## 2.   Loan Liabilities Composition After the Revision

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---

### Summary of mission outcomes and priority recommendations
- ESS technical assistance mission visited Geostat during May 6–10, 2019, following up November 2016, to assess progress and provide recommendations on ESS, financial account components, and reconciliation with NBG datasets.
- Review of other sectors’ loans and reclassification outcomes:
  - 372 loans identified as possibly contracted within a direct investment relationship and subject to detailed scrutiny.
  - Source text reports two related counts after investigation:
    - “157 loans gauged as being from affiliated creditors after chain-of-ownership investigation.” (Summary section)
    - In a reclassification exercise subsection the report states “125 loans were gauged as being from affiliated creditors applying established criteria …” (both figures appear in the source).
  - The exercise resulted in reclassifying about USD$700 million of loan liabilities from other investment to direct investment—debt instruments.
- Coverage and methodological treatment of import/export of cars:
  - Geostat analyzed declared prices for imported, exported, and re-exported cars and agreed a method to fill gaps and address valuation limitations.
  - Pilot adjustment showed import of cars increased by 3.4 percent for one month; reexport increased by 0.7 percent for one month. (Pilot exercise tables give month-specific values; see “Import/export of cars” section.)
- Crypto assets and gambling transactions coverage:
  - Georgia is among four countries leading in mining Bitcoins; mission drafted a list of indicators for collecting data on crypto assets to be tested with targeted companies.
  - Geostat to prepare list of questions for existing surveys to capture value of bets by nonresidents and their winnings; discussions with GGDA and casinos planned.
- Treatment of LLC Marabda-Kartsakhi Railway debt liabilities:
  - Loan liability remains an existing debt of LLC Marabda-Kartsakhi Railway until the joint enterprise is established per loan agreement; contingent until establishment and transfer of obligations.
- Staffing:
  - Staff resources at Geostat for ESS are insufficient; recommendation to consider additional staff (permanent or contractual).
- Priority recommendations (highlights):
  - August 2019: Reclassify loans assessed as between affiliated entities from other investment to direct investment in balance of payments, IIP, external debt statistics, and CDIS. Responsible: Geostat, NBG.
  - December 2019: Introduce changes in IMTS for addressing issues in coverage and valuation of import, export, and re-export of cars. Responsible: Geostat.

### Action plan (priorities, milestones, and target dates)
- High priority (H):
  - Finalize revision of other sectors loan liabilities for identifying affiliation of creditors and debtors. Target: July 2019.
  - Reclassify loans between affiliated entities from other investment to direct investment in balance of payments, IIP, external debt statistics, and CDIS. Target: August 2019.
  - Introduce IMTS changes for coverage and valuation of import, export, and re-export of cars. Target: December 2019.
  - Adjust survey forms to include questions on crypto assets and gambling. Target: September 2019.
  - Launch collection of ESS data based on revised survey forms. Target: October 2019.
  - Increase staff resources allocated to External Trade and Foreign Investments Statistics Department. Target: 2020.
- Medium priority (M):
  - Finalize list of indicators for crypto assets and discuss with companies. Target: July 2019.
  - Finalize list of indicators related to gambling activity with GGDA. Target: September 2019.
  - Monitor crypto assets market for potential new reporters. Target: Ongoing.
  - Start disseminating aggregated direct investment data on assets–liabilities basis. Target: March 2020, together with publication of IIP by the NBG.
  - Adjust revision approach to allow introducing changes to previous years during compilation of quarterly data to assure consistency with balance of payments. Target: Regularly, when needed.
- Outcome targets emphasize:
  - Use of latest manual concepts and definitions.
  - Adequate source data and resources.
  - Improved data dissemination.

### Trade in goods — methodology, adjustments, and results
- CDDB-based trade in goods statistics:
  - Adequate coverage for imports/exports by legal entities; individuals above non-duty import limits; and postage packages.
  - Geostat replaces CDDB data on import/export of gas and electricity with company-provided transporter data.
- NBG adjustments and mirror statistics approach:
  - NBG uses Geostat aggregated trade data and applies additional adjustments based on mirror statistics (UN Comtrade) for major partners, grouping countries into eight groups with average adjusting ratios.
  - Example adjustments to exports of goods (Quarter 4, 2018):
    - Zone 1: Applied Coefficient (%) 1.29 — The Data on Export of Goods Before Adjustment 139.90 After Adjustment 180.47
    - Zone 2: 1.31 — 155.34 → 203.50
    - Zone 3: 1.32 — 122.62 → 161.25
    - Zone 4: 1.33 — 160.47 → 213.43
    - Zone 5: 1.33 — 78.55 → 104.47
    - Zone 6: 1.31 — 147.36 → 193.04
    - Zone 7: 1.25 — 17.71 → 22.14
    - Zone 8: 1.30 — 84.51 → 109.86
    - Non-adjustable export: 1.27 → 1.27
    - Total: 907.73 → 1,189.42
    - Adjustment value: 281.69
    - Average adjustment coefficient: 31.0 %
  - Mission reiterated collaboration with Customs and partner countries where substantial CDDB–Comtrade discrepancies arise.

### Import/export of cars — issues, agreed estimation approach, and pilot results
- Coverage problem:
  - SAMIA grants importers 60+30 days to register imported cars; cars re-exported within that period may be included in export data without inclusion in import data, creating coverage gaps in IMTS.
- Agreed estimation approaches by importer type and car category:
  - Importer: Companies; Car Category: New cars
    - Price Analysis: Export prices are higher than import prices
    - Estimation Approach: If exported car is not included in import, estimate the import price by deducting (i) the estimated profit margin (approximately 15 percent) and (ii) freight and insurance (based on an ad-hock survey of importers).
  - Importer: Companies; Car Category: Used cars
    - Price Analysis: Export prices are lower than import prices
    - Estimation Approach: (i) Consider the export price as import prices; (ii) estimate export prices by adding the profit margin (approximately 10 percent).
  - Importer: Individuals; Car Category: New cars
    - Price Analysis: Export prices are understated mainly for cars with high engine capacity
    - Estimation Approach: Conduct a detailed analysis of data for one month and decide if there is basis for adjusting. If decision is to adjust, estimate adjustment coefficient based on analysis results.
  - Importer: Individuals; Car Category: Used cars
    - Price Analysis: Export prices are lower than import prices
    - Estimation Approach: (i) Consider export prices as import prices; (ii) introduce the estimated values of imported cars in imports for t-2 month; (iii) estimate export prices by adding the profit margin (approximately 10 percent) for all types of cars.
- Pilot exercise results (one-month adjustments):
  - Change of Motor Vehicles (HS 870321-870380): Import in February 2019
    - Import (before change): 648.1 Mill. USD
    - Change: 22.6
    - Change, %: 3.5
    - Import (after change): 670.7
  - Change of Motor Vehicles (HS 870321-870380): Reexport in April 2019
    - Reexport (before change): 307.4 Mill. USD
    - Change: 2.4
    - Change, %: 0.8
    - Reexport (after change): 309.8
- Recommendation: Geostat should coordinate with the NBG to adjust import/re-export of cars in IMTS and balance of payments to assure consistency.

### Improving accuracy of balance of payments and IIP statistics — direct investment and loan reclassification
- Direct investment compilation and reconciliation:
  - Geostat collects, compiles, and disseminates direct investment data via SEEA (quarterly and annual).
  - Geostat verifies and validates data from direct investment reporters; NBG verifies and validates data for non-direct investment reporters.
  - Geostat and NBG reconciled direct investment data disseminated by Geostat with those included in IIP by NBG, eliminating discrepancies between IIP and CDIS data.
  - Alignment enabled by Geostat establishing an integrated direct investment database including flows and positions and accounting for price and exchange rate changes.
  - Geostat has been removing from the database companies that did not submit the survey for two consecutive years and did not fill tax returns; mission advised a more precautionary approach—remove companies only if proof of liquidation exists.
  - In 2018 Geostat started disseminating positions on direct investment in BPM6 basis for balance of payments/IIP consistency and in BPM5 basis for CDIS consistency.
- Loan liabilities reclassification:
  - Targeted 1,073 private sector loans that registered disbursements/repayments during 2016–2018.
  - From the targeted loans, 372 loans were identified as possibly being contracted within the direct investment relationship and were subject to detailed scrutiny.
  - After investigating the chain of ownership, the report contains two differing counts in different sections:
    - One section states “157 loans gauged as being from affiliated creditors after chain-of-ownership investigation.”
    - Another subsection states “125 loans were gauged as being from affiliated creditors applying established criteria such as the maturity of loan, interest rates, or similarity in names of borrower and lender.”
  - Mission assessed applied selection criteria and assisted in deciding on ten uncertain cases.
  - The Geostat–NBG exercise resulted in reclassifying about USD$700 million of loan liabilities from other investment to direct investment—debt instruments.
- Composition indicators presented (end-2018, in percent and million USD):
  - Yearly percentages shown in the source figure: 3.84%, 7.83%, 12.25%, 7.45%, 3.12%, 4.86%, 1.20% (associated with 2010–2016 series as shown in the figure).
  - Loans reclassified to DI: 18%
  - Loans in other investment: 81%
  - Other (to be analyzed): 1%

### Reclassification exercise — recommendations
- Reclassify the loans assessed as being between affiliated entities from other investment to direct investment in balance of payments, IIP, external debt statistics, and CDIS.
- Finalize the revision of other sectors loan liabilities for identifying the affiliation of creditors and debtors.
- Start disseminating the aggregated direct investment data in Geostat publications on assets – liabilities bases, in addition to directional principle.

### Exploring new data sources and methodological issues (crypto assets, intermediaries, gambling)
- Crypto assets
  - Coverage of transactions related to crypto assets in ESS of Georgia has been of concern.
  - Georgia is among the four countries leading in mining Bitcoins; a number of companies in the country are involved in mining crypto assets, including a subsidiary of Bitfury Group.
  - Meeting with Bitfury subsidiary: agreed that a list of indicators for collecting data on crypto assets will be drafted and tested with the Bitfury subsidiary. The draft list of indicators is presented in Appendix II.
  - Appendix II (questionnaire on crypto assets) includes indicators such as:
    - Number of Bitcoins mined during the reported period (Units)
    - Value of Bitcoins mined (at price of the day of the transaction) (Currency)
    - Fees received for validating the transactions (Currency)
    - Number of Bitcoins sold to nonresidents (Units)
    - Of which through the domestic intermediary (e.g., E-Money) (Units)
    - Funds received from parent company other than loans and funds in equity (Currency)
    - Fixed assets (e.g., computers, servers, etc.) (Currency)
    - Intellectual property (Currency)
- Intermediary (e-Money)
  - e-Money maintains e-wallets with full identification and is able to provide data for balance of payments purposes based on residence concept.
  - NBG conducted a survey of e-Money during 2017–2018; mission recommended NBG review the survey questionnaire with e-Money and launch it on a regular basis.
- Gambling
  - Need to improve coverage of transactions related to gambling due to growing nonresidents’ activities.
  - Geostat to prepare list of questions to include in existing surveys to capture value of bets by nonresidents and their winnings; GGDA to support arranging meetings with a few biggest casinos to assess feasibility of reporting such data.

### Treatment of Marabda-Kartsakhi Railway loan liabilities
- Context and contractual provisions:
  - Marabda-Kartsakhi Railway LLC identified as “borrower”; Article 5 of the Intergovernmental Agreement envisages transfer of infrastructure to a joint venture with equal equity participation by Azerbaijan Railways and Georgian Railways after completion.
  - Paragraph 8.2 of the Credit Agreement states that borrower’s obligations, including obligations to repay the loan/loans, shall no longer be in force from the moment an Agreement is signed between the borrower and the joint venture regarding the transfer of the right to use the railway infrastructure and the assignment of all loan obligations with regard to repayment of the funds.
- Application of statistical criteria (based on 2014 External Debt Statistics: Guide for Compilers and Users):
  - The creditor (Azerbaijan Ministry of Transport) owns a claim on Marabda-Kartsakhi Railway LLC identified as debtor.
  - The Loan Agreement requires future payments to be made; this determines the liability as a debt.
  - Accrual basis in ESS requires recording the claim/liability when actual resource flows take place, i.e., when loan tranches are disbursed by Marabda-Kartsakhi Railway LLC.
  - The transfer of obligations for repaying the Loan to the joint venture is a contingent liability until the establishment of the joint venture; the joint venture cannot be made liable before incorporation.
- Recommendation and classification:
  - Liability for the loan disbursed by Marabda-Kartsakhi Railway LLC should be classified in balance of payments, IIP, and EDS under other investment – loans – other sectors.
  - Reclassification of the Loan to direct investment debt instruments is not applicable until the joint venture is established and the debt liability is transferred.
  - When the joint venture is established and the debt liability is transferred, the debt liability will be reclassified from other investment to direct investment – debt instruments.

### Other issues, progress, and institutional recommendations
- Progress since the 2016 mission:
  - Out of 17 actions recommended by the 2016 mission, 11 were completed and work on the remaining is ongoing.
  - Achievements include:
    - Methodology for estimating value of imported hepatitis C medicines was reviewed.
    - SEEA report form adjusted for better aligning to reporters’ terminology and reducing reporting burden.
    - Discrepancies between balance of payments data compiled by the NBG and direct investment data produced by Geostat have been eliminated.
    - Extensive work for compiling direct investment data disseminated by Geostat in an integrated format that includes both transactions and positions.
  - Appendix IV provides details on implementation status of 2016 mission’s recommendations (completed and ongoing actions).
- Revisions and consistency:
  - Until 2016 Geostat’s revision policy did not allow revision of published data considered final, causing inconsistencies with NBG data.
  - In July 2016 Geostat changed policy to permit revision once a year when annual data are published.
  - Recommendation: Geostat‘s revision approach of direct investment data to be adjusted to cover previous quarters for the current year while compiling quarterly data; data for previous years to be revised while compiling annual data.
- Staffing:
  - Staff resources assigned to production of ESS at Geostat are insufficient.
  - Recommendation: consider allocating additional staff to the External Trade and Foreign Investments Statistics Department (either on a permanent or contractual basis).
- Capacity development support:
  - Mission supported Eurostat’s regional program “Statistics through the Eastern Partnership” and the Twinning project with Statistics Denmark.
  - Mission assisted in identifying areas for new datasets (e.g., foreign affiliates statistics) and in developing an action plan to implement modules covering mirror trade data comparison with EU members and an enterprise survey on cross-border trade in services.
- Final recommendations (selected):
  - Adjust the revision approach for allowing introducing changes to data for previous years during the compilation of quarterly data, when there is need to assure their consistency with balance of payments data.
  - Increase the staff resources allocated to External Trade and Foreign Investments Statistics Department.

*Source: 2.   Loan Liabilities Composition After the Revision (1geoea2019002).*

### 2.   Loan Liabilities Composition After the Revision  _______________________________________________ 12

### 2.   Loan Liabilities Composition After the Revision

### Summary of mission outcomes and priority recommendations
- An ESS technical assistance mission visited Geostat during May 6–10, 2019, a follow up to November 2016, to assess progress and provide recommendations on ESS, financial account components, and reconciliation with NBG datasets.
- Review of other sectors’ loans identified possible affiliation:
  - 372 loans identified as possibly contracted within direct investment relationship and subject to detailed scrutiny.
  - 157 loans gauged as being from affiliated creditors after chain-of-ownership investigation.
  - Resulted in reclassifying about USD$700 million of loan liabilities from other investment to direct investment—debt instruments.
- Coverage and methodological treatment of import/export of cars was addressed:
  - Geostat analyzed declared prices for imported, exported, and re-exported cars and agreed a method to fill gaps and address valuation limitations.
  - Pilot adjustment showed import of cars increased by 3.4 percent for one month; reexport increased by 0.7 percent for one month.
- Crypto assets and gambling transactions coverage:
  - Georgia is among four countries leading in mining Bitcoins; mission drafted a list of indicators for collecting data on crypto assets to be tested with targeted companies.
  - Geostat to prepare list of questions for existing surveys to capture value of bets by nonresidents and their winnings; discussions with GGDA and casinos planned.
- Treatment of LLC Marabda-Kartsakhi Railway debt liabilities:
  - Loan liability remains an existing debt of LLC Marabda-Kartsakhi Railway until the joint enterprise is established per loan agreement.
- Staffing:
  - Staff resources at Geostat for ESS are insufficient; recommendation to consider additional staff (permanent or contractual).
- Priority recommendations (Table 1 highlights):
  - August 2019: Reclassify loans assessed as between affiliated entities from other investment to direct investment in balance of payments, IIP, external debt statistics, and CDIS. Responsible: Geostat, NBG.
  - December 2019: Introduce changes in IMTS for addressing issues in coverage and valuation of import, export, and re-export of cars. Responsible: Geostat.

### Action plan (priorities, milestones, and target dates)
- High priority (H):
  - Finalize revision of other sectors loan liabilities for identifying affiliation of creditors and debtors. Target: July 2019.
  - Reclassify loans between affiliated entities from other investment to direct investment in balance of payments, IIP, external debt statistics, and CDIS. Target: August 2019. (PR)
  - Introduce IMTS changes for coverage and valuation of import, export, and re-export of cars. Target: December 2019. (PR)
  - Adjust survey forms to include questions on crypto assets and gambling. Target: September 2019.
  - Launch collection of ESS data based on revised survey forms. Target: October 2019.
  - Increase staff resources allocated to External Trade and Foreign Investments Statistics Department. Target: 2020.
- Medium priority (M):
  - Finalize list of indicators for crypto assets and discuss with companies. Target: July 2019.
  - Finalize list of indicators related to gambling activity with GGDA. Target: September 2019.
  - Monitor crypto assets market for potential new reporters. Target: Ongoing.
  - Start disseminating aggregated direct investment data on assets–liabilities basis. Target: March 2020, together with publication of IIP by the NBG.
  - Adjust revision approach to allow introducing changes to previous years during compilation of quarterly data to assure consistency with balance of payments. Target: Regularly, when needed.
- Outcome targets emphasize use of latest manual concepts and definitions, adequate source data, adequate resources, and improved data dissemination.

### Trade in goods — methodology, adjustments, and results
- CDDB-based trade in goods statistics:
  - Adequate coverage for imports/exports by legal entities; individuals above non-duty import limits; and postage packages.
  - Geostat replaces CDDB data on import/export of gas and electricity with company-provided transporter data.
- NBG adjustments:
  - NBG uses Geostat aggregated trade data and makes additional adjustments based on mirror statistics (UN Comtrade) for major partners and groups countries into eight groups with average adjusting ratios.
  - Example adjustments to exports of goods (Quarter 4, 2018) (Table 2):
    - Geographical Zone applied coefficient and export before/after adjustment:
      - Zone 1: Applied Coefficient (%) 1.29 — The Data on Export of Goods Before Adjustment 139.90 After Adjustment 180.47
      - Zone 2: 1.31 — 155.34 → 203.50
      - Zone 3: 1.32 — 122.62 → 161.25
      - Zone 4: 1.33 — 160.47 → 213.43
      - Zone 5: 1.33 — 78.55 → 104.47
      - Zone 6: 1.31 — 147.36 → 193.04
      - Zone 7: 1.25 — 17.71 → 22.14
      - Zone 8: 1.30 — 84.51 → 109.86
      - Non-adjustable export: 1.27 → 1.27
      - Total: 907.73 → 1,189.42
      - Adjustment value: 281.69
      - Average adjustment coefficient: 31.0 %
  - Mission reiterated collaboration with Customs and partner countries where substantial CDDB–Comtrade discrepancies arise.

- Import/export of cars — issues and agreed estimation approach (Table 3)
  - Problem: SAMIA grants importers 60+30 days to register imported cars; cars re-exported within that period may be included in export data without inclusion in import data, creating coverage gaps in IMTS.
  - Geostat price analysis distinguished new vs used cars and companies vs individuals. Agreed estimation approaches:
    - Importer: Companies; Car Category: New cars
      - Price Analysis: Export prices are higher than import prices
      - Estimation Approach: If exported car is not included in import, estimate the import price by deducting (i) the estimated profit margin (approximately 15 percent) and (ii) freight and insurance (based on an ad-hock survey of importers).
    - Importer: Companies; Car Category: Used cars
      - Price Analysis: Export prices are lower than import prices
      - Estimation Approach: (i) Consider the export price as import prices; (ii) estimate export prices by adding the profit margin (approximately 10 percent).
    - Importer: Individuals; Car Category: New cars
      - Price Analysis: Export prices are understated mainly for cars with high engine capacity
      - Estimation Approach: Conduct a detailed analysis of data for one month and decide if there is basis for adjusting. If decision is to adjust, estimate adjustment coefficient based on analysis results.
    - Importer: Individuals; Car Category: Used cars
      - Price Analysis: Export prices are lower than import prices
      - Estimation Approach: (i) Consider export prices as import prices; (ii) introduce the estimated values of imported cars in imports for t-2 month; (iii) estimate export prices by adding the profit margin (approximately 10 percent) for all types of cars.
  - Pilot exercise results (one-month adjustments):
    - Change of Motor Vehicles (HS 870321-870380): Import in February 2019 (Table 4)
      - Import (before change): 648.1 Mill. USD
      - Change: 22.6
      - Change, %: 3.5
      - Import (after change): 670.7
    - Change of Motor Vehicles (HS 870321-870380): Reexport in April 2019 (Table 5)
      - Reexport (before change): 307.4 Mill. USD
      - Change: 2.4
      - Change, %: 0.8
      - Reexport (after change): 309.8
  - Recommendation: Geostat should coordinate with the NBG to adjust import/re-export of cars in IMTS and balance of payments to assure consistency.

### Improving accuracy of balance of payments and IIP statistics — direct investment and loan reclassification
- Direct investment compilation:
  - Geostat is responsible for collecting, compiling, and disseminating direct investment data via SEEA (quarterly and annual).
  - Verification/validation:
    - Geostat verifies and validates data from direct investment reporters.
    - NBG verifies and validates data for non-direct investment reporters.
  - Reconciliation outcomes:
    - Geostat and NBG reconciled direct investment data disseminated by Geostat with those included in IIP by NBG; reconciliation eliminated discrepancies between IIP and CDIS data.
    - Alignment was enabled by Geostat establishing an integrated direct investment database including flows and positions and accounting for price and exchange rate changes.
  - Treatment of “other changes”:
    - “Other changes” mainly include reclassifications due to change in residence or institutional sectors and downward adjustments for liquidation of companies.
    - Geostat has been removing from the database companies that did not submit the survey for two consecutive years and did not fill tax returns; mission advised a more precautionary approach—remove companies only if proof of liquidation exists.
  - Dissemination:
    - In 2018 Geostat started disseminating positions on direct investment in BPM6 basis for balance of payments/IIP consistency and in BPM5 basis for CDIS consistency.
- Loan liabilities reclassification:
  - Review of other sectors’ loans aimed to identify affiliation of debtors and creditors for improved classification.
  - From 372 private sector loans reviewed, 157 were assessed as loans from affiliated creditors and reclassified.
  - The Geostat–NBG exercise resulted in reclassifying about USD$700 million of loan liabilities from other investment to direct investment—debt instruments.
  - The mission assessed selection criteria and assisted in deciding on an additional ten uncertain cases.

*From: 2.   Loan Liabilities Composition After the Revision (1geoea2019002).*

### 21. For improving the accuracy of classification of balance of payments components, a

### 21. For improving the accuracy of classification of balance of payments components, a

### Reclassification exercise of other sectors’ loans
- Targeted 1,073 private sector loans that registered disbursements/repayments during 2016–2018.
- From the targeted loans, 372 loans were identified as possibly being contracted within the direct investment relationship and were subject to detailed scrutiny.
- After investigating the chain of ownership, 125 loans were gauged as being from affiliated creditors applying established criteria such as the maturity of loan, interest rates, or similarity in names of borrower and lender.
- The mission assessed the applied selection criteria and assisted in deciding on ten uncertain cases.
- The exercise resulted in reclassifying about USD$700 million of loan liabilities from other investment to direct investment—debt instruments.
- Composition indicators presented in the source (end-2018, in percent and million USD):
  - Yearly percentages: 3.84%, 7.83%, 12.25%, 7.45%, 3.12%, 4.86%, 1.20% (associated with 2010–2016 series as shown in the figure).
  - Loans reclassified to DI: 18%
  - Loans in other investment: 81%
  - Other (to be analyzed): 1%

### Recommendations from the reclassification exercise
- Introduce changes in IMTS for addressing issues in coverage and valuation of import, export, and re-export of cars;
- Finalize the revision of other sectors loan liabilities for identifying the affiliation of creditors and debtors;
- Reclassify the loans assessed as being between affiliated entities from other investment to direct investment in balance of payments, IIP, external debt statistics, and CDIS;
- Start disseminating the aggregated direct investment data in Geostat publications on assets – liabilities bases, in addition to directional principle.

### Exploring new data sources and methodological issues (crypto assets, intermediaries, gambling)
- Crypto assets
  - Coverage of transactions related to crypto assets in ESS of Georgia has been of concern.
  - Georgia is among the four countries leading in mining Bitcoins; a number of companies in the country are involved in mining crypto assets, including a subsidiary of Bitfury Group.
  - Meeting with Bitfury subsidiary: discussed availability of information related to transactions with nonresidents and pilot blockchain land-titling project; agreed that a list of indicators for collecting data on crypto assets will be drafted and tested with the Bitfury subsidiary. The draft list of indicators is presented in Appendix II.
  - Appendix II (questionnaire on crypto assets) includes indicators such as:
    - Number of Bitcoins mined during the reported period (Units)
    - Value of Bitcoins mined (at price of the day of the transaction) (Currency)
    - Fees received for validating the transactions (Currency)
    - Number of Bitcoins sold to nonresidents (Units)
    - Of which through the domestic intermediary (e.g., E-Money) (Units)
    - Funds received from parent company other than loans and funds in equity (Currency)
    - Fixed assets (e.g., computers, servers, etc.) (Currency)
    - Intellectual property (Currency)
- Intermediary (e-Money)
  - e-Money requires every client to create an e-wallet maintained on the company’s platform with full identification (e.g., passport data stored).
  - Company able to provide data for balance of payments purposes based on residence concept.
  - NBG conducted a survey of e-Money during 2017–2018; mission recommended NBG review the survey questionnaire with e-Money and launch it on a regular basis.
- Gambling
  - Need to improve coverage of transactions related to gambling due to growing nonresidents’ activities.
  - Meeting with President of GGDA: Geostat to prepare list of questions to include in existing surveys to capture value of bets by nonresidents and their winnings; GGDA to support arranging meetings with a few biggest casinos to assess feasibility of reporting such data.

### Treatment of Marabda-Kartsakhi Railway loan liabilities
- Context
  - Debt liabilities arise from foreign financing of the Marabda-Kartsakhi Railway project linking Azerbaijan and Turkey through Georgia.
  - Signed agreements identify Marabda-Kartsakhi Railway LLC as “borrower”; Article 5 of the Intergovernmental Agreement envisages transfer of infrastructure to a joint venture with equal equity participation by Azerbaijan Railways and Georgian Railways after completion.
  - Paragraph 8.2 of the Credit Agreement states that borrower’s obligations, including obligations to repay the loan/loans, shall no longer be in force from the moment an Agreement is signed between the borrower and the joint venture regarding the transfer of the right to use the railway infrastructure and the assignment of all loan obligations with regard to repayment of the funds.
- Application of statistical criteria (based on 2014 External Debt Statistics: Guide for Compilers and Users)
  - Key criteria and conclusions applied to Marabda-Kartsakhi Railway LLC loan:
    - (i) The Azerbaijan Ministry of Transport, identified in the Loan Agreement as creditor, owns a claim on Marabda-Kartsakhi Railway LLC identified as debtor.
    - (ii) The Loan Agreement requires future payments to be made; this requirement determines the liability as a debt. The principle of ownership is applicable—the Azerbaijan Ministry of Transport owns a claim and the debtor has a liability.
    - (iii) Accrual basis in ESS requires recording the claim/liability when actual resource flows take place, i.e., when loan tranches are disbursed by Marabda-Kartsakhi Railway LLC.
    - (iv) The claim and liability are recorded in books of both parties on the date when change of ownership takes place—the date of disbursement.
    - (v) The transfer of obligations for repaying the Loan to the joint venture is a contingent liability until the establishment of the joint venture; the joint venture cannot be made liable before incorporation.
- Recommendation and classification
  - Liability for the loan disbursed by Marabda-Kartsakhi Railway LLC should be classified in balance of payments, IIP, and EDS under other investment – loans – other sectors.
  - Reclassification of the Loan to direct investment debt instruments is not applicable until the joint venture is established and the debt liability is transferred.
  - When the joint venture is established and the debt liability is transferred, the debt liability will be reclassified from other investment to direct investment – debt instruments.
- Appendix III reproduces the relevant paragraphs from 2014 EDS used as criteria (Paragraphs 2.4, 2.7, 2.8, 2.10, 2.25, 2.26, 3.17).

### Recommendations on new data sources and Marabda-Kartsakhi loan
- Finalize the list of indicators related to transactions in crypto assets and discuss them with relevant companies;
- Finalize the list of indicators related to gambling activity, in cooperation with the GGDA;
- Adjust the survey forms for including questions related to transactions in crypto assets and gambling activity;
- Launch the collection of data for ESS based on the revised survey forms;
- Monitor the developments in the market of crypto assets in Georgia for identifying potential new reporters;
- Continue classifying the Marabda-Kartsakhi Railway LLC’s loan liability under other investment – loans – other sectors.

### Other issues, progress, and institutional recommendations
- Progress since the 2016 mission
  - Out of 17 actions recommended by the 2016 mission, 11 were completed and work on the remaining is ongoing.
  - Achievements include:
    - Methodology for estimating value of imported hepatitis C medicines was reviewed;
    - SEEA report form adjusted for better aligning to reporters’ terminology and reducing reporting burden;
    - Discrepancies between balance of payments data compiled by the NBG and direct investment data produced by Geostat have been eliminated;
    - Extensive work for compiling direct investment data disseminated by Geostat in an integrated format that includes both transactions and positions.
  - Appendix IV provides details on implementation status of 2016 mission’s recommendations, including completed and ongoing actions (e.g., review quarterly ratios for adjusting trade in goods data; adjust survey forms; start compiling position data for direct investment in integrated format; implement revision policy changes).
- Revisions and consistency
  - Until 2016 Geostat’s revision policy did not allow revision of published data considered final, causing inconsistencies with NBG data.
  - In July 2016 Geostat changed policy to permit revision once a year when annual data are published.
  - Recommendation: Geostat‘s revision approach of direct investment data to be adjusted to cover previous quarters for the current year while compiling quarterly data; data for previous years to be revised while compiling annual data.
- Staffing
  - Staff resources assigned to production of ESS at Geostat are insufficient.
  - Recommendation: consider allocating additional staff to the External Trade and Foreign Investments Statistics Department (either on a permanent or contractual basis).
- Capacity development support
  - Mission supported Eurostat’s regional program “Statistics through the Eastern Partnership” and the Twinning project with Statistics Denmark.
  - Mission assisted in identifying areas for new datasets (e.g., foreign affiliates statistics) and in developing an action plan to implement modules covering mirror trade data comparison with EU members and an enterprise survey on cross-border trade in services.
- Recommendations (final)
  - Adjust the revision approach for allowing introducing changes to data for previous years during the compilation of quarterly data, when there is need to assure their consistency with balance of payments data;
  - Increase the staff resources allocated to External Trade and Foreign Investments Statistics Department.

*Source: 1geoea2019002 - IMF mission report content (extracted chapter/section).*

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_Source: https://www.imf.org/-/media/files/publications/cr/2019/1geoea2019002.pdf_