and the private sector as a supplier, a contractual relationship between the
public sector as contractors and the private sector as a contractor, with public sector payment
obligations covered by future revenues of the contracting entity's budget, whereby those
commitments exceeding the specified percentage of the budget of the contracting authority; ...).
The legal regulation of the forms of public-private partnership should also take into account the
risks associated with this form of cooperation. By concluding contracts for the provision of
public services or the construction or operation and maintenance of public infrastructure, the
public-sector transfers part of the risks associated with the performance of tasks in these areas
to the private sector. The transfer of responsibilities to the private sector is, of course,
accompanied by the transfer of competencies, which, in the event of adverse developments in
the scope and quality of public services provided, reduces the public sector's ability to make
rapid and effective redress. Experience with unsuccessful public and private sector cooperation
has shown that, in the event of a failure of this cooperation, other unplanned public finance
implications are also revealed.
In addition to the issue of adequate legal regulation of public-private partnerships, it is also
necessary to address the issues of transparency of public procurement processes that are
inevitably linked to the implementation of PPP projects. Transparency requires that all
processes be transparent and thus able to be evaluated by prevalent environment, thus reducing
the possibility of corruption and improper execution of competencies. Transparency of a public
contract makes it possible to make open decisions which can be re-verified and logically
explained, concerning all phases of the award of a contract – announcement of the public
procurement procedure; disclosure of the relevant terms, and set decision criteria and deadlines.
Insufficient transparency may prevent private partners from participating in public
procurement.
93
Transparency may be negatively affected mainly by insufficient (incomprehensive) notification
of the announcement of the public procurement procedure, discrimination towards candidates,
failure to observe the rules on public procurement, but also the lack of budget constraints and
corruption. The contracting authority may systematically favour certain entities through unclear
procurement procedures. The lack of information makes it impossible to respect the principle
of transparency. In the case of public procurement, the information is made available through
announcement of the public procurement. For the mandatory notification of the announcement
of the public procurement procedure, Slovak law prescribes its form, differentiated for
individual public procurement procedures. This announcement of the procedure is binding on
the entire subsequent procurement process, in particular as regards the defining the subject of
the procurement, the conditions for participation in the tender and the criteria for the evaluation
of the winning bid. These may not be changed either in tender documents or in the evaluation
of the bids.
One of the most important tools for fair and successful procurement in the selection phase is
the development of clear and comprehensible documents relating to the tender. Incorrect,
unclear, inaccurate and generally incomprehensible documents relating to the tender is a source
of non-transparency in public procurement and is therefore a potential source of bribery and
corruption. The standard of documents relating to tenders in the Slovak Republic is strikingly
low, especially in terms of inadequate qualifications of the public procurement authorities, and
in some cases also deliberately poor quality processed documents (the procurer thus creating
space for changing the subject or the price of the contract after conclusion of the contract - to
changes in the content of contracts and prices are one of the most frequent cases of violation of
the Public Procurement Act). Discrimination towards bidders indirectly reduces transparency -
by introducing different possibilities of interpreting tender conditions and criteria, thereby
creating opportunities for bribery, corruption and other problems. It can again be said that
Slovakia has this problem. Growing corruption also raises public procurement spending and a
reduction in the number of bidders in public procurement contracts, especially from small and
medium-sized businesses that do not have the funds to pay bribes.
The most significant source of non-transparency and subsequent corruption may be a simple
non-compliance with public procurement rules. Failure to comply with the rules on public
procurement occurs in all phases of the procurement process: the choice of procurement
procedure; shortcomings in the content of the notification of announcement; the procurement
procedure; insufficiently precise description of the contract; establishing ambiguous conditions
for participation in the tender and ambiguous criteria for evaluation of bids; establishing an
unreasonably short period for the submission of bids; unjustified elimination of candidates from
the tender; failure to comply with the announced terms for participation in the tender and the
criteria for evaluating the tender; not respecting the choice of bidder by the selection committee
when evaluating the tender; changes to the announced terms and conditions when signing the
contract with the winning bidder, etc.
The conclusions published in this study are the result of the VEGA 1/0405/15 Programme
Budgeting project as a tool for New Public Management.
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úsekov pozemných komunikácií.
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Contact information
prof. Ing. Beáta Mikušová Meričková, PhD.
Univerzita Mateja Bela v Banskej Bystrici, Faculty of Economics
Tajovského 10, 975 90 Banská Bystrica, Slovakia
Ing. Nikoleta Muthová
Univerzita Mateja Bela v Banskej Bystrici, Faculty of Economics
Tajovského 10, 975 90 Banská Bystrica, Slovakia
Ing. Marián Holúbek
Univerzita Mateja Bela v Banskej Bystrici, Faculty of Economics
Tajovského 10, 975 90 Banská Bystrica, Slovakia
96
FISCAL DECENTRALIZATION AND WASTE MANAGEMENT IN
SLOVAKIA
Katarina Orsagova, Maria Horehajova
Abstract
Waste management is a challenge for regional and local government authorities due to
increasing generation of municipal waste and high costs associated with its disposal. Fiscal
decentralization with the aim to ensure more efficient management of public services, is
supposed to create the conditions for higher quality of waste management. The objective of our
research was to determine major changes in outcomes of municipal waste management since
2005 and to reveal the main factors involved in these changes. The research was carried out at
regional and district levels. Analysed data was collected from existing Slovak and European
databases, Regional Waste Information System (RISO) and scientific literature. The outcomes
of research revealed the best regions based on the selected indicators of the rate of recycled and
recovered municipal waste. The situation in the districts was evaluated on the basis of seven
indicators, taking into account especially the landfilling, recycling, the total weight of municipal
waste generated as well as the average annual population of the districts. Factors influencing
observed indicators show there is a possibility to improve municipal waste management by
means of fiscal decentralization measures.
Keywords: waste management, municipal waste generation, recycling, energy recovery, fiscal
decentralization
JEL Classification: R11
INTRODUCTION
Waste management is an agenda that has an important place in managing environmental
protection at not only the transnational, national or regional level, but it is also an essential
component of local government competencies. Fiscal decentralization in Slovakia brought the
most important changes between 2001 and 2005, and consequently local and regional
authorities received new competences, roles and responsibilities for several areas of life,
including waste management. The essential part of scientific activity whose main objective is
sustainable regional development is research dealing with the tasks fulfillment of local
government waste management and their achieved results, the biggest problems and the efforts
to uncover their causes.
Our aim was to answer the following question: How the outcomes of municipal waste
management including separation, recycling, recovery, landfilling and overall generation of
municipal waste in Slovakia changed in 10 years since 2005. Main changes were evaluated at
district level (LAU1) based on data from the Regional Waste Information System (RISO). In
particular, we expected improvement in the recycling of municipal waste, both due to fiscal
decentralization, which should have helped to manage municipal waste more efficiently, as well
as due to the possibility of using EU funds under the Operational Program Environment.
In the first part of our contribution, we focused on a brief chronological overview of the
legislative norms related to fiscal decentralization as well as their impact on waste management.
The second part of our contribution deals with the development of municipal waste recycling
at the regional level between 2005 and 2015. Through the average annual growth rate of
recycled and recovered municipal waste, the situation in the regions has been confronted with
97
the possibility of meeting the target that was defined by the European Commision (EC) in the
recycling rate of municipal waste by 2020.
In the third part, based on the Screening of Waste Management (EC, 2012) and data from RISO,
we focused on the most problematic area of waste management, which is, from the point of
view of local self-government, municipal waste and related activities such as separation,
recycling, recovery and landfilling. In addition to a brief overview of the results of the
municipal waste management from the point of view of the eight regions, we have deeper
analyzed the situation at district level. Based on the seven selected indicators, we evaluated the
outcomes of municipal waste management in 2005 and 2015 at district level, using the principal
components analysis in order to reduce the number of variables. The results of the analysis are
also displayed on maps.
The latest legislation on waste management has the ambition to address some of the
shortcomings we have identified. Since the new Act on waste was adopted in 2015, it is too
soon to evaluate its effectiveness. We expect that in the near future we will be able to examine
to what extent the taken measures like, for example the emergence of the organizations of
responsible producer (ORP), are able to solve existing shortcomings in the outcomes of
municipal waste management.
1. DATA AND METHODOLOGY
In 2012, the EC issued a report titled Screening of the waste management performance of EU
member states, prepared by the German consulting company BiPRO (2012). The report
evaluates the municipal waste management performance. BiPRO has rated the EU member
states according to 18 criteria and each state could score a maximum of 42 points. Slovakia
reached 17 points, with six criteria scoring zero points and ranked among the ten member states
with the worst results. The worst-off areas of municipal waste management include low amount
of municipal waste recycled, the absence of waste prevention program, high amount of
municipal waste disposed, the lack of forecasting of municipal waste generation and treatment
capacity in the waste management programme.
From the point of view of the regions (NUTS 3), we focused on the recycled and recovered
waste rate as a percentage of total municipal waste that we monitored between 2005 and 2015.
We have recalculated both indicators to relative values and combined them into a single
indicator as a proportion of the amount of recycled and energy-recovery waste in total municipal
waste. We assumed the positive changes in the management of municipal waste, especially in
the field of recycling due to fiscal decentralization. With the aim to evaluate possibilities to
achieve the EC targets in recycling, we used the calculation of the average annual growth rate
of the total amount of municipal waste recycled and recovery (R) for the period 2005 to 2015.
At district level, we have selected 6 following indicators from the RISO database: municipal
waste disposed in landfill (D01) the amount of municipal waste recycled and recovered (R),
municipal waste energy recovery (R01), municipal waste reuse (R2789), municipal waste
recycling (R345) and total municipal waste generation (TWG). The seventh variable we have
used was the average population of the district in the given year. With the aim to evaluate the
performance of districts, we used the principal components analysis, which reduces the number
of original variables. Using KMO and Bartlett's test, we verified the ability to process selected
variables using the principal components analysis. According to the authors (Kaiser, 1974),
value of 0.5 for KMO is barely accepted, values between 0.6 and 0.8 are middling and values
above 0.9 are superb. Since our test results for KMO reached 0.698 in 2005 (Table 1) and 0.717
in 2015 (Table 2), we have decided to use principal component analysis.
98
Table 1 – KMO a Bartlett’s Test 2005
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,698
Bartlett's Test of Sphericity Approx. Chi-Square 507,520
df 21
Sig. ,000
Source: own processing in SPSS
Table 2 – KMO and Bartlett’s 2015
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. ,717
Bartlett's Test of Sphericity Approx. Chi-Square 859,420
df 21
Sig. ,000
Source: own processing in SPSS
According to the obtained values of the principal components in 2005 and 2015 we have
compiled the order of the best districts and the results for both monitored years were processed
into a graphical representation of the map of the districts of Slovakia. We have used the obtained
data to determine whether there has been changes and whether the implications of fiscal
decentralization and the adopted waste management legislation have been demonstrated. We
assumed, the ranking of districts was influenced in particular by the low recycling rate, which
along with the economic disadvantage of waste recovery as compared to landfill was included
among the main problems of waste management already in 2007(Plekanec, 2007).
2. DECENTRALIZATION AND ITS IMPACT ON WASTE MANAGEMENT
Since the early 1990s, decentralization of the public sector has been a paradigm of reform,
which includes changes in organizational structure to provide public services more efficient.
After changes in the organization of state administration and self-government, fiscal
decentralization began in 2001 and went on in two stages.
The first stage was mainly related to the new way of managing and financing public services
that have been transformed from state to local government. In 2001, the so-called "Competence
Act" (416/2001) passed and, over the next two years, more than 400 competencies have been
transferred from the state administration authorities to municipalities and self-governing
regions (later renamed to higher territorial units). According to the above Act, the municipalities
and self-governing regions ensured their tasks using their own budgets while the state budget
financed transferred competencies. This phase of fiscal decentralization mainly concerned
expenditures that increased considerably in the budgets of municipalities after the transfer of
competences. The transfer of competencies has also brought about a number of other problems
and financial costs related to the state of movable and immovable property, such as the fact that
the law obliged municipalities to continue the purpose-built use of the facilities taken over.
(Niznansky, 2005). In several cases, previous decisions and contracts concluded by central
government authorities have led to higher costs for local governments.
Legislative year 2001 did not only introduce legal standards on fiscal decentralization, but also
meant a certain breakthrough in waste management. Although in the past local authorities have
99
been obliged to ensure municipal waste collection, Act No. 223/2001 on waste has expanded
their competencies in waste management. The basic document, which is to deal with the issue
of waste generation, waste management, its impact on the environment and its disposal, is the
Waste management program (WMP). The Ministry of the Environment prepared the first Waste
Management Program of the Slovak Republic in 1993 and on its basis the regional and district
authorities have been working on the WMP since 1996. The Waste Act of 2001 also imposes
on municipalities an obligation to prepare WMPs and as well gives them opportunities to create
WMP together with other waste producers. According to the latest Waste Act no. 79/2015, the
municipality is obliged to prepare WMP if it produces more than 350 tonnes per year of
municipal waste, including small construction waste, or has a population greater than 1000. The
importance of WMP was clearly confirmed between 1993 and 1996. Waste management
programs developed at the level of waste producers were of particular importance. Many
developers for the first time have recognized their responsibilities in this area (Kollar, V. 2014).
In addition to the tasks associated with the preparation of the WMP, the law also requires local
authorities to introduce separate collection of paper, metal, glass and plastics, as well as the
obligation to separate biodegradable waste according to the strategy of the Slovak Government.
Although the law passed in June 2001, the validity of some regulations was postponed to May
1, 2010. The municipalities had a 10-year transitional period for introducing a separate waste
collection and the Slovak Government approved the Strategy on the Management of
Biodegradable Waste in December 2010.
The increase in local government spending due to delegated competencies along with the
ineffective provision of public services as well as new waste management tasks led to the
second phase of fiscal decentralization, which was to address the revenue side of local and
regional government budgets. The financial independence of self-governments has
strengthened as generation of financial resources were transferred to municipalities and higher
territorial units (Nemec, Spacek, 2017). At this stage, there are two fiscal laws relating to the
budgetary rules of public administration and territorial self-government (No. 523 and No. 583
of 2004), as well as two laws on the budget determination and the income tax distribution to
the territorial self-government bodies (No. 564 and No. 668 / 2004). An important step on the
way to the reform of waste management was the Act of the National Council of the Slovak
Republic No. 582/2004 on local taxes and local fees for municipal waste and small construction
waste. Under that Act, municipalities may set a fee for mixed municipal and biodegradable
municipal waste as well as separated waste collection and insufficiently separated collection of
municipal waste. The municipality may determine the amount of the charge within the range
set by the law in, so called, the Generally binding regulation, otherwise the fee is determined
by the legally set minimum. Municipalities may use revenue from local fees for municipal waste
and small construction waste explicitly for the collection, transport, recovery and disposal of
municipal waste and small construction waste.
The abovementioned laws have been amended several times in particular with regard to changes
resulting from the EU legislation and the objectives of the EC in the area of waste management.
One important document affecting the waste management record is, for example, the waste
categorization, which is based upon the European Waste Catalogue, the EC no. 2014/955.
Slovakia has been using the Regional Information System on Waste (RISO) since 1995 for
processing data on the origin and methods of waste management. There is an exception for
municipal waste, the records of which since 2003 have been provided by the Statistical Office
of the Slovak Republic based on an inter-departmental agreement. Statistical Office processes
data on municipal waste according to the European Waste Catalogue.
100
3. MUNICIPAL WASTE MANAGEMENT IN THE REGIONS OF SLOVAKIA
According to the Waste Act (No. 223) of 2001, separation of municipal waste is mandatory for
municipalities, but screening results show that the recycling is still one of the worst rated issues.
As the municipalities had a ten-year transitional period, we looked at the results of the recycling
of municipal waste in the individual regions of Slovakia from this perspective. We were looking
at the rate of recycled and recovered municipal waste between 2005 and 2015, assuming that at
least towards the end of the transition period, in 2011, it will increase significantly. Our
assumption resulted from two facts: 1 May 2010 separation of municipal waste became
mandatory for municipalities and in December 2010, the Slovak Government approved
Strategy for the Management of Biodegradable Waste.
Table 3 Rate of recycled and recovered municipal waste as a percentage of total municipal
waste 2005 - 2015
Regions 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
BA 4.15 9.11 54.37 54.86 57.89 57.69 65.20 63.36 65.28 66.82 68.39
TT 1.32 4.17 7.44 5.58 9.74 12.00 12.14 13.95 16.94 20.21 19.65
TN 4.38 5.99 8.51 7.16 10.66 12.87 13.00 16.39 21.46 20.11 20.56
NR 2.33 4.80 6.93 10.57 8.49 9.16 12.84 13.02 15.06 14.15 18.55
ZA 1.51 2.75 4.41 7.01 6.51 7.99 10.74 13.26 16.19 20.84 18.79
BB 1.98 1.22 3.38 3.38 9.37 13.93 13.50 18.59 15.62 20.75 20.32
PO 2.89 9.81 13.44 8.54 8.77 8.08 12.30 11.90 13.94 15.11 16.03
KE 1.90 1.53 4.80 32.67 6.04 29.70 42.73 46.52 48.28 47.62 49.62
Source: Statistical office of the Slovak Republic
Table 3, as well as Figure 1, show that in given period there was no significant increase in the
rate of recycled and recovered municipal waste in any region. A substantial increase in the rate
of energy recovered municipal waste has been recorded only in the BA region since 2007 and
in the KE region since 2008. Although the material recovery has not increased in these regions,
the overall rate of recycled and recovered municipal waste has significantly improved. This was
because in 2007-2008 there were large municipal waste incinerators that, as a result of the
reconstruction and modernization, increased their capacities in the BA region from 13 tonnes
of recovered municipal waste in 2006 to 115 378 tonnes in 2007. Similarly, in the KE region
amount of recovered municipal waste increased from 8.5 tonnes in 2007 to 45 067 tonnes in
2008.
Although we have seen a growing trend in separation of municipal waste in all regions, the
trend is slow in six regions and is not improving even under the influence of the legislative
standards adopted and related responsibilities of local government bodies.
101
Figure 1 Rate of recycled and recovered municipal waste as a percentage of total municipal
waste 2005 - 2015
Source: Statistical office of the Slovak Republic
The aim to achieve a 50 % recycling rate of municipal waste by 2020, set out in Annex no. 3 to
Act no. 79/2015 on waste, can be considered unrealistic, based on the current situation.
However, according to the European Environment Agency (EEA), six EU member states have
already achieved this target and therefore there is a new EC challenge to increase recycling to
60% by 2025 and to 65% by 2030.
Figure 2 Average annual growth rate of recycled and recovered municipal waste 2005 – 2015
Source: Own calculation based on statistical data provided by Statistical office of the Slovak Republic
In Slovakia, the rate of recycled and recovered municipal waste reached only 30% of total
municipal waste in 2015. To achieve a 50 percent recycling rate, as in the six EU countries
mentioned above, the average annual growth rate of recycling should have been more than 27
0
10
20
30
40
50
60
70
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
BA TT TN NR ZA BB PO KE
0
2
4
6
8
10
12
14
16
BA TT TN NR ZA BB PO KE
102
percent. As shown in Figure 2, none of the regions achieved even 15 percent of average annual
growth rate in 2005 - 2015.
4. OUTCOMES OF MUNICIPAL WASTE MANAGEMENT AT DISTRICT LEVEL
For the analysis of municipal waste management at NUTS 4 level, we have selected 69 districts,
eliminating the districts of Bratislava I through V and the districts of Košice I to IV as well as
Košice-periphery due to the existence of large municipal waste incinerators in these cities. The
construction of two large - municipal waste incinerators has changed the situation in these
districts so much that data from this area would significantly distort the evaluation of the results
of other districts.
Using the principal components analysis, we have reduced the number of variables to two major
components, which in 2005 account for 72% of the variance, and in 2015 for 81% of the total
variability of inputs. The matrices of the component values (Tables 4 and 5) show that the first
component correlates most with the municipal total waste generation TWG, and therefore we
can call it the component of the total waste generated. The second component is the most visibly
correlated with the municipal waste energy recovery indicator R1 and therefore we call it the
component of the waste recovery.
Table 4 Component Matrix 2005
Component
1 2
D01 ,893 -,291
R ,754 ,516
R1 ,261 ,753
R2789 ,457 -,286
R345 ,791 ,269
TWG ,908 -,266
PO ,906 -,184
Extraction Method: Principal
Component Analysis.
a. 2 components extracted.
Table 5 Component Matrix 2015
Component
1 2
D01 ,946 -,022
R ,926 ,040
R1 ,285 ,888
R2789 ,568 -,479
R345 ,852 ,001
TWG ,975 -,010
PO ,905 ,014
Extraction Method: Principal
Component Analysis.
a. 2 components extracted.
103
Starting from the Component Matrices, we can use the relationships between components and
variables to calculate the values of the so-called component score, according to which we have
determined the ranking (Table 6) of the 10 best performing districts in the SR.
Table 6 Component of the total waste generated
District
2005
Component 1
District
2015
Component 1
ML -1,167 ML -1,369
SO -1,096 SO -1,277
PT -1,067 BS -1,243
BS -1,056 SP -1,217
GL -1,052 PT -1,180
SP -1,044 GL -1,110
KA -1,034 TR -1,067
TR -0,973 KA -1,061
MY -0,945 SK -1,010
DT -0,916 LE -0,997
Source: own processing based on component values from SPSS
We have evaluated the first component in order from the smallest to the highest values, so the
listed districts have the best results regarding the amount of municipal waste generated. These
are usually smaller and poorer districts in the east and south of Slovakia, which, especially for
economic reasons, generate less amount of municipal waste. A comparison of the two tables
shows that there has been no significant changes over the 10-years period when up to seven out
of ten districts were ranked in the top ten in both monitored years. According to RISO data the
reason for this outcome is, mainly, a small increase of the total amount of waste generated
compared to other districts in Slovakia. The representation of the districts in the first tenth did
not change significantly, even if we used as variables the relative values per capita.
Figure 3 Slovak districts in 2015 according to the first component
Source: own processing based on the values of component 1
104
Notable is the fact that these are districts with a larger proportion of the rural population, which
apparently generates a smaller amount of municipal waste. Nearly 40% of municipal waste is
biodegradable waste and we therefore assume that the rural population processes this waste for
compost or uses it as feed in domestic livestock, reducing the amount of total municipal waste
generated. This assumption is also confirmed by the fact that, according to the first component,
the worst are districts with the largest share of the urban population, in some cases the districts
with the seats of the regional cities. For better illustration, we depicted the component values
graphically to the map of Slovakia's districts (Figure 3) using the colour scale from the best ten
(black colour) to the worst ten districts (white colour).
For a more comprehensive assessment of municipal waste management, we also used the
second principal component, which we called the recycling component. According to the
component of the waste recovery score from SPSS, we have compiled the order of the ten most
successful districts (Table 7).
Table 7 Component of the waste recovery
District
2005
Component 2
District
2015
Component 2
BB 5,985 PK 5,708
BJ 1,584 ZA 4,361
HC 1,278 BB 0,983
PK 1,264 IL 0,783
PB 1,2169 SC 0,179
PD 1,165 MI 0,149
TN 0,667 ZH 0,136
NM 0,553 MA 0,129
LE 0,537 SI 0,083
PU 0,427 RK 0,076
Source: own processing based on component values from SPSS
There have been more changes in waste recovery component comparing to the component 1.
These changes result from the possibility of using EU funds for the introduction of separate
collection of municipal waste. In the top ten of the evaluated districts in 2015 there are only
two districts, Banská Bystrica and Pezinok, from the top ten evaluated districts in 2005. The
table 7 also shows that in the top ten, there are districts with high share of the urban population;
actually, there are two districts (BB, ZA) with the seats of the regional cities. Higher
representation of larger cities on the first places of the district ranking can be explained by the
obligation to separate collection of biodegradable waste from 2010. Although biodegradable
waste increases the total amount of municipal waste generated in urban areas, it is positive that
in some districts, it does not get into landfill but since 2010, it has been more and more separated
and subsequently processed. Nevertheless, there are still many districts with a high proportion
of urban population (TT, NR, TN, PP) with low rates of municipal waste recovery. Figure 4
shows districts sorted by the waste recovery component and distinguished by a colour scale
from the top ten districts (black colour) to the ten worst districts (white colour).
105
Figure 4 Slovak districts in 2015 according to the second component
Source: own processing based on the values of component 2
The situation in the most districts with poor results in waste recovery and recycling proves that
one of the reasons is the high cost of municipal waste separation. Subsequently these costs
increase waste fees, although paradoxically, the EC Screening of 2012 criticizes Slovakia for
low fees for the disposal of municipal waste. In our research, we did not address the criteria
that led the EC to evaluate municipal waste charges, but we consider it important to set the
system so that there is inversely proportional relationship between fees and recycling rates. The
new Act no. 79/2015 on waste is supposed to solve this issue of local government authorities
by extended producer responsibility for product from design to waste. According to the law,
Producer Responsibility Organizations (PROs) should represent producers, in relationship with
self-government and they are supposed to take over the existing system of municipal waste
collection in the municipality. According to research on the efficiency of waste collection
services (Soukupova, 2017) contracting out has a cost-reducing effect. The PROs bear the costs
associated with separate collection and disposal of municipal waste, and consequently will
reduce costs of municipalities. Separate collection of municipal waste will be free of charge for
citizens, and the larger the amount of municipal waste is separated the less the waste will end
up in the landfill, which should ultimately be reflected in lower charge for disposal of municipal
waste in landfill.
CONCLUSION
Waste management is an important element in regional development that can hamper the
development of the region on the one hand, but on the other hand, the proper use of waste
potential can help its development. Slovakia has large reserves in this area, which result mainly
from long-term problems concerning not only generation and disposal of waste but also the
overall approach to the waste management. Missing WMPs show that the central government
authorities, as well as local government authorities still pay little attention to waste
management.
One of the problematic areas of municipal waste management is recycling and recovery of
waste. Our analysis at regional level has shown wide differences between regions and although
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two of them BA and KE have greatly improved their results in municipal waste recovery,
mainly thanks to the modernization and reconstruction of large municipal waste incinerators,
all other regions are lagging behind. Likewise, at the level of LAU1 there are still many districts
with a large share of urban population (NR, TT, PD, TN) with poor results in waste recovery.
Waste recovery and recycling are related to the collection of separate municipal waste, which
is a major challenge for municipalities. The cost of collecting municipal waste is an important
factor that affects separate collection. Based on a survey of 15 municipalities in eastern
Slovakia, the share of separated waste is only 11% of total municipal waste after 10 years of
separate collection. The owner of a private company providing separate collection services of
municipal waste pointed out that the reason for the low separation rate is in particular
insufficient environmental education in schools, low state support and high costs of secondary
separation (Marasova, 2014). The form of delivery of waste collection services also determines
the total cost incurred by municipalities (Soukupova, 2017). PROs can be one of the ways
helping reduce the cost of municipal waste collection.
The second problem area is the amount of municipal waste generated. Districts with a high
share of the urban population show a high increase in this indicator, which of course increases
the cost of municipal waste collection, treatment, separation and landfill sites. Reducing the
amount of municipal waste generated requires comprehensive measures in its management.
Although fiscal decentralization has brought new opportunities for local self-government
authorities, the waste management has not made much of it. Under the Operational Program
Environment in the period 2007-2013 the EU funds and the state budget financed 52 projects
(83.6 million €), which concerned in particular the closure and reclamation of municipal
landfills. This process should have created on one side the pressure to reduce the amount of
waste generated and, on the other side, encourage municipalities to increase the volume of
separated waste. Our research has shown that this target has not been achieved and the total
volume of municipal waste is growing especially in districts with a high proportion of urban
population.
Preventive, educational or system programs for comprehensive solution of municipal waste are
absent in the given period, which is reflected in the current negative assessment of waste
management in Slovakia. The Waste Management Program for 2016-2020 criticizes the
treatment of biodegradable waste, which accounts for 37.5% of municipal waste, and at present
up to 70% of biodegradable waste ends in landfills. The installed infrastructure of separate
collection is inadequate and its current capacities do not allow Slovakia to achieve the
objectives set by the EC. Slovakia has only two high capacity municipal waste incinerators that
can produce electricity and heat from municipal waste. These are just some issues the municipal
waste management should especially focused on. A new Act No.79/2015 on waste should help
increase the separation rate of municipal waste as well as it should also contribute to the system
solution of the waste management. The results of the Waste Management Program measures
for 2016-2020 and some legislative changes will need to be monitored and evaluated on a
continuous basis.
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Contact information
Katarina Orsagova
Department of Economics
Faculty of Economics, Matej Bel University
Tajovskeho 10, 97590 Banska Bystrica, Slovakia
Maria Horehajova
Department of Economics
Faculty of Economics, Matej Bel University
Tajovskeho 10, 97590 Banska Bystrica, Slovakia