## 1armea2022001

## Source details

**Canonical URL:** [1armea2022001](https://www.imf.org/-/media/files/publications/cr/2022/english/1armea2022001.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/cr/2022/english/1armea2022001.pdf.md)
- [Structured JSON version](/-/media/files/publications/cr/2022/english/1armea2022001.pdf.json)

---

### Mission overview and objectives
- Mission dates: September 27–October 8, 2021.
- Mission team: Ms. Ivana Jablonská and Mr. David Bailey.
- Requesting authority: Ministry of Finance (MoF).
- Supporting department: IMF Middle East and Central Asia Department (MCD).
- Main objectives:
  - Assist authorities to finalize a comprehensive sectorized list of all public sector units (Public Sector Institutional Table, PSIT).
  - Compile annual general government Government Finance Statistics (GFS) data for 2020.
  - Provide practical and tailored training to improve capacity to compile and disseminate GFS.

### Priority recommendations and timelines
- December 2021
  - Finalize and publish the Public Sector Institutional Tables (PSIT), in cooperation with Armstat and the CBA.
  - Responsible Institution: MoF
- March 2022
  - Strengthen and formalize the cooperation between statistical compilation institutions.
  - Responsible Institutions: MoF, Armstat, CBA
- June 2022
  - Secure access to detailed data for budgetary government held in the Treasury Single Account (TSA) and establish processes to use the data in GFS compilation.
  - Responsible Institution: MoF
- Two-year priority focus: The three recommendations above carry particular weight for improving GFS quality and completeness.
- Continuous (regular)
  - Regularly review and update the PSIT in cooperation with Armstat and CBA.
  - Responsible Institution: MoF

### Detailed technical recommendations (selected, with deadlines)
- October 2021
  - Compile and disseminate GFS for 2020, through the IMF’s annual GFS database, using the current data reports and general government delineation.
  - Update and transmit to the IMF the climate change questionnaire with 2020 data on government policy indicators.
  - Responsible Institution: MoF
- December 2021
  - Finalize the PSIT and share with Armstat, CBA and the IMF; seek to make publicly available by (or as soon as possible after) the target deadline.
  - Define and formalize GFS data requirements for access to in-year and historic TSA data, including GFSM 2001 and budget codes.
  - Develop a work plan for extension and improvement of GFS and PSDS; share with CCAMTAC.
  - Responsible Institution: MoF
- March 2022
  - Ensure adequate staff capacity for the GFS work plan.
  - Establish a technical working group with MoF, Armstat, and CBA to meet regularly on sector classification and methodology.
  - Put in place Memoranda of Understanding (MoU) between MoF, Armstat, and CBA for data sharing and sector classification.
  - Establish clear processes and documentation to update PSIT annually or biennially.
- June 2022
  - Develop and test new GFS compilation systems/processes for budgetary government using detailed TSA data.
  - Responsible Institution: MoF
- September 2022
  - Compile and disseminate GFS for 2021 (and at least the previous 5 years) through IMF annual GFS database using: (i) detailed TSA data for budgetary government; (ii) existing data sources for extrabudgetary government; and (iii) additional data for general government units identified through the PSIT.
  - Responsible Institution: MoF
- October 2022
  - Investigate differences between GFS and national accounts data and implement a program to bring the two into alignment where appropriate.
  - Responsible Institutions: Armstat, MoF
- September 2023
  - Establish efficient data collection arrangements covering all general government units; frequency to depend on materiality and fiscal risks.
  - Responsible Institutions: MoF, Armstat, CBA

### PSIT size, sector classification findings, and specific unit-level notes
- Latest draft PSIT size: 3,456 institutional units.
- Overall PSIT summary (as presented)
  - Joint Stock Companies (JSCs): Government Units 151; Public Corporations 79; Not yet classified 0; Total 230
  - State Non-Commercial Organizations (SNCOs): Government Units 1,829; Public Corporations 12; Not yet classified 0; Total 1,841
  - Local Non-Commercial Organizations (LNCOs): Government Units 1,180; Public Corporations 0; Not yet classified 0; Total 1,180
    - Note: Although the State Registry lists 1,440 LNCOs, to-date only 1,182 have been confirmed.
  - Public Financial Corporations: Government Units 1; Public Corporations 21; Not yet classified 0; Total 22
  - Public Foundations: Government Units 39; Public Corporations 17; Not yet classified 70; Total 126
  - Public Entities in process of liquidation: Government Units 14; Public Corporations 0; Not yet classified 43; Total 57
  - Total: Government Units 3,214; Public Corporations 129; Not yet classified 113; Total 3,456
  - Note: Nine privatized public entities were identified by the MoF and have been excluded from this list.
- Public foundations
  - 70 public foundations remained unclassified at time of review.
  - Mission reviewed 70 unclassified foundations and established preliminary classifications for 41; 29 required further examination.
  - Default classification guidance: classify public foundations as extrabudgetary government units given non-commercial nature — but apply default only when necessary on a case-by-case basis.
  - Suggested information sources: internet searches for charters, annual reports, accounts; contact relevant ministry or local community if necessary.
  - Recommendation: include liquidation-status notes and keep units in process of liquidation in PSIT until fully liquidated.
- Public financial organizations (selected)
  - Extrabudgetary Central Government Units: Deposit Guarantee Fund of Armenia; Pension Guarantee Management Fund.
  - Public Financial Corporations (selected list): Central Bank of Armenia; Export Insurance Agency of Armenia CJSC; Development and Investments Corporation of Armenia CJSC; Panarmenian Fund; Armenian Card CJSC; National Mortgage Company CJSC; Homes for Youth CJSC; Small and Medium Business Credit Support CJSC; Vehicle Single Window CJSC; Stak Processing CJSC; Stak Money Transfer CJSC; Hayincassatsia CJSC; Financial System Mediator.
  - Notes:
    - Panarmenian Fund previously thought not to be an institutional unit; new CBA information suggests it is.
    - Stak Money Transfer CJSC and Stak Processing CJSC merged in January 2021.
    - Hayincassatsia began liquidation in 2020.
  - Classification uncertainties: ACRA Credit Reporting JSC and Armenian Motorinsurers’ Bureau may be public financial corporations but mission could not establish public-sector control; German-Armenian Fund appears not to meet criteria for a separate institutional unit.

### Sector classification of health units (JSCs) — regional breakdown (number of units)
- Ministry of Health: Public Corporation 3 / Central Government 13 / Local Government 0 / Total 16
- Aragatsotn province: 2 / 2 / 0 / 4
- Ararat province: 3 / 4 / 0 / 7
- Armavir province: 5 / 1 / 0 / 6
- Gegharkunik province: 7 / 1 / 0 / 8
- Kotayk province: 3 / 5 / 0 / 8
- Lori province: 12 / 2 / 0 / 14
- Shirak province: 9 / 11 / 0 / 20
- Syunik province: 2 / 5 / 0 / 7
- Tavush province: 1 / 0 / 3 / 4
- Vayots Dzor province: 2 / 1 / 0 / 3
- Yerevan municipality: 0 / 0 / 32 / 32
- Total: Public Corporation 49 / Central Government 45 / Local Government 35 / Total 129

### PSIT presentation, identifiers, and documentation
- PSIT must transparently reflect frequent public sector composition changes (dissolutions, new units, mergers, restructures).
- Recommended PSIT format: two elements
  - I. List of all Public Sector Units as of a Point in Time (e.g., 31st December)
  - II. List of all Changes in Classification of Public Sector Units Between Updates (e.g., 1st January to 31st December)
- Recommended template fields (examples): Tax Payer Identifier; State Registry Number; Legal Entity Code; Legal Form; Basis of sectorization/resectorization; Sector/Subsector; Armenian name; English name; New unit (in year); Dissolved unit (in year); Effective dates; Previous Sector/Subsector; Additional notes.
- Unique identifiers:
  - Inconsistencies in identifier format were observed (separators “.”, “,”, or removed; some identifiers included leading blank spaces).
  - Recommendation: present all identifiers consistently and in same format as used in other government datasets; remove blank spaces preceding identifiers.
- Documentation:
  - Maintain transparent electronic documentation explaining rationale for each sector classification decision.
  - Consider including a short rationale column in published PSIT.

### GFS compilation for 2020 — provisional results, coverage, and quality checks
- Responsible units and handover
  - GFS responsibilities now with Financial Statistics and Risks Department (FSRD), MoF.
  - Public Debt Management Department (PDMD) to assist compiling GFS for 2020; PDMD compiled balance sheet data for budgetary general government for 2020.
  - Final GFS for 2020 expected to be transmitted to IMF Statistics Department before end of October 2021.
- Provisional GFS for 2020 — coverage
  - Covered budgetary central government, budgetary local government, and SNCOs.
  - Compilation used ten summary data reports and required considerable manual intervention.
- Internal consistency checks
  - Compiled GFS for 2020 showed good consistency across sectors and between ‘above-the-line’ and ‘below-the-line’ transactions.
  - Total statistical discrepancy (between ‘above-the-line’ and ‘below-the-line’) was limited to 1.3 percent of total expenditure.
- Provisional GFS 2020 — Statement of Operations (selected lines, in billion AMD)
  - 1 Revenue: 1,535.9 191.2 -179.2 1,547.9 156.1 -83.0 1,621.0
  - 11 Taxes: 1,360.4 0.0 -9.1 1,351.4 30.8 -1.4 1,380.8
  - 13 Grants: 53.2 155.3 -153.2 55.3 81.6 -81.6 55.3
  - 14 Other revenue: 122.2 35.9 -16.9 141.2 43.8 0.0 185.0
  - 2 Expense: 1,643.7 178.8 -179.2 1,643.3 121.3 -83.0 1,681.6
  - 21 Compensation of employees: 176.1 139.5 0.0 315.6 27.6 0.0 343.2
  - 22 Use of goods and services: 179.2 26.9 -16.2 189.9 19.4 0.0 209.3
  - 24 Interest: 164.8 0.0 0.0 164.8 0.1 0.0 164.9
  - 25 Subsidies: 119.1 0.0 0.0 119.1 0.4 0.0 119.4
  - 26 Grants: 186.9 0.0 -153.2 33.6 64.4 -81.6 16.4
  - 27 Social benefits: 534.3 1.4 0.0 535.8 2.3 0.0 538.1
  - 28 Other expense: 283.4 11.0 -9.8 284.6 7.1 -1.4 290.3
  - 31 Gross investment in nonfinancial assets: 226.2 0.0 0.0 226.2 17.1 0.0 243.3
  - 311 Fixed assets: 226.2 0.0 0.0 226.2 36.3 0.0 262.5
  - 314 Nonproduced assets: 0.0 0.0 0.0 0.0 -19.2 0.0 -19.2
  - 2M Expenditure (2+31): 1,869.9 178.8 -179.2 1,869.5 138.4 -83.0 1,924.9
  - NLB Net lending (+) / Net borrowing (-) (1-2M): -334.0 12.4 0.0 -321,6 17.8 0.0 -303.8
  - 32 Net acquisition of financial assets: 19.7 12.4 0.0 32.1 17.8 0.0 49.9
  - 33 Net incurrence of liabilities: 353.7 0.0 0.0 353.7 0.0 0.0 353.7
  - NLBz Overall statistical discrepancy: NLB vs Financing (32-33-NLB): 0.0 0.0 0.0 0.0 0.0 0.0 0.0
  - Note: Due to rounding components may not sum to totals.
- Provisional GFS 2020 — Expenditure by Functional Categories (COFOG) (selected lines, in billion AMD)
  - 7 EXPENDITURE [=2M]: 1,869.9 178.8 -179.2 1,869.5 138.4 -83.0 1,924.9
  - 701 General public services: 344.3 11.8 -11.0 345.2 36.1 -79.2 302.0
  - 702 Defense: 387.8 0.3 -0.3 387.8 0.1 0.0 387.9
  - 704 Economic affairs: 125.6 15.8 -8.9 132.5 10.8 0.0 143.3
  - 707 Health: 148.2 10.2 -11.6 146.8 0.4 0.0 147.2
  - 709 Education: 143.8 111.6 -112.2 143.2 48.9 -3.7 188.4
  - 710 Social protection: 521.8 5.3 -5.4 521.7 3.1 0.0 524.8
  - 7z Statistical discrepancy: 2M vs Sum of COFOG Divisions: 0.0 0.0 0.0 0.0 0.0 0.0 0.0
  - Note: Due to rounding components may not sum to totals.

### Data sources, TSA advantages, and consolidation challenges
- Current data-source limitations
  - GFS compilation relied on summary reports that lack sufficient disaggregation and counterpart information; compilation was resource intensive and required considerable manual intervention because most reports included only Armenian descriptions without budget or GFS codes.
  - Summary reports constrained transaction classification and consolidation; many items were matched to single GFS categories based on broad assumptions despite more detailed underlying data existing.
  - Expenditure aggregation weaknesses for budgetary central government (examples of shares of total expenditure):
    - Acquisition of services and products: 9.5% of total expenditure — no counterparty information.
    - Subsidies and grants: 16.1% of total expenditure — limited counterparty information.
    - Pensions: 18.8% of total expenditure — single line does not identify separate pension payments.
    - Other Expenses: 14.8% of total expenditure — single residual item requiring disaggregation.
    - Sum across “not elsewhere classified” categories in COFOG breakdown: 6.2% of total expenditure — “nec” usage particularly high for social protection.
  - Recommendation: avoid aggregating military spending into single “other expenses” line in GFS; record in relevant GFSM 2014 categories even if budget presentations aggregate or suppress details.
- Advantages of using detailed TSA data
  - TSA database contains budget codes and GFSM 2001 classifiers and holds disaggregated data necessary for accurate classification and consolidation.
  - Benefits of using detailed TSA data:
    - Increase accuracy of detailed GFS revenue and expenditure categories.
    - Reduce use of residual “other” categories.
    - Allow more detailed and accurate consolidation of general government transactions.
    - Reduce complexity and risk of manual errors; increase automation of GFS compilation.
    - Provide additional data required by Armstat for national accounts.
  - Practical notes:
    - Treasury official indicated no anticipated obstacles to MoF GFS compilers accessing detailed TSA data; Head of the Treasury confirmed willingness to work with MoF to establish GFS data requirements and update Ministerial Order (no. 5) if necessary.
    - Armstat NA compilers could possibly access TSA data but would require a separate request process.
    - TSA contains GFSM 2001 codes rather than GFSM 2014 codes; mission: this is not an obstacle because GFSM 2001 and GFSM 2014 are based on same basic framework and differences can be addressed in compilation.
  - Time series recommendation:
    - TSA database contains budgetary data back to 2006.
    - When transitioning to TSA-based compilation, implement new processes not only for the latest year but for at least the previous five years to facilitate consistent GFS time series.
- Consolidation challenges
  - Current consolidation limited due to lack of detailed data; reconciling grant expense and revenue for consolidation is particularly difficult.
  - Finalized PSIT will introduce new consolidation challenges by identifying state-owned enterprises and foundations currently not in GFS; implementing changes requires detailed data for transactions and stock consolidation.
  - Mission provided training on consolidation theory and a short guide tailored to Armenian context.

### Institutional arrangements, cooperation, and CCAMTAC workplan guidance
- Intra-agency (MoF)
  - GFS compilation responsibilities passed from PDMD to FSRD; PDMD and FSRD to cooperate on 2020 transmission.
  - Need to enhance cooperation within MoF, notably Treasury data exchange with GFS compilers.
- Inter-agency (MoF, Armstat, CBA)
  - Recommendation: formalize cooperation via MoU among MoF, Armstat, and CBA covering data exchange, sectorization, and methodological issues.
  - Interim: establish data exchange channel and include Armstat staff informally in MoF sectorization discussions.
  - Data sharing: Armstat holds useful data but currently considered “confidential”; Armstat should explore anonymization or removal of sensitive fields to enable sharing.
  - Recommended creation of a cross-institutional technical working group to resolve data-sharing and methodology issues.
- Consistency across macroeconomic statistics — published discrepancy for 2018 (all figures in billion AMD)
  - Revenue: GFS 1,384.5 ; NA 1,646.6 ; Difference -262.1
  - of which: Taxes: GFS 1,284.4 ; NA 1,372.7 ; Difference -88.3
  - of which: Non-taxes: GFS 100.1 ; NA 273.9 ; Difference -173.8
  - Expense: GFS 1,331.4 ; NA 1,369.4 ; Difference -38.0
  - of which: Compensation of employees: GFS 175.1 ; NA 468.7 ; Difference -293.6
  - of which: Subsidies: GFS 142.6 ; NA 5.4 ; Difference 137.2
  - of which: Grants: GFS 72.5 ; NA 57.5 ; Difference 15.0
  - of which: Others: GFS 941.2 ; NA 837.8 ; Difference 103.4
  - Transactions in nonfinancial assets: GFS 149.3 ; NA 237.6 ; Difference -88.3
  - Surplus (+) / Deficit (-): GFS -96.2 ; NA +39.6 ; Difference -135.8
  - Mission advice: MoF and Armstat should collaborate to understand reasons for differences (likely different data sources) and implement a program to bring NA and GFS into alignment.
- CCAMTAC workshop and country work plan (WP)
  - Opening regional GFS/PSDS workshop: September 13–17, 2021 (virtual).
  - Objective: identify TA needs and establish country WP to improve compilation and dissemination of fiscal data.
  - WP areas: (i) Coverage (Units, Stocks, Flows); (ii) Frequency and Timeliness; (iii) Quality (internal and intersectoral consistency; classification; metadata; revisions).
  - Requirement: Armenia and CCAMTAC members should establish medium-term WPs and transmit them to the Resident Advisor before the end of 2021.
  - Follow-up: update draft WP considering mission outcomes and pandemic/virtual work constraints and transmit updated WP to CCAMTAC highlighting high priority issues.

### Capacity building, staffing, and operational recommendations
- Training provided on GFS framework, revenue and expense classifications, and international dissemination practices.
  - Emphasis: GFSM 2014 does not include residual categories; classify all revenue and expense items appropriately.
  - Emphasis: distinctions between grants, subsidies, other transfers; between taxes and non-taxes; integrated nature of GFS framework and built-in consistency checks.
- Staffing
  - Current GFS unit staffing: three persons (each with other responsibilities), considered insufficient to advance the medium-term work plan.
  - Recommendation: ensure adequate staff capacity to deliver on GFS work plan targets.
- Immediate GFS coding and data-quality priorities
  - Ensure GFS coding corrections from December 2019 TA mission have been incorporated.
  - Ensure data supplied by ministries and other units are recorded consistently with GFS principles.
  - Minimize or stop use of residual “other” categories.

*IMF TA mission report: Summary of Mission Outcomes and Priority Recommendations (Republic of Armenia, September 27–October 8, 2021). Source: 1armea2022001.*

### 1. List of Priority Recommendations ________________________________________________________________ 7

### 1armea2022001 - 1. List of Priority Recommendations

### Mission overview and objectives
- Mission dates: September 27–October 8, 2021.
- Mission team: Ms. Ivana Jablonská and Mr. David Bailey.
- Requesting authority: Ministry of Finance (MoF).
- Supporting department: IMF Middle East and Central Asia Department (MCD).
- Main objectives:
  - Assist authorities to finalize a comprehensive sectorized list of all public sector units (Public Sector Institutional Table, PSIT).
  - Compile annual general government Government Finance Statistics (GFS) data for 2020.
  - Provide practical and tailored training to improve capacity to compile and disseminate GFS.

### Training and information sessions provided
- Training topics:
  - Sectorization rules and practical implementation for selected Armenian units.
  - Revenue and expenditure classifications as defined in the Government Finance Statistics Manual 2014 (GFSM 2014), with emphasis on items of special interest to Armenian authorities.
  - Consolidation, including drafting a short set of guidelines for Armenian GFS compilers.
- Information session topics:
  - Overview of uses and benefits of the GFS framework.
  - International GFS and Public Sector Debt Statistics (PSDS) data reporting.
  - Consistency of macroeconomic statistics and cooperation among compilers.
  - Relationship between International Public Sector Accounting Standards (IPSAS) and GFS.
- Materials distributed in English and Armenian.

### Key institutional observations and recommendations (summary)
- Cross-institutional cooperation:
  - Improving cooperation between MoF, Armstat (Statistical Committee of the Republic of Armenia), and the Central Bank of Armenia (CBA) is important to reduce discrepancies between statistical outputs and improve overall quality.
  - The mission highlighted discrepancies between national accounts (NA) and GFS publications and stressed the importance of using the finalized PSIT across all macroeconomic statistics.
- Data sources and compilation processes:
  - Current GFS compilation data sources lack sufficient detail and disaggregation to produce high-quality GFS or to automate compilation.
  - Treasury Single Account (TSA) database contains budget codes and GFSM 2001 classifiers and holds disaggregated data necessary for accurate classification and consolidation, but these codes are not currently utilized in GFS compilation.
  - Mission strongly encourages MoF to secure access to detailed TSA data for GFS compilers.
- Staffing:
  - GFS responsibilities now reside with the MoF’s Financial Statistics and Risks Department (FSRD).
  - Current GFS unit staffing: three persons (each with other responsibilities), considered insufficient to advance the medium-term work plan.
- PSIT:
  - Authorities have made progress developing a comprehensive PSIT; mission assisted with sectorization of foundations and some public financial corporations.
  - Importance of finalizing, publishing, and regularly updating the PSIT (annual or biennial) with transparent documentation explaining rationale for sector classification decisions.

### Priority recommendations (Table 1)
- December 2021
  - Finalize and publish the Public Sector Institutional Tables (PSIT), in cooperation with Armstat and the CBA.
  - Responsible Institution: MoF
- March 2022
  - Strengthen and formalize the cooperation between statistical compilation institutions.
  - Responsible Institutions: MoF, Armstat, CBA
- June 2022
  - Secure access to detailed data for budgetary government held in the Treasury Single Account (TSA) and establish processes to use the data in GFS compilation.
  - Responsible Institution: MoF

### Two-year priority focus
- The mission provided detailed recommendations spanning a two-year period; the three priority recommendations above carry particular weight for improving GFS quality and completeness.

---

### Detailed technical recommendations (selected items from Table 2)
- October 2021
  - Compile and disseminate GFS for 2020, through the IMF’s annual GFS database, using the current data reports and general government delineation.
  - Responsible Institution: MoF
  - Update and transmit to the IMF the climate change questionnaire with 2020 data on government policy indicators.
  - Responsible Institution: MoF
- December 2021
  - Finalize the PSIT and share a final version with Armstat, CBA and the IMF, seeking to make the PSIT publicly available by (or as soon as possible after) the target deadline.
  - Responsible Institution: MoF
  - Define and formalize the data requirements of the GFS compilation departments within the MoF for access to in-year and historic data in the TSA; data should be sufficiently detailed for GFS compilation, including consolidation, and should include the GFSM 2001 and budget codes held within the TSA.
  - Responsible Institution: MoF
  - Develop a well-structured and realistic work plan for the extension and improvement of GFS and PSDS, building on the 2020 MoF Action Plan and discussions with the mission; the work plan is to be shared with CCAMTAC.
  - Responsible Institution: MoF
- March 2022
  - Ensure adequate staff capacity to deliver effectively on the agreed activities and targets in the GFS work plan.
  - Responsible Institution: MoF
  - Establish a technical working group to discuss sector classification and GFS/statistical methodology issues; group to meet regularly and be composed of technical staff from MoF, Armstat, and CBA.
  - Responsible Institutions: MoF, Armstat, CBA
  - Put in place Memoranda of Understanding (MoU) between MoF, Armstat, and CBA to ensure relevant data can be freely shared for statistical compilation and sector classification.
  - Responsible Institutions: MoF, Armstat, CBA
  - Establish clear and transparent processes and documentation to allow the PSIT to be updated and maintained on a regular annual or biennial schedule.
  - Responsible Institution: MoF
- June 2022
  - Develop and test new GFS compilation systems/processes for budgetary government using detailed TSA data.
  - Responsible Institution: MoF
- September 2022
  - Compile and disseminate GFS for 2021 (and data for at least the previous 5 years) through the IMF’s annual GFS database using: (i) detailed TSA data for budgetary government; (ii) existing data sources for extrabudgetary government; and (iii) additional data for general government units currently missing but identified through the PSIT.
  - Responsible Institution: MoF
- October 2022
  - Investigate differences between GFS and national accounts data and implement a program to bring the two into alignment where appropriate.
  - Responsible Institutions: Armstat, MoF
- September 2023
  - Establish efficient data collection arrangements covering all general government units; frequency (monthly, quarterly or annual) to depend on materiality of units and associated fiscal risks.
  - Responsible Institutions: MoF, Armstat, CBA
- Continuous (regular)
  - Regularly review and update the PSIT in cooperation with Armstat and CBA.
  - Responsible Institution: MoF

---

### Sector classification findings and PSIT summary
- Latest draft PSIT size: 3,456 institutional units.
- The mission reviewed the draft PSIT and applied sector classification principles; improved data led to some corrections to previous preliminary classifications, notably for Joint Stock Companies (JSCs) and State Non-Commercial Organizations (SNCOs) using the “market test”.
- PSIT coverage note: Budgetary central and local government units were currently missing from the PSIT; authorities plan to add central government units that constitute budgetary central government and regional (Marzes) and local community government units that constitute budgetary local government.

- Table 3. Summary of Sector Classifications in Latest PSIT (as presented)
  - Joint Stock Companies (JSCs): Government Units 151; Public Corporations 79; Not yet classified 0; Total 230
  - State Non-Commercial Organizations (SNCOs): Government Units 1,829; Public Corporations 12; Not yet classified 0; Total 1,841
  - Local Non-Commercial Organizations (LNCOs): Government Units 1,180; Public Corporations 0; Not yet classified 0; Total 1,180
    - Note: Although the State Registry lists 1,440 LNCOs, to-date only 1,182 have been confirmed.
  - Public Financial Corporations: Government Units 1; Public Corporations 21; Not yet classified 0; Total 22
  - Public Foundations: Government Units 39; Public Corporations 17; Not yet classified 70; Total 126
  - Public Entities in process of liquidation: Government Units 14; Public Corporations 0; Not yet classified 43; Total 57
  - Total: Government Units 3,214; Public Corporations 129; Not yet classified 113; Total 3,456
  - Note: Nine privatized public entities were identified by the MoF and have been excluded from this list.

### Public foundations (classification issues and guidance)
- Public foundations definition: Non-commercial organizations established by government to pursue social, charitable, cultural, educational, scientific, health, or environmental aims.
- PSIT status: 70 public foundations remained unclassified at time of review.
- Mission actions:
  - Reviewed 70 unclassified public foundations and established preliminary classifications for 41; 29 required further examination.
- Mission recommendation:
  - Default classification for public foundations should be as extrabudgetary government units given their non-commercial nature.
  - However, apply the default only when lack of necessary information prevents sector classification on a case-by-case basis.
  - Suggested sourcing information via internet searches for charters, annual reports, and/or accounts; if unsuccessful, MoF compilers should contact relevant ministry or local community for information.
- Data-sharing note:
  - Armstat holds data on public foundations established with educational/academic aims; cross-checking with Armstat is useful but was complicated by severe limitations on data-sharing between Armstat and MoF.
- Liquidation:
  - PSIT includes units that have been liquidated or are in process of liquidation; mission recommended that units in the process of liquidation remain included in the PSIT under the appropriate sector classification until fully liquidated, with additional notes to inform users of liquidation status.

### Public financial organizations (Table 4 summary)
- Extrabudgetary Central Government Units:
  - Deposit Guarantee Fund of Armenia
  - Pension Guarantee Management Fund
- Public Financial Corporations:
  - Central Bank of Armenia
  - Export Insurance Agency of Armenia CJSC
  - Development and Investments Corporation of Armenia CJSC
  - Panarmenian Fund
  - Armenian Card CJSC
  - National Mortgage Company CJSC
  - Homes for Youth CJSC
  - Small and Medium Business Credit Support CJSC
  - Vehicle Single Window CJSC
  - Stak Processing CJSC
  - Stak Money Transfer CJSC
  - Hayincassatsia CJSC
  - Financial System Mediator
- Notes:
  - The Panarmenian Fund was thought not to be an institutional unit in the previous TA mission but new information from the CBA suggests it is an institutional unit.
  - Stak Money Transfer CJSC and Stak Processing CJSC merged in January 2021.
  - Hayincassatsia began a process of liquidation in 2020.

---

*IMF TA mission report: Summary of Mission Outcomes and Priority Recommendations (Republic of Armenia, September 27–October 8, 2021).*

### 18. With the assistance of the statistical department of the CBA the mission reviewed

### 1armea2022001 - 18. With the assistance of the statistical department of the CBA the mission reviewed

### Classification of public financial institutions
- The latest PSIT includes 22 financial organizations, but duplication and some non-financial units were identified.
- Table 4 (in source) lists the financial organizations classified.
- ACRA Credit Reporting JSC and Armenian Motorinsurers’ Bureau may be public financial corporations, but the mission could not establish whether they met the criteria to be considered public sector controlled.
- The German-Armenian Fund appears not to meet the criteria for a separate institutional unit.

### Health units (JSCs): sector classification and regional heterogeneity
- The mission observed considerable heterogeneity in sector classification of health units constituted as JSCs and recommended consultation with the Ministry of Health to check plausibility, particularly the distinction between local and central government classifications.
- Table 5. Sector Classification of Health Bodies (JSCs) by Region — Number of units by sector classification (Public Corporation / Central Government / Local Government / Total)
  - Ministry of Health: 3 / 13 / 0 / 16
  - Aragatsotn province: 2 / 2 / 0 / 4
  - Ararat province: 3 / 4 / 0 / 7
  - Armavir province: 5 / 1 / 0 / 6
  - Gegharkunik province: 7 / 1 / 0 / 8
  - Kotayk province: 3 / 5 / 0 / 8
  - Lori province: 12 / 2 / 0 / 14
  - Shirak province: 9 / 11 / 0 / 20
  - Syunik province: 2 / 5 / 0 / 7
  - Tavush province: 1 / 0 / 3 / 4
  - Vayots Dzor province: 2 / 1 / 0 / 3
  - Yerevan municipality: 0 / 0 / 32 / 32
  - Total: 49 / 45 / 35 / 129

### PSIT presentation, documentation, and inter-agency collaboration
- The public sector composition changes frequently (dissolutions, new units, mergers, restructures); the PSIT must transparently reflect these changes.
- The mission reminded the MoF of a PSIT template suggested in January-February 2021 that records sector classification at a point in time and captures changes over a period (template reproduced in Appendix I of source) and recommended MoF adopt a similar template for sharing and publishing the PSIT.
- Recommendations:
  - Maintain transparent electronic documentation explaining the rationale for each sector classification decision, to facilitate future reference and amendments.
  - Consider including within published PSIT a column with a short explanation of the rationale for each sector classification (in addition to detailed internal documentation).
  - MoF should work more closely with Armstat and the CBA when finalizing and updating the PSIT to leverage data held by these agencies and to ensure consistency across macroeconomic statistics (e.g., GDP, external current balance, government net lending/net borrowing).
- Unique identifiers:
  - Use of unique tax and entity identifiers within the PSIT was welcomed, but inconsistencies in identifier format were noted (separators “.”, “,”, or removed; some identifiers included leading blank spaces).
  - All identifiers must be presented consistently and in the same format as used in other government datasets; remove blank spaces preceding identifiers.

### GFS coordination, provisional GFS for 2020, and handover of responsibilities
- The Financial Statistics and Risks Department (FSRD) at the MoF has taken over responsibility for GFS coordination and compilation.
- As part of the transfer, the Public Debt Management Department (PDMD) will assist compiling GFS for 2020; PDMD compiled balance sheet data for budgetary general government for 2020 and will work with FSRD to integrate stocks with transactional data for 2020.
- Final GFS for 2020 were expected to be transmitted to the IMF’s Statistics Department before the end of October 2021.
- The mission assisted authorities to compile provisional GFS for 2020 using available summary data reports; compiled GFS were transactional cash data for expense and revenue, and transactions in nonfinancial assets, financial assets, and liabilities, with expenditure broken down by economic and functional categories (COFOG). Provisional tables reproduced in Appendices II and III (source).
- Provisional GFS for 2020 covered budgetary central government, budgetary local government, and SNCOs.
- Compilation used ten summary data reports; the process was resource intensive and required considerable manual intervention because most reports included only Armenian descriptions without any budget or GFS codes.
- Internal consistency:
  - The compiled GFS for 2020 showed good consistency across sectors and between ‘above-the-line’ and ‘below-the-line’ transactions.
  - Example: total functional expenditure exactly matched expenditure by economic transactions.
  - Total statistical discrepancy (between ‘above-the-line’ and ‘below-the-line’ transactions) was limited to 1.3 percent of total expenditure.
- Definition note:
  - Above-the-line transactions refer to revenue, expense, and transactions in nonfinancial assets; below-the-line transactions are the transactions in financial assets and liabilities (‘financing’).

### Challenges from reliance on summary data sources
- Summary reports limit accuracy of transaction classification and consolidation.
  - Insufficient disaggregation hindered matching items to specific GFS categories; many items were matched to single GFS categories based on broad assumptions despite existence of more detailed underlying data.
  - Limited information on transaction counterparts in summary reports constrained consolidation between government units; different government counterparts are sometimes conflated (example: “current grants to SNCOs and LNCOs”).
- Expenditure aggregation weaknesses for budgetary central government (examples from Table 6):
  - Acquisition of services and products: 9.5% of total expenditure — no counterparty information; lack of detail prevents quality assurance that transactions are payments for services rendered.
  - Subsidies and grants: 16.1% of total expenditure — limited counterparty information required for consolidation; lack of detail prevents quality assurance that transfers meet GFS definitions of subsidies and grants.
  - Pensions: 18.8% of total expenditure — single line does not identify separate pension payments; cash transfers from Armenian residents to private pension funds (which flow through the TSA) are not identifiable.
  - Other Expenses: 14.8% of total expenditure — single residual item likely covers many different types of expense and requires disaggregation to appropriate GFS categories.
  - Sum across “not elsewhere classified” categories in COFOG breakdown: 6.2% of total expenditure — usage of “not elsewhere classified (nec)” line items should be limited; “nec” expenditure is particularly high for social protection expenditure.
- The mission noted some “other expenses” related to Ministry of Defense spending; recommended recording military spending in relevant economic transaction categories in GFS rather than aggregating into a single “other expenses” line to preserve macro-fiscal confidentiality while improving classification accuracy. If sensitivities are about budget presentations, authorities could suppress or aggregate detailed line items in disseminated budget presentations while recording correct GFSM 2014 categories in GFS.

### Capacity building and training
- The mission provided bespoke training on the GFS framework, revenue and expense classifications, and international data dissemination practices, emphasizing:
  - GFSM 2014 does not include residual categories; classify all revenue and expense items appropriately.
  - Distinctions between grants, subsidies, and other transfers, and between taxes and non-taxes.
  - The integrated nature of the GFS framework and built-in consistency/quality checks used in IMF annual GFS reporting templates.

### Advantages of using detailed Treasury Single Account (TSA) data
- The mission strongly urged MoF compilers to use detailed TSA data (which includes both budget codes and GFSM 2001 codes) directly for GFS compilation because this should:
  - Increase the accuracy of detailed GFS revenue and expenditure categories.
  - Reduce the use of residual “other” categories.
  - Provide information to allow more detailed and accurate consolidation of general government transactions.
  - Reduce complexity and risk of manual errors in current compilation processes.
  - Increase automation of GFS compilation.
  - Provide additional data required by Armstat when compiling general government statistics for national accounts.
- A Treasury official indicated no anticipated obstacles to MoF GFS compilers accessing detailed TSA data; the Head of the Treasury confirmed willingness to work with MoF to establish GFS data requirements for TSA data and update Ministerial Order (no. 5) if necessary to provide required access.
- Armstat NA compilers could possibly access TSA data but would require a separate request process.
- GFSM version compatibility:
  - The TSA contains GFSM 2001 codes rather than GFSM 2014 codes; this is not considered an obstacle because GFSM 2001 and GFSM 2014 are based on the same basic compilation framework and many GFSM 2014 changes are elaborations rather than structural changes.
  - Differences between GFSM 2001 and GFSM 2014 can be addressed within GFS compilation processes.
- Immediate priorities recommended:
  - Ensure GFS coding corrections identified in a previous TA mission (December 2019) have been incorporated.
  - Ensure data supplied by ministries and other government units are recorded consistently with GFS principles.
  - Minimize or stop use of residual “other” categories.

### Time series consistency and revisions
- The TSA database contains budgetary data back to 2006.
- Recommendation: when transitioning GFS compilation processes to use detailed TSA data, implement the new processes not only for the latest year but also for at least the previous five years to facilitate consistent GFS time series.
- The authorities acknowledged GFS in the IMF annual GFS database was not fully consistent over the time series due to methodological improvements implemented for 2019 data.
- The authorities indicated revision of historical GFS data (pre-2019) would be deferred until late 2021 or early 2022 due to the handover of GFS compilation responsibilities.
- The mission suggested priority after disseminating 2020 data should be to advance use of detailed budgetary data in GFS compilation and that historical data might be revised concurrently when implementing improvements using detailed TSA data.

### Consolidation
- Current consolidation practices are limited due to lack of detailed data; reconciling grant expense and revenue data for consolidation within general government is particularly difficult.
- Sometimes consolidation must use counterpart aggregated data for communities or extrabudgetary units rather than state budget data, reducing reliability.
- The finalized PSIT will introduce new consolidation challenges by identifying state-owned enterprises and foundations currently not included in GFS compilation, and by indicating some SNCOs currently included within GFS will need exclusion; implementing these changes will require detailed data to consolidate transactions and stock positions appropriately.
- The mission provided detailed training on consolidation theory and practice, including pragmatic “rules of thumb” and a short guide tailored to the Armenian context for GFS compilers.

*Source: 1armea2022001 — mission report excerpt*

### 40. The GFS/PSDS capacity development support to be provided to Armenia by

### 40. The GFS/PSDS capacity development support to be provided to Armenia by CCAMTAC

### Capacity development events and objectives
- The opening regional GFS/PSDS workshop organized by CCAMTAC took place virtually on September 13–17, 2021.
- Main objective of the workshop:
  - Identify each country’s TA needs and establish country work plan (WP) to improve the compilation and dissemination of its fiscal data.
- Workshop activities:
  - Provided theoretical background on key principles and concepts of the compilation of GFS and PSDS.
  - Enabled countries to exchange practices in the compilation of these statistics.
  - The Armenian authorities delivered a well-prepared presentation on the current status of GFS compilation.

### Country work plan (WP) guidance and timeline
- The mission bridged the Armenian GFS action plan (published as a Ministerial Decree in September 2020) into a CCAMTAC country WP template and advised the authorities on how to complete it.
- WP template requests setting up objectives in the following areas:
  - (i) Coverage (Units, Stocks, Flows);
  - (ii) Frequency and Timeliness (frequency and timeliness of transmission of annual and high frequency data);
  - (iii) Quality (internal and intersectoral consistency; classification of specific operations; availability of metadata; and data revisions).
- Requirement and timeline:
  - Armenia and other CCAMTAC member countries should establish their GFS/PSDS medium term WPs and transmit them to the Resident Advisor before the end of 2021.
- Follow-up actions by authorities:
  - Update the draft work plan as appropriate, taking into account the current situation and compilation practices as well as the outcome of this mission.
  - Ensure objectives in the WP are realistic given the current pandemic situation and virtual way of work.
  - Transmit the updated WP to CCAMTAC and highlight high priority issues for future missions.

### Institutional arrangements — findings and recommendations
- Overarching view:
  - Improving intra- and inter-institutional cooperation will improve the quality and consistency of all domains of macroeconomic statistics.
  - The mission delivered an information session on the consistency of macroeconomic statistics and the need for close cooperation among their compilers.
  - Presence of staff from CBA and Armstat during the sessions was appreciated and evidenced interest in improving and aligning statistics.

- Intra-agency cooperation (Ministry of Finance)
  - GFS compilation responsibilities have been passed recently from the PDMD to the FSRD in the MoF.
  - The handover from PDMD of theoretical knowledge and experience in compilation of GFS had been ensured.
  - Staff of the two departments will cooperate in the preparation of the next transmission of the annual GFS questionnaire for 2020.
  - Cooperation among various departments of the MoF needs to be enhanced, notably with respect to data exchange between the Treasury and those involved in GFS compilation.
  - Several MoF staff had been trained in GFS at various IMF trainings and there is good general understanding of basic GFS principles and the GFS framework within various MoF departments.

- Inter-agency cooperation (MoF, Armstat, CBA)
  - Mission recommendation: formalize cooperation between MoF, Armstat and CBA, ideally by signing a Memorandum of Understanding (MoU) by all three institutions.
  - Current situation noted by mission:
    - Cooperation between MoF on one side and Armstat and CBA on the other side is not formalized.
    - A MoU seems to exist between Armstat and CBA but not with the MoF.
  - Proposed MoU coverage:
    - (i) Exchange of relevant data;
    - (ii) Sectorization of entities;
    - (iii) Methodological issues.
  - Recommended institutional mechanism:
    - Creation of a cross-institutional technical working group to resolve issues relating to data sources/sharing and statistical methodology.
  - Interim steps prior to MoU:
    - MoF should establish a channel to exchange data with Armstat even before signing an MoU.
    - Suggested Armstat staff participate in MoF discussions on sectorization of units on an informal basis.
  - Data sharing specifics:
    - Treasury official confirmed Armstat would in principle be able to access detailed TSA data to help compile NA.
    - Armstat holds data which can inform and support MoF work in compiling and maintaining the PSIT, but currently these data are considered “confidential” and are not shared.
    - Armstat should explore ways to share data with MoF, perhaps by removing or anonymizing any fields considered confidential or sensitive.

### Consistency across macroeconomic statistics — discrepancies and action
- Key finding:
  - Published NA data for the general government sector is materially different from published GFS data for the Consolidated Budget for 2018.
- Comparison between publications (National Accounts of Armenia 2019 published 20 November 2020 vs Finance Statistics of Armenia 2019 published 30 October 2020):
  - Table 7. Comparison of Published GFS and NA Data for 2018 (all figures in billion AMD)
    - Revenue: GFS 1,384.5 ; NA 1,646.6 ; Difference -262.1
    - of which: Taxes: GFS 1,284.4 ; NA 1,372.7 ; Difference -88.3
    - of which: Non-taxes: GFS 100.1 ; NA 273.9 ; Difference -173.8
    - Expense: GFS 1,331.4 ; NA 1,369.4 ; Difference -38.0
    - of which: Compensation of employees: GFS 175.1 ; NA 468.7 ; Difference -293.6
    - of which: Subsidies: GFS 142.6 ; NA 5.4 ; Difference 137.2
    - of which: Grants: GFS 72.5 ; NA 57.5 ; Difference 15.0
    - of which: Others: GFS 941.2 ; NA 837.8 ; Difference 103.4
    - Transactions in nonfinancial assets: GFS 149.3 ; NA 237.6 ; Difference -88.3
    - Surplus (+) / Deficit (-): GFS -96.2 ; NA +39.6 ; Difference -135.8
- Mission advice:
  - MoF and Armstat statistical compilers should work together to understand reasons for differences and implement a program of work to bring NA and GFS publications into alignment.
  - Note: This inconsistency between NA and GFS publications was first highlighted in a previous TA report (December 2019) and has not been resolved.
  - Armstat and MoF officials examined possible reasons; the most likely reason emerging was the use of different data sources for the two publications.

### Officials met during the mission
- Officials from the Ministry of Finance and Armstat included (department/role as listed):
  - Mr. Loris Muradyan — Financial Statistics and Risks Department
  - Ms. Arusyak Gevorgyan — Financial Statistics and Risks Department
  - Mr. Poghos Baloyan — Financial Statistics and Risks Department
  - Mr. Artur Hambardzumyan — Public Debt Management Department
  - Ms. Ruzanna Gabrielyan — Budget Process Organization Department
  - Ms. Gayane Zargaryan — Budget Execution Reporting Department
  - Ms. Emma Ghaytanjyan — Budget Execution Reporting Department
  - Mr. Zhirayr Titizyan — Treasury Operations Department
  - Mr. Raffi Aleksanyan — Accountancy, Methodology & Reporting Monitoring Department
  - Ms. Sveta Harosyan — Budget Process Organization Department
  - Ms. Narine Tolmajyan — Accountancy, Methodology & Reporting Monitoring Department
  - Ms. Lilit Sargsyan — Budget Process Organization Department
  - Ms. Haykush Titizyan — Finance Statistics Division
  - Ms. Lusya Khachatryan — Macroeconomic Indicators and National Accounts Division
  - Mr. Arsen Ohanjanov — Finance Statistics Division
  - Ms. Astghik Barutchyan — Finance Statistics Division
  - Ms. Nadejda Astvatsaturova — Macroeconomic indicators and National accounts division
  - Ms. Arus Tonapetyan — Macroeconomic indicators and National accounts division
  - Mr. Gagik Aghajanyan — Statistics Department
  - Mr. Tigran Baghdasaryan — Statistics Department
  - Ms. Arpine Petrosyan — Statistics Department
  - Ms. Peprone Margaryants — Statistics Department
  - Ms. Shake Titanyan — Statistics Department

### Appendix highlights: PSIT template and provisional GFS for 2020
- PSIT compilation guidance:
  - Proposed PSIT update frequency: compiled and updated annually (although a biennial update process might alternatively be considered).
  - Presentational format consists of two elements:
    - I. List of all Public Sector Units as of a Point in Time (e.g., 31st December)
    - II. List of all Changes in Classification of Public Sector Units Between Updates (e.g., 1st January to 31st December)
  - Reasons for changes in sector classification:
    - (i) formation of new units;
    - (ii) dissolution of existing units;
    - (iii) change in sector classification due to new information or “resectorization”.
  - Template fields shown (examples): Tax Payer Identifier; State Registry Number; Legal Entity Code; Legal Form; Basis of sectorization/resectorization; Sector/Subsector; Armenian name; English name; New unit (in year); Dissolved unit (in year); Effective date from which sectorization applies; Date of dissolution from which sectorization ends; Effective date of new sectorization; Previous Sector/Subsector; Additional notes.

- Appendix II. Provisional GFS for 2020 – Statement of Operations (in billion AMD)
  - Transactions affecting net worth:
    - 1 Revenue: 1,535.9 191.2 -179.2 1,547.9 156.1 -83.0 1,621.0
    - 11 Taxes: 1,360.4 0.0 -9.1 1,351.4 30.8 -1.4 1,380.8
    - 12 Social contributions: 0.0 0.0 0.0 0.0 0.0 0.0 0.0
    - 13 Grants: 53.2 155.3 -153.2 55.3 81.6 -81.6 55.3
    - 14 Other revenue: 122.2 35.9 -16.9 141.2 43.8 0.0 185.0
    - 2 Expense: 1,643.7 178.8 -179.2 1,643.3 121.3 -83.0 1,681.6
    - 21 Compensation of employees: 176.1 139.5 0.0 315.6 27.6 0.0 343.2
    - 22 Use of goods and services: 179.2 26.9 -16.2 189.9 19.4 0.0 209.3
    - 24 Interest: 164.8 0.0 0.0 164.8 0.1 0.0 164.9
    - 25 Subsidies: 119.1 0.0 0.0 119.1 0.4 0.0 119.4
    - 26 Grants: 186.9 0.0 -153.2 33.6 64.4 -81.6 16.4
    - 27 Social benefits: 534.3 1.4 0.0 535.8 2.3 0.0 538.1
    - 28 Other expense: 283.4 11.0 -9.8 284.6 7.1 -1.4 290.3
    - 31 Gross investment in nonfinancial assets: 226.2 0.0 0.0 226.2 17.1 0.0 243.3
    - 311 Fixed assets: 226.2 0.0 0.0 226.2 36.3 0.0 262.5
    - 314 Nonproduced assets: 0.0 0.0 0.0 0.0 -19.2 0.0 -19.2
    - 2M Expenditure (2+31): 1,869.9 178.8 -179.2 1,869.5 138.4 -83.0 1,924.9
    - NLB Net lending (+) / Net borrowing (-) (1-2M): -334.0 12.4 0.0 -321,6 17.8 0.0 -303.8
    - 32 Net acquisition of financial assets: 19.7 12.4 0.0 32.1 17.8 0.0 49.9
    - 33 Net incurrence of liabilities: 353.7 0.0 0.0 353.7 0.0 0.0 353.7
    - NLBz Overall statistical discrepancy: NLB vs Financing (32-33-NLB): 0.0 0.0 0.0 0.0 0.0 0.0 0.0
  - Note: Due to rounding components may not sum to totals.

- Appendix III. Provisional GFS for 2020 – Expenditure by Functional Categories (COFOG) (in billion AMD)
  - 7 EXPENDITURE [=2M]: 1,869.9 178.8 -179.2 1,869.5 138.4 -83.0 1,924.9
  - 701 General public services: 344.3 11.8 -11.0 345.2 36.1 -79.2 302.0
  - 702 Defense: 387.8 0.3 -0.3 387.8 0.1 0.0 387.9
  - 703 Public order and safety: 151.4 0.7 -0.7 151.5 0.0 0.0 151.5
  - 704 Economic affairs: 125.6 15.8 -8.9 132.5 10.8 0.0 143.3
  - 705 Environmental protection: 4.4 3.4 -3.2 4.7 16.5 0.0 21.2
  - 706 Housing and community amenities: 8.9 0.0 0.0 8.9 13.5 0.0 22.4
  - 707 Health: 148.2 10.2 -11.6 146.8 0.4 0.0 147.2
  - 708 Recreation, culture, and religion: 33.6 19.6 -26.0 27.3 9.0 0.0 36.3
  - 709 Education: 143.8 111.6 -112.2 143.2 48.9 -3.7 188.4
  - 710 Social protection: 521.8 5.3 -5.4 521.7 3.1 0.0 524.8
  - 7z Statistical discrepancy: 2M vs Sum of COFOG Divisions: 0.0 0.0 0.0 0.0 0.0 0.0 0.0
  - Note: Due to rounding components may not sum to totals.

*Source: Excerpt from 1armea2022001 - 40. The GFS/PSDS capacity development support to be provided to Armenia by (PDF).*

---


_Source: https://www.imf.org/-/media/files/publications/cr/2022/english/1armea2022001.pdf_