Uganda
Technical Assistance Report-Report on Government Finance Statistics

This Technical Assistance Report discusses technical advice and recommendations given by the IMF mission to the authorities of Uganda regarding compilation and dissemination of government finance statistics and public sector debt statistics according to international standards. Automation of the collection of source data for extra-budgetary units and local governments is recommended, first through the use of data collection templates and second through incorporation of these institutional units into the Integrated Financial Management and Information System. Historical data on the stock of arrears and related repayments should also be provided to enable assessment of progress on reducing and clearing arrears.

Abstract

This Technical Assistance Report discusses technical advice and recommendations given by the IMF mission to the authorities of Uganda regarding compilation and dissemination of government finance statistics and public sector debt statistics according to international standards. Automation of the collection of source data for extra-budgetary units and local governments is recommended, first through the use of data collection templates and second through incorporation of these institutional units into the Integrated Financial Management and Information System. Historical data on the stock of arrears and related repayments should also be provided to enable assessment of progress on reducing and clearing arrears.

I. Executive Summary

In response to a request from Ugandan authorities and in consultation with the International Monetary Fund’s (IMF’s) African Department, Brooks Robinson, Regional Government Finance Statistics (GFS) Advisor for the IMF’s East Africa Regional Technical Assistance Center (AFRITAC, AFE), and Clément Ncuti (an IMF GFS Expert) conducted a GFS technical assistance (TA) mission to Kampala, Uganda during March 7–18, 2016. The mission was part of AFE’s collaboration program with the East African Community (EAC) Secretariat, and supported efforts to align compilation and dissemination of GFS and public sector debt statistics (PSDS) with international standards. The mission’s main objectives were to assist authorities in the compilation and dissemination of annual and high-frequency GFS for financial years (FYs) 2013/14 and 2014/15.

A November 2015 TA visit to Uganda revealed that authorities were well advanced in the compilation of preliminary general government finance statistics for FY 2013/14; although source data collection methods (manual retrieval and transcription of data from hard-copy annual audited financial reports) appeared to be too resource intensive and time consuming. As noted, the mission anticipated assisting authorities in finalizing revised and new general government finance statistics for FYs 2013/14 and 2014/15, respectively. However, the mission found that authorities encountered challenges in completing collection of FY 2014/15 source data in advance of the mission, and requested that the mission focus on finalizing GFS for FY 2013/14 and on compiling historical general government finance statistics for FYs 2006/07 – 2012/13. The mission also found that, like other EAC partner states, Uganda faces several other challenges in fulfilling its fiscal and debt data development (Government Finance Statistics Manual 2014 (GFSM 2014) implementation) plan.

During the course of the mission, the following key recommendations evolved:

  • Promulgate widely the Public Sector Institutional Table that has been developed, because it can help ensure consistency across all of the nation’s macroeconomic statistics.

  • Automate the collection of source data for extrabudgetary units and local governments first by using data collection templates, and second by incorporating these institutional units into the Integrated Financial Management and Information System.

  • Disseminate to the IMF the new general government finance statistics that were nearly finalized for FY 2013/14 during the mission; and FY 2014/15 general government finance statistics should be disseminated as soon as they are available.

  • For high-frequency Statements of Operations, measure the period-by-period difference between tax collections and related remittances to the Uganda Consolidated Fund, and the difference between accrual basis above-the-line Expenditure and cash basis below-the-line Net financing (i.e., the float) in order to identify potential reasons for sizeable swings in the Statistical discrepancy.

  • Provide historical data on the stock of Arrears and related repayments to enable an assessment of progress on reducing and clearing Arrears.

The mission team transmits its warm appreciation to authorities for the hospitality and cooperation extended during the mission, which contributed significantly to the mission’s success.

II. Introduction

1. In response to a request from Ugandan authorities and in consultation with the International Monetary Fund’s (IMF’s) African Department, Brooks Robinson, Regional Government Finance Statistics (GFS) Advisor for the IMF’s East Africa Regional Technical Assistance Center (AFRITAC, AFE), and Clément Ncuti (an IMF GFS Expert) conducted a GFS technical assistance (TA) mission to Kampala, Uganda during March 7–18, 2016.1 The mission was part of AFE’s collaboration program with the East African Community (EAC) Secretariat, and supported efforts to align compilation and dissemination of GFS and public sector debt statistics (PSDS) with international guidelines. The mission’s main objectives were to assist authorities in the compilation and dissemination of annual and high-frequency GFS for financial years (FYs) 2013/14 and 2014/15.

2. A November 2015 TA visit to Uganda revealed that authorities were well advanced in the compilation of preliminary general government finance statistics for FY 2013/14; although source data collection methods (manual retrieval and transcription of data from hard-copy annual audited financial reports (AAFRs)) appeared to be too resource intensive and time consuming. As noted, the mission anticipated assisting authorities in finalizing revised and new general government finance statistics for FYs 2013/14 and 2014/15, respectively. However, the mission found that authorities encountered challenges in completing the FY 2014/15 statistics in advance of the mission, and requested that the mission focus on finalizing GFS for FY 2013/14 and on preparing historical general government finance statistics for FYs 2006/07 – 2012/13.

3. Besides the compilation and dissemination of annual general government finance statistics, the mission’s main tasks were:

  • Assist authorities in compiling and disseminating high-frequency GFS.

  • Assist authorities in planning to automate source data collection.

  • Engage authorities on issues of concern with the IMF’s African Department: e.g., large swings in the Statistical discrepancy that are associated with high-frequency GFS; and Arrears.

  • Assist authorities in finalizing and beginning to implement a GFS data quality improvement work program (DQIWP).

  • Assess the status of Uganda’s fiscal and debt data development (Government Finance Statistics Manual 2014 (GFSM 2014) implementation) plan.

  • Fulfill authorities’ requests for TA.

4. The remainder of this report unfolds as follows. Section III highlights the Government of Uganda’s (GOU’s) institutional structure. Section IV discusses automating GFS source data collection. Section V concerns compilation of general government finance statistics. Section VI covers the compilation of high-frequency GFS estimates for budgetary central government (BCG). Sections VII and VIII consider concerns raised by the IMF’s African Department: Large swings in the Statistical discrepancy and Arrears. Section IX discusses efforts to motivate a GFS DQIWP in Uganda. Section X concerns the status of Uganda’s GFSM 2014 implementation plan. Section XI outlines GFS TA and training opportunities for Ugandan authorities during FY 2016/17. Section XII is the conclusion. Germane, yet secondary, documents are provided in the appendix.

III. The Government of Uganda Institutional Structure

5. The GOU is comprised of 523 institutional units (Table 1) via the following subsectors of the public sector: BCG and extrabudgetary units (EBUs) constitute central government; central government combines with local governments (LGs) to comprise the general government subsector; and financial and nonfinancial public corporations make up the public corporate sector. Uganda’s National Social Security Fund (NSSF) is classified as a provident fund and as a financial public corporation; therefore, the nation has no social security funds subsector. Uganda, like other nations within the EAC, has no state governments.

Table 1.

Government of Uganda Institutional Structure

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Source: Mission Team.

6. Uganda’s Public Sector Institutional Table was reviewed during a July 2014 GFS TA mission.2 The table, when promulgated widely, can help ensure that all of the nation’s macroeconomic statistics are consistent. Previous mission teams have advised authorities to promulgate the table widely, but, to date, this has not been done. Therefore, the recommendation is repeated here.

Recommendation:

  • Authorities should conduct annual maintenance of, and promulgate widely, Uganda’s Public Sector Institutional Table because it can help ensure consistency across all of the nation’s macroeconomic statistics.

IV. Automating Data Collection for EBUS and Local Governments

7. As noted earlier, an important initial objective of the TA mission was to assist authorities in finalizing general government finance statistics (Statement of Operations) for FY 2014/15. However, authorities were unable to complete the compilation of these statistics prior to the mission. One of the key reasons for the delay in compiling these statistics was the methodology that is employed currently to collect data for EBUs and LGs: i.e., paper copies of the AAFRs for these institutional units are collected, and the Ministry of Finance, Planning, and Economic Development’s (MoFPED’s) staff transcribes fiscal statistics from these reports into a GFS database for the compilation process. As Table 1 reflects, there are 63 EBUs and 306 LGs, which makes this data collection process labor intensive and time consuming. Note, however, that unlike data for EBUs and LGs, source data for the BCG are obtained in automated fashion from MoFPED’s departments, the Integrated Finance Management and Information System (IFMS), and the Bank of Uganda (BoU).

8. Other EAC nations have sought to solve the timeliness problem that is associated with collecting source data for annual general government finance statistics. Specifically, Kenya and Tanzania have developed templates to collect annual data for all general government institutional units or for institutional units in subsectors for which data collection has not been automated. In fact, Kenya has gone beyond annual data collection via templates, and is now planning to collect quarterly GFS source data using this method.

9. Ugandan authorities indicated that they are interested in using templates to collect source data for general government finance statistics. They were motivated to make this consideration in line with the African Department’s request for high frequency data as part of the monitoring of the Policy Support Instrument (PSI) arrangement that Uganda has with the IMF.

10. In March of 2015, Uganda’s Parliament passed a new Public Finance Management (PFM) Act that provides for the type and frequency of budget reports. Provisions for reporting that are reflected in the Act require that every three months accounting officers should prepare and submit to the Secretary of the Treasury an expenditure commitment report (article 16 and 21). Furthermore, accounting officers are required to prepare and submit half-year financial statements to the Accountant General not later than February 15 of each financial year, and annual accounts two months after the end of each financial year (articles 49 and 50).

11. With the new reporting requirements providing authority to the Accountant General to request entities to report on a quarterly, bi-annual and annual basis, and the need to start using templates to collect high-frequency source data, the PFM Act provides an unprecedented opportunity for the Ugandan authorities to push ahead with the use of templates for data collection.

12. In order to ensure timeliness in the compilation of general government finance statistics, the mission urges authorities to move forward with their plans to collect data first via data collection templates, and second by planning to incorporate EBUs and LGs institutional units into IFMS. While employing the data collection template method, we advise authorities to consider: (1) collecting data from the entire population via templates; or (2) using stratified sample surveys to collect data via templates on a high-frequency basis.

Recommendation:

  • Authorities should automate the collection of source data for EBUs and LGs first by using data collection templates (annually and on a high-frequency basis), and second by ultimately incorporating these institutional units into the IFMS.

V. Compilation of Annual General Government Finance Statistics

13. As noted above, authorities did not complete the compilation of general government finance statistics for FY 2014/15 prior to the mission; therefore, the mission could not take up the review and validation of these statistics. However, the mission team provided guidance to authorities on compiling a general government finance statistics dataset for FY 2013/14 in a GFSM 2014 Statement of Operations framework, and reviewed compilation performed on historical general government finance statistics spanning FYs 2006/07 – 2012/13. The mission also assisted in the development of a brief source data inventory statement (Appendix II) that documents the source data that are required to compile general government finance statistics. Authorities are expected to compile general government finance statistics for FY 2014/15 in the near-term, and promised to disseminate the dataset to the IMF. The mission reviewed FY 2014/15 annual and monthly GFS for BCG as these statistics were compiled prior to the mission.

14. For BCG, Table 2 shows that tax Revenue data were from MoFPED’s Tax Policy Department (TPD). Nontax Revenue (excluding Grants) data were from TPD, the Accountant General’s Department (AGD), and ministries, departments, and agencies’ (MDA’s) appropriation in aid (AIA) statements. Grants Revenue was from a reconciliation between the Bank of Uganda (BoU) and MoFPED’s Department of Assistance and Regional Cooperation (DARC). Expenses data were from IFMS; MoFPED’s Debt Management Department (DMD, Interest); legacy releases from MoFPED’s Budget Directorate (BD, Grants to other levels of government); and proportions of Grants (development project related Revenue) and Loans (development project related Incurrence of Liabilities) reconciled between the BoU and DARC that are deemed to be Expense items. Data on domestically financed Net acquisition of nonfinancial assets (NANFA) were from IFMS, MoFPED’s AGD (disposal of NANFA), and legacy releases from BD deemed to be NANFA items. Data on externally financed NANFA were from a reconciliation between BoU and MoFPED’s DARC (proportions of external development project Grants and Loans that are deemed to be nonfinancial assets). Net Acquisition of Financial Assets (NAFA) data were from the BoU’s Depository Corporations Survey (DCS) and from the AGD. Domestic Net incurrence of liabilities (NIL) data were from the BoU’s DCS—validated by MoFPED’s DMD data. Data on foreign NIL were from MoFPED’s DMD and DARC—reconciled with BoU data. Source data for EBUs and LGs were obtained from AAFR tabulations.

Table 2.

Source Data for FY 2013/14 General Government Finance Statistics1

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Source: Mission team.

The full forms for the acronyms in this table are: AAFR—Annual Audited Financial Reports (tabulated by the Ministry of Finance, Planning and Economic Development (MoFPED)); AGD—Accountant General’s Department within MoFPED; AIA—Appropriations in Aid; BD—Budget Directorate within MoFPED; BoU–Bank of Uganda; DARC—Department of Development Assistance and Regional Coordination within MoFPED; DMD—Debt Management Department within MoFPED; IFMS–Integrated Financial Management and Information System; MDA’s—Ministries, Departments and Agencies; and TPD—Tax Policy Department within MoFPED.

15. A few adjustments were made to source data when compiling the general government finance dataset. The following sections describe the specific methodology used during the compilation process.

A. BCG

16. Data on BCG tax and nontax Revenue from TPD were obtained from the Uganda Revenue Authority (URA) and reclassified into tax and other revenue categories by MoFPED’s Macroeconomic Policy Department (MEPD) staff. Grants Revenue data were obtained from a reconciliation between the BoU and MoFPED’s DARC and were not adjusted. Revenue data reflect a cash basis of recording.

17. All BCG Expense data were from IFMS, except for Interest data, which were from the DMD, and for Grants to other levels of government data, which were from BD’s legacy releases. BCG Expense data were reported with no adjustment, with the exception of expenses financed by external capital grants and loans. Spending on development projects financed from external capital grants and loans of a recurrent nature are apportioned into corresponding Expense items using ratios that the authorities develop each year from budget projections. All IFMS Expense data reflect an accrual basis of recording.

18. BCG data on domestically financed NANFA were mainly from IFMS and were reported with no adjustment. Data on NANFA financed from external capital grants and loans were obtained as a proportion of total inflows of external capital grants and loans that are apportioned to NANFA based on annual budget projections.

19. No adjustments were made to BCG NAFA and NIL data, other than exchange rate conversions of selected items.

B. EBUs and Local Governments

20. As reflected in Table 2, all source data for the major economic classifications for EBUs and LGs were obtained from AAFR tabulations, and are compiled into GFS without adjustments.

C. Results for FY 2013/14

21. Appendix III presents provisional results of the general government finance statistics compilation for FY 2013/14. These statistics remain provisional until Uganda’s Statistical Committee formally validates the institutional table for FY 2013/14 and confers concerning certain reclassifications that were recommended by the mission, e.g.:

  • Determine the appropriate sectoral classification of certain institutional units (e.g., the Uganda Revenue Authority (URA) and embassies).

  • Reclassify BCG transfers to international organizations representing membership dues as Use of goods and services.

  • Reclassify BoU recapitalization from NAFA Loans to investment in equity (Equity and investment fund shares).3

  • Reclassify misclassified Grants Expense within EBUs and Local Governments’ as other expense.

22. Provisional results for FY 2013/14 show that general government Revenue amounted to USH 9,682.7 billion, while Expense amounted to USH 9,178.5 billion, leading to a Net operating surplus of USH 504.2 billion. NANFA was USH 3,233.2 billion, thereby producing a Net borrowing position of USH (2,729) billion. Net financing was USH (2,556.1) billion, being derived from NAFA of USH (4,406.5) billion and NIL of USH (1,805.4) billion. Consequently, the Statistical discrepancy was USH 172.9 billion.

D. Statement of Sources and Uses of Cash

23. The mission provided guidance on the compilation of a general government Statement of Sources and Uses of Cash for FY 2013/14. The mission noted that while all GFS data on EBUs and LGs were on a cash basis, it was not the case for the BCG. BCG data reported in the general government Statement of Operations include a mix of cash and accrual data. All expense and domestically financed NANFA statistics drawn from IFMS are on an accrual basis. However, Revenue and Expense not drawn from IFMS (legacy releases, and apportioned expenses financed from external capital grants and loans), NANFA financed by external capital Grants and Loans, NAFA, and NIL are all on a cash basis.

24. The mission could not assist in the completion of the compilation of a general government Statement of Sources and Uses of Cash owing to a lack of accurate and comprehensive cash basis data. For the compilation of a statement of Sources and Uses of cash, the mission urged authorities to begin collecting expenditure data on a cash basis from IFMS and crosschecking those data with data on outflows from the Uganda Consolidated Fund’s (UCF).

Recommendations:

  • Authorities should validate the FY 2013/14 general government finance statistics and disseminate them to the IMF’s Statistics Department.

  • Authorities should finalize compilation of the FY 2014/15 general government finance statistics and disseminate them to the Statistics Department as soon as they are finalized.

  • Authorities should compile general government Statements of Sources and Uses of Cash for FYs 2013/14 and FY 2014/15 and disseminate them to the Statistics Department as soon as they are finalized.

VI. High-Frequency General Government Finance Statistics for BCG

25. One of the mission’s objectives was to assist authorities in compiling and disseminating high-frequency GFS. Uganda has been submitting high-frequency GFS for BCG to the IMF’s African Department for some time. There are no high-frequency source data (as of yet) for EBUs and LGs. High-frequency data for BCG for FY 2013/14 and FY 2014/15 were available during the mission and were posted on the MoFPED website. The mission assessed the quality of these data and raised concerns similar to those of the African Department about large month-to-month swings in the Statistical discrepancy.

26. Other than the just-mentioned large swings in the Statistical discrepancies, the monthly data seemed to be of good quality—averaging to annual values for both of the financial years that were reviewed. The mission investigated reasons for large swings in the Statistical discrepancies and the findings are reported in the next section.

Recommendation:

  • Authorities should disseminate to the IMF’s Statistics and African Departments the high frequency GFS BCG data as soon as they are compiled.

VII. Statistical Discrepancy Swings

27. Leading up to this GFS TA mission, the African Department communicated its concerns about large swings in the Statistical discrepancy (errors and omission) for Uganda’s high-frequency (monthly) GFS for BCG (Statement of Operations). An important objective of the mission was to attempt to identify the substantive causes of these large swings.

28. The mission identified three elements that could potentially be contributing to swings in the Statistical discrepancy in high-frequency GFS data and investigated them. (i) Tax Revenue; (ii) quarterly spending on Grants that are consistently high in the first month of the quarter; and (iii) IFMS Expense and NANFA categories that are recorded on an accrual basis while the remainder of the Statement of Operations is recorded on a cash basis.

29. First, Taxes (Revenue) reported in the monthly Statement of Operations reflect amounts collected as reported by taxpayers through their declarations. The mission noted that there could be a timing mismatch when Revenue is reported as collected, and when the Revenue is remitted to the UCF at the BoU. A particular case of when the mismatch could be most pronounced is when Revenue payment deadlines fall on the last day of a month. Amounts paid by taxpayers at URA’s revenue collection points (mainly commercial banks) on the last day of the month would be remitted to the UCF only after 48 hours.4 While the revenue collection is recorded in the Statement of Operations in that month, the corresponding entry in the form of a change in BCG’s Currency and deposits at the BoU would be recorded the following month. Similarly, amounts not collected through commercial banks but rather through URA’s offices on the last day of the month, which are not remitted to the UCF the same day, would be recorded as Revenue in the Statement of Operations in that month, but only reflected as a change in Currency and deposits the following month.

30. Second, the mission noted that there was consistently high Grants Expense during the first month of every quarter. Investigating this issue further showed that there were strong negative correlation (-.73) between Grant Expenses and Net Lending/Borrowing (NL/B) and a positive correlation (.52) between NL/B and the Statistical discrepancy. Grants to other levels of governments (EBUs and LGs) are usually recorded in IFMS at the beginning of each quarter, thereby explaining the large Grants Expense in the first month of each quarter. While IFMS transactions reflect a commitment, they do not translate into actual payment during the same month. With such inconclusive results, the mission investigated this timing mismatch on a more general basis.

31. Third, IFMS Expenditure recorded in BCG Statement of Operations for any month is on an accrual basis. Expenditure represents commitments through IFMS for the supply of goods and services, and for the acquisition of nonfinancial assets that may not have necessarily been paid for during the same month the commitment is made and recorded in IFMS. While Expenditure from IFMS is recorded on an accrual basis, Revenue and Net Financing items are recorded on a cash basis in the Statement of Operations. The mismatch in the timing of recording Expenditure and the corresponding effective cash payment—if not taken into account through adjustment of transactions recorded in any month for the float (i.e., the difference between expenditure commitments (accrual) and payments (cash))—can lead to a Statistical discrepancy. The mission suggested two approaches for determining the value of the float during the month. One approach would entail extracting Expenditure data from IFMS on a cash basis and comparing those data with IFMS Expenditure data on a commitment basis to determine the float. The alternative approach would be to compare data from the BoU on actual spending during the month with IFMS accrual-based Expenditure data to determine the float. The monthly Statement of Operations could, therefore, record the float as a financing item to equilibrate above-the-line transactions on Expenditure with below-the-line financing (namely Other accounts payable). Using IFMS commitment (accrual) and payments (cash) data, the mission computed the float for the months of FYs 2013/14 and FY 2014/15. However, a strong correlation between the float and the Statistical discrepancy could not be established.

32. Therefore, the mission concluded that, while it may not be possible to establish a high statistical correlation between any one of the elements examined and the Statistical discrepancy, in combination, these elements, and potentially other factors contribute to the Statistical discrepancy and its large swings.

Recommendations:

  • Authorities should keep track of revenue collections in transit and in vaults and make adjustments to the monthly Statement of Operations to match Revenue transactions above the line with the change in Currency and deposits below the line.

  • Authorities should develop estimates of the float (i.e. the difference between expenditure commitments (accrual) and payments (cash)) and make adjustments to the monthly Statement of Operations to match above-the-line Expenditure transactions with below-the-line financing.

VIII. Arrears

33. In addition to concern about swings in the Statistical discrepancy, the African Department also expressed concerns about recent growth in Uganda’s Arrears. The mission pledged to explore this topic. The mission sought to clarify:

  • How does Uganda define Arrears?

  • How are Arrears measured?

  • Why are Uganda’s Arrears increasing?

  • How does Uganda plan to halt the increase in, and reduce, Arrears?

34. According to authorities, transactions that are commenced during an accounting period (a financial year) for which goods or services are delivered to GOU institutional units, but for which payment is not made, constitute an “unpaid bill.” However, if “unpaid bills” remain unpaid after the close of financial year, then they become Arrears.5 Also, Arrears arise primarily from two other sources: (i) unfavorable judicial rulings for which no provisions have been made; and (ii) unpaid pension payments.

35. Although information on the stock of Arrears is only available on MoFPED’s Internet website for the year ending June 30, 2015, the ministry provided a preliminary comparison of Arrears for FYs 2013/14 and 2014/15. 6 Table 3 reveals that there were 115 reporting units (Ministries, Agencies, Referral Hospitals, and Embassies/Missions). For FY 2013/14, USH 1,232 billion in Arrears was reported, while the value was USH 1,208 billion for FY 2014/15. In other words, the stock of Arrears declined over the period by about USH 124 billion. Importantly, of the 115 units reporting, only 31 units reflected an increase in their stock of Arrears from FY 2013/14 to FY 2014/15. Notably, this is an annual analysis, while the African Department appeared to be concerned about quarterly increases in Arrears. The mission was unable to conduct an analysis of quarterly Arrears data.

Table 3.

Comparison of Arrears for FYs 2013/14 and 2014/15

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Source: MoFPED and Mission Team.

36. Authorities indicated that efforts are made each year to obtain records from MDAs concerning the stock of Arrears. The expectation is that, except for judicial rulings that are adverse to the GOU and that are linked to past events, there should be no increase in historical Arrear values. However, for reasons already mentioned, Arrears for the most recent year can arise. To reduce the stock of Arrears, the GOU sets aside funds in the budget each year to pay down Arrears.

Recommendation:

  • GOU should improve its accounting treatment of Arrears as Other accounts payable, and treat payment of Arrears as a transaction (reduction) in Other accounts payable.

IX. Data Quality Improvement Work Program

37. During an AFE – EAC Secretariat jointly-sponsored Regional GFS Workshop in November 2015 in Gisenyi, Rwanda, Ugandan representatives developed a DQIWP.7 The mission team made efforts to motivate the evolution of the DQIWP. For example, during one of the mission’s working sessions, a Uganda Bureau of Statistics staffer, who had attended the just-mentioned workshop, presented the DQIWP. However, Uganda’s GFS Technical Working Group (TWG) has not finalized the DQIWP, and efforts have not begun to implement it—these are efforts about which there was agreement during the November workshop. Authorities indicate that they have plans to fulfill the agreement.

38. The mission team made a concerted effort to emphasize Dimensions 2 (Methodological Soundness) and 3 (Accuracy and Reliability) of the DQIWP during the mission, and identified significant room for improvement.8 However, authorities must become convinced that there are considerable advantages to implementing the DQIWP and to reaping the associated benefits.

Recommendation:

  • Uganda’s GFS TWG should finalize and begin implementation of the DQIWP.

X. Status of Uganda’s GFSM 2014 Implementation Plan

39. As already noted, an important objective of the mission was to assess the status of Uganda’s GFSM 2014 implementation plan. Appendix IV provides an update on the status of the plan as of March 2016. Seven of the 15 plan components are completed, eight remain “in progress,” and the target dates have been breached for three of the components. Two of these breaches can be resolved by disseminating already compiled GFS. The mission recommends that the GFS TWG consult and reschedule a target date for providing Uganda’s fiscal year Budget in a GFSM 2014 framework.

40. In addition to the implementation plan’s status, it is important to assess the status of recommendations that have been formulated as part of recent TA mission reports and other documents associated with TA missions/visits. Appendix V provides an update on the status of these recommendations. Notably, 10 of the 16 recommendations reflect an “In progress” status.

Recommendation:

  • The GFS TWG should monitor the GFSM 2014 implementation plan and outstanding recommendations more closely, and develop a systematic plan for meeting plan target dates and for fulfilling recommendations.

XI. Uganda’s TA and Training Requirements

41. Uganda’s GFS and PSDS compilers do not appear to require any TA or training in the near term other than that already planned (Table 4). An exception may be that, as Uganda undertakes automation of its GFS source data collection, data providers (respondents) may require certain training to complete data collection forms accurately. However, the mission team believes that current GFS compilers are sufficiently trained, and should be able to conduct this training on their own behalf. Otherwise, the mission team urges authorities to ensure that all relevant compilers be permitted to participate in the TA and training opportunities that are cited in Table 4.

Table 4.

Uganda GFS TA and Training Opportunities through FY 2016/17

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Source: Mission Team.

XII. Conclusion

42. This report recounts mission findings and accomplishments. The fact that FY 2014/15 general government finance statistics could not be compiled during the mission was disappointing to the mission team, but the near complete compilation of the FY 2013/14 general government finance statistics was satisfying. In addition, the complete review and analysis of historical general government finance statistics for FYs 2006/7 through 2012/13 and of monthly BCG GFS for FY 2013/14 was a favorable outcome. Nevertheless, the mission team identified important challenges that Ugandan GFS compilers should meet head on.

43. A key challenge is automation of GFS source data collection, especially for EBUs and LGs. In fact, the compilation of general government finance statistics for FY 2014/15 was delayed mainly because of the labor-intensive and time-consuming manual processing procedures that are currently in place to compile GFS for EBUs and LGs. The mission team discussed this challenge with authorities and urged automation of the source data collection process first by data collection through electronic templates, and second by incorporating institutional units in these general government subsectors into IFMS.

44. Given that Uganda is behind the curve on meeting the data collection automation challenge (compared with Kenya and Tanzania), the mission team recommends that Uganda redouble its efforts to fulfill this aspect of its GFSM 2014 implementation plan. However, the mission team has no doubt that Uganda’s GFS compilers are equal to the challenges that lie ahead. At the same time, the mission team is concerned that there appears to be a buildup of TA mission recommendations that are not being resolved—something that the mission team adds to by providing 11 new recommendations in this report, which are repeated in their entirety in Box 1.

TA Report Recommendations

  • Conduct annual maintenance of, and promulgate widely, Uganda’s Public Sector Institutional Table because it can help ensure consistency across all of the nation’s macroeconomic statistics.

  • Automate the collection of source data for EBUs and LGs first by using data collection templates (annually and on a high-frequency basis), and second by ultimately incorporating these institutional units into the IFMS.

  • Authorities should validate the FY 2013/14 general government finance statistics and disseminate them to the IMF’s Statistics Department.

  • Authorities should finalize compilation of the FY 2014/15 general government finance statistics and disseminate them to the Statistics Department as soon as they are finalized.

  • Authorities should compile general government Statements of Sources and Uses of Cash for FYs 2013/14 and FY 2014/15 and disseminate them to the Statistics Department as soon as they are finalized.

  • Authorities should disseminate to the IMF’s Statistics and African Departments the high frequency GFS BCG data as soon as they are compiled.

  • Authorities should keep track of revenue collections in transit and in vaults and make adjustments to the monthly Statement of Operations to match Revenue transactions above the line with the change in Currency and deposits below the line.

  • Authorities should develop estimates of the float (i.e. the difference between expenditure commitments (accrual) and payments (cash)) and make adjustments to the monthly Statement of Operations to match above-the-line Expenditure transactions with below-the-line financing.

  • GOU should improve its accounting treatment of Arrears as Other accounts payable, and treat payment of Arrears as a transaction (reduction) in Other accounts payable.

  • Uganda’s GFS TWG should finalize and begin implementation of the DQIWP.

  • The GFS TWG should monitor the GFSM 2014 implementation plan and outstanding recommendations more closely, and develop a systematic plan for meeting plan target dates and for fulfilling recommendations.