Zambia
Technical Assistance Report-Report on Government Finance Statistics
Author: International Monetary Fund. Statistics Dept.
Publication Date:
20 Jul 2020
eISBN:
9781513550640
Language:
English
Keywords:
ISCR; CR; statement of operation; GFS statement; compilation file; GFS compilation; classification assistant; public finance; Government finance statistics; Business enterprises; Financial statements; Data collection; Civil society organizations; expenditure transaction; TA mission; GFS classification assistant; cashflow statement; GFS Multiperiod Classification Assistant
Download PDF (4.4 MB)

In response to a request from the authorities and as part of the United Kingdom’s Department for International Development (DFID) Enhanced Data Dissemination Initiative (EDDI) 2 project, a Government Finance Statistics (GFS) mission visited Lusaka, Zambia, during November 19–30, 2018. This was the third mission to Zambia under the DFID EDDI2 project, following the March 2016 and November 2017 missions. The mission worked essentially with staff at the Zambia Central Statistical Office (CSO) Public Finance Unit (PFU), but also had meetings with staff from the Ministry of Finance’s Accountant General, Budget, Investment and Debt Management, and Economic Management departments.

Abstract

In response to a request from the authorities and as part of the United Kingdom’s Department for International Development (DFID) Enhanced Data Dissemination Initiative (EDDI) 2 project, a Government Finance Statistics (GFS) mission visited Lusaka, Zambia, during November 19–30, 2018. This was the third mission to Zambia under the DFID EDDI2 project, following the March 2016 and November 2017 missions. The mission worked essentially with staff at the Zambia Central Statistical Office (CSO) Public Finance Unit (PFU), but also had meetings with staff from the Ministry of Finance’s Accountant General, Budget, Investment and Debt Management, and Economic Management departments.

Summary of Mission Outcomes and Priority Recommendations

1. In response to a request from the authorities and as part of the United Kingdom’s Department for International Development (DFID) Enhanced Data Dissemination Initiative (EDDI) 2 project, a Government Finance Statistics (GFS) mission visited Lusaka, Zambia, during November 19–30, 2018. This was the third mission to Zambia under the DFID EDDI2 project, following the March 2016 and November 2017 missions. The mission worked essentially with staff at the Zambia Central Statistical Office (CSO) Public Finance Unit (PFU), but also had meetings with staff from the Ministry of Finance’s Accountant General, Budget, Investment and Debt Management, and Economic Management departments.

2. The mission reviewed progress against recommendations of previous GFS technical assistance (TA) missions and further assisted with improving the quality of GFS currently compiled and disseminated. The mission found that owing to lack of resources at the CSO, both staff and financial, there had been challenges implementing recommendations from the previous GFS TA missions and very little progress was made. Out of 34 recommendations from previous missions only 3 were completed, 2 were partly completed, 13 were ongoing, and 18 were not done. The CSO was nevertheless able to compile GFS for the Budgetary Central Government (BCG) that it submitted for publication in the GFS Yearbook (GFSY). Working with staff at the CSO’s PFU, revised series for the BCG for the period 2007–2017 were compiled, and preliminary GFS for local governments, extrabudgetary units, and social security funds were also compiled.

3. Data accuracy, comprehensiveness and consistency across institutions requires further improvement to meaningfully inform policy decision making. Different sets of fiscal data are currently produced, for different purposes, at the Ministry of Finance, and the CSO, but while source data are essentially the same, aggregates are not consistent across. Some differences can be explained, but others cannot. Inaccuracy or incomprehensiveness of the data could adversely affect policy making and needs to be addressed, to ensure currently compiled and disseminated fiscal data are consistent and differences in aggregates in the different reports explained.

4. Broadening the coverage of GFS beyond what is currently compiled and disseminated would give a better sense of the true size of government operations. Budgetary entities undoubtedly represent the highest share of government operations in Zambia, but operations of EBUs and public corporations, not currently included in the scope of data are also not insignificant. Very preliminary data for levels of government other than budgetary entities showed that as of end 2016: local government entities (for a representative sample of local governments) had a surplus of a little less than 0.1 percent of GDP; social security funds also had a surplus of about 1.7 percent; while EBUs had a deficit of about 0.1 percent of GDP. Social security funds (as would be expected) held sizeable financial assets (about 7.1 percent of GDP). Data was also collected for a sample of public corporations (both financial and nonfinancial) that indicated combined assets of close to 60 percent of GDP (the Bank of Zambia was included). Collecting data for representative entities beyond budgetary entities would help having a better understanding of possible fiscal vulnerabilities and risks those entities could pose on fiscal policy.

5. There have been notable improvements with GFS compilation, but challenges remain. Institutional capabilities and processes for sustainable compilation of good quality fiscal data are weak. Resource constraints will likely not be overcome immediately, but some efficiency gains could be achieved through coordinated work. Strengthening coordination with data providing agencies and automating the existing manual data manipulation processes could hasten progress and not require a lot of additional resources—accessing source data directly from providing agencies rather than manual typing data from PDF documents is an example of efficiency gains that are within reach, at no additional cost.

6. To support progress in the above work areas, the mission recommended a detailed action plan with the following priority recommendations carrying particular weight to make headway in improving GFS. Further details on the priority recommendations and the related actions/milestones can be found in the action plan under Detailed Technical Assessment and Recommendations.

Table 1.

Zambia: Priority Recommendations

article image

Status of GFS Compilation and Dissemination

A. Implementation of Recent GFS TA Missions’ Recommendations

7. Progress with implementation of recommendations from recent GFS TA missions remains slow owing to the fact that several institutions are responsible for their implementation. The mission reviewed progress against the 34 recommendations of previous GFS TA missions in April 2016 and in November 2017. Seven of the 34 recommendations relate to the institutional operational capacities of CSO including training in GFS, while 27 relate to the methodologies in the compilation of GFS. Out of 34 recommendations three were completed, two were partly completed, 11 were ongoing (of which 3 have since been achieved), and 18 were not done (Appendix I).

8. Inadequate staffing and resources at the CSO’s Public Finance Unit (PFU) constitute a significant risk to improving the quality of GFS compilation. The mission understood that the lack of progress was primarily due to resource constraints, both staff, and financial resources. Strengthening staff resources, through an increase in staff number, and staff capacity, within available means, could help improve GFS compilation for a broader coverage than is currently done.

Recommended Actions:

  • Strengthen the PFU’s staffing, including through among others, an increase in the number of interns allocated to the unit; and temporary staff relocation from other units within the CSO during slow periods in those units.

  • Support CSO staff participation to regional and online courses on GFS and PSDS.

B. Institutional Coverage of the Public Sector

9. The mission reviewed the existing institutional table for the public sector. The mission revisited the public sector institutional table developed during previous missions and reclassified institutional units on the basis of new information available.

10. A revised preliminary public sector institutional table for Zambia identified 454 institutional units. The general government comprises 398 institutional units including 2 social security funds, 109 local government entities, and 287 central government entities. There are 56 public corporations, 50 of which are nonfinancial public corporations (Figure 1).

Figure 1.
Figure 1.

Zambia: Public Sector Institutional Table

Citation: IMF Staff Country Reports 2020, 220; 10.5089/9781513550640.002.A001

Source: Zambia Central Statistical Office and Mission.

11. Reclassification of institutional units pertain essentially to social insurance schemes. A distinction is made between social security schemes and employment related social insurance schemes (Box 1). Two social security schemes were identified: (i) the National Pension Scheme Authority (NAPSA), and; (ii) the Workers Compensation Fund Board (WCFB). The two other social insurance schemes: (i) the Public Service Pension Fund (PSPF), and; (ii) the Local Authorities Superannuation Fund (LASF) were identified to be employment related social insurance schemes serving a sub-set of the population comprising civil servants only, and were therefore reclassified within general government, but not as social security funds, as the mission understood both are unfunded defined benefits schemes. The Pension and Insurance Authority (PIA) was found to be a regulatory entity, and not presenting any of the characteristics of a social protection entity and was reclassified as a public financial corporation as it primarily is engaged in the regulation of pension and insurance entities.

Recommended Action:

  • Review and finalize the preliminary public sector institutional table and disseminate it afterwards; and ensure consistent use across all macroeconomic accounts.

Zambia: Social Insurance Schemes in Zambia

Social insurance schemes in Zambia comprise a multitude of entities (the Pension and Insurance Authority had 120 registered pension schemes/funds in January 2017), of which four are the most prominent: (i) the National Pension Scheme Authority (NAPSA), (ii) the Workers Compensation Fund Board (WCFB), (iii) the Public Service Pension Fund (PSPF), and (iv) the Local Authority Superannuation Fund (LASF).

NAPSA was established in February 2000 through the national pension scheme Act no.40 of 1996, following the closure of the Zambia National Provided Fund (ZNPF). NAPSA provides three types of benefits: retirement, invalidity, and survivors’ benefits. It also provides funeral grants to survivors of deceased members. Membership to the Scheme is compulsory for all employed persons. Membership to the Scheme covers all categories of employment for as long as a contract of service between the employer and the employee exists.

WCFB was established through Act no.10 of 1999 following the merger of the Workers Compensation Board that was responsible for accidents and scheduled diseases arising in the course of employment, and the Pneumoconiosis Compensation Board that was responsible for lung diseases caused by silica in the mines. The scheme provides for compensation of workers for disabilities suffered or diseases contracted during the course of employment and is mandatory for all employed persons. Being a contributory scheme providing social protection, with membership covering a large portion of the population, WCFB is classified as social security fund.

PSPF was established as a defined benefit scheme in 1997 through an Act of Parliament with the intention to consolidate the law relating to pensions and other benefits for persons employed in the public service. The Fund covers employees in the public service prior to 1 February 2000, including the teaching service and defense forces. With membership limited to certain employees, and being an unfunded defined benefit scheme, PSPF is classified as an employment related pension scheme, and classified within general government.

LASF was created under the Government Notice No.314 of 1954 and covers employees of the local authorities prior to 1st February 2000. The Fund is designed to provide income security in the event of retirement, permanent invalidity and survivorship. Membership to the LASF is limited to all councils (city, municipal, and district councils), ZESCO, the National Housing Authority, Lusaka water sewerage company, and Eastern water and sewerage company. With membership limited to certain employees, and being an unfunded defined benefit scheme, LASF is classified as an employment related pension scheme, and classified within general government.

Source: Zambia Ministry of Labor and Social Security, NAPSA, WCFB, PSPF, LASF.

C. GFS Compilation for the Budgetary Central Government

Source Data and Classifications of BCG GFS from the CSO

12. GFS for the Budgetary Central Government (BCG) are compiled by the CSO. The PFU at CSO uses the Ministry of Finance’s annual Financial Report (FR) for compiling annual BCG GFS. The FR are compiled annually by the Accountant General’s office, consistent with Article 211(1) of the Constitution of Zambia. The FR are consolidated financial statements that cover Ministries, Provinces, and Spending Agencies (MPSAs) included in the national budget and is based on financial statement prepared and submitted by the MPSAs to the Ministry of Finance. The FR includes statements of: (i) cash receipts and payments, (ii) budget execution, (iii) comparison of authorized provision and actual expenditure by MPSAs, and (iv) comparison of budget and actuals by functional classification. The FR are submitted to the Auditor General every year, within three months after each financial year. The FR includes notes and appendices that together with the statements constitute source data used by the PFU in compiling annual BCG GFS. The CSO does not compile high-frequency GFS for the BCG. GFS compiled by the PFU at the CSO are disseminated to the IMF’s Statistics Department (STA) for publication in the GFSY.

13. GFS compilation at the CSO requires improvements and better resource allocation. Staffing at the CSO’s PFU is insufficient, not adequately trained, but could also benefit from additional resources for data collection and processing. The manual processing of data from the Ministry of Finance is error prone and time consuming. A GFS compilation file exists, that is used to put together transactions on revenue, expenditure and financial assets and liabilities, and expenditure by Classification of Functions of Government (COFOG) based on budget entities’ cost centers. Data inputted into the file has to be manually processed in large Excel files (the expenditure file for 2017 had 120,000 rows of data), mapped to the GFSM 2014 classifications, and summarized before being copied into the GFS compilation file. The revenue source file’s presentation was change for 2017 requiring changes to the GFS compilation file mapping (there are now three separate series on revenue—for 2007 to 2010, for 2011 to 2016 and the latest of 2017). The current approach to GFS compilation is not sustainable and would need to be improved. A possible option to consider would be the automation of the manual mapping processing done at the CSO directly into IFMIS at the Ministry of Finance, to provide summarized reports that then the CSO could use for GFS compilation. Ultimately, only one set of fiscal data needs to be produced and used both by the Ministry of Finance and the CSO to serve their different purposes.

Source Data and Classifications of BCG GFS from the Ministry of Finance

14. The Ministry of Finance, through its Budget office also compiles fiscal statistics, but aggregates and balances differ from those of statistics compiled by the CSO. Data used to compile fiscal statistics at the Budget Office presumably comes from the same source as that used for compilation of FR, although may slightly differ owing to end of year adjustments that may be included in the data from FR and not necessarily reflected in the Budget Office data. Differences however, are significant and on all categories of revenue, expenditure and financing (Figure 1), that cannot be explained by end of year adjustments alone.

15. Differences in the institutional coverage in both sets of data, and the basis of recording of expenditure transactions could explain the differences but this remains to be investigated. It is important that the differences are investigated and explained. Focus should be put on explaining differences in the recording of taxes, grant revenue, interest expense, and transactions in financial asset and liabilities. A rather large transaction in financial assets, on the change in the government currency and deposits in 2017 for 18.3 billion Kwacha (7.5 percent of GDP) was included in the FR and reflected in the CSO’s BCG GFS. The mission understood that the transaction was the result of an adjustment to closing balances in 2016 that were erroneously overstated by the inclusion of the IMF account balances.1 No further details were provided, but it may be worth investigating the transaction given the size.

16. The Budget Office compiles both high-frequency and annual fiscal statistics, but classifications could be improved. Classifications in the GFS compiled are somehow aligned with the guidelines of the GFSM 2001, although the presentation of the statement of operations includes transactions in financial assets and some transactions in liabilities above the line. Financing, in the statement of operations is limited to transactions in liabilities pertaining to external and domestic borrowing. Further to that, the statement of operations includes transactions that, for consistency with the GFSM 2014 guidelines would be recorded differently. These transactions relate to:

  • Receipts of sales of crops from the strategic reserves classification—these receipts should not be recorded as revenue:

    • o When the crops are being purchased by government for storing in the strategic reserve, record an increase in inventories nonfinancial assets (goods for resale) and a decrease in cash (currency and deposits).

    • o When the crops are sold from the strategic reserves: record a decrease in inventories nonfinancial assets (goods for resale) and an increase in cash (currency and deposits).

  • Transactions in financial assets and liabilities above the line—these ought to be reclassified below the line, and not enter in the calculation of the fiscal balance (net lending/net borrowing).

  • The change in balances—in the statement of operations, as currently computed, is recorded above the line, and is used as a residual to equate transactions above the line, with transactions below the line (that it has to be reminded, are limited to a subset of transactions in liabilities). A more appropriate recording of transactions, that also allows consistency across macroeconomic accounts, would be to first record the change in balances (understood as the change in cash and deposits) below the line, as part of transactions in financial assets, but also to record as the change in cash, only amounts deemed so, that is, from data included in the Bank of Zambia’s Depository Corporation Survey (DCS) as the change in government deposits2 plus any cash holding not deposited in the banking system. Any residual, or difference between transactions above the line, and below the line, would be recorded as a statistical discrepancy, below the line.

  • Grants and other payments—as currently included in the statement of operations record transactions on various expense items on subsidies, grants, social benefits, other expense, and some transactions in assets and liabilities that may need to be recorded separately to clearly distinguish the true economic nature of each transaction. These include: the farmers’ input support program, food security pack, fuel payment arrears, ZESCO electricity subsidy. The bullets below discuss some of the items and appropriate classification.

  • Farmers’ Input Support Program (FISP) classification—receipts from repayments under the FISP program are recorded as revenue but should be reclassified. The mission understood that under the FISP, farmers receive subsidized agricultural inputs of which a portion is provided without expectation of repayment, while another portion is provided with some expectation of repayment. FISP spending is currently recorded under expense as “grants and other payments” when payments are made to farmers. When farmers repay the portion for which repayment is expected, the proceeds are currently recorded as “non-tax revenue”. A more appropriate way of recording FISP transactions would require distinguishing the portion for which repayment is expected from that which repayment is not expected first, then record each transaction separately as follows:

    • o For transactions where repayment is expected: FISP payments to eligible farmers would be recorded below the line as an acquisition of a financial asset in the form of a loan, with a corresponding transaction as a reduction in another form of financial asset in the form of currency and deposits (if the payment is made cash), or accounts payable (if not cash payment is made the moment the transaction is recorded, but there is expectation of payment subsequently). When farmers repay, reverse transactions are recorded, with a reduction in financial assets in the form of a loan, and an increase in another financial asset in the form of currency and deposits. It is important to keep records of amounts that need to be repaid, to inform the financial balance sheet of government, as these loans constitute financial assets of government.

    • o For transactions where repayment is not expected: FISP payments to eligible farmers would be recorded as another expense (current transfer not elsewhere classified) with a corresponding reduction in currency and deposits (if the payment is made in cash). Since no repayment would be expected, no other transaction would be recorded.

  • Food security pack classification—are currently recorded under “grants and other payments” but do not appear to be payments made to another level of government, but rather payments directly to households. These payments should therefore be reclassified either a social assistance benefits, if they are meant to cover specific social risks or alternatively as other expense—current transfers not elsewhere classified.

  • Fuel payment arrears classification—the mission understood that the stock of arrears for fuel payments were converted into a debt instrument, for which the servicing of the debt is recorded now under “grants and other payments”. First, the creation of the debt instrument ought to be recognized in the statement of operation the year, and month in which debt was issued in replacement of the arrears through an increase in debt securities below the line. Subsequent payments, in reduction of the debt incurred would be recorded as a reduction in debt securities, also below the line.

  • ZESCO electricity subsidy—are included as “grants and other payments” but ought to be recorded separately from grants, as subsidies.

  • Ordinary grants—may need checking to ensure there are no funds, labelled as grants, provided to public corporation. The preliminary list of public sector units produced during the mission provides an indication of all units of the public sector. Should there be amounts, within ordinary grants provided to entities regarded as public corporations in the list, they ought to be recorded as subsidy instead of grants, unless the funds are meant for recapitalization, in which case they would be classified as other expense (capital transfers) if the government does not expect any return on those funds; or as a financial asset either in the form of a loan (if there is a loan agreement and the corporation will repay the fund), or an equity (if government increases its shareholding in the corporation) if the government acquires an effective financial claim3 from the payment it is making to the corporation.

  • Social benefits classification—social benefits in the statement of operations include payments made to the pension fund that include grants to the pension fund; and funds meant for covering the financing gap of the pension fund. None of these transactions relate to social benefits as such and should be reclassified. The only transactions that ought to be recorded under social benefits, given available information4, would be limited to social assistance benefits. The reclassification however, would need to take into account the nature of the transaction involved:

    • o If the payments relate to actual social contributions the government as an employer is making on behalf of its employees, out of the current period wages and salaries, then these payments ought to be recorded under compensation of employees as social contributions. However, if these payments are not meant for the current period contributions, they should be classified elsewhere (see below).

    • o If the payments are transfers made to the pension fund, as another level of government entity, the payments ought to be recorded as grants to other levels of government. Also included as grants would be the payments made to cover the “financing gap” as these appear to be recurrent and not one-off payments.

  • On-lending to, and repayments of corporations—when government borrows and on-lends funds to a corporation (public or private), the borrowing is recorded first as an increase in loan liabilities and a corresponding increase in cash and then recorded as a decrease in cash and an increase in loan financial assets when the funds are on-lent to a corporation. When corporations repay government on the funds on-lent, repayment of interest is recorded as a revenue as property income (interest), and principal repayment is recorded as a decrease (negative) in loan financial assets. It appears that the current statement of operations does not fully capture all on-lending transactions.

  • Empowerment fund classification—the empowerment fund covers spending made in support for youth and gender led projects that the mission understood were loans meant to be repaid. For recording purposes, if there is a realistic expectation that the funds provided to eligible recipients under the empowerment fund schemes are going to be repaid, then they should be recorded as a loan financial asset (below the line, and not like what is currently done above the line). If the expectation is that those funds will not be repaid (which seems to be the case because there is no evidence of actual repayments), then they should be recorded as another expense (current transfers).

Recommended Actions:

  • Investigate the recording, and adjustment to cash and cash equivalents in the Ministry of Finance’s Financial reports for financial years 2015–2017 pertaining to overstatement of IMF account balances.

  • Investigate and address (or explain) differences in fiscal statistics from the Budget Office at the Ministry of Finance, and the CSO’s PFU with the aim to have consistent data being disseminated and used for policy purposes, and compilation of other macroeconomic statistics.

  • Improve classifications in the Budget Office’s statement of operations to align to the GFSM 2014.

D. GFS Compilation for Local Governments

Source Data and Coverage

17. There are no formal mechanisms for data collection for local governments in place at the CSO. Available information indicates a total of 109 institutional units, that may qualify as local government entities, that include provinces (10), city councils (5), municipal councils (13), and town councils (91). It is only starting during a previous GFS TA mission that the PFU at the CSO has started collecting data, for GFS compilation from local governments. No specific template exists for data collection and data is not always available in an electronic format. Staff from the CSO were nevertheless able to access data on revenue, and expenditure, from all the five city councils and all municipal councils. The data, some of which was received in a non-electronic format were manually entered into Excel, following what appears to be a standardized classification of revenue and expenditure transactions, although not used consistently across councils. Staff from the PFU ensured that data entry for the data received from the various local government entities is consistent across the entities, to allow easier aggregation. The data do not include stock positions, and no information is included on the change in cash and/or bank balances, although some transactions in financial assets and liabilities are included.

18. The Ministry of Finance is planning on starting to collect data from local governments. A new unit, the Intergovernmental Relations (IGR), was established at the Ministry of Finance, in August 2018 and will be expected to collect and compile quarterly data from local governments. Templates for data collection were developed, and assistance is being sought from GIZ to develop an application for planning and budgeting that would also allow automated data collection and compilation. As of end 2018, the unit had already received 22 reports, for the first quarter of 2018. The IGR is planning on starting to produce a “Yellow Book” (an activity based annual budget only currently produced at the central government level) for the local government starting in 2020. Reporting from the application, when it is completed, using data on the performance against the budget, from the “Yellow Book” would constitute a comprehensive and consistent data source for compilation of GFS for the local government going forward. Efforts to bring the project to fruition should be maintained.

Compilation of GFS Using Existing Data for Local Government

19. The mission compiled a partial GFS statement of operations using data currently available at the CSO. Using data that the PFU at the CSO had transcribed from reports collected from city councils and municipal councils on their revenue and expenditure transactions for the period covering 2015 to 2018, a partial statement of operations was produced, using the GFS Multiperiod Classification Assistant.

20. The data include transactions in financial assets and liabilities labelled as revenue and expenditure. There are on the revenue side of local government statements, transactions that relate to repayments on loan assets, and borrowing, that are reclassified respectively as transactions in financial assets and liabilities respectively. Similarly, on the expenditure side of the local government statements, loans assets disbursements, and repayment of payables are reclassified as transactions in financial assets and liabilities respectively.

21. Partial automation of compilation of local government GFS may need to be considered going forward. The manual process of transcribing data into Excel is time consuming and error prone and may not be the recommended option to collecting data from local governments for GFS compilation purposes going forward. As an initial step to consider, would be to have local governments filling a designated template, that is then submitted electronically to the CSO for aggregation. Subsequently, and as is currently considered in other domains at the CSO for data collection, a data portal with the template embedded could be used to collecting data from local governments.

22. The data collected and compiled for the period 2015 to 2018 may need to be checked to fill gaps, then validated and disseminated. While available data do not indicate changes in the stock of cash, it could be assumed that part (or all) of the difference between transactions in revenue and expenditure and financing other than the change in cash does constitute the change in cash and deposits at the local government.

23. Although not representative of all the local government, preliminary GFS indicate aggregated positive fiscal balances over the period 2015–2018 (Figure 3). Total revenue averaged about 824 million Kwacha a year (about 0.36 percent of GDP) over the period for all the local government entities, while expenditure averaged 705 million Kwacha a year (about 0.31 percent of GDP), resulting in a net lending (surplus) on average a year of 118 million Kwacha (about 0.05 percent of GDP). These fiscal aggregate, reflect the largest local government entities in Zambia, and although not comprehensive, indicate the little significance of local governments in Zambia’s financial operations.

Figure 2.
Figure 2.

Zambia: Differences in CSO and MOF GFS for BCG

Citation: IMF Staff Country Reports 2020, 220; 10.5089/9781513550640.002.A001

Source: Ministry of Finance and Zambia Central Statistical Office
Figure 3.
Figure 3.

Zambia: Budgetary Central Government GFS

Citation: IMF Staff Country Reports 2020, 220; 10.5089/9781513550640.002.A001

Source: Zambia Central Statistical Office.
Recommended Actions:

  • Check and validate the preliminary data on local governments for 2015–2018, collect and compiled data for the missing local government entities and start disseminating the data upon validation.

  • Establish mechanisms to automate data collection from local governments, starting initially with standardized data collection templates, and then in time, with data collection portals.

E. GFS Compilation for Social Security Funds

Source Data and Coverage

24. The mission identified two social security funds. NAPSA and WCFB were both identified as social security funds (Box 1). The PFU at the CSO collected financial statements, in print form, for the social security funds that it transcribed in Excel for use in the compilation of GFS. WCFB’s available data cover the period 2013–2016 while NAPSA data cover the period 2014–2017. The mission understood that prior to the closure of the Zambia National Provident Fund (ZNPF) and its merger with NAPSA, separate financial statements were available for both ZNPF and NAPSA. It is only starting with fiscal year 2016 that consolidated data are available for the defunct ZNPF and NAPSA. Data for the period 2014–2017 present aggregates for ZNPF and NAPSA separately. Data do not indicate, transactions between the two schemes for that period, that may warrant consolidation, but that remains to be confirmed. The mission therefore aggregated data for ZNPF and NAPSA for the years 2014 and 2015.

Compilation of GFS from Financial Statements for Social Security Funds

25. Available data are quite comprehensive for the compilation of GFS for the social security funds subsector. The mission used the data in Excel transcribed by staff from the PFU at the CSO to map data from the financial statements into GFS. The main challenge with using manually entered data, from paper files, is the possible errors in the transcriptions, especially on the signs of entries in the financial statements and particularly the statement of cashflows. The three main statements from the financial statements of both NAPSA and WCFB, that is, (i) the statement of comprehensive income, (ii) the statement of financial position, and (iii) the statement of cashflows were transcribed into Excel, but notes associated to the statements were not.

26. A GFS classification assistant was used to compile GFS statements for the social security funds subsector. Data from NAPSA and WCFB were populated into a GFS Multiperiod Classification Assistant, making adjustments to signs in the statement of comprehensive income (claims and pensions paid are recorded with a negative sign in financial statements but reverted to a positive sign to record an expense transaction) and in the statement of cashflows (relying primarily on the accuracy of transcription into Excel on the notation of increases/(decreases) to determine the sign and the recording as a revenue or expense item). General guidance is provided in Appendix III on the compilation of GFS from financial statements.

27. GFS statements for the social security funds subsector presents a statistical discrepancy. Preliminary GFS statement of operations compiled include a statistical discrepancy that may be owed to possible omissions, wrong sign assignment, or error in the manual data transcription. The discrepancy is not large, relative to net lending/net borrowing (5.3 percent of net lending/net borrowing on average between 2015–2017). The integrated stocks and flows also show a minor “residual” (or the change in stock positions that is not explained by transactions and other economic flows). The discrepancies will need to be further investigated and reduced or eliminated, by checking conformity of data transcribed into Excel with the print statements, and details included in the notes to the financial statements.

28. Preliminary GFS indicate aggregate positive fiscal balances over the period 2014–2017 (Figure 4). The WCFB had a net borrowing (deficit), although small relative to the large net lending of NAPSA (NAPSA’s assets in 2016 were seven times those of the WCFB) that contributed to the average surplus in the social security funds subsector of 3.3 billion Kwacha over the period 2015–2017 (about 1.6 percent of GDP). Total assets of the social security funds at end 2017 amounted to roughly 23 billion Kwacha (about 9.3 percent of GDP) of which the largest component were financial assets (about 8.2 percent of GDP) that are mostly represented by debt securities. Debt liabilities of the social security funds at end 2017 amounted to 535 million Kwacha (about 0.2 percent of GDP) that was entirely made of payables. No details are available on the estimate of net implicit obligations for future social security benefits from available data but would presumably exist in some form from financial statements or actuarial studies performed by either of the social security funds.

Figure 4.
Figure 4.

Zambia: Local Government GFS

Citation: IMF Staff Country Reports 2020, 220; 10.5089/9781513550640.002.A001

Source: Zambia Central Statistical Office.
Recommended Action:

  • Investigate the source of the statistical discrepancy in the GFS statement of operations and the residual from the integrated balance sheet for the social security funds subsector and reduce or eliminate the discrepancy/residual.

F. GFS Compilation for Extrabudgetary Units

Source Data and Coverage

29. Financial statements for only a select number of EBUs were available for compilation of GFS for the subsector. The PFU collected print and electronic PDF copies of financial statements for about 29 institutional units that have been tentatively classified as EBUs in the preliminary institutional table. There may be (upon confirmation after review of the institutional table) up to 224 EBUs. Data available represents 13 percent of all possible EBUs and only accounts for 10.5 percent of all grants from BCG to EBUs (measured by comparing total grants revenue of the 29 institutional units with available data, and grant expense from the BCG). A closer look at the financial statements of some of the 29 institutional units indicates however, that at least up to 8 could be, on the basis of their funding structure, reclassified as BCG entities. A more comprehensive coverage of the EBUs subsector requires data collection for additional entities, with emphasis on the most representative, based on their size.

Compilation of GFS from Financial Statements for EBUs

30. Financial statements of EBUs are in different forms and shapes, but nevertheless include data that can be used to compile GFS for the subsector. Most of the entities for which data was collected had financial statements that included an income statement, a statement of financial position, and a statement of cashflows, although for some of the entities, the accounts are not reconcilable. It may also be possible that owing to manual data entry from paper based financial statements to Excel, there may have been transcription errors.

31. Data available span from 2011 to 2017 but not consistently for all entities. Only two of the entities: PSPF and LASF have the longest continuous data availability, covering the period 2011–2016. The other entities have data for periods ranging from one year to four years continuously. The inclusion of data for one large entity for only one year distorts the trend and appears as if something material happened during the year, while that is only driven by the inclusion of the operations of one entity. This is the case of the National Road Fund Agency (NRFA), for which data is only available for 2017 but affects all aggregates for the EBUs subsector for that year (Figure 5).

Figure 5.
Figure 5.

Zambia: Social Security Funds GFS

Citation: IMF Staff Country Reports 2020, 220; 10.5089/9781513550640.002.A001

Source: Zambia Central Statistical Office.
Figure 6.
Figure 6.

Zambia: Extrabudgetary Units GFS

Citation: IMF Staff Country Reports 2020, 220; 10.5089/9781513550640.002.A001

Source: Zambia Central Statistical Office.

32. Very preliminary GFS for EBUs have high statistical discrepancies and need to be further improved. Having a better understanding of the extent of EBUs operations would require first broadening the coverage to include at least all the most representative entities, but also collecting data consistently over a couple of years, while ensuring that the data entry reflects as accurately as possible the content of financial statements collected. Establishing mechanisms to collect data on EBUs on a more regular basis could go a long way in helping to improve the coverage and comprehensiveness of EBU’s data available for GFS compilation. Although data is incomplete, has statistical discrepancies, and may suffer from inaccuracies due to manual data collection and processing, it nevertheless points to the significance of the subsector, and the need to pay a closer look at financial operations of EBUs. Just for the year 2017, with data available for only 10 entities, preliminary revenue amounted to about 32.6 billion Kwacha (about 13.2 percent of GDP), and expenditure were about 42.6 billion (about 17.3 percent of GDP), resulting in a net borrowing (deficit) of about 10 billion Kwacha (about 4.1 percent of GDP).

Recommended Actions:

  • Review and validate the preliminary data for EBUs for the 2011–2017 period and collect additional data for the missing most representative EBUs (based on relative size).

  • Establish mechanisms to collect data from EBUs on a more regular basis.

G. GFS Compilation for General Government

33. Compilation of general government GFS can be envisaged on an experimental basis in the very short run. There are at least data on transactions in revenue, expense, and assets and liabilities (even partially) for all subsectors of the general government. While data is not very representative for EBUs, an attempt can be made, on an experimental basis, to consolidate all the available subsectors (BCG, EBU, LG, SSF) into general government GFS. Consolidation would not be perfect as data is not comprehensive in the first place but would pave the way on improvements required going forward to arriving at consolidated data. General guidance is provided in Appendix IV on consolidation of general government GFS.

H. GFS Compilation for Public Corporations

34. The PFU collected financial statements of public financial and nonfinancial corporations that could be used for compiling GFS for the public sector. Financial statements were collected for a total of 22 public nonfinancial corporations out of possible 50 (Table 2) and all known 6 public financial corporations (Table 3) for the period covering 2010–2017. The combined assets of public nonfinancial corporations financial statements are available amounted to about 75.7 billion Kwacha (about 34.9 percent of GDP) while it was about 50.7 billion Kwacha (about 23.4 percent of GDP) for the public financial corporations.

Table 2.

Zambia: Financial Statements of Public Nonfinancial Corporations Availability

article image
Source: CSO’s Public Finance Unit.
Table 3.

Zambia: Financial Statements of Public Financial Corporations Availability

article image
Source: CSO’s Public Finance Unit.

35. Collection of the financial statements of public corporations is a first step that now needs to be followed with compilation of GFS for those entities. An approach similar to that used with the financial statements of EBUs may need to be used to compile GFS for public corporations. Data from the financial statements, where available, on the income statements, statements of financial position, and cashflow statements were included in a GFS Multiperiod Classification Assistant but have not yet been mapped to GFS categories. Priority may be given to the largest corporations (e.g. The Zambia Electricity Supply Corporation (ZESCO)) when the first attempt is made in compiling GFS for public corporations, while data is also collected at the same time for the remaining public nonfinancial corporations for which data is currently not available.

Recommended Actions:

  • Review and validate data entry from available financial statements of public corporations.

  • Collect financial statements for missing public nonfinancial corporations, and for missing years, for those available.

  • Establish mechanism to collect data from public corporations on a more regular basis.

I. Data Dissemination

36. Data is now disseminated to the GFSY on a regular basis. Series on annual GFS compiled during the previous mission and updated during this mission were disseminated for inclusion in the GFSY. The data only covers the budgetary central government, and only includes debt liabilities data on stock positions. However, transactions only cover the budgetary central government, and stock positions are limited to debt liabilities. No high-frequency GFS are currently disseminated. As data coverage improves, with the availability of GFS for other subsectors of the general government, and consolidation is done, dissemination of data for a broader coverage of government may also need to be considered.

37. Data dissemination on the National Summary Data Page (NSDP) has lapsed. The last available data on government operations and debt posted on the NSDP dates back to 2016. There have been no updates since. Efforts would be required to resume dissemination on the NSDP, and the Statistics Department of the IMF remains available to provide assistance in support of resumption of data dissemination.

Recommended Actions:

  • Start disseminating GFS for broader government coverage (i.e. Central Government, and General Government) as consolidated data becomes available.

  • Resume data dissemination on the NSDP.

J. Follow-Up

38. A follow up GFS TA mission is tentatively scheduled towards the end of 2019 to further assist with improvements in GFS compilation and dissemination. The mission would aim to assist with improving data compiled so far for all subsectors of the general government, and initiate consolidation first for the BCG and EBUs to arrive at preliminary central government GFS, but also explore possibility to consolidate the central government data with that of local governments. Investigating and explaining the differences in BCG data between the CSO and the Ministry of Finance and ensuring that data compiled for EBUs for the 2011–2017 period have been validated and completed with additional data for the most significant ones would help make faster progress during the follow up mission.

Detailed Technical Assessment and Recommendations

article image
article image

A. Officials Met During the Mission

article image
article image

Appendix I. Status of Implementation of Previous Technical Assistance Mission Recommendations

article image
article image
article image
article image
Note:

Constitutes a priority recommendation

Also included in the action plan for implementing the GFSM 2014.

Appendix II. Terms of Reference for the Government Finance Statistics Technical Working Group

Background

1. The Central Statistical Office (CSO) is mandated, through the provisions of the Statistics Act (cap 127 of the laws of Zambia) to collect and compile statistics for all macroeconomic sectors; that is, national accounts and price statistics, external sector statistics, government finance statistics, and monetary and financial sector statistics; in order to inform policy.

2. The CSO has, in accordance with that mandate, been collecting and compiling Government Finance Statistics (GFS), that it disseminates to the International Monetary Fund (IMF) Statistics Department for worldwide dissemination. The GFS collected, are also used in the compilation of other macroeconomic statistics, including, and not limited to national accounts (GDP).

3. Recent technical assistance missions to the CSO have revealed deficiencies in the coverage and comprehensiveness of available GFS that undermine the quality of the data, but also that of other sectors for which GFS is an input. The missions made recommendations aiming at improving the quality of GFS in order to better inform Zambia’s policy makers.

4. It is in this regard, that the CSO, is setting up a technical working group, comprising all data providing entities, to steer the process of improving the quality, comprehensiveness, and coverage of GFS currently compiled and disseminated by the CSO.

Current Challenges

5. Data currently collected has gaps, that require immediate attention for improved quality. The deficiencies in the current available GFS relate to the following areas:

  • Data coverage—the Public sector is understood to comprise different entities, performing various activities, that are controlled by government. This include entities involved in non-market activities (namely general government entities, including budgetary entities, local governments, and autonomous central government entities), and entities involved in the provision of goods and services on a market basis (namely public corporations, or parastatals). To have a comprehensive understanding of the extent of government activities requires capturing all the operations of all those entities. At present however, data compiled is limited to the narrowest coverage of government, comprising only budgetary entities, excluding therefore all autonomous or extra budgetary central government entities, local governments, social security funds, and public corporations. Expanding the coverage of data currently compiled, through the identification of source data, and assigning responsibility for the collection and compilation of such data, requires a concerted effort that would involve not just the CSO, but also other government entities.

  • Data comprehensiveness—to improve the quality of data currently compiled requires not only to have an understanding of what the transactions of all government entities are, but also, what their stock positions are, that is, how much assets they have, and how much they owe (liabilities) to other economic actors. A better understanding of the assets and liabilities position of government is extremely important for policy making, to know what government’s net worth is, and its trends, and how government fiscal policy affects its financial position. No data is currently collected on a comprehensive manner, to show what the assets and liabilities of government are, thereby hampering proper monitoring of fiscal positions.

  • Data classifications—international best practices recommend classifications of fiscal operations in line with the Government Finance Statistics Manual (GFSM) 2014 and the Public Sector Debt Statistics Guide (PSDSG) 2013, both aligned with the System of National Accounts (SNA) 2008, governing other macroeconomic statistical systems. While data currently compiled has attempted to broadly align to the classifications in the GFSM 2014 and the PSDSG 2013, gaps remains however, especially on classification of transactions and debt stock, leading to differences in classifications used across government, and sometimes inconsistencies in datasets produced by the Government of Zambia (particularly on differences between the Ministry of Finance and CSO data).

  • Data timeliness and frequency—only annual GFS has been compiled and disseminated by the CSO to date, with a lag of more than 11 months after the end of the reporting period. No monthly or quarterly data is currently disseminated, although some data is compiled, solely for use in the compilation of national accounts. Old data, that is available infrequently is of little use to policy makers, that require up-to date data, that is available frequently. Compilation of quarterly GFS is therefore necessary going forward, to inform decision making, in addition to being used as an input in the compilation of other macroeconomic statistics also compiled on a quarterly basis (e.g. quarterly GDP).

Objectives of the GFS Technical Working Group

6. In view of the daunting challenges faced in compilation of GFS and debt statistics at the CSO, it is of paramount importance that concerted effort by data producers, and data users is made, to address the issues identified jointly.

7. The technical working group therefore aims to:

  • 1. Foster and support initiatives aimed at promoting efficiency in the production of timely government finance statistics across the public-sector units;

  • 2. Promote data sharing among institutions to enhance compilation of government finance statistics;

  • 3. Harmonising government finance statistics input data emanating from different institutions to avoid inconsistencies;

  • 4. Facilitate institutional (interagency) coordination in the production of government finance statistics;

  • 5. Check for completeness of scope and coverage of government finance data in Zambia;

  • 6. Ensure comprehensive coverage of government finance statistics data for rebasing of national accounts for the year 2017;

  • 7. To help validate the institutions register (i.e. public sector institutional table) covered under government finance statistics.

Institutions on the Technical Committee

  • 1. Central Statistical Office—Economic and Financial Statistics Division

  • 2. Ministry of Finance—Budget—Budget Execution

  • 3. Ministry of Finance—Budget—Intergovernmental Fiscal Relations

  • 4. Ministry of Finance—Economic Management and Finance

  • 5. Ministry of Finance—Investment and Debt Management

  • 6. Accountant General—Local Government Unit

  • 7. Accountant General—Revenue

  • 8. Accountant General—Expenditure

  • 9. Accountant General—Asset Management

  • 10. Office of the Auditor General—Public Debt and Investment

  • 11. Industrial Development Corporation

  • 12. Ministry of Local Government

  • 13. Lusaka City Council

  • 14. Bank of Zambia

  • 15. National Assembly

  • 16. Pensions and Insurance Authority

  • 17. Local Authorities Superannuation Fund

  • 18. NAPSA

  • 19. Public Service Pensions Fund

Appendix III. Compilation of GFS from Financial Statements1

1. The main source data for budgetary central government are mainly accounting records or budget execution data. However, for extra-budgetary units/entities, social security funds, public corporations, and local governments in some cases, the main source data are likely to be financial statements. This appendix provides summary guidelines for the compilation of GFS from financial statements.

2. The financial statements to be used are the income statement, balance sheet, and cash flow statement. These statements will usually have been prepared in accordance to private sector accounting rules and follow a noncash basis of recording. Thus, the statements need to be adjusted to conform to the guidelines of the GFSM 2014.

3. In general terms, the process involves preparing bridge tables and derivation tables, and then using them to convert the source data from the national presentation to the GFSM 2014 presentation.

4. More specifically, the steps to follow to compile GFS from financial statements are (a) prepare bridge tables for the income statement, balance sheet, and cash flow statement; (b) calculate the changes between the closing and opening balance sheet values for each category of assets and liabilities; (c) prepare derivation tables for the major GFS aggregates; (d) compile GFSM 2014 detail tables and summary statements; and (e) verify the accuracy of the process.

5. Preparation of the bridge tables requires classifying all items in the financial statements according to the GFSM 2014 classifications. All flows that are not transactions should be identified and excluded from revenue, expense, and transactions in assets and liabilities. These flows are called other economic flows and comprise price changes (revaluations) and other changes in the volume of assets and liabilities. In the income statement these flows are typically called gains/losses from sales of assets, foreign exchange rate gains/losses, impairment of assets/losses, revaluations, provisions, and allowances.

6. The information on the transactions in assets and liabilities for a given period is obtained in general from changes in balance sheet (stock) values. More specifically, the differences between the closing and opening balance sheet values have to be calculated, and then adjusted to remove other economic flows. The information on stocks of assets and liabilities should be calculated for many assets as the balance sheet value of the asset minus accumulated depreciation, minus depreciation for the current accounting period. While for other assets it should be calculated as the balance sheet value of the asset minus allowances for impairment or doubtful accounts.

7. Preparation of the derivation tables and bridge tables requires making prior adjustments to the financial statements to conform to GFSM 2014 classifications. Financial statements frequently include under revenue and expense items that the GFSM 2014 classifications include elsewhere. Common examples are: (a) the disposals and acquisitions of nonfinancial assets, which the GFSM 2014 classifies as transactions in nonfinancial assets; (b) loan disbursements and repayments, which the GFSM 2014 classifies as transactions in financial assets; and (c) profits and losses in the sale of assets, which the GFSM 2014 classifies as other economic flows. Once the necessary derivation tables and bridge tables have been prepared they can be used to compile GFS for the various subsectors (extrabudgetary units, local governments) and sectors (general government).

8. Several actions can be taken to verify the accuracy of the compilation process. First, the values of the major GFS aggregates should correspond to the values calculated in the derivation tables. This action normally involves iteration between the bridge tables, derivation tables, and detail tables/summary statements. Second, the value for net lending/borrowing should be the same whether calculated as revenue minus expense minus transactions in nonfinancial assets, or as net acquisitions of financial assets minus net incurrence of liabilities.

In practice, there is often a difference, which should be recorded as a statistical discrepancy in a separate line. Third, the values for each category of assets and liabilities in the closing balance sheet should be equal to their opening balance sheet value, plus transactions and other economic flows during the period. Fourth, the net change in the financial asset Currency and deposits in the Statement of Government Operations should be equal to the net change in the stock of cash in the Statement of Sources and Uses of Cash (and the institution’s cash flow statement).

9. There are two items that will appear regularly in financial statements that require guidance on how to address: provisions and depreciation. Provisions are not an item in the GFS system, which does not consider them liabilities, but only a setting aside of funds for a specific purpose. The flow is recorded only when the actual loss is incurred. Depreciation is also not an item in the GFS system, which uses instead the concept of consumption of fixed capital. Excluding the items for provisions and depreciation of assets when compiling GFS from financial statements would introduce discrepancies, thereby making the task more difficult. It is recommended that the following rules of thumb be used instead: (a) treat provisions as a proxy for a loss, and (b) treat depreciation as a proxy for consumption of fixed capital. In other words, treat provisions as another change in the volume of assets, and depreciation as an expense.

10. A caveat regarding consumption of fixed capital. Compilers should always try first to obtain figures for this item from the entity responsible for compiling national accounts. It is possible that figures would be available quarterly and annually for general government and its subsectors, and perhaps also for public corporations. Only to the extent that these figures are not available should depreciation be used as a proxy for consumption of fixed capital. Also, depreciation is likely to be a good proxy if assets are valued at fair market prices, but a poor proxy if assets are valued at historical costs.

11. A note of caution concerning the compilation of GFS from financial statements. One of the more challenging aspects of the compilation task is to get the signs right when calculating the major GFS aggregates and balancing items. For example, the financial statements may include under revenue an item with a negative sign, which the GFS system treats as an expense. In the compilation process this item would be moved to expense with a positive sign. Another example concerns holding gains and losses, which can appear with different signs depending on where they are presented in the financial statements. A further example concerns financing items. In the GFSM 1986 financing is shown with a sign opposite the overall deficit/surplus, whereas in the GFSM 2014 it is shown with the same sign as the cash surplus/deficit. Briefly stated, keeping track of the signs can be challenging, and getting the signs wrong leads to discrepancies. Therefore, when compiling GFS from financial statements close attention has to be paid to how the item affects a certain aggregate or balancing item to get the signs right.

Appendix IV. Consolidation of General Government GFS1

1. When GFS have been compiled for all individual subsectors of the general government (public) sector, these statistics must be aggregated and consolidated. Aggregation is the simple addition of all data categories across subsectors. Consolidation is a method of presenting statistics for a set of units grouped together as if they constituted a single unit, which involves the elimination of all transactions and reciprocal stock positions between units in the subsector or sector being consolidated. Consolidation is normally the final step in organizing and presenting government data following the accounting rules of the GFSM 2014 system. The main reason for presenting GFS in a consolidated manner is because it provides a more effective way of assessing the overall impact of government operations on the total economy, or the sustainability of government operations; in other words, because consolidation heightens the analytical usefulness of the statistics.

Purpose of Consolidation

2. Consolidation eliminates double counting of transactions or stocks among units being consolidated, thereby producing aggregates not affected by internal interactions. At identical levels of activity, without consolidation, a country that employs a unified or centralized budgetary mechanism to carry out transactions would show smaller unconsolidated aggregates than a country that conducts the same level of activity but uses a decentralized mechanism to channel funds from the budget (Table 2).

3. Two countries, A and B, have the same values for revenue, expense and the gross operating balance at the central government level. However, they channel their resources very differently. The central government of country A spends 110 directly and transfers 10 to its local governments, which spend the whole amount; whereas the central government of country B spends 30 directly and transfers 90 to its local governments, which spend the whole amount. If we now compare in the table both countries at the general government level, we see that simply aggregating transactions for central government and local governments shows country B to have significantly higher revenue and expense than country A. However, if we add the figures after consolidation (i.e., after the elimination of internal transactions) then both countries have the same aggregates of revenue and expense at the general government level. We also notice that the Gross Operating Balance (GOB) of the general government is unaffected by consolidation.

Table 1.

Zambia: Illustration of Unconsolidated Versus Consolidated Data

article image
GOB: Gross Operating Balance

4. The main impact of consolidation is on the magnitude of aggregates, as illustrated above. Consolidation adjustments do not have an impact on the balancing items in the GFS system, as the consolidation process is symmetric within a given table or statement (set of accounts), again as illustrated above. Consolidation takes place both within a particular subsector (intra-governmental) and between subsectors (inter-governmental) that belong to a given sector. Therefore, intra-governmental consolidation always takes place when compiling GFS for any given subsector, whereas inter-governmental consolidation only takes place when compiling GFS for a sector that groups together more than one subsector. Typical sectors compiled where inter-governmental consolidation takes place include the central government, general government, nonfinancial public sector, and public sector. Intra-governmental consolidation within a particular subsector is always done before any inter-governmental consolidation.

Key Items to Focus on Consolidation

5. Proper consolidation depends on a thorough review of the accounts to be consolidated to identify internal transactions and stockholdings. The goal is not perfect consolidation, but rather to eliminate—in a consistent manner—transactions and positions that have a significant effect on the final aggregates. Where a review of the accounts reveals that there are small transactions that may be difficult to fully identify, resources should not be devoted to identifying these transactions and their magnitudes. Generally, it is recommended that for the consolidation of flows of the central government and general government sectors priority be given to identifying three potential items for elimination through consolidation: transfers between government units, transactions in financial assets and liabilities, and interest income/expense. Only in cases where intergovernmental taxes and purchases of goods and services are known to be large, should efforts be made to identify and eliminate through consolidation these transactions. For stocks, priority should be given to identifying two items: loans, and debt securities.

6. For many countries, the largest class of intra- and inter-governmental transactions eligible for consolidation relates to various types of transfer payments. These may be current and capital grants between levels of government, transfers within institutional units or transfers among institutional units. Central governments frequently make grants to lower levels of government or to other institutional units (for example, universities, hospitals, and nonprofit institutions) at the central government level. These transfers are generally easy to identify and should all be eliminated through consolidation. For social security funds, general transfers between subsectors should be consolidated. However, direct payments by government as an employer to social security schemes are never consolidated. These payments are always shown as if paid to employees who, in turn, make the contributions to social security schemes, and are treated as part of compensation of employees.

7. There are many types of financial transactions among government units. Governments may make loans to other governments for policy and other purposes, and government units may acquire the liabilities of other government units for liquidity and other purposes. All direct loans between government units should be eliminated through consolidation, and all acquisitions of other governments’ securities in direct transactions should also be eliminated. Government debt instruments acquired on secondary markets should not be consolidated in transactions data, as these transactions take place with nongovernmental units. However, these acquisitions should be consolidated in balance sheet or debt statistics.

8. Intra- and inter-governmental holdings of financial assets and liabilities, and therefore interest payments, are very common. Interest income from and expense to other government units is generally easy to identify in the accounts and should always be subject to consolidation. Concerning stocks, consolidation is necessary in the presentation of financial assets and liabilities for a government’s balance sheet. Only claims on units outside the government subsector or sector to be consolidated and liabilities to outside units should remain on the consolidated balance sheet. In other words, all reciprocal creditor-debtor relationships within the units being consolidated should be eliminated, but priority should be given to those related to loans and debt securities.

9. All transactions that are to be consolidated should preferably be identified in the accounting codes for transactions, with the counterparty of the transaction also clearly identified. If such counterpart identification is not currently included in accounting codes, this should be a priority when the chart of accounts is revised. In general, this procedure facilitates the consolidation process and, in particular, its automation.

Rules of Thumb for Consolidation

10. In principle, when a transaction to be eliminated through consolidation is identified (e.g., a grant from the central government to the local government), the corresponding receipt should be found in the accounts of the counterparty (in this case the local government). However, when the counterparts’ accounts are reviewed, there may be no record of the grant, or the grant may be credited in a different period, or the grant receivable may have a different value from the grant payable, or it may be classified as something other than a grant. There are many reasons for such discrepancies (timing differences, classification differences, accounting discrepancies, valuation differences, etc.). Addressing these discrepancies not only promotes proper consolidation, but also improves the overall quality of the data.

11. A practical way to address discrepancies when consolidating data is to use the following rules of thumb:

  • The “one-side” rule of thumb. If there is convincing evidence from one of the parties that a transaction took place, it can be imputed to the other side, even in the absence of the counterpart records. When such an adjustment is made in the data for a unit where the transactions cannot be directly identified, the records for that unit need to be properly modified.

  • The “top-down” rule of thumb. Often, budgetary accounts, or central government accounts as a whole, are more complete, timely, detailed, and accurate than, for example, the local government accounts (or even extra-budgetary accounts). When there is clear evidence that the central government made a transfer (or any other transaction) to a local government, the transaction, its timing, and its value can be imputed to the local government. Similarly, one can often rely on the originator of a transaction to have more reliable accounting records.

  • The “creditor is right” rule of thumb. For transactions in financial assets and liabilities, normally the creditor can be expected to maintain the most reliable records. For loans, the creditor unit usually maintains the most complete records, although in some cases the debtor unit may be equally reliable. For securities, especially bearer instruments, only the creditor may have the information needed for consolidation. For example, when a central government issues bearer securities, some may be acquired by local governments, and the central government may have no direct information on who is holding the securities, especially if they can be acquired on secondary markets. It is, therefore, necessary to rely on the creditor records of the local governments.

12. Judgment and the cost/benefit rule must always be applied during consolidation, the effort and cost to identify an amount to be consolidated should be directly proportional to the expected amount and its impact on the aggregates.

13. An effective tool to use during the consolidation process is a table that presents both parties to the flows or stocks and shows the amounts each party has recorded for each item to be consolidated. Then the rules of thumb can be applied to reach consistency on the amounts between both parties, while at the same time keeping the balancing items unchanged. Applying the rules of thumb often leads to making corrections to the accounts of one or even both parties, thereby modifying the values of balancing items. However, these corrections are a benefit of the consolidation process, and not a result of the consolidation itself, which is always symmetric. In other words, the consolidation takes place after the amounts have been reconciled and involves eliminating the same amount for both parties.

1

Note 3 in the Ministry of Finance’s 2017 Financial Report indicated that the closing balance for 2016 was erroneously overstated by the inclusion of the IMF account balances. However, the closing balance in the 2015 Financial Report (17.35 billion Kwacha) was not substantially different from the unadjusted closing balance in the 2016 Financial Report (17.28 billion Kwacha) which does not support the explanation in the note to the 2017 FR.

2

Care should be exercised to ensure that institutional coverage in the DCS is consistent with that of fiscal statistics, and in this case, the institutional coverage is limited to the budgetary central government.

3

See Figure A3.2 on the decision tree for the statistical treatment of “capital injections” and paragraphs A3.47-A3.52 in the GFSM 2014.

4

No information is available as to whether there is an employment related social insurance scheme controlled classified as a budgetary central government unit, for which benefits payments would be recorded under employment related social benefits.

1

Extracted from the Government Finance Statistics: Compilation Guide for Developing Countries (IMF, 2011).

1

Extracted from the Government Finance Statistics: Compilation Guide for Developing Countries (IMF, 2011).

Same Series

Other IMF Content

Other Publishers

Cover IMF Staff Country Reports
Zambia: Technical Assistance Report-Report on Government Finance Statistics
Author: International Monetary Fund. Statistics Dept.
Volume/Issue:
Volume 2020: Issue 220
Publisher:
International Monetary Fund
ISBN:
9781513550640
ISSN:
1934-7685
Pages:
44
DOI:
https://doi.org/10.5089/9781513550640.002

Zambia: Public Sector Institutional Table

Zambia: Differences in CSO and MOF GFS for BCG

Zambia: Budgetary Central Government GFS

Zambia: Local Government GFS

Zambia: Social Security Funds GFS

Zambia: Extrabudgetary Units GFS