Journal Issue
Share
Article

Bolivia

Author(s):
International Monetary Fund
Published Date:
August 2007
Share
  • ShareShare
Show Summary Details

I. Overall Assessment

1. The quality of Bolivia’s macroeconomic statistics has improved over recent years and the statistics have been broadly adequate for macroeconomic analysis and policy design and monitoring. Nevertheless, the ROSC mission identified shortcomings in some statistical practices that have the potential for detracting from the accurate and timely analysis of economic and financial developments and the formulation of appropriate policies. The authorities have established a good track record of implementing recommendations of technical assistance missions and have demonstrated a commitment to pursue plans and programs to further improve their statistics. The authorities are strongly committed to adhering to internationally accepted standards and good practices, as demonstrated by their participation in the General Data Dissemination System (GDDS) and their forthcoming subscription to the more demanding Special Data Dissemination Standard (SDDS).

2. Bolivia has an effective legal and institutional framework that supports statistical quality. The resources are generally commensurate with the current volume of statistical services, but insufficient to advance the implementation of needed improvements in most datasets. The work of all statistical agencies is based on professionalism, transparency, and adherence to ethical standards. The methodologies for the consumer price index (CPI), monetary, and balance of payments (BOP) statistics are basically sound, but there is room for improving the conceptual framework, scope, classification, and basis for recording in all other datasets. Adequate source data are generally available, except for national accounts and the producer price index (PPI). The reference year for national accounts (1990) has become obsolete and there is excessive use of fixed intermediate consumption/output coefficients. Indirect estimates of illegal production linked to the transformation of the coca leaf, some informal industrial and domestic trade activities, and shuttle trade are made, but related exports are excluded from BOP statistics. Furthermore, the CPI and PPI weights have not been updated during the past 16 years. Most of the official statistics are consistent within each dataset and over a reasonable period of time, but consistency with other datasets needs to be improved for the national accounts. Most datasets meet the periodicity and timeliness recommended by the GDDS, with the GFS, GDP, monetary, and BOP also meeting SDDS requirements.

3. Bolivia participates in the GDDS since November 2000 and meets the recommendations for the coverage, periodicity, and timeliness of most required data categories. However, there are some exceptions, including (a) the periodicity and timeliness of the manufacturing and producer price indexes; (b) the coverage of the consolidated central government operations; and (c) dissemination of data on public and publicly guaranteed debt service schedule. Bolivia compiles and disseminates most encouraged data categories. Exceptions are the debt service schedule of private external debt not publicly guaranteed and the timeliness of data on gross national income, capital formation, and savings. A share price index is not compiled because the volume of transactions in shares in the stock exchange is very small. Appendix I provides an overview of Bolivia’s dissemination practices compared to the GDDS.

4. In applying the current version of the IMF’s 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 four.

5. Prerequisites of quality and assurances of integrity:

  • The National Statistical Institute (NSI) has a legal and institutional environment that supports the production and dissemination of national accounts and price statistics. The laws establish mandatory data reporting by public and private entities to the NSI and the confidential nature of individual information, but no sanctions or fines are specified for noncompliance. Resources should be strengthened to establish a regular program of economic surveys for national accounts and to improve the quality of the PPI. Formal mechanisms to consult data users need to be strengthened. The NSI applies strict technical principles and professional ethics in the compilation and dissemination of statistics, and promotes a culture of professionalism. The terms and conditions under which statistics are produced are not available on the NSI website, but various publications reproduce the relevant legal precepts. Information on internal government access to data before their release to the public is only disseminated on the IMF’s DSBB. The legal framework establishes sanctions for improper behavior of public servants in the performance of their functions, and these regulations are made known to the staff.

  • The Ministry of Finance (MOF) has a legal and institutional environment that supports the compilation and dissemination of government finance statistics (GFS). Data sharing and coordination among and within institutions are broadly adequate, but there is some room for improvement (e.g., by centralizing the compilation and dissemination of GFS). Although resources are commensurate with the current needs of statistical programs, additional personnel and financing resources will be required for developmental work, including the adoption of the Government Finance Statistics Manual 2001. Regular procedures to consult with data users and to monitor the quality of the statistics need to be established. Data are collected, compiled and disseminated on an impartial basis. The MOF promotes a culture of professionalism and is authorized to respond to misinterpretation/misuse of fiscal data. The terms and conditions under which the MOF collects, compiles, and disseminates GFS are specified in relevant laws, which are available to the public. The legislation provides guidelines on staff behavior and administrative procedures, which are well known by the staff.

  • The compilation of statistics by the Central Bank of Bolivia (CBB) is based on a legal framework that supports mandatory data reporting and the confidentiality of the reported data. Inter-agency coordination is effective, but there is room for improving the data sharing arrangements with the NSI for the provision of timely survey data for the BOP. Human resources dedicated to the compilation of monetary and BOP statistics are adequate, but insufficient for conducting surveys needed for the BOP. The CBB maintains some informal contacts with data users, but there are no formal mechanisms to monitor the relevance of the statistics or to identify emerging data requirements. The statistics are compiled and disseminated following strict technical criteria and within a culture of professionalism. The terms and conditions under which statistics are compiled and disseminated are available to the public. Information on internal government access to data before their release to the public is disseminated on the CBB website and the IMF’s DSBB. The CBB’s Code of Conduct establishes ethical principles for CBB staff, including integrity, professional independence, and confidentiality. Staff of the CBB must sign at the start of each year a confidentiality agreement concerning the activities and operations of the reporting institutions.

  • The Superintendency of Banks and Financial Entities (SBFE) has the legal authority to collect data from all financial intermediaries under its supervision and the laws include penalties in cases of delays or inaccurate reporting. While the SBFE’s main function is to collect data for supervisory purposes, it has always demonstrated willingness to meet the CBB’s emerging data needs. Technical criteria alone are applied in the selection of data collection methods and processes and activities in the workplace promote a culture of professionalism. The terms and conditions for collecting data for supervisory purposes are specified in the relevant laws, which are available to the public. The SBFE’s Ethics Code contains rules on staff conduct, which are known by all staff.

6. The methodologies for the CPI, as well as monetary and BOP statistics broadly follow international standards. However, there are important shortcomings in the methodological soundness of the national accounts, PPI, and GFS, where progress towards adopting the latest statistical manuals has been slower. In general, there is room for improving the scope of all datasets. For example, important economic activities are missing in the PPI, including agriculture, mining, energy, water, gas, and services. For national accounts, the institutional sector accounts are compiled only up to the capital account and the nonprofit institutions serving households sector (NPISH) is not investigated. Indirect estimates of illegal production linked to the transformation of the coca leaf, some informal industrial and domestic trade activities, and shuttle trade are made. The GFS exclude data from some decentralized agencies and local governments and the consolidated central government data are not compiled, even though information is available. Monetary aggregates exclude data for Investment Funds Management Societies, which issue liabilities that should be included in broad money. The BOP excludes unrecorded trade and some other transactions with nonresidents. There is room to improve classification and sectorization systems for all datasets, in particular for GFS, where there are significant departures from best practices, e.g., in the classification of royalties, commissions, tax returns, social assistance benefits, and lending minus repayments. The basis for recording national accounts, prices, and monetary statistics follow international best practices. Recording of transactions for the BOP and GFS could be improved, for example, by fully adopting accrual accounting.

7. While ample source data sustain a high level of accuracy and reliability in the monetary statistics, there is significant room for improvement in all other datasets, especially for national accounts and the PPI. Source data are very good for monetary statistics, are reasonably available for the CPI, but are insufficiently developed for the national accounts, the PPI, GFS, and BOP statistics. Despite recent improvements in the data sources for national accounts, such as the conduct of a household survey, important weaknesses remain. For example, a comprehensive business directory does not exist, the compilation of the annual manufacturing, foreign direct investment, and tourism surveys were suspended, and economic censuses are not conducted on a regular basis. With respect to the PPI, the basket is not fully representative of current national output. There is some overlapping of responsibilities in the collection of source data for GFS, and the coverage of certain services and financial transactions in the BOP needs to be expanded. Assessment and validation of source data for GFS, monetary, and BOP statistics are sound, but need to be strengthened for national accounts and price indices. Statistical techniques need to be improved for most datasets. For example, the reference year for national accounts (1990) has become obsolete and there is excessive use of fixed intermediate consumption/output coefficients; CPI and PPI weights have not been updated during the past 16 years and new products are not introduced in the CPI. The procedures for validating intermediate and final data are sound. For the most part, revision studies and analysis are conducted and used to inform the statistical processes. However, only the analyses of revisions to monetary statistics are documented on a systematic basis.

8. Serviceability of the macroeconomic statistics is broadly satisfactory, as confirmed by the results of a user survey conducted in the context of this assessment. With the exception of the PPI and the public and publicly guaranteed debt service schedule, data in all assessed areas are compiled and disseminated with the periodicity and timeliness recommended by the GDDS. Furthermore, all data categories in the GFS, monetary, and BOP datasets, meet the periodicity and timeliness required by the more demanding SDDS. Macroeconomic statistics are broadly consistent within the dataset and can be reconciled over a reasonable period of time. While publicly available information permits the reconciliation of GFS, monetary, and BOP statistics, there is room to improve the consistency of national accounts with other datasets. The statistical agencies have well established revision policies and practices for most datasets, and preliminary and revised data are identified in the publications. However, neither the revision cycle nor the analyses of revisions are publicized.

9. There are opportunities to improve the accessibility of official statistics, for example, by disseminating the advance release calendars on the websites of all statistical agencies and improving access to data via the Internet. Currently, the advance release calendar for all the assessed datasets is disseminated on the CBB website. A government policy advisory committee is provided with data that may or may not be disseminated to the public. However, this practice does not affect the pre-scheduled release. Detailed metadata are posted on the websites of the statistical agencies and in the publications, with the exception of metadata for GFS, which are only available on the IMF’s DSBB. All data-producing agencies provide effective assistance to users.

10. At the request of the authorities, current data dissemination practices were also reviewed against the requirements of the Special Data Dissemination Standard (SDDS). 1 The following points about the coverage, periodicity, and timeliness prescriptions of the data dimension highlight some significant issues to be addressed prior to subscription to the SDDS:

  • In the real sector,

    • i. Data on employment, unemployment, and wages/salaries need to be compiled on a quarterly basis and disseminated within three months after the end of the reference period. While data for public sector employment and wages/salaries meet the SDDS standard, data for the private sector are only compiled every six months and disseminated with a four-month lag. Data on unemployment are only compiled on an annual basis and disseminated with a four-month lag; and

    • ii. The PPI needs to be compiled on a monthly basis and disseminated within a month of the end of the reference period. Currently, the PPI is compiled on a quarterly basis and disseminated with a ten-week lag.

  • In the fiscal sector, the consolidated operations of the central government (budgetary, extrabudgetary, and social security operations) are not compiled, even though the data for the component subsectors are available. Data on the consolidated operations of the general government and the nonfinancial public sector are compiled and disseminated.

  • All data categories in the financial and external sectors meet the SDDS prescriptions on coverage, periodicity, and timeliness.

11. Advanced release calendars for all data categories are disseminated at: http://www.bcb.gov.bo/sitio/estadisticast.php?n2=5&n3=9&n4. Appendix III in the accompanying document presents a more detailed description of current practices regarding coverage, periodicity, and timeliness of data compared to the SDDS.

12. Bolivia should be able to meet the remaining requirements for SDDS subscription in the very short term, particularly because the country is entitled to take two flexibility options. This means that for any two prescribed data categories listed above (employment, unemployment, wages/salaries, and the producer price index), periodicity and/or timeliness may be less than prescribed. 2

II. Assessment by Agency and Dataset

13. 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 using the July 2003 vintage of the DQAF. 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 2ad. 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 3af.

Table 1.Bolivia: Data Quality Assessment Framework July 2003—Summary Results
Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO =Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable
DatasetsNational

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 environmentLOOOLOOLO
0.2 ResourcesLOLOLNOLOLOLO
0.3 RelevanceLOLOLOLNOLOLO
0.4 Other quality managementOOOOOO
1. Assurances of integrity
1.1 ProfessionalismOOOOOO
1.2 TransparencyLOLOOLOOO
1.3 Ethical standardsOOOOOO
2. Methodological soundness
2.1 Concepts and definitionsLOLOLOLOOO
2.2 ScopeLOOLNOLOLOLO
2.3 Classification/sectorizationLOLOLOLNOLOLO
2.4 Basis for recordingOOOLOOLO
3. Accuracy and reliability
3.1 Source dataLNOOLNOLOOLO
3.2 Assessment of source dataLOLOLOOOO
3.3 Statistical techniquesLNOLNOLNOOOLO
3.4 Assessment and validation of intermediate
data and statistical outputsOOOOOO
3.5 Revision studiesLOLOLOLOOLO
4. Serviceability
4.1 Periodicity and timelinessOOLNOOOO
4.2 ConsistencyLOOOLOOLO
4.3 Revision policy and practiceLOLOLOLOLOLO
5. Accessibility
5.1 Data accessibilityLOLOLOLOLOO
5.2 Metadata accessibilityOOOLOOO
5.3 Assistance to usersOOOOOO
Practice observed: current practices generally in observance 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.
Practice observed: current practices generally in observance 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.Bolivia: Assessment of Data Quality—Dimensions 0 and 1—National Statistical Institute
0. Prerequisites of quality1. Assurances of integrity
Legal and institutional environment. Provisions for producing statistics are included in the DL 14100, from November 5, 1976, that created the National Statistical Information System. The Supreme Decree 21855, from January 14, 1988, transferred the compilation of the national accounts from the CBB to NSI. Article 15 of DL 14100 establishes mandatory data reporting by public and private entities to the NSI. Although Article 21 establishes the confidential nature of individual information, no sanctions or fines are specified for noncompliance. NSI has signed special agreements with various institutions to facilitate data sharing and coordination.Professionalism. NSI’s Statistical Principle of Integrity clearly states the importance of applying technical principles and professional ethics in the compilation and dissemination of statistics. Professionalism is promoted, among other measures, by sending compilers to training courses and specialized seminars abroad, and by receiving technical assistance from other countries and international organizations. The National Accounts Directorate monitors media coverage of national accounts data and the NSI is entitled to comment when statistics are misinterpreted or misused.
Resources. While some resources have been allocated to modernize the national accounts, additional resources are required to strengthen the data collection and compilation program. The staff, computing, and financing resources are adequate for the regular compilation of CPI, but inadequate for the PPL Staff performance is reviewed every six months.



Relevance. The NSI does not have formal mechanisms to consult data users on their information needs. However, the Institute strives to adopt best international practices.



Other quality management. The Institutional Strategic Plan for 2005–2009 aims to obtain the ISO 9000:2000 quality certification for the NSI’s main statistical products. The authorities strongly support the adoption of international manuals and guides and seek technical and financial support in that regard.
Transparency. Although the legislation governing the terms and conditions under which statistics are produced by the NSI is not available on its website, various publications and documents disseminated through the website reproduce the relevant legal precepts. Major changes in the conceptual framework, source data, and statistical techniques of the national accounts were announced in advance (e.g., the introduction of the base year 1990). Metadata for quarterly GDP, institutional sector accounts, and others are disseminated on the website. An advance release calendar is provided to the public. Data released to the public are clearly identified as NSI’s product by name and logo. Information on internal government access to data before their release to the public is disseminated on the IMF’s DSBB but not on the NSI website. Adequate documentation is available on the methodology used for compiling price indices.
Ethical standards. The Law No. 2027 on Public Servants and the NSI’s Staff Regulation establish sanctions for improper behavior of public servants in the performance of their functions. These regulations are made known to the staff.
Table 2b.Bolivia: Assessment of Data Quality—Dimensions 0 and 1—Ministry of Finance
0. Prerequisites of quality1. Assurances of integrity
Legal and institutional environment. The MOF has a legal and institutional environment that supports the collection, compilation, and dissemination of GFS, budget, and accounting data. This responsibility is assigned to the MOF by the Law on Organization of the Executive Branch, known as the “LOPE” (Law N° 3351 of March 9, 2006) and the Law of Government Administration and Control, known as the “SAFCO” (Law No. 1178 of July 20, 1990), and its subsequent by-laws and regulations. The Fiscal Programming Unit (UPF) in the MOF is in charge of GFS compilation, though this responsibility is shared with the General Directorate of Accounting (GDA). Data sharing and coordination among and within institutions are adequate, but there is some room for improvement (e.g., by centralizing the compilation and dissemination of GFS). The UPF compiles above-the-line data and the CBB compiles below-the-line data, and both share the compilation and dissemination of public debt data. The GDA compiles GFS following the GFSM2001 methodology for publication in the IMF GFS Yearbook. The current legislation and procedures require that each public entity submits budgetary and financial statements to the MOF. The laws specify penalties for noncompliance.Professionalism. There are no specific laws or other formal provisions that explicitly address professional independence or prohibit political interference. Nevertheless, government finance statistics are compiled on an impartial basis. A culture of professionalism is clearly recognized as essential to the credibility of statistical results in the internal provisions of the MOF and in the principles of Law on Public Servants of October 27, 1999 (Law No. 2027) and its by-laws and provisions. The choice and tenure of the managers are based on an independent process. Efforts are made to promote professionalism by sending staff to training courses abroad and by on-the-job training. Also, professionalism is fostered by analytical work, publication of methodological papers, and organization of lectures and seminars. Research and analysis are encouraged and the result of these academic activities are published on the MOF website. No evidence exists of political interference in the choice of data sources and statistical methods and decisions about dissemination. The MOF is empowered to respond to misinterpretation/misuse of fiscal data.
Resources. Although resources are commensurate with the current needs of statistical programs, additional personnel and financing resources could be required to perform new compilation tasks, such as the expansion of the institutional and transaction coverage of the GFS already compiled, and the implementation of the GFSM2001 analytical framework.



Relevance. Regular procedures to consult with data users and to monitor the quality of the statistics need to be established.
Transparency. Current legislation establishes that the public has unimpeded access to the fiscal data. The terms and conditions under which the MOF collects, compiles, and disseminates GFS are specified in the relevant laws, which are available to the public. All fiscal data products are disseminated through the MOF website and Statistical Bulletin, but do not clearly identify the compiling agencies and data sources. Advance notice is not given to the public about major changes in the methodology or other relevant changes that materially affect the GFS.
Other quality management. There are processes in place to focus on and monitor quality, and to deal with quality considerations in the planning of the statistical program.Ethical standards. Staff behavior is guided by law and administrative procedures of the civil service, which are made known to the staff.
Table 2c.Bolivia: Assessment of Data Quality—Dimensions 0 and 1—Central Bank of Bolivia
0. Prerequisites of quality1. Assurances of integrity
  • Legal and institutional environment. Provisions for producing statistics are included in the Law 1670/95 (Law of the Central Bank of Bolivia) that contains: (1) the obligation of the Superintendency of Banks and Financial Entities (SBFE) to provide the CBB with all the information received from banks and other entities of the financial sector (art. 40); (2) mandatory data reporting directly to the CBB of all information requested by it from banks and other financial intermediaries (art. 40); (3) the CBB’s responsibility for recording public and private sector external debt (art. 21); (4) strict confidentiality of the received information (art. 80); and, (5) provisions governing the publication of economic and financial data (art. 43). Institutional arrangements are in place for effective transmission of source data from the SBFE (monetary) and the NSI (balance of payments) to the CBB. However, some data sharing arrangements with the NSI have not provided effective and timely survey data. The Law 1670/95 does not include any specific regulation establishing that the CBB is responsible for compiling and disseminating balance of payments data. However, the CBB is publicly recognized as the sole institution with these responsibilities and has disseminated balance of payments statistics since 1938.

  • Resources. Human resources dedicated to the compilation of monetary and balance of payments statistics are adequate, but insufficient for balance of payments surveys. Technical resources and data processing equipment are adequate, but compilers have limited telephone communication and Internet access. A recent presidential decree reducing public service salaries may negatively affect staffing.

  • Relevance. The CBB does not have formal mechanisms to consult data users about their information needs, but users' feedback are taken into account to improve the statistical processes. The CBB shows its commitment to improve the country’s macroeconomic statistics by participating in statistical meetings and seminars organized by international and regional organizations.

  • Other quality management. The CBB’s authorities are aware that continued efforts are needed to improve the quality of the statistics produced by the Bank, as shown in their request for IMF technical assistance in monetary statistics and flow of funds accounts. The compilation and dissemination of quarterly balance of payments, IIP, private sector debt data, and monthly reserves template data, as well as the country’s efforts to subscribe to the SDDS, further demonstrate this commitment.

  • Professionalism. Monetary and balance of payments statistics are compiled and disseminated following strict technical criteria, and with professional independence. When statistics are misinterpreted or misused the CBB provides comments and clarifications mainly through its Institutional Communications Department.

  • Transparency. The terms and conditions under which statistics are compiled and disseminated are widely available to the public. Internal government access to data before their release to the public is acknowledged on the CBB website and the IMF’s DSBB. Changes in methodology and source data are described in the semiannual CBB’s External Sector Bulletin. Usually, advance notice is given for major changes in balance of payments statistics.

  • Ethical standards. The CBB’s Code of Conduct establishes ethical principles for CBB staff, including integrity, professional independence, and confidentiality. The CBB’s Internal Staff Regulation establishes staff’s rights and obligations. As part of the public sector, the CBB staff is also subject to Law 2027/99 on Public Servants, which sets out the legal framework for their rights and responsibilities. Pursuant to art. 80 of the Law 1670/95, staff of the CBB must sign at the start of each year a confidentiality agreement concerning the activities and operations of the reporting institutions.

Table 2d.Bolivia: Assessment of Data Quality—Dimensions 0 and 1—Superintendency of Banks and Financial Entities
0. Prerequisites of quality1. Assurances of integrity
  • Legal and institutional environment. Law 1488/93 (Law of Banks and Financial Institutions) endows the SBFE with the authority to request from all financial intermediaries information on their financial situation and operations (art. 93). Article 99 of the same law contemplates penalties in cases of delays or inaccurate reporting, with fines of around US$62 per day for noncompliance. Articles 86 and 89 of law 1488/95 protect the confidentiality of the reported data. Other depository corporation (ODCs) transmit daily to the SBFE, in electronic format, their balance sheets of the previous day, plus data on interest rates. ODCs transmit to the SBFE their monthly balance sheets and sectorized accounts for monetary statistics purposes two days after the end of the reference month. Institutional arrangements are in place for electronic data transmission from the SBFE to the CBB. Data are transmitted from the ODCs to the SBFE, and from the SBFE to the CBB, via dedicated encrypted lines.

  • Resources. Human, technical, and financial resources are adequate. Salaries in the SBFE have been historically higher than in the rest of the public sector and broadly competitive with the private sector, contributing to low staff turnover ratio. However, a recent presidential decree reducing public service salaries and flattening the salary scale may negatively affect staffing. Several senior SBFE staff have recently left for the private sector.

  • Relevance. The SBFE’s main function is to collect data for supervisory purposes. Nevertheless, the SBFE has always demonstrated willingness to accommodate CBB’s emerging data needs for the compilation of monetary statistics, for example, by requesting additional information from the ODCs and introducing ad-hoc changes to the chart of accounts. Staff of the SBFE regularly attend meetings and participate in international courses offered by other supervisory agencies and central banks.

  • Other quality management. The SBFE’s authorities are aware that continued efforts are needed to improve the quality of its statistical products.

  • Professionalism. The SBFE is a technical institution that has administrative and financial autonomy. Technical criteria alone are applied by data compilers and analysts, and they are totally independent in their choice of data collection methods. Processes and activities in the workplace promote a culture of professionalism.

  • Transparency. The legal terms and conditions for collecting data for supervisory purposes are specified in the relevant laws, which are available to the public. Government officials outside the SBFE have no access to the data until it is released to the general public. The SBFE statistical products are clearly identified as such. Information of public nature, such as balance sheets of ODCs, are available on the SBFE’s website and its monthly Boletin Informative, which also contains data on interest rates, financial soundness indicators, deposits and loans by volume, sectoral distribution of loans, etc. The SBFE also publishes a weekly letter containing an analytical description of the financial sector.

  • Ethical standards. SBFE staff receive a copy of the Ethics Code, which contains rules on their conduct regarding truthfulness, respect to individuals, responsibility, transparency, integrity, and confidentiality.

Table 3a.Bolivia: Assessment of Data Quality—Dimensions 2 to 5—National Accounts
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
  • Concepts and definitions. The national accounts are compiled following the 1968 SNA. However, some important features of the 1993 SNA have been incorporated.

  • Scope. The accounts cover annual and quarterly GDP by the expenditure and production approaches at current and constant 1990 prices, annual GDP by the income approach at current prices, and annual supply and use. Also, a seasonally adjusted quarterly GDP is compiled. Indirect estimates of illegal production linked to the transformation of the coca leaf, some informal industrial and domestic trade activities, and shuttle trade are made. The scope also includes institutional sector accounts from the production up to the capital account.

  • Classification/sectorization. National classifications of economic activities and products are based on ISIC Rev. 3 (except for agriculture) and the CPC, respectively. The COICOP is applied to classify households' consumption expenditure by purpose. COFOG is not applied.

  • Basis for recording. Transactions are recorded on an accrual basis. Preliminary estimates of government transactions are registered on a cash basis, but later adjusted to accrual. Transactions among subsidiaries of the same corporation are recorded on a gross basis.

  • Source data. The availability of economic statistics has deteriorated in recent years due to the suspension of various important surveys. Price and volume indices based on the quarterly manufacturing survey have lost coverage due to its outdated 1990 fixed basket of products. The availability of price statistics is limited. Economic and households surveys were recently conducted to update the base year for national accounts and the CPI.

  • Assessment of source data. Sampling errors are not estimated in some surveys. Source data are principally assessed in the context of revisions.

  • Statistical techniques. Sound techniques are employed to adjust for scarce data sources. The 1990 base year is outdated. Due to limited source data, excessive use of fixed 1990 coefficients is made in the compilation of supply and use tables. Changes in inventories are obtained as residuals. The treatment of pension funds and the techniques applied to estimate financial intermediation services indirectly measured (FISIM) at constant prices could be improved.

  • Assessment and validation of intermediate data and statistical outputs. Intermediate data and outputs are assessed and validated against available information.

  • Revision studies. Analyses of revisions are carried out and documented. However, revision studies are conducted only on an ad-hoc basis.

  • Periodicity and timeliness. While preliminary GDP data meet GDDS recommendations on periodicity and timeliness, users have expressed an urgent need to improve timeliness.

  • Consistency. Internal and intertemporal consistency of GDP figures are verified in the framework of Supply and Use tables, compiled at current and constant prices. Quarterly GDP estimates are consistent with annual estimates. Consistency with BOP and GFS is not verified on a regular basis and may be affected by the lack of estimates of illegal trade in BOP statistics.

  • Revision policy and practice. Revisions follow a regular schedule. The revision cycle is predetermined and stable from year to year, but is not publicized. Preliminary data are clearly identified, but not revised data. Documentation on analysis of revisions and a revision study made for the construction activity are prepared but not disseminated.

  • Data accessibility. National accounts are disseminated on the NSI website and publications. They include tables and charts, as well as analysis. An advance release calendar is posted on the CBB website. A government policy advisory committee is provided with data that may or may not have been disseminated to the public. However, this practice does not affect the pre-scheduled release.

  • Metadata accessibility. Metadata on various national accounts components are posted on the NSI website.

  • Assistance to users. Specific contact points are provided on the NSI website, but not on the publications. A virtual library and a catalog of publications are on the website and in the NSI Central Library. Photocopies and printouts of tables are available to the public upon request. The public may subscribe to receive information by e-mail.

Table 3b.Bolivia: Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
  • Concepts and definitions. The CPI follows the 1968 SNA household consumption concept and uses sufficiently detailed expenditure data from the 1990 Household Budget Survey (HBS). There is an adequate level of detail for both goods and services. The new HBS to update the CPI weights follows the 1993 SNA.

  • Scope. The CPI is calculated at the national level and for the four largest cities in the country (La Paz, Santa Cruz, Cochabamba, and El Alto). The CPI weights are representative only of consumption by urban households. The new CPI will include six additional cities.

  • Classification/sectorization. Goods and services are classified using an adaptation of the classification of consumption expenditure of households by purpose, in accordance with the 1968 SNA. The index is calculated by city for nine headings and 25 groups at the national level. The products of the new CPI basket will be classified using the COICOP.

  • Basis for recording. The prices are market prices paid by households at the points of sale at which transactions are conducted and are inclusive of all taxes on goods and services.

  • Source data. The 1990 HBS was used for the CPI weights. Some 15,500 monthly prices from 332 items (goods and services) are collected in direct interviews at different points of sale, representing the places where consumers do their purchases. The 2003/2004 HBS will be used to derive the new CPI weights. Some 31,700 monthly prices from 508 items will be collected.

  • Assessment of source data. Data are checked for logical consistency using manual and automated validation methods, including routine checks for extreme values. The share of consumption expenditure not covered by the index is 10 percent. Response rates, editing rates, and sampling errors are not calculated.

  • Statistical techniques. CPI uses the Lowe formula. Procedures for imputation are not sound. Weights have not been updated for the past 16 years. The current weight and price reference periods are not the same.

  • Assessment and validation of intermediate data and statistical outputs. CPI is subject to validation with respect to primary data from individual price observations and to the different levels of aggregation.

  • Revision studies. Analyses of revisions are conducted but revision studies are not performed.

  • Periodicity and timeliness. Periodicity and timeliness meet GDDS recommendations. The index is published the first business day after the reference month. There are some advance releases (three per month) at shorter intervals for internal use.

  • Consistency. Price statistics are consistent over time and all-items index tabulations are consistent with the different aggregations. A chained index between old and new series is available.

  • Revision policy and practice. The monthly CPI is disseminated as final. However, bias for changes in the structure of weights are not revised.

  • Data accessibility. The CPI is disseminated via press releases and posted on the NSI website. Detailed tables cover the country and four main cities. They contain indices and percentage changes by chapters, groups, and subgroups. A government policy advisory committee is provided with data that may or may not have been disseminated to the public. However, this practice does not affect the pre-cheduled release. Data are released according to a well established calendar, which is disseminated on the CBB website.

  • Metadata accessibility. Concepts, methodology, and data sources for CPI compilation are available to users on the NSI website.

  • Assistance to users. The NSI provides contact information on the website and publications. Assistance is provided to users by responding to queries and providing photocopies and printouts of tables. Data are available by subscription or upon request.

Table 3c.Bolivia: Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
  • Concepts and definitions. The PPI weights of manufacturing goods are based on the value of gross output, excluding intermediate input, and are in broad conformity with the guidelines in the 1968 SNA and the PPI Manual. The survey to update the PPI weights was conducted in 2005 and follows the 1993 SNA.

  • Scope. The PPI includes prices for 35 groups of manufacturing industries. The share of goods output by economic activity not covered by the index is 15 percent. Geographic coverage is nationwide, excluding Pando. The PPI excludes economic activities, such as agriculture, forestry, mining and quarrying, power, water, gas, construction, and commercial and other services.

  • Classification/sectorization. ISIC rev. 2 is used for classifying the manufacturing industry producer price index (IPPIM). The index is disaggregated by group of activity (four digits), grouping (three digits), and industrial division (two digits).

  • Basis for recording. Market prices of manufactured goods are used. Prices of goods and services are recorded in the period they are purchased.

  • Source data. The principal source for constructing the PPI baskets was the Annual Economic Survey (1990). Coverage by group of economic activity consists of those groups that generate 85 percent of the value added of the manufacturing industry and, within each group, those products that represent more than 70 percent of the gross value of output. Quarterly prices of 125 generic products are collected through direct interviews of 313 establishments. The PPI basket is not fully representative of current national output. Source data are not timely.

  • Assessment of source data. The PPI is subject to validation with respect to individual prices and the different levels of aggregation. The intermediate results for the PPI are validated against those reported for the CPI. Response rates to price surveys and sampling errors are not calculated.

  • Statistical techniques. Missing prices are imputed. PPI uses the Laspeyres formula. Weights have not been updated in 16 years.

  • Assessment and validation of intermediate data and statistical outputs. The PPI is validated with individual prices and different levels of aggregation.

  • Revision studies. Analysis of revisions is conducted but revision studies are not performed.

  • Periodicity and timeliness. Neither periodicity nor timeliness meet GDDS recommendations. The PPI is compiled on a quarterly basis and disseminated 10 weeks after the end of the reference quarter.

  • Consistency. The current quarterly PPI has been published consistently since December 1985. Price statistics are consistent over time and all items index tabulations are consistent with the different aggregations. A chained index between old and new series is available.

  • Revision policy and practice. Newly released PPI data are preliminary and final data are published after 2-3 quarters. Revisions do not follow a regular schedule. Preliminary data are clearly identified, but not revised data. Studies and analyses of revisions are not made public.

  • Data accessibility. The PPI is disseminated quarterly through the Short-term Economic Indicators published by the NSI and annually in the Statistical Yearbook. Data are also available via the Customer Service Unit (CSU). Detailed tables contain indices by division, grouping, and group of manufacturing activity. An advance release calendar is not available.

  • Metadata accessibility. Methodologies on the PPI are available to users in the NSI publication, Indice de Precios, Productor Industrial Manufacturero Sistema de Metadatos. This document is posted on the NSI website.

  • Assistance to users. A contact point is provided on the NSI website. CSU also provides assistance to users by responding to queries and providing photocopies and printouts of tables upon request. The data are also available to the public at the NSI Central Library.

Table 3d.Bolivia: Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
  • Concepts and definitions are broadly consistent with the recommendations of the GFSM1986. The authorities have not yet prepared a plan to migrate to the GFSM2001.

  • Scope for institutional and transaction coverage is incomplete because detailed data of some decentralized units and some local governments are not collected.

  • Classification/sectorization. Departures from the GFSM1986 include: (1) consolidated central government data are not compiled, even though information is available; (2) misclassification of royalties, commissions for interest, tax returns, social assistance benefits, and lending minus repayment; (3) some data are not disaggregated; and (4) classification of tax revenues, financing, and debt do not strictly follow international recommendations.

  • Basis for recording. Mostly done on a cash basis, but some adjustments to accrual are made. Flows are valued at market prices and financial stocks at nominal or face value. Grossing/netting procedures are not fully consistent with international standards.

  • Source data for GFS are: (1) the Integrated System of Management and Administrative Modernization; (2) the integrated system of accounting; (3) the UPF system; (4) the External Debt Management and Financial Analysis System; and (5) independent systems of some public units. These systems are not fully integrated, which leads to undue burden in data collection and compilation. Institutional coverage is incomplete. Data sources are timely and reasonably approximate the recommended definitions, scope, classifications, valuations, and basis of recording.

  • Assessment of source data. Performed routinely by visiting data producing units, cross-checking activities, and conducting data trend analysis. Queries are submitted to data producing units to review and revise the data.

  • Statistical techniques. Techniques for derivation, aggregation, valuation, conversion to domestic currency, preparation of bridge tables, and estimation used for compilation of GFS are sound.

  • Assessment and validation of intermediate data and statistical outputs. Final data are validated against budgetary and accounting data sources.

  • Revision studies and analyses are conducted, but not documented.

  • Periodicity and timeliness for GFS meet GDDS recommendations. Data for the consolidated nonfinancial public sector and consolidated general government are disseminated monthly with a lag of six weeks, foreign public debt data are disseminated monthly with a lag of one month, and domestic public debt data are disseminated weekly with a lag of two days.

  • Consistency. Fiscal data are consistent within the dataset and reconcilable over a reasonable period of time. Consistency with monetary and balance of payments statistics is assessed regularly. Consistency between GFS and national accounts is not verified.

  • Revision policy and practice. The revision schedule is predetermined and reasonably stable, but not made known to the public. The first published annual GFS data are preliminary, and final data are published after the data have been revised. Data tables do not include explanatory notes for revisions made. Revision studies and analysis of revisions are not made public.

  • There is room to improve accessibility to the GFS in the Statistical Bulletin and on the MOF website, which could facilitate proper interpretation of the data and international comparisons. Dissemination media and format are adequate. GFS are disseminated according to a preannounced schedule available on the CBB website and the IMF’s DSBB. GFS are disseminated on the MOF and CBB websites simultaneously to all users.

  • Metadata accessibility. Metadata is only available on the IMF’s DSBB. Metadata has not been updated since November 2005.

  • Assistance to users is provided via a contact e-mail address posted in the MOF publications and website. Documents and other services, including information on any changes, are widely available.

Table 3e.Bolivia: Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
  • Concepts and definitions. Monetary statistics follow the recommendations of the MFSM.

  • Scope. The depository corporations survey (DCS) covers the CBB, all commercial banks, credit unions, savings and loans associations, and the private financial funds. The accounts of banks in liquidation are included. The DCS does not cover seven Investment Funds Management Societies (SAFIs), which issue debit cards to their clients and account for around 6 percent of the ODC’s liabilities included in broad money.

  • Classification/sectorization of financial instruments broadly follows the MFSM, with some exceptions. ODC data do not distinguish between other nonfinancial corporations and other resident sectors. Transactions with SAFIs are classified as transactions with OFCs rather than with ODCs. There are problems of classification and application of residency criterion by some ODCs.

  • Basis for recording. Monetary statistics are produced on an accrual basis, which is consistent with the MFSM. Financial instruments are valued at market prices or amortized cost. Accounts in foreign currency are converted into national currency using the market exchange rate.

  • Source data. The DC survey is based on the consolidated balance sheets of the CBB and ODCs. The SBFE provides the CBB with daily balance sheets of the ODCs and a monthly report with a detailed sectorization of the accounts.

  • Assessment of source data. The Economic Policy Advisory Office (APEC) has electronic access to the accounting records of the CBB. Data for the ODCs are validated by the SBFE and electronically processed by the APEC.

  • Statistical techniques. Sound statistical techniques are used. The DCS is based strictly on the balance sheets of the CBB and the ODCs, and the supplementary monthly report with more detailed sectorization of the accounts of the ODCs.

  • Assessment and validation of intermediate data and statistical output. Monetary data are validated through the accounting identity: net foreign assets plus net domestic assets equal broad money. Interbank positions are automatically validated by the SBEF. Credit to the public sector is compared with debtor’s data.

  • Revision studies. Analyses and studies of revisions are conducted and documented. The results of these studies are used to improve the statistical process.

  • Periodicity and timeliness meet GDDS recommendations and SDDS requirements.

  • Consistency. Monetary data are disseminated in consistent historical series. Discrepancies arise in the aggregated accounts of the ODCs because the SAFIs report claims on commercial banks for deposit certificates, which are reported as liabilities to the private sector (deposits) by commercial banks. Monetary data are consistent with balance of payments and government finance data.

  • Revision policy and practice. The CBB does not have a regular revision schedule because data are disseminated as final and revisions are infrequent. Revisions studies are not disseminated, but revisions resulting from changes in methodology are documented in footnotes to the tables. Preliminary data are clearly identified.

  • Data accessibility. Data are presented in an aggregated form with methodological notes. The CBB publishes an advance release calendar. Data are posted on the CBB website and published in the CBB Monthly Bulletin. A government policy advisory committee is provided with data that may or may not have been disseminated to the public. However, this practice does not affect the pre-scheduled release.

  • Metadata accessibility. Bolivia has posted its monetary metadata on the IMF’s DSBB since November 2000. The CBB website contains metadata and provides a hyperlink to the IMF’s DSBB.

  • Assistance to users. Information on the contact person for monetary statistics is available on the CBB website and also on the IMF’s DSBB. There is a catalog with CBB’s publications, documents, and other services to users.

Table 3f.Bolivia: Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
  • Concepts and definitions broadly follow the BPM5 guidelines. Resident units are defined in conformity with BPM5.

  • Scope is broadly consistent with BPM5. However, data exclude: (1) unrecorded trade (contraband, shuttle trade, and illegal trade); (2) some government bonds issued locally and held by nonresidents; and (3) deposits of nonresidents in the financial sector.

  • Classification/sectorization are broadly in line with BPM5 guidelines. However, more detailed breakdown is needed for the classification of several services. In addition, there are instrument misclassifications (e.g., trade credits are included in loans) and capital transfers are included in current transfers. Most institutional units are attributed to the relevant sector according to the BPM5.

  • Basis for recording. In general, the principle of market valuation is used. However, flows derived from stocks of nonbank deposits abroad (assets) are not adjusted for exchange rate changes. Recording is mostly done on an accrual basis in accordance with BPM5, but interest on public sector external debt is recorded on a due-for-payment basis, and some dividends are recorded when paid rather than when declared payable.

  • Source data are broadly sufficient to compile statistics. Data sources include (1) CBB data; (2) administrative data from the NSI, the SBFE, and other government entities; (3) surveys; (4) direct reporting mainly by nonfinancial entities; and (5) data from foreign/international institutions. Source data for certain services and financial transactions could be improved. Survey data for travel and foreign direct investment from the NSI have not been available since 2004–05, respectively. Hence, the CBB initiated a Foreign Private Capital (FPC) survey in November 2006. The travel survey is expected to be resumed in 2007.

  • Assessment of source data. Source data are routinely checked and analyzed to guide the statistical process.

  • Statistical techniques are used (some of which may need improvement) mainly to adjust trade data, estimate direct investment flows/stocks, and overcome insufficient coverage of services, workers' remittances, and private transfers. The CBB does not estimate unrecorded trade, including illegal activities.

  • Assessment and validation of intermediate data and statistical output. Statistical discrepancies are monitored. Data are validated against available administrative data (including balance sheets) and other dataseis.

  • Revision studies. Analysis of revisions informs statistical processes but they are not regularly documented.

  • Periodicity and timeliness of balance of payments data meet GDDS recommendations and SDDS requirements.

  • Consistency. Balance of payments data are broadly consistent internally and over time. However, errors and omissions are large in some years (an average of 4 percent of GDP during 1995-2005). Balance of payments and IIP data are reconciled quarterly. Data are largely consistent and/or reconcilable with merchandise trade, monetary, GFS, and external debt statistics. However, consistency with national accounts is not verified on a regular basis and may be affected by the lack of estimates of illegal trade, which are imputed in the national accounts.

  • Revision policy and practice. The revision cycle is predetermined and stable, but it is not publicized. Preliminary and revised data are identified. Analyses of data revisions are not disseminated.

  • Data accessibility. Data are disseminated in a format that follows BPM5 standard components. A wide range of data are readily available in different formats and detailed presentations. Time series are available on the CBB website. Data are released on a preannounced schedule and made available to all users simultaneously on the CBB website and in hardcopy publications.

  • Metadata accessibility. Concepts, methodology, and data sources for the balance of payments are available on the CBB website and on the IMF’s DSBB. In addition, the External Sector Bulletin includes a comprehensive sources and methods document.

  • Assistance to users is adequate. The CBB website clearly identifies two contact points for balance of payments data. Contact information is also provided on the Fund’s DSBB.

14. In order to complement the Fund’s assessment of the quality of official statistics, the mission conducted an informal survey of key users of macroeconomic statistics. Questionnaires were sent to a broad range of users who were asked to evaluate key aspects of data quality. Surveys were sent to 329 targeted users, with 85 of them submitting responses, including the main users of official statistics.

15. On a five point scale (1 = poor and 5 = excellent), the average rating for the overall quality of official statistics for all sectors was 3.5. A majority of the respondents expressed satisfaction with the methodological soundness of the data and believed that Bolivia’s statistics were comparable to the statistics disseminated by neighboring countries. Respondents also indicated that they were satisfied with the level of coverage and detail as well as the periodicity. However, respondents expressed general dissatisfaction with the accessibility to metadata and timeliness, particularly of national accounts.

16. Several respondents suggested that the level of detail of economic statistics be expanded by disseminating, for example, GDP by region. In addition, users expressed interest in a producer price index, increased periodicity of labor statistics, and forward looking indicators of economic activity. A more detailed analysis of the Users' Survey and the tabulated results are included in Appendix IV of the accompanying document Detailed Assessments Using the Data Quality Assessment Framework (DQAF).

III. Staff’s Recommendations

Based on the review of Bolivia’s statistical practices, discussions with the data producing agencies, and responses from data users, the mission presents a set of recommendations. They are designed to further increase adherence to internationally accepted statistical practices and would enhance the analytical usefulness of Bolivia’s statistics. The recommendations are subdivided into “High priority” and “Other key recommendations.” While all the high priority actions listed below should be treated as such, the cross-cutting recommendations need to be addressed with the greatest priority. More detailed technical suggestions are included in the Detailed Assessments volume for each dataset.

Cross-cutting Recommendations

High Priority

  • Improve coordination among and within public institutions to facilitate information sharing and to avoid potential duplication in data collection and dissemination, as well as to improve intersectoral consistency.

  • Ensure that agencies and units compiling macroeconomic statistics have adequate resources to undertake needed developmental work.

  • Disseminate macroeconomics statistics simultaneously to all users, publicizing any prior access granted to selected users.

  • Promote the adoption of the new Statistics Law and a National Statistical Plan.

  • Strengthen data sources across all datasets, including surveys and censuses.

Other key recommendations

  • Establish regular mechanisms to monitor the relevance of the statistics and to identify emerging data needs.

  • Provide advance notice of changes in methodology, source data, and statistical techniques and disseminate advance release calendars, revision policies, and revision studies.

National Accounts

High Priority

  • Formulate a comprehensive data collection program of economic censuses and surveys to support the compilation of the national accounts.

  • Improve timeliness of national accounts to meet SDDS requirements.

  • Give high priority to the ongoing project to update the national accounts’ reference year and implement the 1993 SNA, and bring forward the targeted completion date.

  • Improve the quality of the Volume and Producer Price Indices for manufacturing activities and improve the coverage and quality of volume measures for construction, commerce, and service activities.

  • Assess the feasibility of using the households survey, and other sources, where available, to estimate the participation of the informal sector in GDP, and changes in employment and income generation.

Other key recommendations

  • Apply COFOG to the classification of government consumption expenditures.

  • Assess feasibility of compiling directly the changes in inventories for important products.

Consumer Price Index

High Priority

  • Update the CPI basket on the basis of results from the 2003/2004 HBS and the CPI Manual 2004.

Other key recommendations

  • Improve treatment of seasonal products, missing items, quality changes, and introduction of new products.

  • Calculate retroactive index series using chain linking between old a new series.

Producer Price Index

High Priority

  • Adopt the 1993 SNA concepts and definitions, including new weights, changes in inventories, own-account production for final use, and the coverage of economic activities.

  • Improve treatment of seasonal products, missing items, quality changes, and introduction of new products.

  • Improve periodicity and timeliness to meet GDDS recommendations.

Other key recommendations

  • Change the base year of the PPI, updating its weights by using output by industry and including all goods producing activities.

  • Asses PPI data source and calculate the variance or sampling errors to guide the new PPI sample design.

  • Calculate retroactive index series using chain linking, between old a new series.

Government Finance Statistics

High priority

  • Ensure reporting of detailed data on the operations of all general government institutional units to the MOF.

  • Compile and disseminate GFS for operations of the consolidated central government (including budgetary, extrabudgetary, and social security subsectors) and general government (including consolidated central government and regional and local government subsectors) following international best practices.

  • Centralize the compilation of GFS to ensure intra-agency coordination, timely dissemination, and avoid overlapping responsibilities.

  • Integrate and standardize data sources for improving consistency of the GFS and for reducing the collection and compilation burden.

Other key recommendations

  • Adopt a migration plan to the GFSM 2001.

  • Improve presentation of GFS in hard copy and electronic publications.

Monetary Statistics

High Priority

  • Expand the ODC survey with the inclusion of the accounts of the SAFIs.

  • Reclassify accounts of SAFIs from OFCs to ODCs and separate the accounts of the private nonfinancial resident sector into accounts of “other nonfinancial corporations” (private enterprises) and “other resident sectors” (households and NPISHs).

Other key recommendations

  • In collaboration with the SBFE, monitor that in the “sectoral accounts,” ODCs are properly classifying accounts of nonresidents.

  • Compile a monthly OFC survey, with data from insurance corporations, pension funds, NAFIBO, and FONDESIF.

  • Facilitate staff access to Internet and telecommunications.

Balance of Payments Statistics

High Priority

  • In consultation with the NSI, develop a methodology to include unrecorded trade and its counterpart transactions in the BOP.

  • Provide additional staff resources to the BPD to undertake additional tasks associated with the recent introduction of the CBB’s Foreign Private Capital (FPC) survey.

  • Initiate in 2007 quarterly FPC surveys, identifying improvements in design, data validation, and sample techniques, based on the results of the 2006 FPC survey.

  • Continue efforts to improve data collection and estimation techniques for workers’ remittances and other transfers, and certain services and financial transactions.

Other Key Recommendations

  • Resume in 2007 the semiannual travel survey, jointly conducted by NSI and CBB.

  • Apply the accrual principle for recording interest on public sector external debt.

  • Review external debt relief data recording to ensure that treatment is consistent with BPM5, including the recording of debt forgiveness in the capital account.

  • Compile and disseminate data on the external debt-service payment schedule (for total and public sector external debt), in line with the External Debt Guide.

Appendix I. Bolivia: Practices Compared to the GDDS Coverage, Periodicity, and Timeliness of Data
GDDS Data CategoryCoverage (meets GDDS)PeriodicityTimeliness
GDDSBoliviaGDDSBolivia
Data Categories and Indicators
Real Sector
National accounts aggregates:
GDP (nominal and real)YesA (Q)Q6–9 M3 M
Gross national income, capital formation, savingYesAA6–9 M11 M
Production index/indices
Manufacturing or industrial indicesYesMQ6 W2
Primary commodity, agricultural, or other indices, as relevant 1YesAs relevantM3 M6 W
Price indices:
Consumer price indexYesMM1–2 M1 D
Producer price indexYesMQ1–2 M10 W
Labor market indicators:
EmploymentYesAQ (public) 2 Q (private)6–9 MQ (public) 4 M (private)
UnemploymentYesAA6–9 M4 M
Wages/earnings (all sectors)YesAQ (public) 2 Q (private)6–9 MQ (public) 4 M (private)
Fiscal Sector
Central government aggregates:
Revenue, expenditure, balance, and financing with breakdowns (debt holder, instrument, currency), as relevantNoQM1 Q6W
Interest paymentsYesQM1 Q6W
Central government debt:
Domestic and foreign debt, as relevant, with appropriate breakdowns (currency, maturity, debt holder, instrument)YesA (Q)W (domestic) M (foreign)1–2 Q2D (domestic) 1M (foreign)
Government guaranteed debtYesA (Q)M1–2 Q1 M
Financial Sector
Broad money and credit aggregates:
Net external position, domestic credit, broad or narrow moneyYesMM1–3 M3 W
Central bank aggregates:
Monetary baseYesMD1–2 M1 W
Interest rates:
Short- and long-term government. security rates, policy variable rateYesMD31 W
Money or interbank market rates and a range of deposit and lending ratesYesMW31 W
Stock market:
Share price index, as relevantNot relevantM(…)3(…)
External Sector
Balance of payments aggregates:
Imports and exports of goods and services, current account balance, reserves, overall balance.YesA (Q)Q6 M7 W
External debt and service:
Public and publicly guaranteed external debt, broken down by maturityYesQM1–2 Q1 M
Public and publicly guaranteed debt service schedule 4YesTwice A(…)3–6 M(…)
Private external debt not publicly guaranteed, and debt service scheduleStock: YesServiceschedule: NoAStock: QServiceschedule: No6–9 MStock: 3 MServiceschedule: No
International reserves:
Gross official reserves denominated in U.S. dollarsYesMM1–4 W4 W
Reserve-related liabilitiesYesMM1–4 W4 W
Merchandise trade:
Total exports and total importsYesMM8 W–3 M1 M
Major commodity breakdowns with longer time lapseYesMM8 W–3 M1 M
Exchange rates:
Spot ratesYesDD3Same day
D = Daily; W = Week(ly); WD = Working days; M = Month(ly); Q = Quarter(ly); A = Annually; NLT = No later than; (…) = not applicableItalics indicate encouraged categories.

Indexes for construction, telecommunications, electricity, transportation, hydrocarbons, and mining.

While the index is compiled on a quarterly basis, it is only disseminated annually in the NSI’s Statistical Yearbook.

3 Dissemination as part of a high-frequency (e.g. monthly) publication.

Data are compiled but not disseminated.

D = Daily; W = Week(ly); WD = Working days; M = Month(ly); Q = Quarter(ly); A = Annually; NLT = No later than; (…) = not applicableItalics indicate encouraged categories.

Indexes for construction, telecommunications, electricity, transportation, hydrocarbons, and mining.

While the index is compiled on a quarterly basis, it is only disseminated annually in the NSI’s Statistical Yearbook.

3 Dissemination as part of a high-frequency (e.g. monthly) publication.

Data are compiled but not disseminated.

A detailed description of the SDDS can be found on the IMF’s Data Standards Bulletin Board (DSBB) on the Internet at http://www.dsbb.imf.org. A summary is presented in Appendix II of the Detailed Assessment document.

For a detailed description of the flexibility options see the Guide to the Data Dissemination Standards, 1996 (56–59).

Other Resources Citing This Publication