I. Overall Assessment

1. Mauritius has participated in the General Data Dissemination System (GDDS) since September 21, 2000. The authorities have expressed their interest in subscribing to the Special Data Dissemination Standard (SDDS) by the end of 2008. The assessment was therefore conducted against the SDDS. For most of the datasets, Mauritius meets the specifications for coverage, periodicity, and timeliness. Plans are in place to address remaining issues except for offshore financial entities, which are not included in the coverage of the external sector statistics. An action plan will be needed to address this issue. Appendix I provides an overview of Mauritius dissemination practices compared to the SDDS.

2. The quality of the macroeconomic statistics in Mauritius has improved significantly since the previous assessment conducted in 2001. Quarterly national accounts were successfully put in place and the scope of price indices was expanded, in particular for the producer price indices. Work is well advanced to implement the new international methodology for government finance statistics (Government Finance Statistics Manual 2001 (GFSM 2001)).

3. In applying the IMF’s Data Quality Assessment Framework (DQAF July 2003), the remainder of this section presents the mission’s main conclusions. The presentation is done at the level of the DQAF’s quality dimensions, by agency for the first two dimensions and across datasets for the remaining five.

4. Concerning the prerequisites of quality, the legal framework for statistics is strong, although the responsibility to compile government finance statistics is not legally assigned. Plans underway to establish an independent statistical agency with a broader mandate may further enhance the system. Resources are not sufficient for the existing statistical program in the Central Statistics Office (CSO) and the Bank of Mauritius (BOM), although the BOM is in the process of filling additional staff positions. Efforts to monitor the relevance of monetary and balance of payments statistics should be stepped up. The authorities are committed to adhering to internationally accepted standards and good practices, as demonstrated by their engagement in subscribing to the SDDS.

5. Concerning assurances of integrity, both the CSO and the BOM staff have a high level of professionalism and internal guidelines to maintain high ethical standards are in place. Advance notice should be given to users when the methodology is changed in monetary and balance of payments statistics. Also, internal access to these data, or approval for their dissemination to the public, by government officials should be publicly identified for government finance and balance of payments statistics.

6. On methodological soundness, national accounts, price, and government finance statistics are generally sound. For monetary and balance of payments statistics, improvements in all elements are recommended, in particular the coverage of resident global license entities for balance of payments statistics and the discontinuation of the outdated analytical framework for compiling and disseminating monetary statistics.

7. On accuracy and reliability, several issues are noted regarding national accounts, producer price, and balance of payments statistics, especially concerning source data and statistical techniques. Revision studies should be undertaken more regularly.

8. On serviceability, the periodicity and timeliness practices do not meet SDDS requirements for the producer prices index and government finance statistics. There is room to improve data consistency across all data sets. Revision policies should be strengthened in all areas except for national accounts.

9. On accessibility of data, improvements are proposed in all areas. Metadata accessibility should be strengthened for producer price, monetary, and balance of payments statistics. Assistance to users is generally strong, but contact information for balance of payments statistics is lacking. Advance release calendars are not available for government finance, monetary, and balance of payments statistics.

10. With the assistance of the Ministry of Finance and Economic Development and to complement the assessment, a survey was conducted among users of macroeconomic statistics. Questionnaires were sent to 150 users; about 70 responses were received from a broad range of users, including government agencies, private and public enterprises, foreign representations, banks, and academic institutions. Users were asked to evaluate the coverage, periodicity, timeliness, dissemination practices, accessibility, and overall quality of the official statistics. A meeting with users was held. Users expressed general satisfaction with the overall quality of the statistics produced by CSO and the BOM. Users felt that the statistics were generally as good as or better than those disseminated by other countries in the region. The users raised some of the issues highlighted in the mission’s recommendations.

11. Section II provides a summary assessment by agency and dataset based on a four-part scale. This is followed by staff recommendations in Section III. Practices compared to the SDDS are summarized in Appendix I. The authorities’ response to this report and detailed assessments are presented in separate documents.

II. Assessment by Agency and Dataset

12. Assessment of the quality of six macroeconomic datasets—national accounts, consumer price index, producer price index, government finance, monetary, and balance of payments statistics—were conducted. In this section, the results are presented at the level of the DQAF elements and using a four-point rating scale (Table 1). Assessments of the prerequisites of data quality and the assurances of integrity (Dimensions “0” and “1” of the DQAF) are presented in Tables 2a–b. For each dataset, the assessment of methodological soundness, accuracy and reliability, serviceability, and accessibility (Dimensions “2” to “5” of the DQAF) are shown in Tables 3a–f.

Table 1.

Mauritius Data Quality Assessment Framework—Summary Results

Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable

Practice observed: Current practices generally meet or achieve the objectives of DQAF internationally accepted statistical practices without any significant deficiencies. Practice largely observed: Some departures, but these are not seen as sufficient to raise doubts about the authorities’ ability to observe the DQAF practices. Practice largely not observed: Significant departures and the authorities will need to take significant action to achieve observance. Practice not observed: Most DQAF practices are not met. Not applicable: Used only exceptionally when statistical practices do not apply to a country’s circumstances.

Table 1.

Mauritius Data Quality Assessment Framework—Summary Results

Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable

Datasets	National Accounts	Consumer Price Index	Producer Price Index	Government Finance Statistics	Monetary Statistics	Balance of Payments Statistics
Dimensions/Elements
0. Prerequisites of quality
0.1 Legal and institutional environment	O	O	O	LO	O	LO
0.2 Resources	LO	O	LO	LO	LO	LNO
0.3 Relevance	O	O	O	O	O	LO
0.4 Other quality management	O	O	O	O	O	O
1. Assurances of integrity
1.1 Professionalism	O	O	O	O	O	O
1.2 Transparency	O	O	O	LO	LO	LO
1.3 Ethical standards	O	O	O	O	O	O
2. Methodological soundness
2.1 Concepts and definitions	O	O	O	LO	O	O
2.2 Scope	LO	LO	O	O	LO	LO
2.3 Classification/sectorization	O	O	O	O	LO	LO
2.4 Basis for recording	LO	O	O	O	LO	LO
3. Accuracy and reliability
3.1 Source data	LO	O	LO	LO	O	LNO
3.2 Assessment of source data	O	O	O	O	O	LNO
3.3 Statistical techniques	LNO	O	LO	O	O	LO
3.4 Assessment and validation of intermediate data and statistical outputs	LO	O	O	O	O	LO
3.5 Revision studies	O	O	LNO	NO	LO	NO
4. Serviceability
4.1 Periodicity and timeliness	O	O	LO	LO	O	O
4.2 Consistency	LO	O	O	LO	LO	LNO
4.3 Revision policy and practice	O	LO	LO	LO	LNO	LNO
5. Accessibility
5.1 Data accessibility	LO	LO	LO	LO	LO	LO
5.2 Metadata accessibility	O	O	LNO	O	LO	LNO
5.3 Assistance to users	O	O	O	O	LO	LO

Practice observed: Current practices generally meet or achieve the objectives of DQAF internationally accepted statistical practices without any significant deficiencies. Practice largely observed: Some departures, but these are not seen as sufficient to raise doubts about the authorities’ ability to observe the DQAF practices. Practice largely not observed: Significant departures and the authorities will need to take significant action to achieve observance. Practice not observed: Most DQAF practices are not met. Not applicable: Used only exceptionally when statistical practices do not apply to a country’s circumstances.

View Table

Table 1.

Mauritius Data Quality Assessment Framework—Summary Results

Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable

Datasets	National Accounts	Consumer Price Index	Producer Price Index	Government Finance Statistics	Monetary Statistics	Balance of Payments Statistics
Dimensions/Elements
0. Prerequisites of quality
0.1 Legal and institutional environment	O	O	O	LO	O	LO
0.2 Resources	LO	O	LO	LO	LO	LNO
0.3 Relevance	O	O	O	O	O	LO
0.4 Other quality management	O	O	O	O	O	O
1. Assurances of integrity
1.1 Professionalism	O	O	O	O	O	O
1.2 Transparency	O	O	O	LO	LO	LO
1.3 Ethical standards	O	O	O	O	O	O
2. Methodological soundness
2.1 Concepts and definitions	O	O	O	LO	O	O
2.2 Scope	LO	LO	O	O	LO	LO
2.3 Classification/sectorization	O	O	O	O	LO	LO
2.4 Basis for recording	LO	O	O	O	LO	LO
3. Accuracy and reliability
3.1 Source data	LO	O	LO	LO	O	LNO
3.2 Assessment of source data	O	O	O	O	O	LNO
3.3 Statistical techniques	LNO	O	LO	O	O	LO
3.4 Assessment and validation of intermediate data and statistical outputs	LO	O	O	O	O	LO
3.5 Revision studies	O	O	LNO	NO	LO	NO
4. Serviceability
4.1 Periodicity and timeliness	O	O	LO	LO	O	O
4.2 Consistency	LO	O	O	LO	LO	LNO
4.3 Revision policy and practice	O	LO	LO	LO	LNO	LNO
5. Accessibility
5.1 Data accessibility	LO	LO	LO	LO	LO	LO
5.2 Metadata accessibility	O	O	LNO	O	LO	LNO
5.3 Assistance to users	O	O	O	O	LO	LO

Practice observed: Current practices generally meet or achieve the objectives of DQAF internationally accepted statistical practices without any significant deficiencies. Practice largely observed: Some departures, but these are not seen as sufficient to raise doubts about the authorities’ ability to observe the DQAF practices. Practice largely not observed: Significant departures and the authorities will need to take significant action to achieve observance. Practice not observed: Most DQAF practices are not met. Not applicable: Used only exceptionally when statistical practices do not apply to a country’s circumstances.

Table 2a.

Mauritius Assessment of Data Quality—Dimensions 0 and 1—Central Statistics Office

Table 2a.

Mauritius Assessment of Data Quality—Dimensions 0 and 1—Central Statistics Office

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The Central Statistics Office (CSO) is responsible for compiling and disseminating national accounts (NA) statistics, price statistics, and government finance statistics (GFS). The Statistics Act of November 30, 2000 clearly defines the authority of the CSO for compiling and disseminating NA and price statistics. However, the CSO is not assigned legally the responsibility to produce GFS. The Act also ensures mandatory data reporting and guarantees confidentiality of the individual reporters’ data. Data sharing and coordination among the producing agencies are adequate. In addition, the Statistics Advisory Council advises the Minister responsible for statistical matters on coordination of statistical activities in Mauritius. Resources. Staff resources are generally not commensurate with the need to maintain the current statistical programs and to meet international statistical requirements. Besides, staff needs training in international methodological standards. The compilation of NA and price statistics requires additional software facilities. Relevance. The relevance of the statistics is driven by the user needs, which are monitored adequately through periodic user surveys or feedback from users. Other quality management. Quality awareness is evidenced by the mission statement of the CSO, as well as third party audits on quality assessment. Since joining the General Data Dissemination System (GDDS) in 2000, the CSO has undertaken major efforts to improve the quality of its statistics and expand the coverage towards adherence to the Special Data Dissemination System (SDDS).

Professionalism. The legal environment supports the independence of the CSO. The Statistics Act stipulates that statistics are compiled on an impartial basis, and the choices of sources and techniques are based on statistical considerations. The principle of objectivity in data collection, processing, and dissemination is firmly adhered to. There is no external interference in the collection, compilation or dissemination of statistics. The statistical releases are independent of any ministerial commentary that may be given subsequently. Transparency. The Statistics Act defines the terms and conditions under which statistics are produced and disseminated by the CSO. The CSO provides the Minister responsible for statistical matters main highlights of the quarterly publications one day before public release. The provision of such estimates is made known to the public. However, the internal approval process of GFS is not publicized. Products of the CSO are clearly identified as such. The CSO is mentioned as the principal source by the media. Advance notice is given to the users whenever there are major changes in methodology, source data, and statistical techniques. Ethical standards. Staff behavior is guided by the Code of Ethics for public Officers and thee Official Secrets Act. The CSO has also published a “Customer Charter” which outlines the commitment of CSO staff towards users.

View Table

Table 2a.

Mauritius Assessment of Data Quality—Dimensions 0 and 1—Central Statistics Office

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The Central Statistics Office (CSO) is responsible for compiling and disseminating national accounts (NA) statistics, price statistics, and government finance statistics (GFS). The Statistics Act of November 30, 2000 clearly defines the authority of the CSO for compiling and disseminating NA and price statistics. However, the CSO is not assigned legally the responsibility to produce GFS. The Act also ensures mandatory data reporting and guarantees confidentiality of the individual reporters’ data. Data sharing and coordination among the producing agencies are adequate. In addition, the Statistics Advisory Council advises the Minister responsible for statistical matters on coordination of statistical activities in Mauritius. Resources. Staff resources are generally not commensurate with the need to maintain the current statistical programs and to meet international statistical requirements. Besides, staff needs training in international methodological standards. The compilation of NA and price statistics requires additional software facilities. Relevance. The relevance of the statistics is driven by the user needs, which are monitored adequately through periodic user surveys or feedback from users. Other quality management. Quality awareness is evidenced by the mission statement of the CSO, as well as third party audits on quality assessment. Since joining the General Data Dissemination System (GDDS) in 2000, the CSO has undertaken major efforts to improve the quality of its statistics and expand the coverage towards adherence to the Special Data Dissemination System (SDDS).

Professionalism. The legal environment supports the independence of the CSO. The Statistics Act stipulates that statistics are compiled on an impartial basis, and the choices of sources and techniques are based on statistical considerations. The principle of objectivity in data collection, processing, and dissemination is firmly adhered to. There is no external interference in the collection, compilation or dissemination of statistics. The statistical releases are independent of any ministerial commentary that may be given subsequently. Transparency. The Statistics Act defines the terms and conditions under which statistics are produced and disseminated by the CSO. The CSO provides the Minister responsible for statistical matters main highlights of the quarterly publications one day before public release. The provision of such estimates is made known to the public. However, the internal approval process of GFS is not publicized. Products of the CSO are clearly identified as such. The CSO is mentioned as the principal source by the media. Advance notice is given to the users whenever there are major changes in methodology, source data, and statistical techniques. Ethical standards. Staff behavior is guided by the Code of Ethics for public Officers and thee Official Secrets Act. The CSO has also published a “Customer Charter” which outlines the commitment of CSO staff towards users.

Table 2b.

Mauritius Assessment of Data Quality—Dimensions 0 and 1—Bank of Mauritius

Table 2b.

Mauritius Assessment of Data Quality—Dimensions 0 and 1—Bank of Mauritius

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The statistical work of the Bank of Mauritius is governed by the 2004 Bank of Mauritius Act. The BOM’s responsibility for processing and disseminating statistics is clearly specified in Section 5(1)(d) of the Act, which lists among the BOM’s functions the responsibility to collect, compile, and disseminate, on a timely basis, monetary and related financial statistics. To this end, Section 51(1) gives the BOM the power to require information and data from financial institutions. Similarly, Section 51(A) charges the BOM with the responsibility for compiling the balance of payments statistics and gives the BOM the authority to request from any person information and data that are necessary for compiling the balance of payments and external position data. Data sharing and coordination appear to be adequate for monetary statistics. For balance of payments, improvements are necessary for collection of data on Global Business Licence Holders. Confidentiality rules for individual disclosure are not in place. Resources. Staff resources for compiling monetary statistics are broadly adequate, but additional staff are required for balance of payments statistics as more surveys are necessary. Further formal training and on- the-job experience are needed for staff in both monetary statistics and balance of payments. Computing resources and physical facilities are adequate. Measures to ensure efficient use of resources are implemented, although more effort is needed to streamline the reporting arrangements for the depository corporations. Relevance. A number of advisory and oversight bodies have the authority to monitor the accuracy, timeliness, and coverage of monetary and balance of payments statistics, including the Statistics Advisory Council, the Banking Committee, and the BOM’s technical committee on statistics that comprises representatives of all depository corporations. Users’ needs are monitored through surveys and meetings of the technical committee on monetary statistics, but there is no formal monitoring of users’ needs for balance of payments statistics. Other quality management. Management is aware of the need to maintain quality as shown for example by the recent reorganization within the BOM to create a statistics division.

Professionalism. The statutory provisions under which the BOM compiles the monetary statistics and balance of payments are adequate to support its independence in conducting these functions. Specifically, Section 3 (3) of the BOM Act grants the BOM independence in performing its functions. Statistics are compiled on an impartial basis and staff are free to choose the most appropriate data sources and statistical techniques. The professionalism of the staff is promoted through participation in external courses and on-the-job training, although no current members of staff have attended a training course on balance of payments statistics for several years. Transparency. Practices are not always transparent. For example, (i) the public is not always given an advance note of major changes in methodology; and (ii) the balance of payments statistics are not clearly identified as being compiled by the BOM. Ethical standards. The BOM Act provides broad ethical guidelines for employees of the BOM and, in addition, the staff of the BOM are bound by a formal code of conduct promulgated by the Bank. The BOM has the right to comment on erroneous interpretation and misuse of the statistics, although this right is rarely exercised.

View Table

Table 2b.

Mauritius Assessment of Data Quality—Dimensions 0 and 1—Bank of Mauritius

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The statistical work of the Bank of Mauritius is governed by the 2004 Bank of Mauritius Act. The BOM’s responsibility for processing and disseminating statistics is clearly specified in Section 5(1)(d) of the Act, which lists among the BOM’s functions the responsibility to collect, compile, and disseminate, on a timely basis, monetary and related financial statistics. To this end, Section 51(1) gives the BOM the power to require information and data from financial institutions. Similarly, Section 51(A) charges the BOM with the responsibility for compiling the balance of payments statistics and gives the BOM the authority to request from any person information and data that are necessary for compiling the balance of payments and external position data. Data sharing and coordination appear to be adequate for monetary statistics. For balance of payments, improvements are necessary for collection of data on Global Business Licence Holders. Confidentiality rules for individual disclosure are not in place. Resources. Staff resources for compiling monetary statistics are broadly adequate, but additional staff are required for balance of payments statistics as more surveys are necessary. Further formal training and on- the-job experience are needed for staff in both monetary statistics and balance of payments. Computing resources and physical facilities are adequate. Measures to ensure efficient use of resources are implemented, although more effort is needed to streamline the reporting arrangements for the depository corporations. Relevance. A number of advisory and oversight bodies have the authority to monitor the accuracy, timeliness, and coverage of monetary and balance of payments statistics, including the Statistics Advisory Council, the Banking Committee, and the BOM’s technical committee on statistics that comprises representatives of all depository corporations. Users’ needs are monitored through surveys and meetings of the technical committee on monetary statistics, but there is no formal monitoring of users’ needs for balance of payments statistics. Other quality management. Management is aware of the need to maintain quality as shown for example by the recent reorganization within the BOM to create a statistics division.

Professionalism. The statutory provisions under which the BOM compiles the monetary statistics and balance of payments are adequate to support its independence in conducting these functions. Specifically, Section 3 (3) of the BOM Act grants the BOM independence in performing its functions. Statistics are compiled on an impartial basis and staff are free to choose the most appropriate data sources and statistical techniques. The professionalism of the staff is promoted through participation in external courses and on-the-job training, although no current members of staff have attended a training course on balance of payments statistics for several years. Transparency. Practices are not always transparent. For example, (i) the public is not always given an advance note of major changes in methodology; and (ii) the balance of payments statistics are not clearly identified as being compiled by the BOM. Ethical standards. The BOM Act provides broad ethical guidelines for employees of the BOM and, in addition, the staff of the BOM are bound by a formal code of conduct promulgated by the Bank. The BOM has the right to comment on erroneous interpretation and misuse of the statistics, although this right is rarely exercised.

Table 3a.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—National Accounts

Table 3a.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—National Accounts

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The national accounts (NA) are compiled in accordance with the System of National Accounts 1993 (1993 SNA). Scope. The CSO compiles and disseminates (i) annual and quarterly GDP at current and constant prices by activity; (ii) annual and quarterly expenditures of GDP at current and constant prices; (iii) components of annual value added by activity; (iv) a sequence of annual accounts for the total economy (up to the capital account); and (v) supply and use tables(SUT) and input/output tables. The production, economic, and the asset boundary are broadly in accordance with the 1993 SNA. However, valuables and some intangible assets are not included into the assets boundary. Classification/sectorization. Institutional units, transactions, and other flows are classified according to the 1993 SNA. The activity, product, trade, and purpose classifications are consistent with international standards. Basis for recording. Market prices are used for valuation of stocks and flows. Recording is done on an accrual basis, with the exception of some government and balance of payments transactions.	Source data. The NA are compiled from comprehensive annual and quarterly data collection programs based on a statistical register. However, the accuracy of the data is reduced by the different accounting years of the units and the lack of information on valuation of changes in inventories. Assessment of source data. Source data are adequately checked for coverage, sampling, and nonsampling errors. Statistical techniques. Production approach GDP estimates are sufficiently detailed. Expenditure GDP aggregates are compiled independently, except for changes in inventories. Annual NA inconstant prices are compiled in average prices of the previous year, while QNA are compiled in 1999 prices. Techniques for deriving volume measures of value added for some activities, taxes, and some expenditure aggregates do notf ollow international standards. Assessment and validation of intermediate data and statistical output. Statistical discrepancies in intermediate data are assessed and investigated. The GDP estimates at current prices are balanced through supply and use tables only every five years. Revision studies. Studies of revisions are carried out and documented routinely.	Periodicity and timeliness. Periodicity and timeliness of the NA data do not meet SDDS requirements. Consistency. The NA data are consistent with the balance of payments data and the government finance statistics data. However, the statistical discrepancy between the GDP by activity and by the expenditure approach is not shown explicitly, but together with changes in inventories. Revision policy and practice. The revision cycle is predetermined and known by the public. Preliminary data are clearly identified. The revised data are disseminated with analysis explaining the difference with the preliminary data.	Data accessibility. Data are disseminated in hardcopy publications and on the web site of the CSO. National accounts data are presented in a clear manner. However, volume measures of GDP aggregates are available only on request. Seasonally adjusted QNA are not published. The release schedule for the national accounts data is preannounced. National accounts are made available to all users at the same time. Metadata accessibility. Detailed metadata on concepts, definitions, and sources are available in hardcopy publications and on the website. The level of details meets the user requirements. Assistance to users. Catalog of publications and information on the contact person for national accounts is available to the users.

View Table

Table 3a.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—National Accounts

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The national accounts (NA) are compiled in accordance with the System of National Accounts 1993 (1993 SNA). Scope. The CSO compiles and disseminates (i) annual and quarterly GDP at current and constant prices by activity; (ii) annual and quarterly expenditures of GDP at current and constant prices; (iii) components of annual value added by activity; (iv) a sequence of annual accounts for the total economy (up to the capital account); and (v) supply and use tables(SUT) and input/output tables. The production, economic, and the asset boundary are broadly in accordance with the 1993 SNA. However, valuables and some intangible assets are not included into the assets boundary. Classification/sectorization. Institutional units, transactions, and other flows are classified according to the 1993 SNA. The activity, product, trade, and purpose classifications are consistent with international standards. Basis for recording. Market prices are used for valuation of stocks and flows. Recording is done on an accrual basis, with the exception of some government and balance of payments transactions.	Source data. The NA are compiled from comprehensive annual and quarterly data collection programs based on a statistical register. However, the accuracy of the data is reduced by the different accounting years of the units and the lack of information on valuation of changes in inventories. Assessment of source data. Source data are adequately checked for coverage, sampling, and nonsampling errors. Statistical techniques. Production approach GDP estimates are sufficiently detailed. Expenditure GDP aggregates are compiled independently, except for changes in inventories. Annual NA inconstant prices are compiled in average prices of the previous year, while QNA are compiled in 1999 prices. Techniques for deriving volume measures of value added for some activities, taxes, and some expenditure aggregates do notf ollow international standards. Assessment and validation of intermediate data and statistical output. Statistical discrepancies in intermediate data are assessed and investigated. The GDP estimates at current prices are balanced through supply and use tables only every five years. Revision studies. Studies of revisions are carried out and documented routinely.	Periodicity and timeliness. Periodicity and timeliness of the NA data do not meet SDDS requirements. Consistency. The NA data are consistent with the balance of payments data and the government finance statistics data. However, the statistical discrepancy between the GDP by activity and by the expenditure approach is not shown explicitly, but together with changes in inventories. Revision policy and practice. The revision cycle is predetermined and known by the public. Preliminary data are clearly identified. The revised data are disseminated with analysis explaining the difference with the preliminary data.	Data accessibility. Data are disseminated in hardcopy publications and on the web site of the CSO. National accounts data are presented in a clear manner. However, volume measures of GDP aggregates are available only on request. Seasonally adjusted QNA are not published. The release schedule for the national accounts data is preannounced. National accounts are made available to all users at the same time. Metadata accessibility. Detailed metadata on concepts, definitions, and sources are available in hardcopy publications and on the website. The level of details meets the user requirements. Assistance to users. Catalog of publications and information on the contact person for national accounts is available to the users.

Table 3b.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index

Table 3b.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Concepts and definitions used in the compilation of the CPI broadly follow international practices and are in line with the recommendations of the Consumer Price Index Manual. CPI concepts include some mixed elements of expenditure under its scope to accommodate users’ needs. Scope. The index covers the expenditures of all household shaving the Mauritian nationality, but excludes the resident foreign workers mainly engaged in the textile industry or construction). Imputed rentals of owner-occupied dwellings are excluded; instead, interest paid on mortgages is included. Classification/sectorization. Classification systems follow international guidelines. The commodities in the CPI are classified according to the Classification of Individual Consumption by Purpose, including 12 divisions, 42 groups, and 84 commodity classes. Basis for recording. Goods and services are generally recorded on an accrual basis, as required by international guidelines.	Source data. Source data for prices and weights are adequate. Weights are derived from the quinquennial household budget survey (HBS), which serves as basis for regular updates of the index. The new CPI series has July 2006-June 2007 as base period and the weights are derived from the2006/07 HBS. Source data and a timely collection support an early release of the CPI. Assessment of source data. Source data are analyzed in the context of revisions. Prices collected are verified according to established procedures for checking price quotations. Statistical techniques. Statistical techniques are broadly in line with recommended practice. The geometric mean formula is used to compile elementary indices and Laspeyres for the upper-level indices. Treatment of missing prices, disappearance of products, and quality adjustment are adequate. Seasonal adjustment is made for the vegetable group using the 12-month moving average price. The weights emerging from the HBS are adjusted for known underreporting in particular items, such as tobacco or alcoholic beverages. Assessment and validation of intermediate data and statistical outputs. Validation procedures are in place. Relevancy checks of the elementary indices are made and any unusual movements are checked. Revision studies. Revision studies on weight revisions are published.	Periodicity and timeliness. The CPI is published on a monthly basis within five working days after the end of the month, meeting SDDS requirements. Consistency. Consistent time series data are available without break for the periods between successive five-yearly HBSs. Revision policy and practice. The weight revision schedule follows a well-established cycle of five years, known to the public. However, the revision policy is lacking in disseminating comparative series for the period following the introduction of a new base and weights. Chain-linked long-term time series are not prepared.	Data accessibility. The main results of the CPI are disseminated every month on the Internet and in the Government Gazette. However, data for only the 12 divisions are available to the public. Additional analyses are included in the dedicated publication- Economic and Social Indicators. An advance release calendar is posted on the website. Detailed indices are available free of charge upon request at the CSO. Metadata accessibility. Metadata are produced at various levels of detail and are available in print and on the website. Comprehensive descriptions of both the HBS and CPI methodologies are published every five years in the relevant issue of the HBS publication. Assistance to users. Adequate service and support to users is provided upon request. Contact person and coordinates are mentioned in the GDDS metadata and in the CSO’s publications.

View Table

Table 3b.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Concepts and definitions used in the compilation of the CPI broadly follow international practices and are in line with the recommendations of the Consumer Price Index Manual. CPI concepts include some mixed elements of expenditure under its scope to accommodate users’ needs. Scope. The index covers the expenditures of all household shaving the Mauritian nationality, but excludes the resident foreign workers mainly engaged in the textile industry or construction). Imputed rentals of owner-occupied dwellings are excluded; instead, interest paid on mortgages is included. Classification/sectorization. Classification systems follow international guidelines. The commodities in the CPI are classified according to the Classification of Individual Consumption by Purpose, including 12 divisions, 42 groups, and 84 commodity classes. Basis for recording. Goods and services are generally recorded on an accrual basis, as required by international guidelines.	Source data. Source data for prices and weights are adequate. Weights are derived from the quinquennial household budget survey (HBS), which serves as basis for regular updates of the index. The new CPI series has July 2006-June 2007 as base period and the weights are derived from the2006/07 HBS. Source data and a timely collection support an early release of the CPI. Assessment of source data. Source data are analyzed in the context of revisions. Prices collected are verified according to established procedures for checking price quotations. Statistical techniques. Statistical techniques are broadly in line with recommended practice. The geometric mean formula is used to compile elementary indices and Laspeyres for the upper-level indices. Treatment of missing prices, disappearance of products, and quality adjustment are adequate. Seasonal adjustment is made for the vegetable group using the 12-month moving average price. The weights emerging from the HBS are adjusted for known underreporting in particular items, such as tobacco or alcoholic beverages. Assessment and validation of intermediate data and statistical outputs. Validation procedures are in place. Relevancy checks of the elementary indices are made and any unusual movements are checked. Revision studies. Revision studies on weight revisions are published.	Periodicity and timeliness. The CPI is published on a monthly basis within five working days after the end of the month, meeting SDDS requirements. Consistency. Consistent time series data are available without break for the periods between successive five-yearly HBSs. Revision policy and practice. The weight revision schedule follows a well-established cycle of five years, known to the public. However, the revision policy is lacking in disseminating comparative series for the period following the introduction of a new base and weights. Chain-linked long-term time series are not prepared.	Data accessibility. The main results of the CPI are disseminated every month on the Internet and in the Government Gazette. However, data for only the 12 divisions are available to the public. Additional analyses are included in the dedicated publication- Economic and Social Indicators. An advance release calendar is posted on the website. Detailed indices are available free of charge upon request at the CSO. Metadata accessibility. Metadata are produced at various levels of detail and are available in print and on the website. Comprehensive descriptions of both the HBS and CPI methodologies are published every five years in the relevant issue of the HBS publication. Assistance to users. Adequate service and support to users is provided upon request. Contact person and coordinates are mentioned in the GDDS metadata and in the CSO’s publications.

Table 3c.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Producer Price Index

Table 3c.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Producer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. PPIs covering the domestic market are separately prepared for (i) the manufacturing sector (PPI-M), (ii) the agricultural sector (PPI-A), and (iii) the construction sector (PPI-C). The PPI-M and PPI-A are output price indices, as opposed to the PPIC, which is an input price index. The PPIs covered by this report (PPI-M and PPI-A) broadly follow internationally accepted concepts. For PPI-A, output is priced at the primary wholesaler but adjustments are made to obtain proxies for farm-gate prices. Scope. For the above-referred coverage retained by the country, the scope of the PPIs is broadly consistent with internationally accepted guidelines. Classification/sectorization. The activities and products covered by PPIs are classified according to the National Standard Industrial Classification of Economic Activities (NSIC), which is compatible with ISIC Rev. 3 at the four-digit level. Basis for recording. Recording is broadly consistent with international guidelines. Ex-factory gate prices are collected for the PPI-M and adjusted wholesale prices are used for the PPI-A. (root crops and fresh vegetables).	Source data. Source data generally accord with international guidelines. However, due to the financial year accounting, there is an excessive 12–15-month lag before incorporating the new weights following the revision of the base year that occurs every five years. Also, adjustment to the current period price used for the compilation of sugar cane data (representing over 60 percent of the PPI-A) is not made. Assessment of source data. Standard editing procedures are used to validate the source data. The source data on prices are routinely reviewed by compilers for temporal consistency. Any large discrepancies are subject to verification with the provider. Statistical techniques. A Laspeyres formula is used to aggregate the elementary indices, compiled as weighted averages of price relatives. Weights are not price updated in the PPI-M (2002 weights and 2003 base period). A seasonal-basket concept (12 different baskets targeting seasonal products) is employed to deal with seasonality in the PPI-A. PPI-M are not seasonally adjusted. Treatment of new products also requires reconsideration to align with good practices. Assessment and validation of intermediate data and statistical outputs. Validation procedures are in place. PPIs are compared against other price indices, as applicable. Revision studies. Revision studies of periodic weight/base change are not conducted but internal analyses are made.	Periodicity and timeliness. The periodicity of indices is monthly but due to the frequency of data collection, dissemination is quarterly, which is not in accordance with SDDS requirements. The indices are released 10–12 weeks (PPI-M) or 8–10 weeks (PPI-A) after the reference quarter. Consistency. The PPIs are internally consistent and comparable with related subindices of the CPI. Revision policy and practice. The regular revision of provisional PPI-A indices for some products is known to the public and data are clearly identified. The weight revision schedule follows a well-established cycle of five years, known to the public. However, consistent long-time series are not available and series are not linked.	Data accessibility. Dissemination media and format are adequate. Level of detail is satisfactory for PPIM. An advance release calendar is posted on the website. More details are available free of charge upon request, but this is not publicized. Metadata accessibility. Limited explanatory notes on the methodology are published in the Social and Economic Indicators and also posted on the Internet. However, detailed methodological notes are not yet prepared. Assistance to users. The CSO has a contact person available to provide further assistance if required. The name of contact persons and contact information are indicated in the publications and the GDDS metadata.

View Table

Table 3c.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Producer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. PPIs covering the domestic market are separately prepared for (i) the manufacturing sector (PPI-M), (ii) the agricultural sector (PPI-A), and (iii) the construction sector (PPI-C). The PPI-M and PPI-A are output price indices, as opposed to the PPIC, which is an input price index. The PPIs covered by this report (PPI-M and PPI-A) broadly follow internationally accepted concepts. For PPI-A, output is priced at the primary wholesaler but adjustments are made to obtain proxies for farm-gate prices. Scope. For the above-referred coverage retained by the country, the scope of the PPIs is broadly consistent with internationally accepted guidelines. Classification/sectorization. The activities and products covered by PPIs are classified according to the National Standard Industrial Classification of Economic Activities (NSIC), which is compatible with ISIC Rev. 3 at the four-digit level. Basis for recording. Recording is broadly consistent with international guidelines. Ex-factory gate prices are collected for the PPI-M and adjusted wholesale prices are used for the PPI-A. (root crops and fresh vegetables).	Source data. Source data generally accord with international guidelines. However, due to the financial year accounting, there is an excessive 12–15-month lag before incorporating the new weights following the revision of the base year that occurs every five years. Also, adjustment to the current period price used for the compilation of sugar cane data (representing over 60 percent of the PPI-A) is not made. Assessment of source data. Standard editing procedures are used to validate the source data. The source data on prices are routinely reviewed by compilers for temporal consistency. Any large discrepancies are subject to verification with the provider. Statistical techniques. A Laspeyres formula is used to aggregate the elementary indices, compiled as weighted averages of price relatives. Weights are not price updated in the PPI-M (2002 weights and 2003 base period). A seasonal-basket concept (12 different baskets targeting seasonal products) is employed to deal with seasonality in the PPI-A. PPI-M are not seasonally adjusted. Treatment of new products also requires reconsideration to align with good practices. Assessment and validation of intermediate data and statistical outputs. Validation procedures are in place. PPIs are compared against other price indices, as applicable. Revision studies. Revision studies of periodic weight/base change are not conducted but internal analyses are made.	Periodicity and timeliness. The periodicity of indices is monthly but due to the frequency of data collection, dissemination is quarterly, which is not in accordance with SDDS requirements. The indices are released 10–12 weeks (PPI-M) or 8–10 weeks (PPI-A) after the reference quarter. Consistency. The PPIs are internally consistent and comparable with related subindices of the CPI. Revision policy and practice. The regular revision of provisional PPI-A indices for some products is known to the public and data are clearly identified. The weight revision schedule follows a well-established cycle of five years, known to the public. However, consistent long-time series are not available and series are not linked.	Data accessibility. Dissemination media and format are adequate. Level of detail is satisfactory for PPIM. An advance release calendar is posted on the website. More details are available free of charge upon request, but this is not publicized. Metadata accessibility. Limited explanatory notes on the methodology are published in the Social and Economic Indicators and also posted on the Internet. However, detailed methodological notes are not yet prepared. Assistance to users. The CSO has a contact person available to provide further assistance if required. The name of contact persons and contact information are indicated in the publications and the GDDS metadata.

Table 3d.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics

Table 3d.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The methodology for compiling statistics on government operations is consistent with the 1986 Manual on Government Finance Statistics (GFSM 1986). The definition of general government is in line with international standards. A detailed migration path to GFSM 2001 is not available. Scope. The data include all general government institutions and their transactions. Published data include budgetary central government, consolidated central government and consolidated general government. Classification/sectorization. The sectorization/classification of government agencies and their transactions are in accordance with the GFSM 1986 methodology. GFS data are provided separately for each level of government. Data on central government debt are classified between domestic and foreign and according to debt holder and instrument. Basis for recording. Data are available on a cash basis and foreign currency transactions are converted into local currency using the official foreign currency rate prevailing at the time the payment is effected.	Source data. Data on transactions of budgetary central government and regional governments are based on final accounts. Data on other units of central government are derived from audited/unaudited accounts submitted by social security funds, extrabudgetary units, and local governments. Central government debt data are obtained from the records held by the Debt Management Unit of the MOFED, the Bank of Mauritius, and Accountant-General. Assessment of source data. The source data are analysed for misreporting and checked for temporal consistency and consistency with other related data. Data inconsistencies are queried. Statistical techniques. Where necessary, sound techniques are in place and are based on accepted statistical processes. Assessment and validation of intermediate data and statistical outputs. Expenditure and revenue data are crosschecked for consistency with other ad-hoc data obtained from government institutions, and data from the Mauritius Revenue Authority. Revision studies. No revision studies are conducted.	Periodicity and timeliness. Consolidated general government data are available annually within 9–10 months, which does not meet SDDS requirements. Budgetary central government data are available on a monthly basis within one month. Central government debt data and debt guaranteed by the central government are available quarterly within one quarter. Consistency. Consistent time series are available. The government finance statistics are consistent with national accounts and balance of payments statistics. The government financing components are consistent with corresponding debt stocks. No regular consistency checks or reconciliations are performed between government and monetary statistics. Revision policy and practice. In general, data are not revised; however, this revision policy is not made clear to the public. The status of the data is clearly defined.	Data accessibility. Data are presented in the GFSM 1986 analytical framework. Data are presented for revenue, expenditure, lending minus repayments, overall balance (surplus/deficit), and foreign and domestic financing. Separate presentations cover each level of government. Data on central government debt are disseminated according to debt holder, instrument, and maturity as well as debt guaranteed by the central government. Additional series are disseminated to meet a range of users’ needs with various levels of details. The data are disseminated in a clear manner with charts and tables to facilitate analysis. An advance release calendar (ARC) is available for the publications of the CSO. However, no ARCs are available for monthly data on central government operations or outstanding central government debt. Metadata accessibility. The “Digest of Public Finance Statistics” includes a description of concepts and definitions of the GFSM methodology. Detailed metadata are available to users through a link to the IMF Website. Assistance to users. Contact persons and their phone numbers are identified in the GFS publications. The Government Gazette contains a list of publicly available publications.

View Table

Table 3d.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The methodology for compiling statistics on government operations is consistent with the 1986 Manual on Government Finance Statistics (GFSM 1986). The definition of general government is in line with international standards. A detailed migration path to GFSM 2001 is not available. Scope. The data include all general government institutions and their transactions. Published data include budgetary central government, consolidated central government and consolidated general government. Classification/sectorization. The sectorization/classification of government agencies and their transactions are in accordance with the GFSM 1986 methodology. GFS data are provided separately for each level of government. Data on central government debt are classified between domestic and foreign and according to debt holder and instrument. Basis for recording. Data are available on a cash basis and foreign currency transactions are converted into local currency using the official foreign currency rate prevailing at the time the payment is effected.	Source data. Data on transactions of budgetary central government and regional governments are based on final accounts. Data on other units of central government are derived from audited/unaudited accounts submitted by social security funds, extrabudgetary units, and local governments. Central government debt data are obtained from the records held by the Debt Management Unit of the MOFED, the Bank of Mauritius, and Accountant-General. Assessment of source data. The source data are analysed for misreporting and checked for temporal consistency and consistency with other related data. Data inconsistencies are queried. Statistical techniques. Where necessary, sound techniques are in place and are based on accepted statistical processes. Assessment and validation of intermediate data and statistical outputs. Expenditure and revenue data are crosschecked for consistency with other ad-hoc data obtained from government institutions, and data from the Mauritius Revenue Authority. Revision studies. No revision studies are conducted.	Periodicity and timeliness. Consolidated general government data are available annually within 9–10 months, which does not meet SDDS requirements. Budgetary central government data are available on a monthly basis within one month. Central government debt data and debt guaranteed by the central government are available quarterly within one quarter. Consistency. Consistent time series are available. The government finance statistics are consistent with national accounts and balance of payments statistics. The government financing components are consistent with corresponding debt stocks. No regular consistency checks or reconciliations are performed between government and monetary statistics. Revision policy and practice. In general, data are not revised; however, this revision policy is not made clear to the public. The status of the data is clearly defined.	Data accessibility. Data are presented in the GFSM 1986 analytical framework. Data are presented for revenue, expenditure, lending minus repayments, overall balance (surplus/deficit), and foreign and domestic financing. Separate presentations cover each level of government. Data on central government debt are disseminated according to debt holder, instrument, and maturity as well as debt guaranteed by the central government. Additional series are disseminated to meet a range of users’ needs with various levels of details. The data are disseminated in a clear manner with charts and tables to facilitate analysis. An advance release calendar (ARC) is available for the publications of the CSO. However, no ARCs are available for monthly data on central government operations or outstanding central government debt. Metadata accessibility. The “Digest of Public Finance Statistics” includes a description of concepts and definitions of the GFSM methodology. Detailed metadata are available to users through a link to the IMF Website. Assistance to users. Contact persons and their phone numbers are identified in the GFS publications. The Government Gazette contains a list of publicly available publications.

Table 3e.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

Table 3e.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The analytical framework for compiling monetary statistics reflects concepts and definitions of the Monetary and Financial Statistics Manual (MFSM). Sectoral balance sheets and surveys are compiled for the central bank and other depository corporations (ODCs). The central bank survey is consolidated with the ODCs Survey to produce the Depository Corporations Survey (DCS). Scope. Institutional coverage includes: the Bank of Mauritius (BOM), 20 universal banks, and 13 nonbank deposit-taking institutions. However, no information is available at the BOM on mutual funds, some of which may need to be included in the coverage. Also, M1 and M2 aggregates are based on data that exclude non-bank depository corporations. Classification/sectorization are consistent with the MFSM, except for the sectorization of the National Pension Fund, which is included as a financial corporation rather than as a part of the central government subsector. Basis for recording. Valuation principles applied by the BOM and ODCs are in general consistent with the MFSM guidelines. However, M1 and M2 aggregates are compiled on a cash rather than on an accrual basis.	Source data. Data for the BOM and the ODCs are derived from accounting records. Data sources are timely and reasonably approximate the definitions, scope, classifications, valuation, and time of recording required for monetary statistics. Assessment of source data. Source data are checked for intertemporal consistency and, when needed, out-of-trend values are verified in direct contacts with reporting units. Statistical techniques. Compilation procedures are to a great extent automated and minimize processing time and errors (e.g., coding, editing, and tabulating errors). Assessment and validation of intermediate data and statistical outputs. Statistical techniques applied in the compilation are sound and a number of built-in consistency checks and validations are used to ensure data consistency. Revision studies. Monetary statistics are considered final when published and are rarely subject to revisions. Occasional revisions are not formally analyzed.	Periodicity and timeliness. The monetary statistics meet the periodicity and the timeliness requirements of the SDDS. Consistency. The monetary statistics are internally consistent and are consistent with the balance of payments data. Intertemporal consistency of monetary data is adequate. Consistency with the balance of payments data is monitored internally within the BOM. Consistency with the government finance statistics is not routinely monitored and no regular reconciliation of the two datasets is carried out. Revision policy and practice. Data are considered final when first publicly released and are not subject to regular revisions. This revision policy is not publicized in national sources. Also, no commentary is provided to the public on the occasional data revisions.	Data accessibility. The presentation of monetary statistics facilitates the interpretation of the data by the users. The data are released simultaneously to all interested parties. However, the schedule for data release is not publicized. Likewise, the policy of making available unpublished data is not publicized. Metadata accessibility. A summary statement of the methodology underlying the compilation of the depository corporations survey was published in the February 2007 issue of the Monthly Statistical Bulletin (MBS), which is also posted on the BOM website. The BOM website provides built-in hyperlinks to the GDDS metadata posted by the IMF on the Dissemination Standards Bulletin Board (DSBB). However, no detailed description of methodology is available and the GDDS metadata are not current. Assistance to users. Details of contact persons are included in metadata posted on the DSBB; however, these details are not current. Email address for external users queries is provided on the website and in the BOM publications. Requests for data from users inside and outside the central bank are considered on a case-by-case basis.

View Table

Table 3e.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The analytical framework for compiling monetary statistics reflects concepts and definitions of the Monetary and Financial Statistics Manual (MFSM). Sectoral balance sheets and surveys are compiled for the central bank and other depository corporations (ODCs). The central bank survey is consolidated with the ODCs Survey to produce the Depository Corporations Survey (DCS). Scope. Institutional coverage includes: the Bank of Mauritius (BOM), 20 universal banks, and 13 nonbank deposit-taking institutions. However, no information is available at the BOM on mutual funds, some of which may need to be included in the coverage. Also, M1 and M2 aggregates are based on data that exclude non-bank depository corporations. Classification/sectorization are consistent with the MFSM, except for the sectorization of the National Pension Fund, which is included as a financial corporation rather than as a part of the central government subsector. Basis for recording. Valuation principles applied by the BOM and ODCs are in general consistent with the MFSM guidelines. However, M1 and M2 aggregates are compiled on a cash rather than on an accrual basis.	Source data. Data for the BOM and the ODCs are derived from accounting records. Data sources are timely and reasonably approximate the definitions, scope, classifications, valuation, and time of recording required for monetary statistics. Assessment of source data. Source data are checked for intertemporal consistency and, when needed, out-of-trend values are verified in direct contacts with reporting units. Statistical techniques. Compilation procedures are to a great extent automated and minimize processing time and errors (e.g., coding, editing, and tabulating errors). Assessment and validation of intermediate data and statistical outputs. Statistical techniques applied in the compilation are sound and a number of built-in consistency checks and validations are used to ensure data consistency. Revision studies. Monetary statistics are considered final when published and are rarely subject to revisions. Occasional revisions are not formally analyzed.	Periodicity and timeliness. The monetary statistics meet the periodicity and the timeliness requirements of the SDDS. Consistency. The monetary statistics are internally consistent and are consistent with the balance of payments data. Intertemporal consistency of monetary data is adequate. Consistency with the balance of payments data is monitored internally within the BOM. Consistency with the government finance statistics is not routinely monitored and no regular reconciliation of the two datasets is carried out. Revision policy and practice. Data are considered final when first publicly released and are not subject to regular revisions. This revision policy is not publicized in national sources. Also, no commentary is provided to the public on the occasional data revisions.	Data accessibility. The presentation of monetary statistics facilitates the interpretation of the data by the users. The data are released simultaneously to all interested parties. However, the schedule for data release is not publicized. Likewise, the policy of making available unpublished data is not publicized. Metadata accessibility. A summary statement of the methodology underlying the compilation of the depository corporations survey was published in the February 2007 issue of the Monthly Statistical Bulletin (MBS), which is also posted on the BOM website. The BOM website provides built-in hyperlinks to the GDDS metadata posted by the IMF on the Dissemination Standards Bulletin Board (DSBB). However, no detailed description of methodology is available and the GDDS metadata are not current. Assistance to users. Details of contact persons are included in metadata posted on the DSBB; however, these details are not current. Email address for external users queries is provided on the website and in the BOM publications. Requests for data from users inside and outside the central bank are considered on a case-by-case basis.

Table 3f.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics

Table 3f.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The concepts and definitions used are generally in line with the methodology set out in BPM5. Scope. While all Mauritian entities, including Global Business Licence Holders (“offshore entities”), are in scope, in practice the GBLs are excluded. Classification/sectorization. The classification is broadly consistent with the main aggregates of the BPM5 but some detail is not provided (for example, no sector detail is published for Portfolio Investment, or instrument detail for Other Investment). Basis for recording. Transactions are recorded at market prices and converted at the exchange rates prevailing at the time of transaction, except for merchandise trade data, which use exchange rates fixed on a weekly basis. Contrary to BPM5, data are recorded almost entirely on a cash, rather than accrual, basis. In accordance with international standards, current and capital accounts transactions are largely recorded on a gross basis, and financial account transactions are recorded on a net basis. There are some instances where current and financial account transactions are recorded as a single net settlement in the current account.	Source data. The source data for the balance of payments statistics are deficient in a number of areas, including the transactions of the offshore sector and non-cash financial transactions. Most data are timely. Assessment of source data. The compilation procedures include cross-checks of the data and comparisons with related data, and the source data are assessed for response errors. However, the lack of written compilation procedures may lead to classification and compilation errors. Statistical techniques. Statistical techniques are generally sound but there are some areas where improvements could be made (such as updating the split between freight and insurance in the cif/fob adjustment; adjusting interest for withholding taxes). Assessment and validation of intermediate data and statistical outputs. Intermediate results are explored where alternative information is available, but discrepancies are not systematically investigated. Revision studies. Revision studies and analyses are not carried out.	Periodicity and timeliness. The periodicity and timeliness meet the requirements of the SDDS. Consistency. The balance of payments data are consistent over time, with the government external debt data published by MOF, and with the trade data published by CSO. However, the balance of payments and the IIP are not consistent. Revision policy and practice. There is no revision policy, and the public is not informed of the reasons for revisions.	Data accessibility. The balance of payments statistics are released simultaneously to all interested parties through the publication of a table in the MSB. However, there is no formal advance release calendar. The availability of detailed data on request in writing is not publicized. Metadata accessibility. No documentation on the methodology used to compile the data is published by the BOM. There is a hyperlink from the BOM website to the GDDS metadata on the Fund’s DSBB, which gives information on these aspects, but the existence of this hyperlink is not publicized. Assistance to users. There is no contact person or unit identified in the BOM publications. There is no formal system for monitoring and reviewing queries from users to determine whether the existing data meet user requirements. There is no formal catalogue of BOM publications.

View Table

Table 3f.

Mauritius Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The concepts and definitions used are generally in line with the methodology set out in BPM5. Scope. While all Mauritian entities, including Global Business Licence Holders (“offshore entities”), are in scope, in practice the GBLs are excluded. Classification/sectorization. The classification is broadly consistent with the main aggregates of the BPM5 but some detail is not provided (for example, no sector detail is published for Portfolio Investment, or instrument detail for Other Investment). Basis for recording. Transactions are recorded at market prices and converted at the exchange rates prevailing at the time of transaction, except for merchandise trade data, which use exchange rates fixed on a weekly basis. Contrary to BPM5, data are recorded almost entirely on a cash, rather than accrual, basis. In accordance with international standards, current and capital accounts transactions are largely recorded on a gross basis, and financial account transactions are recorded on a net basis. There are some instances where current and financial account transactions are recorded as a single net settlement in the current account.	Source data. The source data for the balance of payments statistics are deficient in a number of areas, including the transactions of the offshore sector and non-cash financial transactions. Most data are timely. Assessment of source data. The compilation procedures include cross-checks of the data and comparisons with related data, and the source data are assessed for response errors. However, the lack of written compilation procedures may lead to classification and compilation errors. Statistical techniques. Statistical techniques are generally sound but there are some areas where improvements could be made (such as updating the split between freight and insurance in the cif/fob adjustment; adjusting interest for withholding taxes). Assessment and validation of intermediate data and statistical outputs. Intermediate results are explored where alternative information is available, but discrepancies are not systematically investigated. Revision studies. Revision studies and analyses are not carried out.	Periodicity and timeliness. The periodicity and timeliness meet the requirements of the SDDS. Consistency. The balance of payments data are consistent over time, with the government external debt data published by MOF, and with the trade data published by CSO. However, the balance of payments and the IIP are not consistent. Revision policy and practice. There is no revision policy, and the public is not informed of the reasons for revisions.	Data accessibility. The balance of payments statistics are released simultaneously to all interested parties through the publication of a table in the MSB. However, there is no formal advance release calendar. The availability of detailed data on request in writing is not publicized. Metadata accessibility. No documentation on the methodology used to compile the data is published by the BOM. There is a hyperlink from the BOM website to the GDDS metadata on the Fund’s DSBB, which gives information on these aspects, but the existence of this hyperlink is not publicized. Assistance to users. There is no contact person or unit identified in the BOM publications. There is no formal system for monitoring and reviewing queries from users to determine whether the existing data meet user requirements. There is no formal catalogue of BOM publications.

III. Staff’s Recommendations

13. Based on the review of Mauritius’s statistical practices, discussions with the data producing agencies, and responses from data users (see Appendix III of the Detailed Assessments volume), the mission has developed a set of recommendations. They are designed to increase further Mauritius’s adherence to internationally accepted statistical practices and would, in the mission’s view, enhance the analytical usefulness of Mauritius’s statistics. Some additional technical suggestions are included in the Detailed Assessments volume.