IMF国际货币组织全球-Kingdom-of-Lesotho_Technical-Assistance-Report-Government-Finance-Statistics-Mission-_January-14–25-2019_33页_997kb

Summary of the Government Finance Statistics (GFS) Mission to Lesotho (January 14–25, 2019)

Core Content

This report summarizes the outcomes and recommendations of the Government Finance Statistics (GFS) Mission to Lesotho, conducted from January 14 to 25, 2019. The mission was part of the United Kingdom's Department for International Development (DFID) Enhanced Data Dissemination Initiative (EDDI) 2 and followed up on previous GFS technical assistance (TA) missions in March and November 2016, and May 2018. It also responded to a request from the Lesotho delegation during the 2018 Annual Meetings in Bali for further assistance in improving GFS compilation and dissemination.

Main Objectives

• Review progress on the implementation of past GFS TA recommendations.
• Update the public sector institutional table.
• Assist in incorporating reclassifications and new data into the GFS compilation.
• Improve the accuracy and comprehensiveness of GFS data.
• Develop a GFS improvement work plan for the next two years.

Key Findings

A. Implementation of Recent GFS TA Missions' Recommendations

• Progress on implementing GFS TA recommendations has been slow.
• Only 8 out of 64 recommendations were fully implemented, 14 were partially implemented, and 40 remained unaddressed.
• Lack of formal institutional arrangements and clear responsibilities has hindered the implementation.

B. Institutional Coverage of the Public Sector

• The public sector institutional table was updated to include 109 institutional units.
• 98 are non-market entities (general government), and 11 are market entities (public corporations).
• A working group was established to review and update the table, but progress has been slow.

C. GFS Compilation for the Budgetary Central Government

• The existing GFS compilation file (SGO_DB) was upgraded to include source data from CBL, IFMIS, and the Debt Department.
• Several reclassifications and additions were made:
  • Rand monetary compensations reclassified from property tax to grants.
  • Policy lending transactions and interest repayments added.
  • Unfunded social contributions reclassified to employment-related social benefits.
  • Capital budget transactions reclassified under nonfinancial assets.
  • SACU receipts reclassified for reporting to the IMF.
• A significant statistical discrepancy was reduced from about 10% of GDP to a range of -2 to 2% of GDP over the last five years.
• The mission recommended resolving coverage discrepancies and improving data accuracy by addressing the recording of government equity participation, capital grants, and revaluation of deposits.

D. GFS Compilation for Local Government

• The mission compiled GFS data for 10 district councils using financial statements and a previously developed template.
• A new template was created for the Maseru City Council (MCC) to harmonize data presentation and facilitate aggregation.
• MCC financial statements include both accounts payable and receivable, unlike other district councils.
• A different classification of expenses in MCC's financial statements complicates data aggregation.

E. GFS Compilation for Extrabudgetary Units

• No GFS for extrabudgetary units is currently compiled.
• The MOF is collecting financial statements for identified extrabudgetary units.
• The mission recommended using a similar template to the one developed for local governments to compile GFS for these units.

F. GFS Compilation for the Pension Fund

• The mission compiled GFS for the Public Officers Defined Contributions Pension Fund (PODCPF).
• There may be lags in the receipt of social contributions, which are recognized as contributions payable in the financial statements.

Priority Recommendations

Key Challenges

• Coverage Discrepancy: Transactions above the line (revenue and expenditure) are less comprehensive than those below the line (government deposits).
• Data Accuracy: Incomplete and implausible data in financial statements leads to large statistical discrepancies.
• Recording Basis: Some data is recorded on a cash basis, while others require accrual basis adjustments.
• Source Data Issues: Challenges in collecting and recording grant revenue and other financial flows.

Conclusion

Improving the accuracy, comprehensiveness, and consistency of GFS and Public Sector Debt Statistics (PSDS) remains a critical priority for Lesotho. The mission emphasized the need for better institutional coordination, clearer responsibilities, and more systematic data collection across all levels of government and public entities. Continued efforts to address these issues will be essential for enhancing fiscal transparency and policy-making.