Slovak Republic: Selected Issues

Selected Issues

Abstract

Selected Issues

Eu Funds: Enhancing Absorption to Reduce Regional Disparities1

Slovakia has one of the highest regional disparities among European Union (EU) countries. At the same time, the country receives significant EU transfers, which are mainly devoted to foster regional convergence. However, the absorption of EU funds during the 2007–2013 programming period has been greatly delayed. This study investigates how countries can make optimal use of EU funds to reduce regional disparities. It finds that better institutions and a more educated population positively contribute to higher absorption. Moreover, a greater degree of fiscal decentralization helps increase the rate of absorption.

A. Overview of Regional Disparities in Slovakia

1. Regional disparities in Slovakia are among the highest in the OECD countries and very persistent. As measured by the regional Gini coefficient, Slovakia stands out as the country with the highest regional disparities in the European Union (EU). The regional Gini coefficient has been increasing significantly since the transition with acceleration after the crisis, resulting in the fastest growth among OECD countries (OECD 2015). More than half of the population lives in less-developed regions.

A01ufig1

Regional Gini Coefficient (2007–13)

(Index between 0 and 1)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Sources: Eurostat; and IMF staff calculations.
A01ufig2

Population with Less than Primary Education

(Y25–64, percentage)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Source: Eurostat.

2. Regional disparities in Slovakia are evident along a broad range of indicators. The average income in the East is less than half of that in Bratislava (OECD 2015), with two thirds of the unemployed living in the Eastern part of the country. The rate of participation in the labor market among the Roma, who mainly live in Central and Eastern Slovakia and often in segregated communities, is 20 percent for men and less than 10 percent for women (World Bank, 2012). Long-term unemployment is also disproportionately higher in Eastern Slovakia than in Bratislava. Education attainments show a similar pattern, given the share of population with less than a primary education being twice as high in Eastern Slovakia than in Bratislava.

A01ufig3

Long-term Unemployment

(Percent of active population)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Source: Eurostat.

3. Regional disparities are exacerbated by the lack of infrastructure. Central and Eastern Slovakia show a severe shortage of road infrastructure. The D1 motorway that connects the two major metropolitan areas, Bratislava and Kosice (in the East) has yet to be completed. In addition, workers have very low mobility, as shown by internal migration flows. In 2011, 1.6 percent of the Slovaks aged between 15 and 64 years relocated, with only a quarter moving across regions (Vagac 2013). Intra-regional roads in the East are also severely underdeveloped, making workers’ mobility and freight transportation more difficult.

A01ufig4

Motorways

(Kilometers per thousand square kilometers, 2014)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Source: Eurostat.
A01ufig5

Segregated Roma Communities in Slovakia 1/

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

1/ Legend translation: municipalities with concentrations of segregated Roma settlements

B. EU Funds in Slovakia

4. Reducing economic, social and territorial disparities across European regions and countries is the main long-term goal of the EU Cohesion Policy. Regional disparities have increased with recent enlargements, but also as a consequence of the global financial crisis. Regional disparities in GDP per capita (text chart – blue line), but also in employment rates, narrowed between 2000 and 2007. However, since the onset of the crisis in 2008, regional disparities both within and across countries have increased significantly. As noted by the EU, the crisis put a halt to the converge process across and within European countries.2

A01ufig6

Gini coefficient in the EU (2000 =100)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

5. The 2007–2013 Cohesion Policy has been designed around three new objectives: 1) Convergence (former Objective 1): boost growth in the regions with a GDP per capita less than 75 percent of the EU average. 2) Competitiveness and employment (former Objective 2): address social challenges such as globalization and transition to the knowledge based society in the more developed countries. 3) Territorial cooperation: foster cross-border cooperation.3 Member States set up ‘National Strategic Reference Frameworks’ and national and regional ‘Operational Programmes’ (OP). OPs can be seen as the priority targets and area of investments for each country or region.

A01ufig7

Objectives, Structural Funds and instruments 2007–2013

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

6. During 2007–20154, Slovakia received 12 billion euro in EU funds, equivalent to 15 percent of its GDP5 and more than 2144 euro in per capita terms. Within the Convergence objective, the ERDF and ESF funds are targeted to the regions with a GDP per capita below 75 percent of the EU average. With the exception of Bratislava, the rest of the country has been eligible for these funds. Bratislava, instead, has received financial support to improve competitiveness, support innovations, employment and social inclusion. The whole country has also been eligible for transfers from the Cohesion Fund, available to those in the EU with GDP below the 90 percent of the EU average.6 Slovakia has been participating in eleven OPs. Seven OPs are under the Convergence objectives, three OPs are multi-objective operational programs (Convergence, Regional competitiveness and Employment objective) and one operational program falls under the Regional Competitiveness and Employment objective.

A01ufig8

EU funds absorption rates

(Percent)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Sources: European Commission and IMF Staff calculation

7. Despite the large allocations, spending of EU funds at the beginning of the 2007–2013 programming period has been markedly delayed. Several factors contributed to the slow uptake of funds and therefore to the low absorption rates at the beginning of the last EU cycle. A lack of coordination in setting up the priorities across the OPs, insufficient transparency and verification of public procurement processes by the managing authorities and changes to the Public Procurement Act are among them. The Slovak authorities acknowledged that the slow uptake of EU funds at the beginning of the programming period has been the crucial factor explaining low absorption rates and that a more even spending path would amplify the growth effect of the transfers, contributing more substantially to the reduction of regional disparities.7

A01ufig9

Absorption by Sector, 2014

(Percent)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Sources: European Commission and IMF Staff estimation

8. The rate of absorption has scaled-up at the very end of the programming period. Only in recent years, and especially in 2015, Slovakia increased dramatically the uptake of EU funds. Absorption as of December 2016 was almost 96 percent.8 Slovakia performed below the EU average until the very end of the EU funds cycle.

A01ufig10

Absorption rates–2014

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

9. Absorption in Slovakia has been uneven not only across time, but also across OPs and regions. The regional and sectoral dimensions appear to be relevant when looking at absorption rates. In 2014, several infrastructure OPs show absorption rates below 60 percent, with only social infrastructure being the exception. A report by KPMG shows similar trends for OP Information Environment, OP Education and OP Bratislava Region, which present below-average absorption rates. The fragmentation across OPs has been mentioned as a possible barrier to faster absorption and this hypothesis will be tested in the empirical section of the paper.

10. The uneven absorption of EU funds and the sharp scaling-up in 2015 generated inefficiencies, reducing the potential impact of EU transfers on growth. The aid literature underlines the importance of absorptive capacity for transfers to be used productively by recipient countries and shows that projects undertaken in periods of scaling up of public investment are less likely to be successful (Presbitero 2016 and Berg et al. 2013). Anecdotal evidence shows that, at the end of the programming period, projects were chosen by the urgency to spend the allocated funds, rather than by the quality of the projects. While EU funds supported growth in the short term, by focusing on “shovel-ready” projects, their impact on potential output could have been higher, with better prioritization.9 For instance, the European Commission discusses how progress towards closing the road infrastructure gap have been slow. 10 While the motorway network improved only slightly between 2011 and 2014, the scale-up of EU funds absorption boosted construction with 56 km built in 2015 only.

11. Slovakia also incurred in financial corrections reflecting inefficiencies. In 2014, audits and control systems identified errors related to public procurement and project selection procedures. Payments for nine OPs were interrupted and only resumed in December 2015, after the application of financial corrections (169 euro million imposed by the EC and 41 euro million imposed by the Slovak authorities). 11

12. The Government Office, in a report on the evaluation of structural funds, identified the main factors affecting absorption performance and overall management of EU funds in Slovakia.12 A survey of EU transfers beneficiaries, including central public administration bodies, local and regional government bodies, entrepreneurs and NGOs, identified the following factors as affecting the implementation of Structural and Cohesion Policies:

  • Legislative framework: Frequent legislative changes and amendments to the Public Procurement law have been perceived as a problematic element affecting the ability to access EU funds. Origination of new obligations, ambiguity in the interpretation of the legislation governing the EU transfers, and excessive administration burdens have also been mentioned as difficult factors by the survey respondents.

  • Socioeconomic conditions: A lack of sufficient resources to apply for EU funds, to prepare, and co-finance the projects are considered important limitations to applications. Survey respondents mentioned lack of qualified workforce and poor transport accessibility as limiting elements. Finally, the global financial crisis negatively affected the financial capacity of transfers recipients.

  • Implementation system: Only certain types of expenditures are eligible to be financed through EU transfers. Consequently, according to some survey respondents, EU funded investments did not target the true needs of the Slovak regions.

  • Financial intensity: The lag between the expenditures and their reimbursement has been mentioned as the most problematic factor in this category. Entities with limited own resources are required to use other financial instruments (loans/guarantees) to be able to finance projects.

  • Institutional aspects: Unclear guidance and ambiguous communications on the part of the managing authority constituted a negative factor according to the survey respondents. Insufficient level of expertise and frequent changes in the staff of the managing authorities have been reported as a constraint.

  • Capacities: A lack of experienced staff and overall shortage of staff have been mentioned as significant constraints. Inadequate knowledge of the legislative process and frequent staffing changes in the managing authorities have been negatively affecting the overall process.

C. Literature Review

13. The literature on the effect of the EU transfers on growth show this impact to be modest. Sala-i-Martin (1996) started the debate showing that the regional growth and convergence pattern in the EU was not different from that observed in other federations, which lack a similarly extensive cohesion program. The subsequent papers find mixed evidence on the impact of EU transfers on growth.13 Data limitations on EU transfers at the regional level and endogeneity issues, since poor regions are more likely to receive funds and they are expected to grow faster, are the most common issues in the early literature.

14. A series of recent papers by Becker et al. exploits program evaluations techniques to estimate the causal effect of Objective 1 status on per capita GDP growth of treated regions. They find that expenses through the structural and cohesion funds induced positive average effects on per-capita income growth in those subnational regions in the EU that lagged behind the EU average. But more expenses did not generally induce proportionately larger effects. Regions respond quite heterogeneously with smaller effects found where the institutions are of poor quality and where human capital is scarce (low absorptive capacity).

15. Less is known about what factors determine the absorption of EU funds, which is the focus of this empirical study. Absorptive capacity is a well-investigated concept in the aid literature. For instance, Presbitero (2016) underlines the importance of absorptive capacity for transfers to be used productively by recipients. The paper shows that projects undertaken in periods of scaling up of public investment are less likely to be successful. As underlined by Berg et al. (2013), when investment is scaled up quickly (as often observed during a windfall), absorptive capacity constraints generated by supply bottlenecks or poor planning—can generate inefficiencies and increase costs further. 14 The aid literature generally finds that several types of bottlenecks limit the absorptive capacity, implying that there are diminishing returns to aid (Rajan and Subramanian 2008, Clemens et al. 2012). Moreover, donors’ fragmentation correlates with a lower impact of aid on growth because of higher transaction costs and increased corruption (Easterly (2007) and Djankov et al. (2009)).

A01ufig11

Distribution of the Quality of Government Index

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

D. Data and Empirical Analysis

16. The scope of this section is to investigate the determinants of regional absorptive capacity, building on the analysis by Becker et al. (2013). The empirical analysis will test first the assumption that better quality of government and a more educated population correlate with higher absorption. Furthermore, different aspects of the quality of government index will be considered, controlling for the level of fiscal decentralization as well.

17. The study gathers data from different sources. Data on the allocations and expenditures at the regional level (NUTS2)15 are available from the European Commission for the 28 EU countries.16 Data for NUTS2 covariates are from the Quality of Government Database17, which collects data from different sources and computes the European Quality of Government Index (EQI). The latter is the result of a survey conducted in 2013 on corruption and governance at the regional level within the EU. The survey focuses on both perceptions and experiences with public sector corruption, along with the extent to which citizens believe various public sector services are impartially allocated. The EQI data are built on 16 survey questions, aggregated from the individual to the regional level. There are three main concepts around which the questions are framed: quality, impartiality and corruption.18

18. Regional absorptive capacity is defined as the percentage of funds paid compared to total available budget during the original programming period. Expenditures and allocations are the cumulative sum from 2007 to 2013 for country i, region r and sector s. 19

Absirs20072013=Expendituresirs20072013Allocationsirs20072013

Higher values of the ratio will identify sector/region where spending has been relatively more front-loaded, while lower values of the ratio indicates the presence of absorptive capacity constraints, as spending is strongly back-loaded, and even done the year after the end of the allocation period.

19. A panel regression with fixed effects is estimated.

Absirs2013=α+βXir+λs+φi+uirs

where Xir is a vector of regional institutional and macroeconomic characteristics (including economic performance, quality of regional government, human capital endowment, etc.), while country φi and sector λrs fixed effect control for unobserved heterogeneity in the absorptive capacity at the country level and sectoral level.20 Therefore, the relationship between absorption and the covariates is identified by exploiting the variation across regions within a country controlling for each sector’s absorptive capacity. To decide which is the best proxy for human capital, a number of alternatives were considered. The population between 25 and 64 with upper secondary and post-secondary non-tertiary education (ISCED level 3 and 4) showed up as the variable with the best explanatory power among the “human capital” proxies.

A01ufig12

Quality of Government Pillars 1/

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Sources: The Quality of Government EU Regional Dataset.1/ The Quality of Government Index is built on 16 survey questions. The questions are framed around three central concepts of corruption, impartiality and quality. See European Commission, Regional Governance Matters, 2012 for details on the construction of the Index.
A01ufig13

Different dimensions of the Quality of Government Index

(Percent)

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

Sources: Quality of Government Database

Baseline results

article image
Clustered standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

20. Results show that better institutions and higher education improve absorption. This result confirms the hypothesis of Becker et al. (2013) that only those regions with sufficient human capital and good-enough institutions—are able to turn transfers into faster per capita income growth and per capita investment. The lack of qualified staff was also mentioned in the Government survey as one of the constraints towards better absorption of EU funds. More specifically, if Eastern Slovakia were to improve its Quality of Government Index to the level of EU average (from 47 to 58), absorption would increase by 2.64 percentage points.21

21. The quality of institutions plays a strong explanatory role. The European Quality of Government Index (EQI) is opened-up along its three dimensions: Corruption, Impartiality and Quality. While the Corruption and Quality pillars are relatively straightforward to interpret, the Impartiality pillar need some clarifications. The index of impartiality (Impartial Public Administration) measures to what extent government institutions exercise their power impartially. The definition of impartiality is the following: “when implementing policies, public sector employees should not take anything about the citizen/case into consideration that is not stipulated in the policy”. The empirical results show that the corruption pillar is negatively correlated with absorption (a higher index means lower corruption), whereas the quality pillar displays a positive correlation. Interestingly, the impartiality pillar shows a strong negative correlation. This suggests that if public sector employees do not allow exceptions about procedures or legal processes, this could result in lower absorption. This finding might raise the issue of the administrative burden associated with EU transfer implementation.22 As stressed by the authorities, origination of new obligations, ambiguity in the interpretation of the legislation governing the EU transfers, and excessive administrative burdens constituted barriers to higher absorption.

22. Fiscal decentralization is also an important factor. The ratio of local-to-central government expenditure enters the regression with a positive sign, suggesting that higher fiscal decentralization helps achieve a more efficient spending. Moreover, there is some evidence that a higher degree of fiscal decentralization reinforces the positive effect of good institutions on the absorptive capacity.

23. EU funds fragmentation across operational programs might give rise to coordination issues reducing the efficiency of absorption. Easterly (2007) and Djankov et al. (2009) use a similar strategy to study the effect of aid donors’ fragmentation on growth. These latter argue that when multiple donors are involved, coordination problems might arise increasing corruption. These considerations regarding aid fragmentation across several donors are relevant for the management of EU funds through different OPs. Slovakia has in fact reduced the number of OPs for the 2014-2020 programming period, with respect to the 2007–2013 one. To test for the inefficiencies posed by the dispersion of funds across too many OPs, the baseline specification is augmented with the variable FRAGir, an index of OPs fragmentation at the regional level is constructed as:

A01ufig14

Marginal effect of Quality of Government

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

FRAGir=1Σs=1NSs2

Where Σs=1NSs2 is the Herfindal-Hirschman index of OPs fragmentation. ss is the share of allocation to a certain OPs with respect to the total allocations in a certain NUTS2 region (see chart below). The same variable is computed at the country level (see chart below). The rate of fragmentation in Slovakia is comparable to peers.

A01ufig15

Fragmentation by Operational Program at the NUTS2 level

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

A01ufig16

Fragmentation of EU funds Allocations across OPs

Citation: IMF Staff Country Reports 2017, 072; 10.5089/9781475587937.002.A001

24. The empirical analysis does not find strong support for the hypothesis that more fragmented funds leads to lower absorption. Several specifications, augmented with the rate of fragmentation of EU allocations and expenditures across EU funds at the NUTS2 level, did not produce significant results. This is also true when restricting the sample to new member states only. This non-results might be explained by the relatively low variation in the fragmentation variable.

E. Conclusion

25. This paper attempts to estimate the determinants of absorptive capacity of EU transfers at the regional level. It finds that higher quality of government and a more educated population lead to better absorption of EU funds. In addition, there is evidence that more decentralized spending has a positive impact on the level of absorption. This finding has important implications for the strategies that Slovakia should adopt in order to accelerate fund absorption during the 2014–2020 programming period. Regions with a sufficient level of human capital and with good-enough institutions are more likely to spend the allocated funds in an efficient way and to transform them into growth. Putting in place the appropriate administrative and governance capacities, fighting corruption should therefore be the priority in order to absorb faster, but also to choose higher quality projects. The econometric analysis also tested the role of allocations and expenditures fragmentation, but does not find strong support for the hypothesis that higher OPs fragmentation leads to lower absorption.

26. The empirical results are in line with the findings of the survey conducted by the authorities. Lack of qualified staff, insufficient level of expertise and frequent changes in the staff of the managing authorities, and changes in public procurement law have been mentioned by the Slovak authorities as the most problematic elements in affecting EU funds spending across the country. Moreover, anecdotal evidence suggests that financial and legal illiteracy in some segments of the population might constitute a barrier to apply for EU funds and comply with implementation rules. Technical support for small entrepreneurs could mitigate this issue.

27. The authorities took some measures to improve EU funds management, but challenges remain for the current programming period. The Slovak authorities successfully negotiated thematic areas for the 2014–2020 cycle very early on in the programing period. However, the absorption rates are currently very low (below 5 percent at the end of 2016) and the authorities are still in the process to meet ex-ante conditionality requirements imposed by the European Commission. These requirements are key prerequisite for efficient drawing of funds and when they are not fulfilled, payments can be suspended. Nonetheless, some concrete steps have been taken to improve project implementation. For instance, an electronic system to exchange data between managing authorities and EU funds beneficiaries has been put in place to monitor and evaluate the whole process. The managing authorities started to collaborate with regional offices to offer technical assistance and free consultations to help applicants with the application process. The recently adopted National Public Procurement Package is supposed to facilitate the application and disbursement process. Finally, the number of OPs has been reduced.23

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1

Prepared by Francesca Caselli. We are grateful to the authorities, and in particular to Stefan Domonkos, for useful inputs and comments, and for sharing the Map based on the Atlas of Roma Communities. We thank the European Commission DC Regio, and in particular Violeta Piculescu, for guidance on the EU funds data.

2

Investment for jobs and growth. Promoting development and good governance in EU regions and cities. Sixth report on economic, social and territorial cohesion. http://ec.europa.eu/regional_policy/sources/docoffic/official/reports/cohesion6/6cr_en.pdf

4

Structural and Cohesion Funds (SCF) allocations are budgeted over 7-year program periods. Funds that are not drawn within the pertinent deadlines (two years (T+2) or three years (T+3)) are generally lost for recipients. EU Funds in Central and Eastern Europe,

7

Assessment of Cohesion Policy Impacts on the Development of Slovakia Using a Suitable Econometric Model, Evaluation Report 2014, Slovak Government.

9

IMF Regional Economic Issues Fall 2015 and Assessment of Cohesion Policy Impacts on the Development of Slovakia Using a Suitable Econometric Model, Evaluation Report 2014.

11

Communication from the Commission protection of the EU Budget to end 2014, http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52015DC0503

12

“Evaluation of Contribution of implementing Structural Funds and Cohesion Fund to reduce Regional Disparities in Slovakia” Final Report, Government Office of the Slovak Republic, September 2015.

13

Boldrin and Canova (2001) reach similar conclusions comparing regions receiving and not-receiving the funds. On the contrary, Midelfart-Knarvik and Overnman (2002) and Beugelsdijk and Eijffinger (2005) find a positive effect of EU transfers at the country level on industry agglomeration and on GDP per capita, respectively. At the regional level Cappelan, Castellacci, Fagerberb and Verspagen (2003) and Ederveen, Gorter, de Mooij and Hahuis (2002) estimate a positive effect of structural funds on regional growth, whereas Dall’Erba and Gallo (2008) do not support this conclusion.

14

See also Collier and others (2010), van der Ploeg (2012), and Buffie and others (2012).

15

Nomenclature of Territorial Units for Statistics.

19

The 12 sectors refer to the 12 OPs: Business Support, Energy, Environment and natural resources. Human resources, IT infrastructure and services, Research and Technology, Social Infrastructure, Technical assistance, Tourism and Culture, Transport infrastructure, Urban and rural regeneration and Other.

20

Standard errors are clustered at the country level. The RHS variables are as of 2010, since the QOG index at the NUTS2 level is not available before.

21

From specification in column 3.

22

Calculated with the sample available, not all the EU countries are included.

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1

Prepared by John Ralyea with assistance from Luisa Calixto and Dustin Smith. Thanks to the authorities and European Commission staff for their insightful comments.

3

Pensioners’ inflation follows a particular basket of goods that reflects preferences of the elderly population. For the 2015 Ageing Report pensioners’ inflation was projected to exceed consumer price inflation by 0.003/year.

4

The ceiling on pension benefits is 3 times the average wage.

5

In the short-and medium-term the low projected Pillar II participation reduces the amount of projected contribution transfers from Pillar I to Pillar II.

6

The EC used a Cobb-Douglas function to calculate potential output. In the short run, labor and TFP inputs to the function are adjusted for the business cycle. Constant returns to scale are assumed, with labor’s share of gross value added (GVA) being 65 percent. The latter assumption is likely too high for Slovakia, where total labor compensation is probably closer to 50-60 percent of GVA.

7

In the short to medium term, labor productivity growth is projected to average 2.9 percent per year from 2013–30. This is more than 50 percent higher than the observed average annual labor productivity growth of 1.8–1.9 percent since the 2008 global financial crisis. (See Labor Productivity: Developments and Outlook, Annex I in the accompanying Staff Report.)

8

The minimum participation period was 10 years between 2005-2007. From January 1, 2008, to October 31, 2011, it was increased to 15 years. The minimum period was reset to 10 years again from November 2011 to December 2014. Since 2015, there is no minimum participation period. The only condition to meet before drawing a Pillar II pension is reaching the retirement age (early retirement is also possible under certain conditions).

9

From a projection standpoint, a low assumed participation rate in Pillar II implies lower projected transfers of annual social contributions from Pillar I to Pillar II.

10

New legislation, effective from 2017, allows savers in the 2nd pension pillar to make a one-off withdrawal of their savings upon retiring. The amount eligible for withdrawal depends on their pension from other sources (mainly the first pillar). The use of this provision is extremely uncertain in part because the track record of benefit payments from Pillar II is extremely short. The first benefits were paid in 2015. That being said, the new provision could increase the attractiveness of the Pillar II scheme.

11

The European Commission has also analyzed potential risks to pension spending based on various scenarios. Please see: Pension sustainability in the euro area – fiscal risks associated to demographic and macroeconomic uncertainties and policy options–Issues Note.

12

The Ageing Report’s risk scenario for lower TFP growth assumes that long-run TFP growth for EU countries will be 0.8 percent per year instead of one percent. This assumption leads to an increase in Slovakia’s pension expenditure by 0.4 percentage points over the projection horizon relative to the baseline scenario.

13

Over the 2008–15 period, the net reduction in Pillar II participants was about 16 percent as new entrants to the labor force continued to join Pillar II.

14

Deaths that could be avoided by high-quality healthcare.

15

The baseline reflects the decision at the time of the 2012 pension reforms to gradually move benefit indexation method from a mix of nominal wage and price changes to being solely based changes in pensioner’s prices.

16

Please see the EC’s The 2016 Joint Report on Health Care and Long-term Care Systems and Fiscal Sustainability, Vol. 2, pp. 223-232, for further suggestions for reforms to improve health care in Slovakia.

Slovak Republic: Selected Issues
Author: International Monetary Fund. European Dept.