## cr1772

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---

### A. Overview of Regional Disparities in Slovakia
- Slovakia has one of the highest regional disparities among OECD countries; 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.
- Income and labor-market gaps:
  - The average income in the East is less than half of that in Bratislava (OECD 2015).
  - Two thirds of the unemployed live in the Eastern part of the country.
  - Labor market participation among the Roma (mainly in Central and Eastern Slovakia): 20 percent for men and less than 10 percent for women (World Bank, 2012).
- Education and unemployment spatial patterns:
  - Share of population with less than primary education is twice as high in Eastern Slovakia than in Bratislava.
  - Long-term unemployment is disproportionately higher in Eastern Slovakia than in Bratislava.
- Infrastructure gaps:
  - Central and Eastern Slovakia show a severe shortage of road infrastructure.
  - The D1 motorway connecting Bratislava and Kosice has yet to be completed.
  - Internal migration in 2011: 1.6 percent of Slovaks aged between 15 and 64 relocated, with only a quarter moving across regions (Vagac 2013).

### B. EU Funds in Slovakia: Allocations, Absorption, and Implementation Issues
- Policy context and eligibility:
  - 2007–2013 Cohesion Policy objectives: 1) Convergence (GDP per capita < 75 percent of EU average), 2) Competitiveness and employment, 3) Territorial cooperation.
  - Slovakia participated in eleven OPs: seven OPs under Convergence, three multi-objective OPs, and one OP under Regional Competitiveness and Employment.
- Allocations and macro scale:
  - During 2007–2015, Slovakia received 12 billion euro in EU funds, equivalent to 15 percent of its GDP and more than 2144 euro per capita.
  - Except Bratislava, the rest of the country was eligible under the Convergence objective; Bratislava received support under Regional Competitiveness and Employment.
- Absorption performance and timing:
  - Spending of EU funds during the 2007–2013 programming period was greatly delayed at the beginning.
  - Absorption scaled up dramatically at the very end of the programming period; absorption as of December 2016 was almost 96 percent.
  - Slovakia performed below the EU average until the very end of the EU funds cycle.
- Uneven absorption across OPs and regions:
  - In 2014, several infrastructure OPs showed absorption rates below 60 percent; social infrastructure was an exception.
  - OP Information Environment, OP Education, and OP Bratislava Region presented below-average absorption rates (per KPMG).
  - Fragmentation across OPs identified as a possible barrier to faster absorption.
- Consequences of delayed and uneven absorption:
  - Sharp scaling-up in 2015 generated inefficiencies; projects chosen by urgency to spend rather than by quality.
  - Example: motorway network improved only slightly between 2011 and 2014; scale-up of EU funds absorption boosted construction with 56 km built in 2015 only.
- Financial corrections and audit issues:
  - In 2014 audits identified errors related to public procurement and project selection; payments for nine OPs were interrupted and resumed in December 2015.
  - Financial corrections imposed: 169 euro million by the EC and 41 euro million by the Slovak authorities.
- Government Office evaluation survey—factors affecting absorption:
  - Legislative framework: Frequent legislative changes and amendments to the Public Procurement law; origination of new obligations, ambiguity, and excessive administrative burdens.
  - Socioeconomic conditions: Lack of sufficient resources to apply for EU funds, prepare, and co-finance projects; lack of qualified workforce; poor transport accessibility; negative impact of the global financial crisis.
  - Implementation system: Only certain types of expenditures eligible; perception that EU funded investments did not target true regional needs.
  - Financial intensity: Lag between expenditures and reimbursement problematic; entities required to use loans/guarantees.
  - Institutional aspects: Unclear guidance and ambiguous communications from managing authority; insufficient expertise and frequent staff changes.
  - Capacities: Lack of experienced staff and overall shortage of staff; inadequate knowledge of legislative process and frequent staffing changes in managing authorities.

### C. Definition, Measurement, and Econometric Strategy for Regional Absorptive Capacity
- Definition:
  - Regional absorptive capacity is defined as the percentage of funds paid compared to total available budget during the original programming period.
  - 퐴푏푠 푖푟푠2007−2013 = 퐸푥푝푒푛푑푖푡푢푟푒푠 푖푟푠2007−2013 / 퐴푙푙표푐푎푡푖표푛푠 푖푟푠2007−2013
  - Higher values identify sector/region where spending has been relatively more front-loaded. Lower values indicate absorptive capacity constraints, with spending strongly back-loaded.
- Empirics:
  - Panel regression with fixed effects: 퐴푏푠 푖푟푠2013 = 훼 + 훽 푋 푖푟 + 휆 푠 + 휙 푖 + 푢 푖푟푠
    - X_ir: vector of regional institutional and macroeconomic characteristics (including economic performance, quality of regional government, human capital endowment, etc.).
    - Country fixed effects: φ_i.
    - Sector fixed effects: λ_rs.
  - Identification exploits variation across regions within a country while controlling for each sector’s absorptive capacity.
  - Human capital proxy selected: population 25–64 with upper secondary and post-secondary non-tertiary education (ISCED level 3 and 4).
  - RHS variables are as of 2010; standard errors clustered at the country level.
  - 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.

### D. Baseline Results and Key Empirical Findings
- Main findings:
  - Better institutions and higher education improve absorption.
  - 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.
- Quality of Government (EQI) dimensions:
  - Corruption pillar: negatively correlated with absorption (a higher index means lower corruption).
  - Quality pillar: displays a positive correlation with absorption.
  - Impartiality pillar: shows a strong negative correlation with absorption; suggests strict procedural non-exceptions may reduce absorption, indicating potential administrative burden in EU transfer implementation.
- Fiscal decentralization:
  - The ratio of local-to-central government expenditure enters the regression with a positive sign, suggesting that higher fiscal decentralization helps achieve more efficient spending.
  - Evidence that a higher degree of fiscal decentralization reinforces the positive effect of good institutions on absorptive capacity.
- Fragmentation of EU funds across OPs:
  - Fragmentation index at regional level defined as: 퐹푅퐴퐺 푖푟 = 1 − ∑_{s=1}^{N} s_{s}^{2}, where ∑_{s} s_{s}^{2} is the Herfindal-Hirschman index of OPs fragmentation and s_{s} is the share of allocation to a certain OP with respect to total allocations in a NUTS2 region.
  - The rate of fragmentation in Slovakia is comparable to peers.
  - The empirical analysis does not find strong support for the hypothesis that more fragmented funds leads to lower absorption. Several specifications augmented with the fragmentation rate at NUTS2 level did not produce significant results, including when restricting the sample to new member states only. This non-result might be explained by relatively low variation in the fragmentation variable.

### E. Selected Regression Coefficients and Statistics (preserved)
- Log of GDP per capita: -3.52 (3.90), 1.17 (3.35), -0.91 (3.19), 0.55 (2.78), -8.88** (3.35)
- Log of area: -0.89 (1.05), -0.70 (0.61), -1.03 (1.11), -1.22 (1.16), -3.25*** (0.97)
- Pop.25-64y.o by ed.at.lev.,%, Up-sec and post-sec non-ter educ (lev 3 and 4): 0.69** (0.27), 0.65* (0.33), 0.35 (0.28), -0.15 (0.11)
- Corruption Pillar of EQI Index: 8.36*** (2.45)
- Impartiality Pillar of EQI Index: -8.20*** (2.90)
- Quality Pillar of EQI Index: 4.44** (1.85)
- Normalized EQI Index: 0.31*** (0.11), 0.24*** (0.07), 0.28** (0.10)
- Fiscal decentralization: 0.39** (0.15)
- Observations: 1,128; 1,955; 1,128; 999; 998 (across specifications)
- Country fixed effects: YES (in most specifications)
- Sector fixed effects: YES (in all specifications)
- Significance notation: *** p<0.01, ** p<0.05, * p<0.1

### F. Policy Implications, Conclusions, and Government Actions
- Conclusions:
  - Higher quality of government and a more educated population lead to better absorption of EU funds.
  - More decentralized spending has a positive impact on absorption.
  - Regions with sufficient human capital and good-enough institutions are more likely to spend allocated funds efficiently and transform them into growth.
- Policy priorities:
  - Put in place appropriate administrative and governance capacities.
  - Fight corruption.
  - Choose higher quality projects rather than projects driven solely by urgency to absorb funds.
- Authorities’ measures and remaining challenges:
  - Negotiated thematic areas for 2014–2020 early in the programming period.
  - Absorption rates were very low (below 5 percent at the end of 2016).
  - Authorities still in the process of meeting ex-ante conditionality requirements imposed by the European Commission; when unfulfilled, payments can be suspended.
  - Steps taken: electronic system to exchange data between managing authorities and beneficiaries to monitor and evaluate; collaboration with regional offices to offer technical assistance and free consultations; recently adopted National Public Procurement Package aimed to facilitate application and disbursement process; reduction in number of OPs.
- Persistent constraints (survey and anecdotal evidence):
  - Lack of qualified staff, insufficient expertise, frequent changes in managing-authority staff, changes in public procurement law.
  - Financial and legal illiteracy in some population segments may hinder applications and compliance; technical support for small entrepreneurs could mitigate this.

### G. Projected Age-Related Spending and Headline Figures
- Health and long-term care and pension spending is projected to reach 18.5 percent of GDP in 2060, according to the Ageing Report.
- The EC and the authorities project health and long-term care and pension expenditures to rise 4.5 percentage points of GDP by 2060.
- A worst case scenario presented by the EC indicates total age-related expenditures could reach 25 - 30 percent of GDP, up to 40 percent higher than the baseline.
- Slovakia’s long-term care expenditures are currently low at 0.2 percent of GDP.

### H. Pension Reforms Reflected in the 2017 Budget and Projected Dynamics
- Major 2012 changes:
  - Unification of male and female retirement ages by 2024.
  - Indexation of the retirement age to life expectancy at retirement starting in 2017.
  - Transition from a 50/50 wage/price inflation indexation method to pensioners’ inflation starting in 2018.
- Assessment base for pension contributions:
  - Increased from 4 to 5 times the average economy-wide wage.
  - In 2017, the assessment base increased to 7 times the average wage.
- The ceiling on pension benefits is 3 times the average wage.
- Changes apply to both Pillar I (public defined-benefit PAYG) and Pillar II (private defined-contribution).
- Projected dynamics:
  - Pension expenditures dip initially but then rise as the “baby boom” generation starts to retire in 2035.
  - Assumed Pillar II participation: 10 percent for new labor market entrants (contrasted with 75 percent participation among existing contributors aged 35).
  - The model suggests pension expenditures will be 0.5 percentage points of GDP higher by 2060 relative to the Ageing Report (equivalent to 0.01 percent of GDP a year).
  - Updated model (base year advanced to 2015, IMF projections through 2020 used) implies an increase in pension expenditures-to-GDP of 0.4 percentage points by 2060, relative to the calibrated increase of 2.6 percent of GDP.

### I. Uncertainty, Downside Risks, and Scenario Analysis
- Key uncertainties:
  - Possible over-estimation of total factor productivity (TFP) growth.
  - Large uncertainty surrounding the government’s intentions and rules regarding Pillar II.
  - Frequent changes to Pillar II parameters and multiple “openings” create participation uncertainty and asset-transfer volatility.
- TFP assumptions and concerns:
  - Ageing Report projects Slovakia’s TFP growth averages 2.3 percent from 2013–30 — the highest in the EU.
  - The Ageing Report assumes long-run TFP rates converge to 1 percent, implying labor productivity converges to 1.5 percent.
  - Historical: since 1995 annual TFP growth averaged 2 percent; more recently slowed to 1.8 percent.
  - If recent TFP growth (1.8 percent) prevailed until 2030, potential GDP would be permanently 9 percent lower relative to Ageing Report projections.
  - Aging could reduce TFP: a five-percentage point increase in share of workers aged 55–64 is associated with a decrease in TFP of between two and four percent; for Slovakia this implies a decrease in TFP of 4 to 8 percent by 2045.
- Pillar II uncertainty and effects:
  - Rules governing entry and contribution rates have changed frequently since 2005; minimum participation period varied and was abolished in 2015.
  - Four “openings” allowed exits/entries without penalties; about 420 thousand pensioners exited Pillar II transferring EUR 1.1 billion to Pillar I.
  - High bond allocation (75 percent) and regulatory/market changes have flattened per capita Pillar II asset growth.
  - One-off withdrawal provision effective from 2017 may affect attractiveness; first Pillar II benefits began in 2015.
  - If another 20-30 percent of existing Pillar II participants leave before 2025, pension expenditures could increase by a cumulative 0.2-0.4 percent of GDP over the projection horizon.
- Scenario impacts (selected figures):
  - Public pension/GDP, 2060:
    - Ageing Report baseline: 10.2
    - Updated 2/: 11.0
    - Lower TFP by 0.25 p.p. annually: 12.2
    - Lower Pillar II participation by 25 percent: 11.2
  - Cumulative change 1/ (percentage points):
    - Ageing Report baseline: 2.1
    - Updated 2/: 3.0
    - Lower TFP by 0.25 p.p. annually: 4.3
    - Lower Pillar II participation by 25 percent: 3.3
  - If both alternative scenarios materialize together, pension expense to GDP could increase by a cumulative 1.5 percentage points, on top of the 3 percentage point updated baseline, implying a pension expenditure equivalent to about 12.5 percent of GDP in 2060.

### J. Potential Savings from Further Pension Reforms and Risks from Ad-hoc Changes
- Illustrative potential expenditure savings (percentage points of GDP, 2016–60):
  - Total potential savings from implementing further parametric pension reforms: 1.8 - 2.8
  - Change in valorization formula (weight CPI at 25 percent): 0.6 - 0.8
  - Change in calculation of contribution base (annual assessment): 0.2 - 0.3
  - Link retirement age more closely to life expectancy: 1.0 - 1.5
- Specific reform options and quantified impacts:
  - Tighter link to changes in life expectancy: could reduce pension expenditure by 0.8 percent of GDP in 2060.
  - Valorization formula (25/75 CPI/wage): could yield pension expenditure reduction in the range of 1.0 to 1.5 percent of GDP.
  - Annual assessment base: could increase annual contributions by 0.2-0.3 percent of GDP.
  - Revenue-side options: removing the cap on employee pension contributions; taxing pension earnings above a certain income threshold.
- Risks from ad-hoc policy changes:
  - 2017 budget increases old-age pension benefits by a fixed amount equivalent to 2 percent of the average pension, exceeding the baseline by EUR 110–120 million.
  - Introduction in July 2015 of a minimum pension for pensioners with 30 and more qualified years of pension insurance: estimated annual cost EUR 25-30 million.
  - These ad-hoc changes have added between EUR 135–150 million to annual pension expenditures (0.1–0.2 percent of GDP).

### K. Health Expenditure: Recent Developments, Projections, and Efficiency Measures
- Current and projected spending:
  - General government spends about 5.2 percent of GDP annually on health care.
  - Health care spending projected to increase 40 percent by 2060, due primarily to Slovakia’s rapidly aging population.
- Outcomes:
  - Rate of amenable mortality was 17 percent higher than comparable countries and 93 percent higher the EU average (Ministry of Finance, 2016).
- Expenditure review and short-term target:
  - Government commissioned an expenditure review of health spending in 2016 conducted by Ministry of Finance with joint assistance from the IMF, EC, and OECD.
  - Authorities established a target of no real increase in general government health spending from 2017–19.
- Estimated savings and efficiency gains:
  - Finance ministry estimates savings and efficiency gains worth about 0.5 percent of GDP from the expenditure review.
  - Of the total potential savings in healthcare, some EUR 270 million could be realized in public health insurance spending.
  - Three areas identified for higher spending efficiency: drugs, medical equipment and radiology and laboratories.
  - Oversight of implementation assigned to a new Implementation Unit in the Office of the Deputy Prime Minister.
- Structural reform needs:
  - Need to transition from a hospital-centered and disaggregated health care model to a primary care-centered health system with integrated health care provision to ensure cost-containing measures translate into long-term cost growth reduction.
- Governance and implementation recommendations:
  - Set out clear procedures to support the oversight mandate of the new Implementation Unit, including frequency and nature of reporting by line ministries on progress.
  - Significantly strengthen the role of the Budget Department in the Ministry of Finance to ensure identified measures are effectively integrated into the budget.
  - Require line ministries, including the Ministry of Health, to set out clear plans with realistic timelines for implementing savings measures, including continuous engagement with stakeholders and identifying legislation requirements.
  - Expand current efforts to centralize health procurement to more products.

### L. Long-Term Fiscal Implications and Policy Priorities
- Combined risk impact:
  - Two alternative pension risk scenarios could raise pension expenditure by a cumulative 1.5 percentage points on top of the 3 percentage point updated baseline increase, implying pension expenditure of about 12.5 percent of GDP in 2060.
- Policy priorities to mitigate risks:
  - Implement existing reforms and consider further reforms to the pension system.
  - Enhance TFP growth through measures such as reforms to the legal system and steps to improve the protection of property rights.
  - Improve the quality of public institutions and the education system to boost productivity growth.
  - Maintain political resolve not to open up the Pillar II system again as a risk-mitigating measure.
  - Fiscal consolidation and rigorous implementation of the 2012 pension reforms are critical to prepare Slovakia for fiscal pressures from aging.

*IMF staff compilation from "EU FUNDS: ENHANCING ABSORPTION TO REDUCE REGIONAL DISPARITIES" (February 23, 2017) and related sections in cr1772 as presented in the supplied content unit.*

### References ______________________________________________________________________________ 13

### cr1772 - References ______________________________________________________________________________ 13

### A. Overview of Regional Disparities in Slovakia
- Slovakia has one of the highest regional disparities among OECD countries; 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.
- Income and labor-market gaps:
  - The average income in the East is less than half of that in Bratislava (OECD 2015).
  - Two thirds of the unemployed live in the Eastern part of the country.
  - Labor market participation among the Roma (mainly in Central and Eastern Slovakia): 20 percent for men and less than 10 percent for women (World Bank, 2012).
- Education and unemployment spatial patterns:
  - Share of population with less than primary education is twice as high in Eastern Slovakia than in Bratislava.
  - Long-term unemployment is disproportionately higher in Eastern Slovakia than in Bratislava.
- Infrastructure gaps:
  - Central and Eastern Slovakia show a severe shortage of road infrastructure.
  - The D1 motorway connecting Bratislava and Kosice has yet to be completed.
  - Internal migration in 2011: 1.6 percent of Slovaks aged between 15 and 64 relocated, with only a quarter moving across regions (Vagac 2013).
- Motorway density metric presented as: Kilometers per thousand square kilometers, 2014 (chart referenced).

### B. EU Funds in Slovakia
- Policy context:
  - 2007–2013 Cohesion Policy designed around three objectives: 1) Convergence (GDP per capita < 75 percent of EU average), 2) Competitiveness and employment, 3) Territorial cooperation.
  - Member States set up National Strategic Reference Frameworks and Operational Programmes (OP).
- Allocations and eligibility:
  - During 2007–2015, Slovakia received 12 billion euro in EU funds, equivalent to 15 percent of its GDP and more than 2144 euro per capita.
  - Except Bratislava, the rest of the country was eligible under the Convergence objective; Bratislava received support under Regional Competitiveness and Employment.
  - Slovakia participated in eleven OPs: seven OPs under Convergence, three multi-objective OPs, and one OP under Regional Competitiveness and Employment.
- Absorption performance and timing:
  - Spending of EU funds during the 2007–2013 programming period was greatly delayed at the beginning.
  - Absorption scaled up dramatically at the very end of the programming period; absorption as of December 2016 was almost 96 percent.
  - Slovakia performed below the EU average until the very end of the EU funds cycle.
- Uneven absorption across OPs and regions:
  - In 2014, several infrastructure OPs showed absorption rates below 60 percent; social infrastructure was an exception.
  - OP Information Environment, OP Education, and OP Bratislava Region presented below-average absorption rates (per KPMG).
  - Fragmentation across OPs identified as a possible barrier to faster absorption.
- Consequences of delayed and uneven absorption:
  - Sharp scaling-up in 2015 generated inefficiencies; projects chosen by urgency to spend rather than by quality.
  - Example: motorway network improved only slightly between 2011 and 2014; scale-up of EU funds absorption boosted construction with 56 km built in 2015 only.
- Financial corrections and audit issues:
  - In 2014 audits identified errors related to public procurement and project selection; payments for nine OPs were interrupted and resumed in December 2015.
  - Financial corrections imposed: 169 euro million by the EC and 41 euro million by the Slovak authorities.
- Factors identified by Government Office evaluation survey affecting absorption:
  - Legislative framework: Frequent legislative changes and amendments to the Public Procurement law; origination of new obligations, ambiguity, and excessive administrative burdens.
  - Socioeconomic conditions: Lack of sufficient resources to apply for EU funds, prepare, and co-finance projects; lack of qualified workforce; poor transport accessibility; negative impact of the global financial crisis.
  - Implementation system: Only certain types of expenditures eligible; perception that EU funded investments did not target true regional needs.
  - Financial intensity: Lag between expenditures and reimbursement problematic; entities required to use loans/guarantees.
  - Institutional aspects: Unclear guidance and ambiguous communications from managing authority; insufficient expertise and frequent staff changes.
  - Capacities: Lack of experienced staff and overall shortage of staff; inadequate knowledge of legislative process and frequent staffing changes in managing authorities.
- References to documents and datasets cited in this section (names and URLs retained in source).

### C. Literature Review
- Overall assessment:
  - Literature on the effect of EU transfers on growth shows the impact to be modest; mixed evidence across studies.
  - Early literature challenged by data limitations at the regional level and endogeneity (poor regions more likely to receive funds and expected to grow faster).
- Key findings from cited studies:
  - Sala-i-Martin (1996): regional growth and convergence in the EU not different from other federations lacking similar cohesion programs.
  - Becker et al. (series): structural and cohesion funds induced positive average effects on per-capita income growth in lagging subnational regions, but more expenses did not generally induce proportionately larger effects; heterogeneous regional responses with smaller effects where institutions are of poor quality and human capital is scarce (low absorptive capacity).
  - Aid literature parallels: absorptive capacity important for productive use of transfers (Presbitero 2016); scaling up of public investment may reduce project success and increase inefficiencies (Berg et al. 2013).
  - Donor fragmentation associated with lower aid impact due to higher transaction costs and increased corruption (Easterly 2007; Djankov et al. 2009).
  - Diminishing returns to aid where bottlenecks limit absorptive capacity (Rajan and Subramanian 2008; Clemens et al. 2012).
- Mixed results in regional and country-level studies cited (examples of contrasting findings retained from source).

### D. Data and Empirical Analysis
- Objective:
  - Investigate determinants of regional absorptive capacity, building on Becker et al. (2013).
  - Test assumption that better quality of government and a more educated population correlate with higher absorption; consider aspects of the quality of government index and control for fiscal decentralization.
- Data sources and measures:
  - Allocations and expenditures at regional level (NUTS2) from the European Commission for the 28 EU countries; expenditures are European Commission payouts.
  - NUTS2 covariates from the Quality of Government Database, which computes the European Quality of Government Index (EQI) based on a 2013 survey on corruption and governance at the regional level within the EU.
  - EQI built on 16 survey questions aggregated to the regional level; three main concepts: quality, impartiality and corruption.
  - Nomenclature note: NUTS2 = Nomenclature of Territorial Units for Statistics.
- Empirical strategy notes:
  - The study will test correlations between absorption rates and EQI, education, and fiscal decentralization.
  - Distribution of the Quality of Government Index presented (normalized EQI index chart referenced).
- Citations and data links referenced in source (URLs and database names retained in source).

*Italic: IMF staff compilation from "EU FUNDS: ENHANCING ABSORPTION TO REDUCE REGIONAL DISPARITIES" (February 23, 2017) as presented in the supplied content unit.*

### 18.      Regional absorptive capacity is defined as the percentage of funds paid compared to

### cr1772 - 18.      Regional absorptive capacity is defined as the percentage of funds paid compared to

### Definition and measurement of regional absorptive capacity
- 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.
- Formula:
  - 퐴푏푠 푖푟푠2007−2013 = 퐸푥푝푒푛푑푖푡푢푟푒푠 푖푟푠2007−2013 / 퐴푙푙표푐푎푡푖표푛푠 푖푟푠2007−2013
- Interpretation:
  - Higher values identify sector/region where spending has been relatively more front-loaded.
  - Lower values indicate absorptive capacity constraints, with spending strongly back-loaded, and possibly occurring the year after the end of the allocation period.

### Econometric specification
- A panel regression with fixed effects is estimated:
  - 퐴푏푠 푖푟푠2013 = 훼 + 훽 푋 푖푟 + 휆 푠 + 휙 푖 + 푢 푖푟푠
- Where:
  - X_ir is a vector of regional institutional and macroeconomic characteristics (including economic performance, quality of regional government, human capital endowment, etc.).
  - Country fixed effects: φ_i control for unobserved heterogeneity at the country level.
  - Sector fixed effects: λ_rs control for unobserved heterogeneity at the sectoral level.
- Identification exploits variation across regions within a country while controlling for each sector’s absorptive capacity.
- Human capital proxy selection:
  - 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.
- Notes:
  - 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.
  - 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.

### Baseline results and key empirical findings
- Main findings:
  - Better institutions and higher education improve absorption.
  - 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.
- Quality of Government (EQI) dimensions:
  - Corruption pillar: negatively correlated with absorption (a higher index means lower corruption).
  - Quality pillar: displays a positive correlation with absorption.
  - Impartiality pillar: shows a strong negative correlation with absorption; suggests strict procedural non-exceptions may reduce absorption, indicating potential administrative burden in EU transfer implementation.
- Fiscal decentralization:
  - The ratio of local-to-central government expenditure enters the regression with a positive sign, suggesting that higher fiscal decentralization helps achieve more efficient spending.
  - Evidence that a higher degree of fiscal decentralization reinforces the positive effect of good institutions on absorptive capacity.
- Fragmentation of EU funds across Operational Programs (OPs):
  - Fragmentation index at regional level defined as: 퐹푅퐴퐺 푖푟 = 1 − ∑_{s=1}^{N} s_{s}^{2}, where ∑_{s} s_{s}^{2} is the Herfindal-Hirschman index of OPs fragmentation and s_{s} is the share of allocation to a certain OP with respect to total allocations in a NUTS2 region.
  - The rate of fragmentation in Slovakia is comparable to peers.
  - The empirical analysis does not find strong support for the hypothesis that more fragmented funds leads to lower absorption. Several specifications augmented with the fragmentation rate at NUTS2 level did not produce significant results, including when restricting the sample to new member states only. This non-result might be explained by relatively low variation in the fragmentation variable.

### Selected regression coefficients and statistics (table summary preserved)
- Variables (coefficients; clustered standard errors in parentheses):
  - Log of GDP per capita: -3.52 (3.90), 1.17 (3.35), -0.91 (3.19), 0.55 (2.78), -8.88** (3.35)
  - Log of area: -0.89 (1.05), -0.70 (0.61), -1.03 (1.11), -1.22 (1.16), -3.25*** (0.97)
  - Pop.25-64y.o by ed.at.lev.,%, Up-sec and post-sec non-ter educ (lev 3 and 4): 0.69** (0.27), 0.65* (0.33), 0.35 (0.28), -0.15 (0.11)
  - Corruption Pillar of EQI Index: 8.36*** (2.45)
  - Impartiality Pillar of EQI Index: -8.20*** (2.90)
  - Quality Pillar of EQI Index: 4.44** (1.85)
  - Normalized EQI Index: 0.31*** (0.11), 0.24*** (0.07), 0.28** (0.10)
  - Fiscal decentralization: 0.39** (0.15)
- Observations: 1,128; 1,955; 1,128; 999; 998 (across specifications)
- Country fixed effects: YES (in most specifications)
- Sector fixed effects: YES (in all specifications)
- Significance notation: *** p<0.01, ** p<0.05, * p<0.1

### Policy implications, conclusions and government actions
- Conclusion and policy implications:
  - Higher quality of government and a more educated population lead to better absorption of EU funds.
  - More decentralized spending has a positive impact on absorption.
  - Regions with sufficient human capital and good-enough institutions are more likely to spend allocated funds efficiently and transform them into growth.
  - Priorities: put in place appropriate administrative and governance capacities; fight corruption; choose higher quality projects.
  - No strong empirical support that higher OPs fragmentation leads to lower absorption.
- Survey and anecdotal evidence (authorities’ findings):
  - Constraints to absorption: lack of qualified staff, insufficient expertise, frequent changes in managing-authority staff, changes in public procurement law.
  - Financial and legal illiteracy in some population segments may hinder applications and compliance; technical support for small entrepreneurs could mitigate this.
- Measures taken by Slovak authorities (and remaining challenges):
  - Negotiated thematic areas for 2014–2020 early in the programming period.
  - Absorption rates were very low (below 5 percent at the end of 2016).
  - Authorities still in the process of meeting ex-ante conditionality requirements imposed by the European Commission; when unfulfilled, payments can be suspended.
  - Steps taken: electronic system to exchange data between managing authorities and beneficiaries to monitor and evaluate; collaboration with regional offices to offer technical assistance and free consultations; recently adopted National Public Procurement Package aimed to facilitate application and disbursement process; reduction in number of OPs.

*International Monetary Fund — Slovakia country report section (cr1772) as provided in the source content*

### 13.7 percent of GDP. Over the medium- to

### cr1772 - 13.7 percent of GDP. Over the medium- to

### Projected age-related spending and headline figures
- Health and long-term care and pension spending is projected to reach 18.5 percent of GDP in 2060, according to the Ageing Report.
- The EC and the authorities project health and long-term care and pension expenditures to rise 4.5 percentage points of GDP by 2060.
- A worst case scenario presented by the EC indicates total age-related expenditures could reach 25 - 30 percent of GDP, up to 40 percent higher than the baseline.
- Slovakia’s long-term care expenditures are currently low at 0.2 percent of GDP.

### Pension reforms reflected in the 2017 budget
- Major 2012 changes:
  - Unification of male and female retirement ages by 2024.
  - Indexation of the retirement age to life expectancy at retirement starting in 2017.
  - Transition from a 50/50 wage/price inflation indexation method to pensioners’ inflation starting in 2018.
- Assessment base for pension contributions:
  - Increased from 4 to 5 times the average economy-wide wage.
  - In 2017, the assessment base increased to 7 times the average wage.
- The ceiling on pension benefits is 3 times the average wage.
- Changes apply to both Pillar I (public defined-benefit PAYG) and Pillar II (private defined-contribution).

### Projected dynamics and drivers of pension spending
- Pension expenditures dip initially but then rise as the “baby boom” generation starts to retire in 2035.
- Assumed Pillar II participation:
  - 10 percent for new labor market entrants (contrasted with 75 percent participation among existing contributors aged 35).
- Expected longer contributory periods add to projected pension burden.
- Key drivers highlighted in the model: old-age dependency, coverage, benefit, and labor market ratios.
- The model suggests pension expenditures will be 0.5 percentage points of GDP higher by 2060 relative to the Ageing Report (equivalent to 0.01 percent of GDP a year).
- Updated model (base year advanced to 2015, IMF projections through 2020 used) implies an increase in pension expenditures-to-GDP of 0.4 percentage points by 2060, relative to the calibrated increase of 2.6 percent of GDP.

### Uncertainty and downside risks
- Key sources of uncertainty:
  - Possible over-estimation of total factor productivity (TFP) growth.
  - Large uncertainty surrounding the government’s intentions and rules regarding Pillar II.
  - Frequent changes to Pillar II parameters and multiple “openings” create participation uncertainty and asset-transfer volatility.
- TFP assumptions and concerns:
  - Ageing Report projects Slovakia’s TFP growth averages 2.3 percent from 2013–30 — the highest in the EU.
  - The Ageing Report assumes long-run TFP rates converge to 1 percent, implying labor productivity converges to 1.5 percent.
  - Historical context: since 1995 annual TFP growth averaged 2 percent; more recently slowed to 1.8 percent.
  - If recent TFP growth (1.8 percent) prevailed until 2030, potential GDP would be permanently 9 percent lower relative to Ageing Report projections.
  - Aging could reduce TFP: a five-percentage point increase in share of workers aged 55–64 is associated with a decrease in TFP of between two and four percent; for Slovakia this implies a decrease in TFP of 4 to 8 percent by 2045.
- Pillar II uncertainty and effects:
  - Rules governing entry and contribution rates have changed frequently since 2005; minimum participation period varied and was abolished in 2015.
  - Four “openings” allowed exits/entries without penalties; about 420 thousand pensioners exited Pillar II transferring EUR 1.1 billion to Pillar I.
  - High bond allocation (75 percent) and regulatory/market changes have flattened per capita Pillar II asset growth.
  - One-off withdrawal provision effective from 2017 may affect attractiveness; first Pillar II benefits began in 2015.
  - If another 20-30 percent of existing Pillar II participants leave before 2025, pension expenditures could increase by a cumulative 0.2-0.4 percent of GDP over the projection horizon.

### Scenario analysis and quantified impacts
- Lower TFP growth scenario:
  - A reduction in the TFP growth rate of a 1/4 percentage point per annum increases projected pension expenditure by 1–1.5 percent of GDP.
  - Lower TFP produces a more gradual decline in the benefit ratio because average wage (function of GDP and hours worked) would be lower.
- Reduced Pillar II participation scenario:
  - Further re-openings reducing Pillar II participation could increase pension expenditure 0.3 percentage points of GDP by 2060 (summary table).
  - Historical behavior: during four openings from 2008-15, 35 percent of those who participated in Pillar II at end-2007 transferred to Pillar I.
  - As of end-2015, roughly 1 million contributors to Pillar II.
- Model vs Ageing Report cumulative changes (selected figures):
  - Model cumulative change in pension expenditure (% of GDP) by 2060: 10.75
  - Ageing Report cumulative change by 2060: 10.23
  - Difference by 2060: 0.06
  - Model and Ageing Report path differences include dependency ratio, coverage ratio, benefit ratio, labor market effect, and residual components (detailed table in source).

### Assessment of projections and policy implications
- The Ageing Report projections are comprehensive for non-pension age-related spending but pension projections are idiosyncratic and sensitive to country-specific pension system details.
- Projected pension spending is sensitive to:
  - Assumptions about TFP and labor productivity growth.
  - Long-term participation rates in Pillar II and policy stability around Pillar II parameters.
  - Potential transfers of liabilities and assets between Pillars I and II.
- Potential fiscal consequences include higher public pension expenditure if Pillar II participation falls further or if policy reversals or expanded guarantees occur.

*Source: cr1772 - 13.7 percent of GDP. Over the medium- to*

### 0.8 percent per year instead of one percent.  This assumption leads to an increase in Slovakia’s pension expenditure

### 0.8 percent per year instead of one percent.  This assumption leads to an increase in Slovakia’s pension expenditure

### Pension expenditure scenarios and projections
- Public pension/GDP, 2060:
  - Ageing Report baseline: 10.2
  - Updated 2/: 11.0
  - Lower TFP by 0.25 p.p. annually: 12.2
  - Lower Pillar II participation by 25 percent: 11.2
- Cumulative change 1/ (percentage points):
  - Ageing Report baseline: 2.1
  - Updated 2/: 3.0
  - Lower TFP by 0.25 p.p. annually: 4.3
  - Lower Pillar II participation by 25 percent: 3.3
- Decomposition of effects (levels in percent of GDP, scenario columns correspond to Ageing Report / Updated 2/ / Lower TFP / Lower Pillar II):
  - Dependency ratio effect: 11.3 / 11.8 / 12.2 / 11.9
  - Coverage ratio effect: -4.2 / -4.5 / -4.6 / -4.5
  - Benefit ratio effect: -2.6 / -2.2 / -1.2 / -2.0
  - Labor market effect: -1.3 / -1.3 / -1.4 / -1.3
  - Interaction effects (residual): -1.0 / -0.8 / -0.8 / -0.8
- Notes:
  - 1/ Estimated pension expenditure/GDP for the base year of 2013 in the 2015 Ageing report was 8.12 percent. The actual value was 7.95 percent of GDP, which is used in the updated projections and the two scenarios.
  - 2/ Includes higher initial pension expenditure estimate using caliberated model instead of baseline of 0.5 percent of GDP.
- Quantified scenario interaction:
  - If both alternative scenarios for pension expenditures materialize together, pension expense to GDP could increase by a cumulative 1.5 percentage points, on top of the 3 percentage point increase estimated in the updated baseline, implying a pension expenditure equivalent to about 12.5 percent of GDP in 2060.

### Impact of lower Pillar II participation
- Historical context:
  - 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.
  - The four previous Pillar II openings led 35 percent of Pillar II participants to leave the private pension system.
- Scenario mechanics:
  - If another 25 percent of existing Pillar II participants were to transfer their contributions to Pillar I, the gap between the “desired” replacement rate (about 51.5 percent) and existing projections could be reduced by 25 percent through an increase in the projected replacement rates.
  - A rudimentary regression between projected changes in the benefit ratio, the gross average replacement rate, and other controls was used to translate replacement rate changes into model drivers.

### Potential savings from further pension reforms (2016–60)
- Illustrative potential expenditure savings (percentage points of GDP, 2016–60):
  - Total potential savings from implementing further parametric pension reforms: 1.8 - 2.8
  - Change in valorization formula (weight CPI at 25 percent): 0.6 - 0.8
  - Change in calculation of contribution base (annual assessment): 0.2 - 0.3
  - Link retirement age more closely to life expectancy: 1.0 - 1.5 (noted elsewhere as potentially reducing pension expenditure by 0.8 percent of GDP in 2060 as identified in the Ageing Report)
- Specific reform options and quantified impacts:
  - Tighter link to changes in life expectancy:
    - Current indexation ties adjustments in the retirement age to annual changes in a rolling five-year average of life expectancies at statutory retirement age.
    - Linking changes in the statutory retirement age to current estimated changes in life expectancy at retirement could reduce pension expenditure by 0.8 percent of GDP in 2060.
  - Valorization formula:
    - Accrued pension benefits could be indexed to a weighted average combination of consumer price and nominal wage changes.
    - Assuming a 25/75 weighting scheme, this could yield pension expenditure reduction in the range of 1.0 to 1.5 percent of GDP.
  - Annual assessment base:
    - Changing from monthly to annual assessment of social contributions could increase annual contributions by 0.2-0.3 percent of GDP.
  - Revenue-side options:
    - Removing the cap on employee pension contributions (precedent: special pension system for armed service personnel not capped).
    - Taxing pension earnings above a certain income threshold.
- Risks from ad-hoc policy changes:
  - 2017 budget increases old-age pension benefits by a fixed amount equivalent to 2 percent of the average pension, exceeding the baseline by EUR 110–120 million.
  - Introduction in July 2015 of a minimum pension for pensioners with 30 and more qualified years of pension insurance: estimated annual cost EUR 25-30 million.
  - These ad-hoc changes have added between EUR 135–150 million to annual pension expenditures (0.1–0.2 percent of GDP).

### Health expenditure: recent developments, projections, and efficiency measures
- Current and projected spending:
  - General government spends about 5.2 percent of GDP annually on health care.
  - Health care spending projected to increase 40 percent by 2060, due primarily to Slovakia’s rapidly aging population.
- Outcomes:
  - Rate of amenable mortality was 17 percent higher than comparable countries and 93 percent higher the EU average (Ministry of Finance, 2016).
- Expenditure review and short-term target:
  - Government commissioned an expenditure review of health spending in 2016 conducted by Ministry of Finance with joint assistance from the IMF, EC, and OECD.
  - Authorities established a target of no real increase in general government health spending from 2017–19.
- Estimated savings and efficiency gains:
  - Finance ministry estimates savings and efficiency gains worth about 0.5 percent of GDP from the expenditure review.
  - Of the total potential savings in healthcare, some EUR 270 million could be realized in public health insurance spending.
  - The 2017 budget identifies the savings measures to be implemented.
  - Three areas identified for higher spending efficiency: drugs, medical equipment and radiology and laboratories.
  - Oversight of implementation assigned to a new Implementation Unit in the Office of the Deputy Prime Minister.
- Structural reform needs:
  - Need to transition from a hospital-centered and disaggregated health care model to a primary care-centered health system with integrated health care provision to ensure cost-containing measures translate into long-term cost growth reduction.

### Health spending governance and implementation recommendations
- Recommended steps to strengthen governance, management, and delivery of spending review findings:
  - Set out clear procedures to support the oversight mandate of the new Implementation Unit, including frequency and nature of reporting by line ministries on progress.
  - Significantly strengthen the role of the Budget Department in the Ministry of Finance to ensure identified measures are effectively integrated into the budget.
  - Require line ministries, including the Ministry of Health, to set out clear plans with realistic timelines for implementing savings measures, including continuous engagement with stakeholders and identifying legislation requirements.
  - Expand current efforts to centralize health procurement to more products.

### Long-term feasibility and fiscal implications
- Combined risk impact:
  - Taken together, the two alternative pension risk scenarios could raise pension expenditure by a cumulative 1.5 percentage points on top of the 3 percentage point updated baseline increase, implying pension expenditure of about 12.5 percent of GDP in 2060.
- Policy priorities to mitigate risks:
  - Implement existing reforms and consider further reforms to the pension system.
  - Enhance TFP growth through measures such as reforms to the legal system and steps to improve the protection of property rights (Annex II to the accompanying staff report).
  - Improve the quality of public institutions and the education system to boost productivity growth.
  - Maintain political resolve not to open up the Pillar II system again as a risk-mitigating measure.
- Fiscal consolidation:
  - Fiscal consolidation and rigorous implementation of the 2012 pension reforms are critical to prepare Slovakia for fiscal pressures from aging.

*Source: Slovakian authorities, European Commission, Ministry of Finance, and IMF staff calculations (extracted from the provided content).*

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_Source: https://www.imf.org/-/media/files/publications/cr/2017/cr1772.pdf_