## Preface — Mission objectives, composition, and workshop ## Source details **Canonical URL:** [Preface — Mission objectives, composition, and workshop](https://www.imf.org/-/media/files/publications/tar/2025/english/tarea2025085-source-pdf.pdf) ## Other formats - [Markdown version](/-/media/files/publications/tar/2025/english/tarea2025085-source-pdf.pdf.md) - [Structured JSON version](/-/media/files/publications/tar/2025/english/tarea2025085-source-pdf.pdf.json) --- ### Mission objectives and timing - At the request of the Ministry of Finance (MoF) of Sri Lanka, an IMF Fiscal Affairs Department (FAD) team in collaboration with World Bank staff conducted a capacity development mission on preparing a fiscal risk statement during January 15–28, 2025. - Objective: conduct capacity development on preparing a Fiscal Risk Statement (FRS) and provide technical assistance on fiscal risks analysis. - Government of Sri Lanka (GoSL) aims to publish its first Fiscal Risk Statement (FRS) by June 2025, as mandated by the PFMA. ### Team composition and stakeholder engagement - Team led by Mr. Guohua Huang (Senior Economist, FAD). Team members: Mr. Raju Sharen, Ms. Marie-Hélène Le Manchec, Mr. Matt Crooke, Mr. Sebastian Michael Essl. Ms. Martha Tesfaye Woldemichael participated in the closing meeting. - Main counterpart: Department of Fiscal Policy (FPD); FPD staff attended all mission meetings. - Meetings with Secretary to the Treasury, various MoF departments, Central Bank Governor, Ministry of Energy, NAPPP, Sri Lankan Airlines, Disaster Management Centre, and others. - Delivered a 2-day capacity development workshop with 25 participants; introduced FRAT and SOE Health Check Tool (HCT-SOE) and concluded with an outline for an FRS. ### Acknowledgements - Mission thanks Sri Lankan authorities for open engagement; special coordination support by Ms. Jayanie Wickrama Arachchi and Ms. Manisha Dandunna (Department of Fiscal Policy). --- ### Executive summary — Key findings, risks, and recommended actions ### Context and overall finding - Sri Lanka has faced significant fiscal challenges exacerbated by inadequate monitoring and management of fiscal risks and absence of a focal point for fiscal risk oversight. - No centralized compilation or analysis of fiscal risk data; comprehensive picture of risks to the fiscal outlook is lacking. - Reforms implemented in 2024: introduction of cost-recovery pricing for fuel and electricity; reduction in the ceiling on the stock of guarantees; enactment of the Public Financial Management Act (PFMA) and the Public Debt Management Act (PDMA) with provisions for fiscal risk management. ### Fiscal risks identified as substantial - Macroeconomic risks: - Narrow export base and dependence on tourism and oil imports. - Debt risks: - Public debt ratio estimated to be above 100 percent of GDP in 2024; portfolio risks require assessment. - State-owned enterprises (SOEs): - Extensive footprint with weak financial positions and close linkages to government. - Guarantees and on-lending: - Estimated at around 5.5 percent of GDP as of 2024 (outstanding stock end-September 2024 LKR 1,660 billion). - Public–private partnerships (PPPs): - Over 175 projects reaching financial close with estimated investment of USD 5.3 billion (over 6 percent of 2023 GDP); pipeline of an additional 80 projects worth USD 2 billion. - Financial sector risks: - State-owned bank subsidies costed 0.4 percent of GDP in 2024; lower net inflows to the budget (dividends and levies less budget support) accounted for another 0.2–0.3 percent of GDP. - Natural disasters and climate change: - Average expected fiscal cost of natural disasters between 0.5–1 percent of GDP per annum in previous studies; likely to increase due to climate change. ### Challenges to preparing the first FRS - Limited data availability and quality; fiscal risk information scattered across ministries, departments, and agencies. - Lack of clarity on roles and responsibilities among MDAs. - Given constraints (data, staff capacity, tight timeline), the first FRS must balance credibility and feasibility; qualitative descriptions acceptable where data are unavailable. ### Near-term and medium-term strategy Near term (February–June 2025) - Focused, concise FRS coordinated with other publications; quantify risks where possible. - Issue a Treasury Circular to clearly allocate roles and responsibilities, tasks, timelines, and reporting protocols. - FPD positioned to lead and coordinate FRS preparation; relevant MoF departments prepare sections for risks under their responsibility. - Communicate benefits of comprehensive fiscal risk reporting to politicians and public. Medium term (subsequent 3 years) - Strengthen legal framework relevant to fiscal risk management (e.g., PPP Act, SOE Act, PFM regulations). - Improve coverage and quality of fiscal risk datasets (SOEs, PPPs, natural disasters). - Enhance analysis (stress testing, sensitivity/scenario analysis, credit risk assessments for guarantees). - Strengthen mitigation measures (limiting fiscal exposure to PPPs, insurance and risk transfer, financial stability fund). - Expand FRS coverage (sub-national governments, legal claims) and deepen analysis as reforms progress. --- ### Table of key recommendations (selected actions, responsibilities, timelines) - Prioritize key fiscal risks in the 2025 FRS: macroeconomy, debt, SOEs, natural disasters, financial sector, guarantees and on-lending, PPPs. - Responsible: FPD (lead) with contributions from relevant departments of MoF. - Timeline: Near term. - Issue Treasury Circular to delineate roles/responsibilities and reporting protocols. - Responsible: FPD (lead) with contributions from relevant departments of MoF. - Timeline: Near term. - Identify data sources, develop databases, confirm data quality. - Responsible: Relevant departments of MoF. - Timeline: Near term. - Prepare analysis of individual risks using existing reports, data-based analysis, or qualitative descriptions if data unavailable. - Responsible: Relevant departments of MoF. - Timeline: Near term. - Train staff to enhance capacity for fiscal risk analysis and management. - Responsible: FPD (lead) with contributions from relevant departments of MoF. - Timeline: Near term and medium term. - Strengthen legal framework relevant to fiscal risk management (e.g., PPP Act, financial regulations). - Responsible: Relevant departments of MoF. - Timeline: Medium term. - Improve datasets (SOEs, PPPs, natural disasters); enhance analytical methods (stress testing, credit risk assessments); strengthen mitigation measures. - Responsible: Relevant departments of MoF. - Timeline: Medium term. - Expand FRS coverage (SNGs, legal claims) and deepen analysis. - Responsible: FPD (lead) with contributions from relevant departments of MoF. - Timeline: Medium term. --- ### Macroeconomic risks — analysis, key quantitative findings, and recommended tools ### Current vulnerabilities and data - Structural external vulnerabilities: - Apparel, textiles, tea and rubber account for about 60 percent of merchandise exports. - Volatility analysis (2000–2024, WEO data): - Variability of revenue growth: 15.1 percent. - Variability of nominal GDP growth: 7.3 percent. - Variability of total government expenditure growth: 7.6 percent. - Public debt ratio estimated to be above 100 percent of GDP in 2024. - MFU dataset: comprehensive macro-fiscal aggregates up to 2024, forecasts and outcomes across ten vintages for 2014–2023; lacks fiscal impact of past realized shocks. - Macroeconomic Foundations Tool (MFT) expected operational by the end of April 2025. ### Forecast error analysis (2014–2023; three-year forecast errors) - Nominal GDP: average forecast error shows underestimation of +4.5 percent. - Total government revenues: average forecast error shows overestimation of -2.2 percentage points of GDP. - Government expenditure: average median forecast error of -0.2 percentage points of GDP. - Fiscal balance/budget deficit: average forecast error of -3.2 percentage points of GDP (underestimation of the budget deficit). ### Recommended analytical tools and institutional needs - Debt sustainability analysis (DSA) when capacity permits; PDMO to supply public and publicly guaranteed debt data. - IMF Sovereign Risk and Debt Sustainability Analysis tool recommended for scenario simulation; near term may refer to DSA in recent Article IV or EFF Review. - Risk register for macroeconomic risks: maintain info on nature, recurrence, pattern and fiscal impact of past shocks; define past shocks (e.g., nominal GDP growth falling by one standard deviation). - Scenario and sensitivity analysis: implement stress testing and sensitivity analysis calibrated using forecast error and volatility analysis. ### Recommendations Near Term - 2.1 Derive forecast errors in key macro-fiscal variables and calculate historical volatility for the 2025 FRS. Medium Term (subsequent 3 years) - 2.2 Incorporate largest forecast errors in baseline scenarios; conduct stress testing, sensitivity analysis, and a DSA; build a macroeconomic risk register and categorize impacts as low, medium, high. --- ### State-Owned Enterprises (SOEs) — size, performance, data issues, and credit risk analysis ### SOE sector overview - Nearly 400 public corporations: - Commercial corporations: 41 entities. - Government owned companies: 158 entities. - Statutory boards: 198 entities. - Commercial corporations and government owned companies considered SOEs: 199 entities total, of which 11 are financial entities. ### Financial size and concentration - Of the 188 non-financial SOEs, 41 considered strategically important. - Total liabilities of the 41 strategic SOEs: - LKR 3.2 trillion at end-December 2023. - Equivalent to 11.7 percent of GDP. - Liabilities of the five largest strategic SOEs (CPC, CEB, SLA, NWS&DB, SLPA): - LKR 2.9 trillion; about 90 percent of total liabilities of the 41 strategic SOEs. ### Financial performance, 2018–2023 (key figures) - Profit/Loss Before Tax (In LKR billion) — 41 SOEs: - 2018 -51.5; 2019 -14.8; 2020 31.5; 2021 -96.8; 2022 -774.8; 2023 174.0. - Profit/Loss Before Tax (in percent of GDP) — 41 SOEs: - 2018 -0.3; 2019 -0.1; 2020 0.2; 2021 -0.5; 2022 -3.2; 2023 0.6. - Net outflows from the government (In LKR billion) — 41 SOEs: - 2018 31.4; 2019 21.5; 2020 57.0; 2021 66.5; 2022 99.8; 2023 206.0. - Net outflows from the government (in percent of GDP) — 41 SOEs: - 2018 0.2; 2019 0.1; 2020 0.4; 2021 0.4; 2022 0.4; 2023 0.7. - Historical fiscal burden: net outflows averaged LKR 80 billion per year (0.4 percent of GDP) from 2018 to 2023. ### Drivers of weak performance and recent improvements - Main causes: pricing below cost recovery (fuel and electricity), operational inefficiencies, oil price volatility, currency depreciation, cross-debt, weak governance, weather shocks. - 2023 improvements: - Total profits of LKR 174 billion (0.6 percent of GDP), an LKR 950 billion increase from 2022, largely due to automatic fuel and electricity price adjustments and cost-reflective water tariffs. - Fragilities remain: - 11 SOEs incurred losses of LKR 81 billion (0.3 percent of GDP) in 2023. - Six entities had negative equity totaling Rs 525 billion (1.9 percent of GDP). - SLA: over 90 percent of losses and negative equity; US$310 million debt requiring restructuring. ### Data, institutional arrangements, and reporting - PED responsibilities: reviews budgets and multi-annual plans, monitors performance, hosts governance guidelines and financial statements. - 80 percent of the 2023 posted financial statements have been audited. - PFMA (approved August 2024) requires SOEs to submit medium-term strategic plans, annual budgets, annual action plans and annual reports; SOEs required to publish annual reports on their websites. - MIS: web-based system implemented by PED; contains annual data for strategic SOEs for last five years; coverage and timeliness issues; no legal basis for mandatory entry and absence of built-in consistency checks. ### Data quality issues (MIS-extracted 2023 dataset) and analytical steps - Observed weaknesses: - Inconsistencies (e.g., total liabilities not equal to sum of current and non-current liabilities). - Tax payments recorded with inconsistent signs. - Differences between MIS figures and printed financial statements. - Need to extend coverage to group-level and confirm consistency with MoF departments. - Recommended analytical steps: - Transform and standardize financial data; compute financial ratios (profitability, liquidity, solvency). - Ensure inclusion of non-operating net profit/loss when deriving net profit/loss and return on equity. - Build consistency checks into dataset. ### Credit risk analysis of SOEs — preliminary results (subject to confirmation) - Methodology elements proposed: financial ratios, benchmarks from SOEHCT User Guide, rating granularity (e.g., 1–5 scale). - Preliminary outcomes (based on 2023 PED data and SOEHCT): - One third of the 41 SOEs classified as high or very high risk: 14 SOEs identified as high and very high risk. - These 14 account for 56 percent of total liabilities of the SOEs. - Sector concentration: more than a third of high/very high risk SOEs are in agriculture and plantation. - Eight SOEs operating at a loss and unable to cover costs. - Eight SOEs had return on equity less than 1 percent. - Ten SOEs had a current ratio of less than one. - CEB, CPC and SLA are not among the 14 high/very high risk SOEs; total companies requiring close monitoring expands to 17. ### Scope expansion for the forthcoming FRS Priority reporting elements proposed: - SOEs’ total debt by instrument, short-term vs. long-term and external vs. domestic. - Equity injections and transfer of debt to central government balance sheet. - Risk factors and mitigation strategies submitted by SOEs. - Deviations from SOE budget projections and medium-term plans. - Quasi-fiscal activities and cost estimates. - Forward-looking information influencing SOE performance and risk ratings. - Concluding FRS section should list mitigation measures in place or being implemented and explain how they mitigate risks. ### Recommendations Near Term - 3.1 Require SOEs to timely record financial data in the MIS. - 3.2 Create a consolidated database of SOE financial data with 2023 data; build consistency checks; engage NBD/DTO for inputs. - 3.3 Develop and adopt a credit risk analysis methodology for SOEs. - 3.4 Derive credit risk ratings in a simple Excel file. Medium Term - 3.5 Prepare a comprehensive register of SOEs that are market producers. --- ### Guarantees and on-lending — current situation, reforms, and recommendations ### Current situation and exposures - As of end-September 2024: - Outstanding stock of government guarantees and letters of comfort: LKR 1,660 billion. - Equivalent to approximately 5.5 percent of estimated 2024 GDP (PFMA 3-year average GDP calculation note: ratio would be around 6%). - One-third of outstanding guarantees attributed to currency swap and trade credit provided by Reserve Bank of India to CBSL, backed by GoSL guarantees. - Primary SOE beneficiaries: CEB, CPC, RDA, SLA, NWSDB — collectively account for more than half of outstanding guarantees. - Largest domestic creditors for guaranteed SOE loans: Bank of Ceylon (BOC), National Savings Bank (NSB), People’s Bank (PB). - Deep linkage between GoSL, non-financial SOEs, and state-owned banks amplifies fiscal and financial risks. ### Legal and institutional reforms - PDMA (enacted June 2024): - Assigns responsibility to the PDMO; authority to issue guarantees/on-lending rests with Minister of Finance. - Mandates credit risk assessment before approval; restricts eligibility to entities not in financial distress; requires risk mitigation measures (fees and spreads). - PFMA (enacted August 2024): - Reduces ceiling on outstanding guarantees from 15 to 7.5 percent of GDP, calculated as average of current and previous two financial years. - No explicit limit set for on-lending. ### Reporting, recording, and transparency - Gross exposure to guarantees disclosed in Fiscal Position Report and quarterly debt bulletin; guarantees recorded in an Excel database maintained by DTO. - On-lent loans excluded from GoSL reports; PDMA mandates PDMO’s quarterly public debt reports include detailed information on outstanding guarantees and on-lent loans. - Migration from CS-DRMS to Meridien scheduled for 2025. ### Key issues - Implementing legislation and procedures for PDMA not finalized; coordination and information-sharing requirements unclear. - Data collection cumbersome; inefficient information sharing limits PDMO reporting. - Concept of “financial difficulty” requires clarification with respect to eligibility. - PDMO capacity constraints: credit risk assessments for new requests and outstanding stock have not been undertaken. ### Recommendations Near Term - 4.1 Expedite finalization of legislation and policies to implement PDMA to enable PDMO functionality. - 4.2 Include overview of on-lent loan portfolio in the first FRS. - 4.3 Include overview of guarantees and on-lent loans provided during the past financial year and information on materialized risks. - 4.4 Identify priority capacity building needs for PDMO staff and develop a structured roadmap. Medium Term - 4.5 Develop and implement a comprehensive framework for assessing credit risk from loan guarantees and on-lending. - 4.6 Link risk mitigation measures (fees and spreads) to credit risk assessment results. - 4.7 Enhance future FRSs by incorporating risk measures derived from credit risk assessments, including detailed risk quantification. ### PPP fiscal context (selected figures) - PPP portfolio: Over 175 PPP projects financially closed during 1990–2023. - Estimated implementation cost of closed PPPs: USD 5.3 billion (over 6 percent of GDP). - Port sector investment: USD 2.7 billion. - Power sector investment: USD 2 billion. - Competitive procurement: Only 13 projects awarded through competitive bidding. - Pipeline: Additional 80 projects under consideration with estimated investment of USD 2 billion. --- ### PPPs, financial sector, and natural disaster fiscal risks — oversight, reporting, and data gaps ### PPPs — oversight and monitoring - Lack of centralized oversight and monitoring mechanisms; PMMD could assume monitoring responsibility. - PPPs involve long-term commitments (20–30 years); fiscal risks change by project stage and require periodic reassessment. - Suggested designated MoF team: officers from NPD, NBD and PMMD to independently assess fiscal costs and provide inputs to NPD, NBD and PMMD. - Consider setting fiscal limits on PPP commitments (stock, flows, or both); international examples cited (UK, Hungary, Peru, Brazil, Indonesia, Turkey). - Near Term recommendation for 2025 FRS: provide qualitative discussion on PPP-related fiscal risks, portfolio, identified risks, and government steps to manage risks (Recommendation 5.1). Medium Term recommendations on PPPs - 5.2 Develop comprehensive legal/regulatory framework aligned with PFM Act 2024. - 5.3 Strengthen institutional arrangements; institute centralized oversight and monitoring mechanism assisted by designated MoF team. - 5.4 Establish comprehensive PPP database within MoF. - 5.6 Strengthen capacity across procuring entities and MoF departments. - 5.7 Deepen analysis in future FRSs and progressively adopt a quantitative approach. ### Financial sector — fiscal risk overview and reporting practice - Fiscal risks arise from financial stability interventions, state-owned financial institutions (SOFIs), and quasi-fiscal activities. - For the first FRS, focus on: - Summary indicators of financial sector health and trends for items explicitly covered by government (e.g., deposit insurance). - Performance of state-owned financial institutions and associated net budgetary flows. - How regulatory, coordination and policy frameworks are being strengthened. - Key figures and examples: - LKR 122 billion (0.4 percent of GDP) subsidy paid to two state banks in 2024. - Dividends and levies to GoSL: less than 0.1 percent of GDP in 2023, down from around 0.2 to 0.3 percent of GDP in 2016 and 2017. - Recommended near-term actions: - 6.1 Establish a working-level technical group (FPD lead) to compile inputs for the 2025 FRS; include CBSL, IRC, PED, DFD. - 6.2 Summarize existing CBSL material on financial sector soundness and recent policy responses. Medium Term - 6.3 Summarize stress testing results and crisis management framework developments in future FRSs. ### Natural disasters and climate change — data gaps and cost estimates - Data gaps: - Economic loss estimates not systematically recorded; EM-DAT shows no recorded economic loss after 2017; DesInventar contains field but no entries. - No centrally coordinated estimates of fiscal costs; fiscal data relatively complete for coordination costs, compensation, insurance premiums and mitigation projects; major gaps in reconstruction and rehabilitation costs and reallocated appropriations. - Existing quantitative estimates: - World Bank and GFDRR (2016): annual average economic loss around 1.5 per cent of GDP (excluding 2004 tsunami); middle scenario fiscal costs around 0.5 per cent of GDP (annual average). - UN ESCAP: estimated annual economic losses around 2.5 per cent of GDP; applying WB/GFDRR assumption implies expected annual fiscal costs around 0.9 per cent of GDP. - Climate-change adjusted projections: economic losses increase from 2.5 to 2.8–3.0 per cent of GDP; expected fiscal cost rises to around 1.1 per cent of GDP. - Annual adaptation costs: around USD 430 million or 0.5 per cent of GDP per annum. - Near Term recommendations: - 7.1 Establish a working-level technical group (FPD lead) to compile natural disaster/climate section inputs; DMC, NBD and NPD to establish more complete dataset for past 10 years (February–May 2025). - 7.2 Summarize historical incidence and present available quantitative estimates of expected annual economic losses and fiscal costs in the 2025 FRS covering past 10 years. Medium Term - 7.3 Expand analysis and focus on climate change implications; consider chart-of-accounts marker, update hazard risk profiles every 5 years, integrate climate scenarios with macro framework. --- ### Institutional, data management, analysis and communication guidance ### Institutional arrangements and coordination - Centralize fiscal risk information within government while keeping clear responsibilities for individual entities. - FPD (MFU) positioned to lead and coordinate FRS preparation. - Suggested roles by risk type: - Macroeconomic risks: FPD (consult CBSL/IRD/SLC). - SOE risks: PED (coordinate with DTO/PDMO and NBD). - Guarantees/on-lending: PDMO with NPD, PED involvement. - PPP risks: NPD coordinate with NAPPP. - Financial sector risks: working group with FPD (lead), PED, CBSL and IRC. - Natural disaster risks: working group with FPD (lead/coordinator), DMC, NBD, NPD, MoE. - Recommend issuing a Treasury Circular to allocate roles/responsibilities and establish reporting protocols, templates, frequencies and lags. ### Improving data management and analysis - Identify and leverage dispersed data across MDAs; consider a fiscal risk register listing fiscal impact, likelihood, mitigation strategies and data sources. - Develop bottom-up registers from line ministries to complement high-level MoF register; consider FRAT as data expands. - Validate data quality through cross-verification, consistency checks, feedback mechanisms and regular audits. - Strengthen analytical content by summarizing existing analyses and initiating new analyses where data permit; use qualitative judgment where quantification not possible. ### Communication and capacity building - Engage politicians early to explain benefits of fiscal risk reporting for decision-making and market confidence. - FRS should synthesize fiscal risk register information and present in a public-facing manner, disclosing explicit fiscal risks while considering nondisclosure of certain implicit risks to avoid moral hazard. - Build staff analytical capacity: training in risk types, stress testing, scenario analysis and risk modeling; collaborate with IMF, World Bank and other partners. --- *Source: Preface and selected excerpts from the IMF Fiscal Affairs Department and World Bank mission report (Colombo mission, January 15–28, 2025) and technical assistance chapters in the provided PDF content unit.* ### Preface ................................................................................................................ ### Preface ### Mission objectives and timing - At the request of the Ministry of Finance (MoF) of Sri Lanka, an IMF Fiscal Affairs Department (FAD) team in collaboration with World Bank staff conducted a capacity development mission on preparing a fiscal risk statement during January 15–28, 2025. - Objective: conduct capacity development on preparing a Fiscal Risk Statement (FRS) and provide technical assistance on fiscal risks analysis. ### Team composition - Team led by Mr. Guohua Huang (Senior Economist, FAD). - Team members: Mr. Raju Sharen (IMF Resident PFM Advisor at Colombo), Ms. Marie-Hélène Le Manchec, Mr. Matt Crooke (both IMF Experts), and Mr. Sebastian Michael Essl (Senior Economist, World Bank). - Ms. Martha Tesfaye Woldemichael, IMF’s Resident Representative in Sri Lanka, participated in the closing meeting. ### Stakeholder engagement and meetings - Opening meeting with Secretary to the Treasury, Mr. K. M. Mahinda Siriwardana, and Directors General of: Departments of Fiscal Policy, National Budget, State Accounts, Treasury Operations, National Planning, Public Enterprises, and Public Debt Management Office. - Main counterpart: Department of Fiscal Policy (FPD); FPD staff attended all mission meetings. - Individual meetings held with: Department of Fiscal Policy; Department of National Planning; Department of Treasury Operations; Public Enterprises Department; Department of Project Management and Monitoring; Department of State Accounts; Public Debt Management Office. - Additional meetings with: Dr. P. Nandalal Weerasinghe (Governor, Central Bank of Sri Lanka) and team; Prof. K.T.M. Udayanga Hemapala (Secretary, Ministry of Energy); Mr. Ananda W. Atukorala (Chairman, National Agency for Public Private Partnerships) and team; Mr. Sarath Clement Ganegoda (Chairman, Sri Lankan Airlines) and team; Major General (Retired) Udaya Herath (Director General, Disaster Management Centre) and team. - Mission presented main findings and key recommendations to the Secretary to the Treasury and other senior officers in the MoF. ### Capacity development workshop - Delivered a 2-day CD workshop on Fiscal Risks Analysis and Preparation of Fiscal Risk Statement with 25 participants from various departments of the Treasury. - Presentations covered: types of fiscal risks, especially those associated with macroeconomic risks, financial sector, state owned enterprises, guarantees, natural disasters, and public private partnerships. - Participants introduced to the Fiscal Risks Assessment Tool (FRAT) and the SOE Health Check Tool (HCT-SOE) and completed two exercises. - Workshop concluded with participants preparing an outline of a possible Fiscal Risk Statement. ### Acknowledgements - Mission thanks the Sri Lankan authorities for open and active engagement across ministries, departments, and agencies. - Special thanks to Ms. Jayanie Wickrama Arachchi and Ms. Manisha Dandunna (Department of Fiscal Policy) for coordination and logistical support. ### Executive Summary — Key findings, risks, and recommended actions - Context and overall finding: - Sri Lanka has faced significant fiscal challenges exacerbated by inadequate monitoring and management of fiscal risks. - In the absence of a focal point for fiscal risk oversight, there is no centralized compilation or analysis of fiscal risk data, and a comprehensive picture of risks to the fiscal outlook is lacking. - Authorities have implemented reforms: introduction of cost-recovery pricing for fuel and electricity; reduction in the ceiling on the stock of guarantees; enactment of the Public Financial Management Act (PFMA) and the Public Debt Management Act (PDMA) with provisions for fiscal risk management. - The Government of Sri Lanka (GoSL) aims to publish its first Fiscal Risk Statement (FRS) by June 2025, as mandated by the PFMA. - Fiscal risks identified as substantial in Sri Lanka: - Macroeconomic risks: vulnerability due to volatile GDP and revenue growth, a narrow export base, and high dependency on tourism receipts and oil imports. - Debt risks: although public debt improved after restructuring and fiscal adjustments, portfolio risks still require thorough assessment. - State-owned enterprises (SOEs) risks: extensive SOE footprint with weak financial positions and close financial linkages to government. - Guarantees and on-lending risks: extensive use of government guarantees, estimated at around 5.5 percent of GDP as of 2024, exposing public finances to substantial contingent liabilities. - Public–private partnership (PPP) risks: over 175 projects reaching financial close involving an estimated investment of USD 5.3 billion (over 6 percent of 2023 GDP) and an additional 80 projects worth USD 2 billion in the pipeline. - Financial sector risks: key exposures stem from performance of state-owned financial institutions; in 2024, state-owned bank (SOB) subsidies costed 0.4 percent of GDP, with lower net inflows to the budget (dividends and levies less budget support) accounting for another 0.2–0.3 percent of GDP. - Natural disasters and climate change risks: previous studies indicate the average expected fiscal cost of natural disasters is between 0.5–1 percent of GDP per annum, and likely to increase due to climate change. - Challenges to preparing the first FRS: - Data availability and quality are relatively limited. - Depth of analysis varies across types of fiscal risks. - Fiscal risk information is scattered across ministries, departments, and agencies; no systematic information exchange mechanism established. - Lack of clarity on roles and responsibilities among MDAs for preparing the FRS. - Given constraints (data, staff capacity, tight timeline), the first FRS must balance credibility and feasibility; where data are unavailable, qualitative descriptions can be used. - Near-term and medium-term strategy and priorities: - The FRS should be focused, concise, and coordinated with other publications; quantify risks wherever possible and clearly communicate risk management efforts and mitigation actions. - Near-term priority: clearly allocate roles and responsibilities among MDAs via a Treasury Circular specifying tasks, timelines, and reporting protocols to ensure timely data supply and outputs. - Department of Fiscal Policy (FPD) well-positioned to lead and coordinate FRS preparation; relevant MoF departments prepare sections for risks under their responsibility; line ministries/agencies to identify, assess, and monitor risks within their functions. - Clear communication to politicians and public on benefits of comprehensive fiscal risk reporting and mitigation measures. - Medium-term reforms: - Strengthen legal framework relevant to fiscal risk management (e.g., PPP Act, SOE Act, PFM regulations). - Improve coverage and quality of fiscal risk datasets (e.g., SOEs, PPPs, natural disasters). - Enhance analysis of fiscal risks (e.g., stress testing, sensitivity/scenario analysis, credit risk assessments for guarantees). - Strengthen mitigation measures (e.g., limiting fiscal exposure to PPPs, insurance and risk transfer, financial stability fund). - As reforms progress, expand FRS coverage (e.g., sub-national governments and legal claims) and deepen analysis. ### Table 1 — Summary of Key Recommendations (actions, responsible departments, timeline) - Prioritize the key fiscal risks in the 2025 FRS, including macroeconomy, debt, SOEs, natural disasters, financial sector, guarantees and on-lending, and PPPs. - Responsible: FPD taking the lead with contributions from relevant departments of MoF - Timeline: Near term - Develop a focused and concise FRS with close coordination with other official publications relevant to fiscal risks. - Responsible: FPD taking the lead with contributions from relevant departments of MoF - Timeline: Near term - Issue a Treasury Circular to delineate roles and responsibilities related to FRS preparation, specifying tasks, timelines, and reporting protocols to ensure timely data supply and output achievement. - Responsible: FPD taking the lead with contributions from relevant departments of MoF - Timeline: Near term - Identify the sources of data/information for the selected fiscal risks, develop databases, and confirm data quality. - Responsible: Relevant departments of MoF responsible for respective risks - Timeline: Near term - Prepare an analysis of individual fiscal risk by summarizing existing reports where available, conducting analysis based on related data if no prior analysis exists, or providing a qualitative description of the risks if data is unavailable. - Responsible: Relevant departments of MoF responsible for respective risks - Timeline: Near term - Clearly communicate to politicians the benefits of the FRS in supporting timely decision-making and enhancing market confidence, while also informing the public about the actions taken, including mitigation measures. - Responsible: FPD taking the lead with contributions from relevant departments of MoF - Timeline: Near term - Train staff to enhance their capacity for fiscal risk analysis and management. - Responsible: FPD taking the lead with contributions from relevant departments of MoF - Timeline: Near term and medium term - Strengthen the legal framework relevant to fiscal risk management (e.g. PPP Act, financial regulations). - Responsible: Relevant departments of MoF responsible for respective risks - Timeline: Medium term - Improve coverage and quality of fiscal risk datasets (e.g. SOEs, PPPs, natural disasters). - Responsible: Relevant departments of MoF responsible for respective risks - Timeline: Medium term - Enhance analysis of fiscal risks (e.g. stress testing and sensitivity/ scenario analysis, credit risk assessments for guarantees). - Responsible: Relevant departments of MoF responsible for respective risks - Timeline: Medium term - Strengthen mitigation measures (e.g. limiting fiscal exposure to PPPs, insurance and risk transfer, financial stability fund). - Responsible: Relevant departments of MoF responsible for respective risks - Timeline: Medium term - Expand the coverage of FRS (e.g. SNGs, legal claims) and deepen its analysis. - Responsible: FPD taking the lead with contributions from relevant departments of MoF - Timeline: Medium term *Source: Preface and Executive Summary of the mission report prepared by the IMF Fiscal Affairs Department and World Bank (Colombo mission, January 15–28, 2025).* ### 2. The departments responsible for respective risks are discussed in Section VIII ### 2. The departments responsible for respective risks are discussed in Section VIII ### Introduction and context - Sri Lanka has faced significant fiscal challenges exacerbated by inadequate monitoring and management of fiscal risks and the absence of a focal point for fiscal risk oversight. - Key shocks that have contributed to fiscal pressures include: the COVID-19 pandemic (2020–2021), the Russia-Ukraine war in 2022, the Easter attacks in 2019, oil price increases and tighter financial conditions in 2018, and natural disasters (severe drought and floods in 2017). - Realization of fiscal risks from state-owned enterprises (SOEs) and government guarantees has intensified fiscal vulnerabilities. - Government reforms enacted in 2024: - Public Debt Management Act (PDMA) (2024): mandates credit risk assessments before approving and issuing guarantees or on-lending; restricts eligibility to entities not in financial distress; requires risk mitigation measures such as fees and spreads. - Public Financial Management Act (PFMA) (2024): mandates prudent management and mitigation of fiscal risks and includes provisions addressing SOE and PPP risks. - Other policy changes: alignment of energy pricing with costs and reduction of the ceiling on the stock of guarantees to 7.5 percent of GDP, down from 15 percent. - The PFMA requires the government to specify main sources of fiscal risks and estimate their potential fiscal impact in the Fiscal Strategy Statement (FSS). The government is committed to publishing its first Fiscal Risk Statement (FRS) by June 2025. - Near term defined as between February and June 2025; medium term refers to the subsequent 3 years. ### Macroeconomic shocks — current situation and vulnerabilities - Structural external vulnerabilities: - Narrow export base: apparel, textiles, tea and rubber account for about 60 percent of merchandise exports. - High dependency on tourism and remittances. - Dependence on oil imports, particularly for power generation. - Structural domestic vulnerabilities: - Elevated public debt limiting fiscal space. - Tropical location increasing exposure to extreme weather events. - Lack of a social contract and weak governance affecting policy sustainability. - Volatility analysis (2000–2024, WEO data): - Variability of revenue growth: 15.1 percent. - Variability of nominal GDP growth: 7.3 percent. - Variability of total government expenditure growth: 7.6 percent. - Interpretation: revenue volatility (15.1 percent) is about twice that of GDP (7.3 percent) and notably higher than expenditure volatility (7.6 percent), indicating significant budgetary risk and greater vulnerability relative to selected Asian neighbors. - Public finances outlook: - Public debt ratio is still estimated to be above 100 percent of GDP in 2024. - Potential shocks include intensified regional conflicts (commodity price increases), exchange rate depreciation and resurgence of inflation, global growth slowdown affecting exports and tourism receipts, waning reform momentum, SOE defaults and chronic losses, and natural disasters. - Institutional responsibilities and capacity: - Macro-Fiscal Unit (MFU) at FPD: primary responsibility for assessing macroeconomic risks; prepares FSS and MTFF and monitors fiscal targets. - MFU dataset: comprehensive macro-fiscal aggregates up to 2024, forecasts and outcomes across ten vintages for 2014–2023, but lacks information on fiscal impact of past realized shocks. - Macroeconomic Foundations Tool (MFT): Excel-based tool being adapted with IMF Capacity Development Institute support; expected operational by the end of April 2025. MFU staff trained; significant CD from FAD on macro-fiscal forecasting. ### Macroeconomic shocks — analysis and key quantitative findings - Forecast error analysis (2014–2023; three-year forecast errors): - Nominal GDP: average forecast error shows underestimation of +4.5 percent (pessimistic bias due to underestimation of inflation). - Total government revenues: average forecast error shows overestimation of -2.2 percentage points of GDP. - Government expenditure: average median forecast error of -0.2 percentage points of GDP. - Fiscal balance/budget deficit: combined effect produced an underestimation of the budget deficit with an average forecast error of -3.2 percentage points of GDP. - Volatility analysis recommendations: - Extend volatility measures beyond tax revenue to nominal GDP growth, inflation, interest rate and exchange rate. - Volatilities can be measured as variance or standard deviation of annual changes and compared with peers using FRAT or WEO (data up to 2024). ### Recommended analytical tools and institutional data needs - Debt sustainability analysis (DSA): - Should be prepared when capacity permits; PDMO to supply public and publicly guaranteed debt data and other departments to share contingent liabilities (e.g., bank recapitalization). - IMF Sovereign Risk and Debt Sustainability Analysis tool recommended for scenario simulation; in the near term, authorities may refer to DSA in the most recent Article IV or EFF Review. - Risk register for macroeconomic risks: - Maintain information on nature, recurrence, pattern and fiscal impact of past shocks. - Define past shocks (e.g., episodes where nominal GDP growth fell by one standard deviation relative to its average). - Describe each shock by source, transmission mechanism and fiscal impact; categorize impact as low, medium or high. - Scenario and sensitivity analysis: - Implement stress testing (large, temporary shocks) and sensitivity analysis (smaller, persistent medium-term shocks). - Calibrate shocks using forecast error analysis, volatility analysis and risk register information. ### Recommendations Near Term (for the 2025 FRS) - 2.1 Derive forecast errors in key macro-fiscal variables and calculate historical volatility of key macro-fiscal variables based on existing data for the 2025 FRS. Medium Term (subsequent 3 years) - 2.2 Mitigate the impact of shocks and further refine the quality of the risk quantification: - Incorporate the largest forecast errors in the baseline macroeconomic scenario. - Conduct stress testing and sensitivity analysis. - Conduct a DSA. Engage with PDMO and other departments/institutions for data input. - Build a macroeconomic risk register. Describe each shock in terms of its source, transmission mechanism and fiscal impact, together with a categorization of the impact (low, medium and high). *Source: IMF technical report — Macroeconomic Risks and Fiscal Risk Statement guidance (excerpts).* ### 22. SOEs have a significant presence in Sri Lanka. There are nearly 400 public corporations. ### 22. SOEs have a significant presence in Sri Lanka. There are nearly 400 public corporations. ### Overview of the SOE sector - Nearly 400 public corporations: - Commercial corporations: 41 entities - Government owned companies: 158 entities - Statutory boards: 198 entities - Commercial corporations and government owned companies are considered SOEs: 199 entities in total, of which 11 are financial entities. - Legal status and ownership: - Commercial corporations operate under their own separate legal status. - Government owned companies operate under the Companies Act. - All are fully or almost fully owned by the government. - Statutory boards: involved in non-commercial activities, operate with a balanced budget, are not allowed to borrow independently from central government, and have a good track record of servicing their on-lent debt to central government. - Fiscal role: statutory boards remit a substantial amount of levy to the Treasury. ### Financial size and concentration - Of the 188 non-financial SOEs, 41 are considered strategically important. - The 41 strategic SOEs operate in key sectors such as ports, energy, water, retail, basic food production, mining and construction. - Total liabilities of the 41 strategic SOEs: - LKR 3.2 trillion at end-December 2023 - Equivalent to 11.7 percent of GDP - Liabilities of the five largest strategic SOEs (CPC, CEB, SLA, NWS&DB, SLPA): - LKR 2.9 trillion - About 90 percent of the total liabilities of the 41 strategic SOEs ### Financial performance, 2018–2023 (key figures) - Profit/Loss Before Tax (In LKR billion) - 41 SOEs: 2018 -51.5; 2019 -14.8; 2020 31.5; 2021 -96.8; 2022 -774.8; 2023 174.0 - O/w: main 5 SOEs: 2018 -172.4; 2019 -138.6; 2020 -82.5; 2021 -143.1; 2022 -1,025.0; 2023 132.4 - Profit/Loss Before Tax (in percent of GDP) - 41 SOEs: 2018 -0.3; 2019 -0.1; 2020 0.2; 2021 -0.5; 2022 -3.2; 2023 0.6 - O/w: main 5 SOEs: 2018 -1.1; 2019 -0.9; 2020 -0.5; 2021 -0.8; 2022 -4.3; 2023 0.5 - Net outflows from the government (In LKR billion) - 41 SOEs: 2018 31.4; 2019 21.5; 2020 57.0; 2021 66.5; 2022 99.8; 2023 206.0 - O/w: main 5 SOEs: 2018 0.0; 2019 24.0; 2020 51.3; 2021 63.1; 2022 109.8; 2023 243.5 - Net outflows from the government (in percent of GDP) - 41 SOEs: 2018 0.2; 2019 0.1; 2020 0.4; 2021 0.4; 2022 0.4; 2023 0.7 - O/w: main 5 SOEs: 2018 0.0; 2019 0.2; 2020 0.3; 2021 0.4; 2022 0.5; 2023 0.9 - Historical fiscal burden: net outflows from the government averaged LKR 80 billion per year (0.4 percent of GDP) from 2018 to 2023. ### Drivers of weak performance and recent improvements - Main causes of weak financial performance: - Losses at CEB, CPC and SLA driven by pricing policies below cost recovery (fuel and electricity), causing liquidity problems and hampering investment. - Operational inefficiencies, oil price volatility, currency depreciation, cross-debt, weak governance and weather-related shocks. - Provision of debt-for-equity swaps and debt transfers to central government; deterioration of public banks’ balance sheets. - 2023 improvements: - Total profits of LKR 174 billion (0.6 percent of GDP), an LKR 950 billion increase from 2022, largely due to automatic fuel and electricity price adjustments and cost-reflective water tariffs. - Fragilities remain: - 11 SOEs incurred losses of LKR 81 billion (0.3 percent of GDP) in 2023. - Six entities had negative equity totaling Rs 525 billion (1.9 percent of GDP). - SLA: critical state, contributing over 90 percent of losses and negative equity, with US$310 million debt that needs to be restructured. ### Data, institutional arrangements, and reporting - PED responsibilities: - Reviews annual budgets and multi-annual corporate plans of SOEs, monitors operations against performance benchmarks, with special focus on strategic SOEs. - Hosts SOEs' Corporate Governance Guidelines, Operational Manual, PED's 2022 Annual Report, and strategic SOEs' 2017-2023 financial statements on its website. - 80 percent of the 2023 posted financial statements have been audited. - PFMA (approved August 2024) enhanced reporting requirements for SOEs: - Must submit to the MoF: a medium-term strategic plan, an annual budget, an annual action plan and an annual report (includes financial statement). - Future annual budgets expected to present risk factors and mitigation strategies. - SOEs required to publish the annual report on their website. - Management Information System (MIS): - Web-based MIS implemented by PED to collect financial information; allows data to be downloaded in Excel. - MIS currently contains annual data from strategic SOEs for the last five years; strategic SOEs asked to enter data monthly. - MIS coverage for non-strategic enterprises is uneven and requires further training. - No legal basis for recording data in the MIS; data not systematically entered timely. - MoF divisions: - NBD: data on transactions with the government. - DTO (and soon PDMO): data on guaranteed and on-lent debt. - MoF publications with SOE data: Fiscal Position Report, Fiscal Management Report, PED 2022 Annual Report. Fiscal Position Report provides comprehensive aggregated and company-level data. ### Data quality issues and analytical steps for fiscal risk analysis - Data weaknesses observed in MIS-extracted 2023 Excel dataset for 41 strategic SOEs: - Inconsistencies (e.g., total liabilities not equal to sum of current and non-current liabilities). - Tax payments recorded with negative or positive sign inconsistently. - Differences between MIS figures and printed financial statements (e.g., total liabilities for CEB). - Data coverage should be extended to group-level, not limited to enterprise-level. - Need to confirm consistency of net government flows and guaranteed/on-lent debt with relevant MoF departments. - Absence of built-in consistency checks and legal basis for MIS data entry. - Recommended analytical steps: - Transform and standardize financial data to compute financial ratios (profitability, liquidity, solvency). - Ensure inclusion of non-operating net profit/loss when deriving net profit/loss and return on equity. - Build consistency checks into the dataset. ### Credit risk analysis of SOEs - Proposed methodology elements: - Select financial ratios covering profitability, liquidity and solvency. - Use benchmarks (SOE Health Check Tool (SOEHCT) User Guide provides commonly used benchmarks). - Decide weighting of each ratio (equal weights could be considered). - Decide granularity of rating (number of risk categories). - Assign categories (e.g., 1 very low risk to 5 very high risk). - Preliminary results (based on 2023 PED data and SOEHCT, subject to confirmation): - One third of the 41 SOEs classified as high or very high risk: 14 SOEs identified as high and very high risk. - Sector concentration: more than a third of high/very high risk SOEs are in agriculture and plantation. - These 14 account for 56 percent of the total liabilities of the SOEs. - Eight SOEs operating at a loss and unable to cover costs. - Eight SOEs had return on equity less than 1 percent. - Ten SOEs (or 70 percent of a referenced subset) had a current ratio of less than one. - CEB, CPC and SLA are not among the 14 high/very high risk SOEs; bringing the list of companies requiring close monitoring to 17. - Next steps: - Broaden oversight to SOEs that are market producers (GFSM 2014 definition and a rule of thumb: value of sales at least half of cost of production). - Assess the 147 companies not closely monitored to identify commercially active companies for close monitoring. - Extend analysis beyond the 41 strategic SOEs, as cumulative losses from small loss-making companies could be significant. ### Scope expansion for the forthcoming FRS - Priority reporting elements for FRS: - SOEs’ total debt with all financial instruments, categorized by short-term vs. long-term and external vs. domestic debt. - Equity injections and transfer of debt to the central government balance sheet. - Risk factors affecting enterprise performance and mitigation strategies (submitted by SOEs). - Deviations from SOE budget projections and forecast budgets and medium-term plans. - Presence and performance under performance contracts. - Quasi-fiscal activities and cost estimates. - Forward-looking information to influence SOE performance and risk ratings. - Concluding FRS section should list mitigation measures already in place or being implemented and explain how they mitigate risks. ### Guarantees and on-lending: current situation and risks - As of end-September 2024: - Outstanding stock of government guarantees and letters of comfort: LKR 1,660 billion - Equivalent to approximately 5.5 percent of estimated 2024 GDP - PFMA 3-year average GDP calculation note: ratio would be around 6% - One-third of outstanding guarantees attributed to the currency swap and trade credit provided by the Reserve Bank of India to the CBSL, backed by GoSL guarantees. - Primary SOE beneficiaries of guarantees: CEB, CPC, RDA, SLA, NWSDB — collectively account for more than half of outstanding guarantees. - Largest domestic creditors for guaranteed SOE loans: Bank of Ceylon (BOC), National Savings Bank (NSB), People’s Bank (PB). - Interconnectedness concern: deep linkage between GoSL, non-financial SOEs, and state-owned banks amplifies fiscal and financial risks. ### Recommendations - Near Term - 3.1 Require SOE to timely record financial data in the MIS. - 3.2 Create a consolidated database of SOE financial data with 2023 data. Review the initial dataset and build consistency checks to ensure data integrity. Engage with NBD/DTO for data input. - 3.3 Develop and adopt a credit risk analysis methodology for SOEs. - 3.4 Derive credit risk ratings in a simple Excel file. - Medium Term - 3.5 Prepare a comprehensive register of SOEs that are market producers. *Source: Excerpt from the IMF chapter on SOEs and fiscal risks (text as provided).* ### 41. Guarantees and on-lending have been issued without regard to beneficiaries’ financial ### 41. Guarantees and on-lending have been issued without regard to beneficiaries’ financial health and creditworthiness ### Summary of practices and recent interventions - Guarantees primarily supported key SOEs to sustain service delivery and infrastructure investments, even as these entities operated at a loss. - Guarantees and on-lending were issued without clear policies, eligibility criteria, or a credit risk assessment framework; risk mitigation mechanisms (such as fees) were not imposed. - On-lending often passed original loan terms directly to beneficiaries (SOEs and SMEs) without accounting for credit risk. - Despite weak credit risk assessment and monitoring, only a few guarantees have materialized recently because the GoSL frequently stepped in to absorb risks and prevent SOE defaults. - The GoSL has intervened by restructuring loans with creditors or providing direct financial support rather than allowing guarantees to materialize. - On-lent loans have been converted into equity through debt-for-equity swaps on several occasions, most recently in 2019, to reduce fiscal burden and strengthen SOE balance sheets. - Loans have been on-lent with an implicit understanding that recipients would not be able to repay the debt. ### Legal and institutional reforms - PDMA (enacted in June 2024) - Establishes a legal framework for sound management of guarantees and on-lending, assigning responsibility to the PDMO. - Authority to issue guarantees and on-lending rests with the Minister of Finance; PDMO tasked with management. - Defines policy objective of these instruments as promoting economic development. - Eligible beneficiaries: SOEs, Provincial Councils, and Local Authorities; other entities require parliamentary approval. - Mandates PDMO undertake a credit risk assessment before approving and issuing guarantees or on-lending. - Restricts eligibility to entities that are not in financial distress. - Requires risk mitigation measures, such as fees and spreads. - Implementation steps under way - GoSL finalizing regulation for the PDMO (procedures for managing instruments); regulation is undergoing approval through Cabinet and Parliament. - Guidelines are being drafted to outline processes for assessing, mitigating, monitoring, and reporting credit risk. - Both the regulation and guidelines are expected to be finalized within the current financial year. - PFMA (enacted in August 2024) - Reduces the ceiling on the outstanding stock of guarantees from 15 to 7.5 percent of GDP, calculated as the average of the current and previous two financial years. - No explicit limit set for on-lending; on-lending is indirectly constrained by PFMA's requirement to reduce public debt to sustainable levels. ### Reporting, recording, and transparency - Gross exposure to guarantees is disclosed in GoSL’s fiscal position reports, financial statements, and the quarterly debt bulletin. - Guarantees are recorded in an Excel-based database maintained by the DTO rather than the debt recording and management system. - Reports disclose gross exposure with a breakdown by debtor and creditor, purpose, issuance and maturity dates, but do not provide details such as guarantees issued over the past financial year or any risk assessments. - Information on on-lent loans has been excluded from GoSL reports. - PDMA mandates PDMO’s quarterly public debt reports include detailed information on outstanding guarantees and on-lent loans, improving transparency and reporting standards. - Debt liabilities are currently recorded in the Commonwealth Secretariat Debt Recording and Management System (CS-DRMS); migration to the Commonwealth Secretariat’s Meridien system is scheduled for 2025. ### Key issues identified - Implementing legislation and policies required to operationalize PDMA are not yet finalized; absence of detailed procedures and unclear coordination/information-sharing requirements hamper PDMO’s ability to assess, quantify, and monitor credit risk. - Data collection is cumbersome; inefficient information sharing limits PDMO’s detailed reporting on outstanding guarantees and on-lending. - Need to operationalize PDMA’s policy objective and eligibility criteria: PDMO should coordinate with NPD and other departments to ensure proposed projects align with national priorities. - The concept of “financial difficulty” requires clarification to determine its impact on financing currently loss-making SOEs (the largest beneficiaries of guarantees). - Existing reporting can be complemented immediately: - Include information on guarantees issued during the past financial year and where GoSL had to absorb risk. - Provide the same information for on-lending, currently absent from reporting. - PDMO capacity constraints: - PDMO was recently established and is still developing capacity; credit risk assessments for new requests and the outstanding stock have not yet been undertaken. - PDMO cannot adequately manage risks or incorporate risk quantification and probabilities of materialization into the forthcoming FRS until capacity and systems are developed. - Need for a robust credit risk assessment methodology developed in collaboration with the PED (key elements referenced in paragraph 34 of section III). - Risk mitigation measures (fees for guarantees and spreads for on-lending) should be linked to assessed credit risk and expected losses; such measures should be outlined in the FRS. - PDMO faces a significant workload; should prepare a detailed capacity building roadmap distinguishing urgent short-term training from medium-term capacity development, and seek technical assistance from development partners. ### Recommendations Near Term - 4.1 Expedite the finalization of legislation and policies required to implement the PDMA, enabling the PDMO to effectively carry out its responsibilities. - 4.2 In addition to guarantees, include an overview of the on-lent loan portfolio in the first FRS. - 4.3 Include an overview of guarantees and on-lent loans provided during the past financial year and information on materialized risks. - 4.4 Identify priority capacity building needs for PDMO staff and develop a structured roadmap for addressing them, prioritizing most critical short-term needs. Medium Term - 4.5 Develop and implement a comprehensive framework for assessing the credit risk from loan guarantees and on-lending. - 4.6 Link risk mitigation measures for guarantees and on-lending, i.e., fees and spreads, to the results of the credit risk assessments to ensure consistency and accountability. - 4.7 Enhance future FRSs by incorporating risk measures derived from credit risk assessments, including detailed risk quantification, to improve transparency and risk management. ### Fiscal context and related PPP highlights (selected figures) - PPP portfolio: Over 175 PPP projects have been financially closed during 1990-2023 with most in energy and port sectors. - Estimated implementation cost of closed PPPs: USD 5.3 billion (over 6 percent of GDP). - Port sector investment: USD 2.7 billion. - Power sector investment: USD 2 billion. - Competitive procurement: Only 13 projects awarded through competitive bidding; the rest via unsolicited proposals, direct appointments, and licensing schemes. - Pipeline: An additional 80 projects under consideration with an estimated investment of USD 2 billion. *Source: tarea2025085-source-pdf - 41. Guarantees and on-lending have been issued without regard to beneficiaries’ financial health and creditworthiness (PDF).* ### 65. There is a lack of centralized oversight and monitoring mechanisms for PPPs. A centralized ### tarea2025085-source-pdf - 65. There is a lack of centralized oversight and monitoring mechanisms for PPPs. A centralized ### Public-Private Partnerships (PPPs): oversight and monitoring - Centralized oversight and monitoring mechanism is necessary to monitor fiscal risks throughout the life of PPP contracts. - The Project Management and Monitoring Department (PMMD) could assume responsibility for monitoring PPP projects. - PPPs involve long-term financial commitments: 20-30 years. - Fiscal risks change as projects progress through stages; centralized monitoring is essential to: - track these risks, and - periodically revise fiscal cost assessments. - A designated team in MoF, comprising officers of NPD, NBD and PMMD, could independently assess estimated fiscal costs from these fiscal risks and provide useful information for NPD, NBD and PMMD. ### Fiscal limits and international practices - There are no fiscal limits on PPP commitments despite associated fiscal risks. - Setting limits on government PPP commitments could be considered to manage PPP-related fiscal risks. - Examples of countries that have sought to limit PPP exposure: UK, Hungary, Peru, Brazil, Indonesia, Turkey. - Limits can apply to: - stock (size of the PPP portfolio), - flows (annual fiscal commitments for PPPs), or - both. ### Capacity development and institutional arrangements - Capacity development across procuring entities, the PPP agency, and the Ministry of Finance should be prioritized due to limited awareness of fiscal risks. - The National Agency for Public-Private Partnerships (NAPPP) should be well-resourced to act as a center of excellence and assist line ministries at various project stages. - NAPPP should train officials of procuring entities; well structured and managed projects promote effective fiscal risk management. - MoF officers (relevant departments) should be equipped to: - screen, appraise, and assess fiscal affordability of PPP projects within an integrated public investment management framework (Part IX of the PFM Act), and - monitor project performance. - Efforts should leverage the Financial Management Information System (FMIS) and available tools (e.g., PFRAM) for fiscal risk assessment. ### Fiscal Risk Statement (FRS) treatment of PPPs - The 2025 FRS could provide a high-level discussion on PPP-related fiscal risks based on available information, aiming to deepen analysis in future FRSs. - NPD should obtain from line ministries: project size, purpose, procurement nature, investment, financial and physical progress, government guarantees, risk mitigation strategy, and expected worst-case fiscal cost. - NPD should provide FPD with a brief discussion on: - PPP portfolio size, - sectoral exposure, - associated fiscal risks, - mitigation strategies in place. - Future FRS should present in-depth analysis; international best practices suggest quantifying risks when possible and detailing measures undertaken during the year. - The expected annual receipts and expenditures over the life of PPP contracts should be clearly stated. ### Recommendations on PPPs - Near Term - 5.1 in the 2025 FRS, provide a qualitative discussion on the PPP related fiscal risks mentioning the PPP portfolio, fiscal risks identified in PPP projects, and the steps being taken or being contemplated by government to manage these risks. - Medium Term - 5.2 Develop a comprehensive legal and regulatory framework for managing PPP processes and portfolio, aligned with the PFM Act 2024. - 5.3 Strengthen institutional arrangements by clarifying roles and responsibilities of PPP procuring entities and relevant MoF departments, and by empowering the MoF to stop projects in each step of the project cycle. Institute a centralized oversight and monitoring mechanism for PPP contracts assisted by a designated team in MoF, comprising officers of NPD, NBD and PMMD. - 5.4 Establish a comprehensive PPP database within MOF. - 5.6 Strengthen capacity development across all stakeholders i.e. procuring entities and relevant departments in the Ministry of Finance. - 5.7 Deepen the analysis of PPP portfolio and associated risks in the future FRS by progressively adopting a quantitative approach. ### Financial sector: fiscal risks overview - Fiscal risks can arise from safeguarding financial stability, protecting customers, addressing market failures, or pursuing social and economic development objectives through the financial system. - Financial crises are high-profile examples with wider macroeconomic consequences; full-blown crises occur relatively infrequently where multi-layered oversight and regulation exist. - More frequent fiscal impacts occur when economic shocks and business cycles affect financial institutions, through lower revenues or higher payments to underperforming state-owned enterprises, or via unfunded quasi-fiscal activities. ### Reporting practice for financial sector fiscal risks in the first FRS - Focus elements for the first FRS: - Present summary indicators of financial sector health and analyze trends and risks explicitly covered by government (e.g., deposit insurance). - Analyze performance of state-owned financial institutions and associated net budgetary flows. - Explain how regulatory, coordination and policy frameworks are being strengthened, including extraordinary powers for crisis management and resolution. - Future enhancement: publish results of financial sector stress testing. ### Current situation — overall health of the financial sector - Sri Lanka’s financial system has faced significant challenges but remained relatively stable after policy interventions. - Significant interventions by GoSL and CBSL were required during the recent economic crisis to: - provide financial support to the sector, - reduce exposures to the government and SOEs, - ensure the sector is positioned to grow and support economic recovery. - Overall risks remain elevated but continue to subside. - Outstanding credit contracted for a period but has resumed growing. - Banking sector profitability was impacted by provisioning against declining credit quality which is improving slowly. - Market share of private sector financial institutions has been affected. - More favorable conditions followed macroeconomic policy responses, progress with debt restructuring and recapitalization of state banks. ### Performance of state-owned financial institutions (SOFIs) - Impact on state-owned banks and insurance companies has had significant fiscal implications; temporary retreat of private capital increased state share of financial sector revenues. - Findings: - State-owned institutions have remained profitable, in aggregate, but their share of profits has not increased in line with their increase in market share. - A higher profit share has been retained to satisfy rising regulatory provisions and underpin future growth in credit and underwritten risk, reducing dividends and levies payable to GoSL: less than 0.1 percent of GDP in 2023, down from around 0.2 to 0.3 percent of GDP in 2016 and 2017. - Budgetary support via subsidies and capital injections has had significant fiscal impact, including: - LKR 122 billion (0.4 percent of GDP) subsidy paid to two state banks in 2024, - budgetary support to Sri Lanka Insurance Corporation and Bank of Ceylon of around 0.1 percent of GDP each over 2017 and 2018. - State-owned banks have become less profitable relative to the rest of the banking sector, suggesting inefficiencies or competitive disadvantages. - Examples of quasi-fiscal activities include high interest savings accounts to senior citizens and low interest housing loans for low and middle-income families; no detailed account exists on whether these are adequately compensated through direct budgetary support. ### Regulatory and oversight arrangements - Policy steps: state-owned financial institutions will be subject to the same regulatory and prudential standards as private institutions. - Limits on large exposures will be phased in over 2026 to 2029. - Private sector governance standards and practices are gradually being applied to state-owned financial institutions. - Institutional responsibilities: - CBSL: overall financial stability and prudential supervision of bank and non-bank lending. - IRC: supervision of life and general insurers. - PED: monitors financial performance of state-owned financial institutions. - Financial Sector Oversight Committee (FSOC) and Financial Sector Crisis Management Committee (FSCMC): regulatory coordination and crisis management. ### Financial sector stress testing - CBSL undertakes financial sector stress testing for internal purposes; results are not included in its FSR. - Summary results from stress testing could be included in future FSRs and cross-referenced in the FRS. ### Issues in preparing the financial sector section of the FRS - Recommendation to establish a working-level technical group to support preparation. - Working group composition: FPD (lead coordinator), PED, DFD, CBSL and IRC. - FPD should coordinate strategic content without compiling detailed data inputs. - Sensitivity: respect independence of CBSL and IRC while ensuring their expertise contributes to the FRS. - Suggested analytical content (past 5–10 years): - Aggregate performance assessment of state-owned financial institutions (market share, profitability, solvency, liquidity) covering seven SOBs and four SOIs. - Select FSIs for comparison of state-owned institutions to sector-wide values. - Report explicit financial flows from the sector to government (dividends, levies, taxes). - Report explicit financial flows from government to sector (subsidies, grants, capital injections). - Discuss material examples of quasi-fiscal activities and other material risk exposures (e.g., NITF reinsurance exposure). - Consider anonymized or aggregated disclosure for market-sensitive information. ### Recommendations on the financial sector - Near Term - 6.1 Establish a working-level technical group to compile information and analysis supporting the financial sector section of the 2025 Fiscal Risk Statement. - FPD to compile inputs and establish processes and timelines. - CBSL and IRC to contribute material on sector health and developments; include analysis of adequacy and capitalization of deposit insurance arrangements. - PED to contribute analysis of state-owned banks and insurers; DFD to advise on various financial sector schemes. - 6.2 Summarize existing CBSL material on financial sector soundness and recent policy responses. - Medium Term - 6.3 Develop a more advanced level of practice in financial sector fiscal risk reporting: - Summarize key findings of stress testing / alternative macroeconomic and financial scenarios in FSR. - Discuss development of crisis management framework, including new legal powers and size of the financial stability fund. - Provide further details about FSOC and FSCMC work programs or special topics. ### Natural disasters and climate change: fiscal risk reporting - Fiscal costs arise from relief, recovery, reconstruction/rehabilitation, risk management and mitigation (including insurance and resilient infrastructure). - Indirect costs include impacts on capital base, production, incomes and revenue losses. - Contingent liabilities could be triggered (e.g., via SOEs or PPPs). - Climate change is increasing frequency and impact of natural disasters; more adverse scenarios could reduce potential economic growth and affect fiscal sustainability. ### Reporting elements for natural disaster fiscal risks in the first FRS - Provide historical account of incidence of natural disasters, illustrating main hazards and their economic and fiscal implications qualitatively. - Report quantitative estimates of economic loss and fiscal costs over time to establish potential aggregate impacts. - Examine adequacy of budgetary provisions, contingencies and other strategies for managing fiscal costs of disasters of varying severity. - Advanced practices over time: present results of modelling or stress testing of economic and fiscal impacts under a range of disaster and climate change scenarios. ### Current situation — incidence and costs - Sri Lanka is exposed to floods, landslides, cyclones, drought among the most significant regularly occurring events. - Low-frequency, high-cost event example: 2004 Indian Ocean Tsunami — single largest loss event (over 2 percent of GDP in 2023 terms). - Combined economic loss from floods in 2016 and 2017 was close to 3 percent of GDP in 2023 terms. - Droughts have had sustained impacts on agricultural production and incomes. - Significant dengue fever outbreaks have occurred with moderate frequency. *Source: tarea2025085-source-pdf - 65. There is a lack of centralized oversight and monitoring mechanisms for PPPs. A centralized* ### 85. There are significant gaps for the historical economic loss and fiscal costs of natural ### tarea2025085-source-pdf - 85. There are significant gaps for the historical economic loss and fiscal costs of natural ### Data gaps on historical economic loss and fiscal costs - Economic loss estimates are not systematically recorded; relevant information can be drawn from post-disaster needs assessments following major events. - EM-DAT database: no recorded economic loss associated with major events after 2017 (Figure 7.2). - DesInventar database: contains a field for economic loss but has no data entries. - Data on injuries, deaths and houses damaged or destroyed are included in databases but do not always align with final situation reports, so impacts may be underreported. - No centrally coordinated estimates of fiscal costs associated with major events and no consolidated account of total natural disaster-related spending by year. - Fiscal data relatively complete for: coordination costs, compensation of affected individuals, payment of insurance and reinsurance premiums, and landslide mitigation projects. - Key fiscal data gaps: reconstruction and rehabilitation costs and reallocation of appropriations to Ministries, subnational governments and districts for post-disaster response and recovery. ### Existing quantitative estimates and scenarios - World Bank and GFDRR (2016) estimated: - Annual average economic loss from natural disasters of around 1.5 per cent of GDP (excluding the 2004 Indian Ocean Tsunami). - The 2004 Indian Ocean Tsunami had an estimated loss of over 6 per cent of GDP. - Middle scenario fiscal costs (coordination, relief and recovery for housing and roads): around 0.5 per cent of GDP (annual average). - UN ESCAP more recent estimate: - Estimated annual economic losses from natural disasters of around 2.5 per cent of GDP. - Applying the World Bank/GFDRR middle scenario assumption would translate into expected annual fiscal costs in the order of 0.9 per cent of GDP. - Climate-change adjusted projections: - Under alternative climate change scenarios, projected annual economic losses increase from 2.5 to 2.8–3.0 per cent of GDP. - Adopting the same WB/GFDRR assumption, expected fiscal cost from natural disasters rises to around 1.1 per cent of GDP. - Sri Lanka faces annual adaptation costs of around USD 430 million or 0.5 per cent of GDP per annum. ### Adequacy of budgetary provisions and financial preparedness - It is not possible from available information to gauge overall adequacy of Sri Lanka’s financial preparedness for natural disasters. - Preparing the Fiscal Risk Statement (FRS) requires historical tables and projections of budgetary allocations to: - disaster coordination, relief, reconstruction and rehabilitation costs, - risk management and transfer, - resilience and adaptation initiatives. - Considerations for financial preparedness: - Use of within-year budgetary flexibility (virements and the budget reserve) has supported responses (e.g., substantial reallocations noted in 2016 and 2017 Annual Reports but not quantified). - Review broader financial risk transfer/management mechanisms: potential revisit of the natural disaster fund (which could accumulate unspent provisions), implications of closure of the Natural Disaster Insurance Scheme, availability and pricing of insurance, and new requirements of the PFM Act governing use of the budget reserve and supplementary budgets. - For climate change, FRS should review adequacy of framework relating to: - adaptation investment, - risk retention (contingencies and budgetary reallocation mechanisms), - catastrophe risk insurance or risk ceding arrangements. ### Institutional and technical arrangements for FRS natural disaster section - Recommendation to establish a working-level technical group to support preparation of the natural disaster section of the FRS. - Proposed membership: FPD (lead/coordinator), DMC, NBD, NPD, MoE. - FPD to coordinate preparation strategically but not to be drawn into detailed data compilation; contributing areas to provide detailed inputs. - Near-term approach for the first FRS (2025): - Base on readily available information with modest investments in improving data. - Immediate priority: establish more complete and reliable estimates of direct fiscal costs from natural disasters for the past 10 years (see Annex 1). - If gaps remain, objective to close them quickly. - Linkages with existing national commitments: - Sri Lanka’s NDCs commit to establishing better information on natural disaster risks and estimates of loss and damage and to participate in global initiatives (e.g., Warsaw International Mechanism). - NDMP 2023–2030 includes recommendations relevant to financial preparedness: - Recommendation 3.1: contingency reserves equal to 2 per cent of the total budget of each Ministry and allowing reallocation of budgetary provisions from newly approved projects for post-disaster reconstruction. - Recommendation 3.2: expansion of post-disaster compensation in the medium-term and introducing new tax expenditures in the short-term. - These NDMP recommendations need assessment from an overall PFM perspective given fiscal space limitations. ### Specific near-term and medium-term recommendations - Near Term - 7.1 Establish a working-level technical group to compile available information and analysis supporting the natural disaster and climate change section of the 2025 Fiscal Risk Statement. - FPD would compile inputs from contributing areas and establish agreed processes, timelines and information needs for this and future statements. - DMC, NBD and NPD would work from February to May 2025 to establish a more complete dataset on the fiscal costs of natural disasters from the past 10 years. - 7.2 Summarize historical incidence of natural disasters and present available quantitative estimates of annual expected economic losses and fiscal costs in the 2025 FRS. - This should cover the past 10 years. - The FRS can summarize estimates prepared by other partners on costs of natural disasters and potential impacts of climate change. - It should contain a high-level discussion of adequacy of budgetary provisions and risk management practices, foreshadowing intent to review these closely in future statements. - Medium Term - 7.3 Expand depth of analysis and focus on climate change implications in future FRSs. - Find permanent solutions to facilitate better tracking of natural disaster-related spending, including exploring a marker in the chart of accounts/ITMIS. - Update hazard risk profiles at least every 5 years (in line with planning cycle) and consider generating aggregate multi-hazard loss exceedance estimates. - Ensure main databases are accurate and complete to support better estimation of future impacts. - Integrate climate scenarios with the macroeconomic framework to explore potential impacts (on revenue, productivity etc) in fiscal aggregate projections and DSA. ### Broader FRS institutional, data management, analysis and communication guidance (selected points) - Institutional arrangements - Centralize information on fiscal risks within government while keeping clear responsibilities for individual entities to manage risks from their activities. - FPD (MFU) positioned to lead and coordinate FRS preparation given mandate on macroeconomic and fiscal assessment and policy analysis. - Suggested roles by risk type (overview): - Macroeconomic risks: FPD (consult CBSL/IRD/SLC as required). - SOE risks: PED (coordinate with DTO/PDMO and NBD). - Guarantee/on-lending risks: PDMO (transitioning from DTO) with NPD, PED involvement. - PPP risks: NPD coordinate with NAPPP to develop comprehensive PPPs database. - Financial sector risks: working-level group with FPD (lead), PED, CBSL and IRC. - Natural disaster risks: working-level group with FPD (lead/coordinator), DMC, NBD, NPD, MoE. - Recommend issuing a Treasury Circular to allocate roles and responsibilities and establish reporting protocols, templates, frequencies and lags. - Improving data management - Identify and leverage existing but dispersed data across MDAs; departments of MoF should collaborate with MDAs to identify sources. - Consider a fiscal risk register to list and categorize known and potential fiscal risks; include fiscal impact, likelihood, mitigation strategies and data sources; FPD to lead centralized approach complemented by detailed registers for specific risks (guarantees, SOEs, PPPs). - Future goal: develop bottom-up fiscal risk register from line ministries to complement high-level MOF register; consider using the Fiscal Risk Assessment Tool (FRAT) as data availability expands. - Validate data quality through structured processes: cross-verification, consistency checks, feedback mechanisms, and protocols for regular audits and updates. - Strengthening fiscal risks analysis - Incorporate brief summaries of comprehensive existing analyses (e.g., FSR) into the FRS to avoid redundant re-analysis. - Initiate new analyses where data is accessible; tailor depth to complexity and importance (e.g., scenario analyses and stress testing for macroeconomic risks; SOE performance and governance analysis). - Where quantitative data is not available, develop qualitative descriptions using expert judgment and historical context; highlight implications for fiscal sustainability and mitigation strategies, and flag need for improved data collection. - Developing a communication plan - Engage politicians early to build understanding that comprehensive reporting of fiscal risks supports better fiscal policy, market confidence, and credibility. - Emphasize that transparency and robust analysis can mitigate negative effects on fiscal balances and the economy and prevent abrupt disruptive policy changes when risks materialize. *Source: excerpt from the provided PDF content unit.* ### 107. Collaboration within government is also essential. Given the wide range of information ### tarea2025085-source-pdf - 107. Collaboration within government is also essential. Given the wide range of information ### Collaboration within government - Line ministries, SOEs, and various departments of the MoF all play a role in fiscal risk reform; perspectives on benefits may differ across stakeholders. - The FPD needs to ensure sufficient engagement with stakeholders through both bilateral and multilateral discussions, emphasizing advantages to stakeholders, such as: - improved preparation for the risks they are responsible for; and - reduced disruptions to their own financial management. - Provide clear technical guidance and user-friendly tools (e.g., spreadsheet templates for collecting fiscal risk information) to alleviate burdens on stakeholders. ### Communication with the public - Public disclosure of fiscal risk information is crucial for transparency but must be accompanied by clear explanations of the meaning of fiscal risks. - The FRS should include the government’s current and upcoming measures for risk mitigation. - The FRS should synthesize information from the fiscal risk register and present fiscal risk information in a manner conducive to effective public communication. - The MoF should aim to disclose all explicit fiscal risks but may choose not to disclose certain implicit risks (e.g., potential bailout of large financial institutions) to avoid moral hazard. ### Improving staff capacity - Build analytical capacity of staff involved in fiscal risk analysis and management given limited awareness of fiscal risks. - Training priorities: - educate staff on different types of fiscal risks, focusing initially on priority areas; - hands-on training in stress testing, scenario analysis, and risk modeling to evaluate and manage relevant fiscal risks. - Collaborate with international organizations (e.g., IMF, World Bank) to access global expertise and good practices. ### Recommendations — Near Term - 8.1 Issue a Treasury Circular to clearly allocate roles and responsibilities among ministries, departments, agencies, and SOEs—specifying who is accountable for each task and the associated timelines. - 8.2 Identify the sources of data/information for the selected fiscal risks, develop databases, and confirm data quality. - 8.3 Prepare analysis of the fiscal risks: - If comprehensive analysis is available in other reports, e.g. FSR on financial sector risks, a brief summary of those reports would suffice - If analysis hasn’t been conducted, but related data is available, e.g. macroeconomic risks, SOEs, guarantees, analysis can be performed (analysis depth may vary depending on the issues) - If data are not available, a qualitative description of the risks can be prepared - 8.4 Clearly communicate with politicians about the benefits of the FRS in supporting timely decision-making and enhancing market confidence, while also informing the public about the actions taken to effectively manage fiscal risks to avoid potential misunderstandings. - 8.5 Train staff to enhance their capacity on fiscal risk analysis and management. Seek technical assistance if needed. ### Annex 1 — Outline for the 2025 Fiscal Risk Statement (FRS) - Introduction and overview: - Explain policy motivation and legal requirements for preparing the FRS and how breadth of coverage and depth of analysis will build over time. - Fiscal risk assessment needs to be dynamic; constellations of risks and relative significance will evolve in the Sri Lankan context. - Consider including the Fiscal Risk Heatmap from the FRAT to summarize annual scope and conclusions. - Judgment-based or qualitative assessments are acceptable when quantification is not possible. - Determine thresholds to distinguish categories; some initial thresholds suggested. - Example guidance: previous studies estimate average annual fiscal cost of natural disasters is around 1 per cent of GDP. This suggests unexpected fiscal costs might exceed 0.5 per cent of GDP with medium likelihood (say on average once every 5 years). - Example: Summary of 2025 Fiscal Risk Assessment for Sri Lanka - Likelihood of realization: Remote (<10%) Possible (10-50%) Probable (>50%) - Potential fiscal impact categories: - High (>0.5% of GDP) - Medium (0.1-0.5% GDP) - Low (<0.1% of GDP) ### Macroeconomic Risks - Describe how macroeconomic risks impact fiscal aggregates and the medium-term fiscal strategy. - Economic uncertainty and forecast errors: - Focus on volatility in nominal GDP and its components (real GDP and GDP deflator); volatility affected by real and external shocks. - Use volatility estimates to present a fan chart for nominal GDP and revenue projections (e.g., central case projection +/- one standard deviation). - Present historical forecast/projection errors for nominal GDP, total revenue, primary balance, overall balance, public debt and discuss main drivers. - Discuss recalibration of forecasts under the IMF EFF, new MTFF, and regular evaluation under the FSS. - Main sources of macroeconomic risk: include qualitative discussion of top 3-5 areas that could impact MTFF over a 5-year horizon; present in table format (example entries include GDP growth slower than expected; commodity prices higher than expected; exchange rate depreciation). - Risk mitigation: reference new Fiscal Responsibility Framework, fiscal strategy objectives (revenue mobilization, controlling expenditure growth, rebuilding fiscal buffers), and structural reforms to diversify the economy; mention steps to address systematic biases in forecasting. ### Public Debt - Debt Sustainability Analysis: - Under the new PFM Act, the Finance Minister is required to prepare and publish DSA on an annual basis as a step in establishing/updating the MTFF. - DSA will present an updated central case projection for the debt reduction path implied by recent fiscal performance and latest fiscal aggregate projection vintages. - FRS could present sensitivity analysis or alternative scenarios from the DSA. - Early years may use IMF’s DSA from the most recent Article IV or EFF Review; recent IMF DSAs have included a natural disaster scenario. - When capacity permits, FPD could conduct its own DSA. - Debt Portfolio Analysis: - Include summary information and short discussion of debt portfolio composition and relevant MTDS targets/metrics. - Avoid duplicating quarterly Debt Bulletin content. - Use tables/charts to illustrate term structure, domestic vs FX exposures, fixed vs floating interest rate exposures, and projections of debt servicing costs. - Discuss main risk factors: refinancing risk, interest rate risk, exchange rate risk. - Supplement with information on latest credit risk assessments and ratings from main rating agencies. - Mitigation measures: describe prudent debt management policy, ongoing monitoring against targets, publication of quarterly Debt Bulletin. ### State-owned Enterprises (SOEs) - Describe main types of fiscal risks from SOE operations and impact on fiscal aggregates. - Overview of SOE sector: identify which entities included in SOE fiscal risk analysis: - the 41 most strategic companies; 11 others considered separately under the financial sector. - Financial performance: - Prepare aggregate performance (revenue, profitability) of the 41 strategically important non-financial SOEs over the past 3-5 years. - Include how many of the 41 were profit-making vs loss-making in 2024; identify any with negative equity as at end of 2024. - Include chart identifying SOEs with largest liabilities and contribution to total liabilities. - SOE risk assessment: - Methodology developed to allow MoF to undertake credit risk assessment of individual SOEs (may have used 2023 data) using financial ratio analysis. - Present overview of risk ratings listing number of entities in each risk category (very high, high, medium, low, very low); identify very high or high risk entities and key concerns. - Budgetary impacts: - Present table/chart covering past 5-10 years on aggregate financial flows from SOEs to government (dividends, taxes, levies) and from government to SOEs (subsidies, grants, capital injections); calculate net flows each year and present net flows as percentage of GDP. - Mitigation measures: - Discuss policy reform measures to mitigate risks and measures targeted at high-risk SOEs. - Focus on SOE governance frameworks and steps to improve financial performance or reduce government exposure. ### Guarantees and On-Lending - Portfolio analysis: provide breakdown of loan guarantees and on-lending. - Newly issued guarantees and on-lending: break down newly issued instruments, purpose, and policy alignment. - Risk materialization: discuss historical materialization and highlight the past financial year. - Risk management strategy: discuss policy framework for mitigation and monitoring, and provisioning in the budget. ### Financial Sector - Overall health of the financial system: - Provide summary and a set of financial soundness indicators (profitability, solvency, liquidity, asset quality) in consultation with CBSL and IRC. - Include preliminary FSIs for December 2024 (available from quarterly updates). - Example: Selected Financial Soundness Indicators for Banking Sector - Years: 2020 2021 2022 2023 2024 (Sep) - Profitability - Return on assets (before tax): 1.4 1.6 0.9 1.5 1.8 - Return on equity (after tax): 11.4 14.5 10.4 11.5 13.5 - Solvency - Tier 1 capital adequacy ratio: 13.6 13.2 13.2 15.2 14.7 - Total capital adequacy ratio: 17.1 16.5 16.2 18.4 18.5 - Liquidity - High-quality liquid assets ratio: 24 22.5 18.5 32.2 #.# - Credit quality - Impaired loans (Stage III) ratio: 11.3 12.8 12.4 - Source: Central Bank of Sri Lanka Financial Stability Review 2024 and Q3 2024 Financial Soundness Indicators. - Performance of state-owned financial institutions: - Summarize trends in profitability, solvency, liquidity, asset quality and compare to sector averages. - Present flows from sector to government and from government to sector over a 10-year horizon. - Risk management and oversight arrangements: - Draw on recent CBSL FSRs to discuss recent policy measures and future steps to support financial system stability, including establishment of the financial stability fund. - Provide clear account of coordination arrangements and how systemic risks are monitored and managed. ### Natural Disasters and Climate Change - Incidence of natural disasters: - Report incidence over at least the past 10 years using indicators like number of persons affected or damages/economic loss. - Example visualizations: Sri Lanka number of affected persons, by hazard (persons, log scale); Sri Lanka estimated damages, by hazard (USD, billion). - Sources cited: Sri Lanka Nationally Determined Contributions Implementation Plan 2021-2030; UN ESCAP Risk and Resilience Portal, Sri Lanka country profile. - Estimates of fiscal costs: - Summarize fiscal costs associated with natural disasters over past 10 years drawing on World Bank/GFDRR and UN ESCAP work. - Example table format: Sri Lanka - Estimated Fiscal Costs of Natural Disasters, by year (percent of GDP) with categories for Direct costs and Indirect costs and subcategories (Coordination, Relief, Reconstruction, Transfers, Insurance, Adaptation/Mitigation, Revenue losses) with placeholders #.# across 2015–2024 and Avg. - Probabilistic estimates: - Include probabilistic estimates to illustrate variability; costs for 1-in-10 or 1-in-50 year events can be many multiples of average annual cost (example chart referenced from World Bank/GFDRR Probabilistic Loss Exceedance Curves, Fiscal Costs (LKR, billion)). - Financial preparedness and risk management layers: - Appropriations to Ministries for coordination, relief and infrastructure vs observed historical costs. - Virements, annual budget reserve, constitutional contingency fund, and escape clause under the new Fiscal Responsibility Framework—are these sufficient? - Natural Disaster Fund. - Insurance and other risk transfer arrangements. - Agreements/Contingent Finance Arrangements with Development Partners. - Fiscal buffers—maintain margin for error in fiscal targets (PBT and PEC), reducing debt levels to respond to future disasters. - Climate change: - Summarize material from Sri Lanka’s NDCs and other sources on projected impacts of climate change on frequency and impact of disasters; discuss mitigation and adaptation priorities and associated costs. ### Public Private Partnerships (PPPs) - Provide high-level discussion on PPP-related fiscal risks in the 2025 FRS. - Portfolio analysis: - If data not readily available, use public domain sources (e.g., ADB Public Private Partnership Monitor 2019 and 2023). - Include chart depicting growth of PPP portfolio (number of projects with financial close and value of investment) and sectoral composition changes. - Mention number and sectoral composition of PPP projects in the pipeline (NAPPP details). - Nature of government support: discuss forms of government support provided to PPP projects in Sri Lanka. - Fiscal risk identification, assessment and materialization: - Overview of types of risks identified and assessment of likely fiscal impact; note database growth will refine analysis. - Historical materialization examples where available (e.g., payments due to renegotiation or guarantee calls; example mention: Port City Project – renegotiation). - Risk management strategy: - Discuss policy framework for mitigation and monitoring, planned enactment of comprehensive PPP Law, associated regulations/guidelines, institutional arrangements, recording of contingent liabilities, provisioning in the budget, and limits on exposure to PPPs depending on measures considered for 2026. ### Annex 2 — Quantitative Climate Risk Assessment Fiscal Tool (Q-CRAFT) - Q-CRAFT generates long-term fiscal projections under different climate change scenarios using publicly available data in a structured approach for 171 economies through 2099. - Projections: - Baseline macro-fiscal scenario for GDP and key fiscal indicators grounded in a simple production function and standard debt dynamic equation using budgetary, economic, demographic data and modifiable assumptions. - Cross-country empirical estimates using the Kahn (2021) methodology of temperature impacts on GDP per capita under different climate scenarios are applied to baseline to project to 2099 fiscal indicators (e.g., debt-to-GDP ratio). - User inputs: - Country selection and assumptions for demography, productivity, inflation, and interest rates. - Long-term projections for key fiscal aggregates under baseline and alternative climate scenarios are automatically generated. - The tool and user guide are available at the Fiscal Risks Toolkit Q-CRAFT page (URL provided in source). - Source cited: Tjeerd Tim and Jyoti Rahman, 2024, User Guide for the Quantitative Climate Risk Assessment Fiscal Tool (Q-CRAFT). ### Annex 3 — Illustrative Fiscal Risk Register - Template fields (columns) include: - Risk category; Source; Est. fiscal impact (L/M/H); Comments on fiscal impact (including direction of impact and time horizon); Likelihood of risk materializing (L/M/H); Comments on likelihood; Risk ‘owner’; Mitigation measures in place, and what more can be done; Sources of information and data. - Example risk entries indicated: - Macro risk e.g. Changes to GDP growth - Macro risk e.g. Change in import prices - Specific fiscal risk Public enterprises - Specific fiscal risk Subnational Governments - Specific fiscal risk Natural disasters - Specific fiscal risk PPPs - Notes: - 1. L, M, and H stand for low, medium, and high respectively. - 2. Risk ‘owner’ is the institution responsible for managing related fiscal risks. *Source: IMF Technical Assistance Report (excerpts from the provided PDF content).* --- _Source: https://www.imf.org/-/media/files/publications/tar/2025/english/tarea2025085-source-pdf.pdf_