I. Overall Assessment

1. Chile subscribed to the Special Data Dissemination Standard (SDDS) on May 17, 1996 and started posting its metadata on the Dissemination Standards Bulletin Board (DSBB) on February 19, 1997. Chile is in observance of the SDDS, meeting the specifications for coverage, periodicity, timeliness, and the dissemination of advance release calendars. Chile uses a flexibility option on the timeliness of the central government operations data; although at present it meets SDDS requirements in this regard. Appendix I provides an overview of Chile’s dissemination practices compared to the SDDS.

2. This Report on the Observance of Standards and Codes (ROSC) data module is a reassessment of the exercise conducted in April 2001 but applies an updated framework and covers national accounts, prices, government finance, monetary, and balance of payments statistics. Of these datasets, the National Statistics Institute (NSI) is responsible for price statistics, the Central Bank of Chile (CBCH) is responsible for national accounts, monetary, and balance of payments statistics, and the Budget Directorate (DIPRES) of the Ministry of Finance (MOF) is responsible for the government finance statistics. The Superintendency of Banks and Financial Institutions (SBFI) collects monetary data. Since the assessment in 2001, major methodological improvements include the change of benchmark year of national accounts (NA) and the compilation of a producer price index (PPI), the implementation of the Balance of Payments Manual, fifth edition (BPM5), and the adoption of the Government Finance Statistics Manual 2001 (GFSM2001). Chile’s macroeconomic statistics are timely, generally of high quality, and adequate to conduct effective surveillance. There is a high degree of quality awareness among Chile’s statistical managers and a reputation of integrity of the statistical institutions and processes among data users. However, there is scope for improvement in some areas. Resources at the NSI are inadequate; coordination among statistical agencies should be enhanced, including to ensure intersectoral consistency; there are certain weaknesses in key source data; consultation with users and user groups is inadequate; the legal framework governing the NSI and the legal mandate to request statistical data to the nonfinancial private sector needs to be reinforced; and there is scope for improvement in methodological soundness, particularly regarding classification and sectorization. Moreover, there is a need for a more comprehensive and extensive treatment in the statistics of the copper sector which is pervasively important to a full understanding of the Chilean economy.

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 four. Section II provides a summary assessment by agency and dataset based on a four-point rating scale. This is followed by staff recommendations in Section III. The authorities’ response to this report and a volume of detailed assessments are presented in separate documents.

4. Regarding prerequisites of quality, legal and institutional frameworks are generally adequate, but the independence of the NSI needs to be reinforced. Also, there are no legal precepts empowering the CBCH to require private institutions to respond to data requests solely for statistical purposes, except for information on foreign exchange transactions.¹ Resources are adequate at the CBCH and at the SBFI. Resources need to be strengthened at the DIPRES of the MOF to complete the migration to the GFSM 2001 and ensure adequate business continuity and data sharing. Resources are inadequate at the NSI to ensure (1) the regular updating of the business register, (2) well-diversified outlet and enterprise samples, (3) continuous analysis and implementation of methodological enhancements and improvements in the validation and timeliness of source data for national accounts and price statistics, (4) reliable business continuity planning, and (5) appropriate quality adjustments to price statistics. Macroeconomic datasets could be improved in meeting users’ needs as there are no regular consultations with public and private sector users and user groups have not been fostered. Public knowledge on the PPI is scant and the index credibility has not been well established.

5. The Chilean statistical agencies get high marks in assurances of integrity as they adhere firmly to the principle of objectivity in the collection, processing, and dissemination of statistics. Chile’s macroeconomic and financial institutional environment rests on four pillars: (1) an autonomous central bank that conducts the monetary policy under an inflation targeting scheme, (2) a fiscal policy governed by a fiscal rule aimed at achieving a structural fiscal surplus, which considers long-run copper prices and projected copper output levels (given the significance of copper in the Chilean’s economy), (3) a regulation and supervision of the financial sector according to international standards involving several supervisory entities (including the SBFI), and (4) integration with international markets through trade openness, free capital mobility, and a floating exchange rate regime. There is awareness that policymaking, and decision making in general, require adequate macroeconomic statistics and indicators to monitor significant developments in the economy and to watch for early warnings. Agencies demonstrate professionalism, are transparent in their policies and practices, and provide guidelines to their staff on ethical conduct. Each agency has well-established and documented practices to ensure professionalism and impartiality in their work. Major changes in the conceptual framework, source data, and statistical techniques of macroeconomic statistics are announced in advance. However, at the NSI the short tenure of directors and deputy directors (three years plus one possible renewal) and discretion for removal are not supportive of professional independence. The NSI, MOF, and CBCH statisticians participate with colleagues from other countries in working groups, committees, and other fora leading to close cooperation in statistical matters, and increasing opportunities for sharing good practices and enhancing professionalism. Examples are Chile’s membership in the IMF’s Balance of Payments Committee, and its participation in the International Comparison Program and the UN Ottawa Group on Price Indices (Ottawa Group), and in the Organisation for Economic Cooperation and Development (OECD) as an observer. Although beyond the scope of this assessment, Chile is also participating in the Coordinated Compilation Exercise for Financial Soundness Indicators.

6. Regarding methodological soundness, the macroeconomic statistics broadly follow internationally accepted standards, guidelines, and good practices on definitions, scope, classification and sectorization, and basis for recording. There are some areas for improvement in the scope of the NA regarding the treatment of mineral exploration, agricultural work in progress, and own-account production of computer software, databases, and manufacturing products. There is also room for improvement in the classification of copper derivatives, the functions of government, and individual consumption by purpose.² The consumer price index (CPI) has a limited geographic coverage.³ The basket includes interest rates on consumption loans and mortgage payments with an inconsistent treatment with best practice, and an erroneous classification of educational services that may introduce a downward bias. The PPI does not register copper price movements on an accrual basis. Regarding government finance statistics (GFS), the institutional and transactional coverage for the general government are incomplete. Sectorization is broadly in line with the GFSM 2001, but significant deviations from the GFSM 2001 exist regarding classification systems. Aggregates that do not conform to the GFSM 2001 framework are revenues from copper, subsidies and grants, capital transfers, financing transactions, and the stock of central government debt. Chile’s monetary statistics are in line with the Monetary and Financial Statistics Manual (MFSM), with a few nonmaterial departures regarding the valuation of financial instruments, accrual of interest on nonperforming loans, and the recording of gold holdings at the CBCH. Securities issued by the CBCH and liabilities of mutual funds are not properly sectorized in the CBCH and Other Depository Corportions (ODCs) surveys, respectively. Chile’s balance of payments (BOP) statistics are broadly in line with the BPM5, but there are a few departures regarding the basis for recording public and private sector external debt (where interest is recorded on a cash basis) and some foreign direct investment transactions.

7. Accuracy and reliability of macroeconomic statistics in Chile are adequate. Source data and statistical techniques are sound and statistical outputs sufficiently portray reality. Looking forward, rapid expansion of services and of the financial system presents challenges to ensure reliable source data and continuous compliance with international standards. The business register is partially outdated and not updated regularly, while the frequency of the Household Budget Survey (HBS) is not in line with international best practice, which may affect the quality of household consumption expenditure data for NA. The source data available for agriculture, fishing, some services, and quarterly estimates are limited in scope. Lack of timeliness in validating data on the NSI’s surveys limits their potential use. For most surveys, scientific sampling techniques are not used. For the HBS and most business surveys, no information is available concerning sampling errors and nonsampling errors. There are no explicit estimates of nonobserved activities (informal, unrecorded, and underground activities). Changes in inventories are obtained as residuals in the framework of the supply-and-use table and hence their resulting price movements are erratic. The CPI basket and weight structure are outdated, but there are plans to address this weakness. CPI source data consistency is not verified with other sources of information. Procedures to refresh outlets in the CPI sample are not in place, adjustments for quality differences are generally not made, and sources of errors are not investigated routinely. For the PPI, adjustments for quality differences are not made (in particular, the copper price recollection procedure increases quality induced volatility), and missing prices are carried forward from the last observed price in most of the categories. Regarding the GFS, stock data on financial assets and liabilities are only recorded at face value. Monetary statistics could be enhanced through additional validations of source data and cross-checking with fiscal data.

8. Serviceability of macroeconomic statistics gets high marks, as confirmed by the results of the users’ survey conducted prior to the mission’s arrival to Santiago. Macroeconomic statistics are available with adequate periodicity and timeliness. Most datasets follow the international good practices of providing the public with a clear statement of the revision schedule and of identifying provisional estimates. Macroeconomic statistics are broadly consistent. Some inconsistencies between NA and GFS resulting from differences in coverage, sectorization, and classification are reconcilable. GFS are not internally consistent due to differences in source data and valuation methods used to compile debt flows and stocks. In addition, GFS are not routinely reconciled with data from other data producing agencies, except for NA. Monetary data on net credit to the government are not reconciled with fiscal data. BOP statistics are not consistent with external debt statistics (which value portfolio liabilities on a nominal basis), but differences are reconcilable. GFS are not entirely consistent with external debt statistics due to discrepancies in the residence criteria.

9. Accessibility to macroeconomic statistics is very good. All datasets are readily available to the public in electronic form and, in general, are easily downloadable from the websites of the data-producing agencies (particularly from the CBCH’s website), and presented in a user-friendly format. However, price statistics are not presented in a way that facilitates proper interpretation and meaningful comparisons. Appropriate analysis of current-period price developments is not included with press releases and data dissemination formats hinder redissemination and analysis of inflation trends. The NSI does not publish the X1 price index (the CBCH’s core inflation definition) although the estimate is prepared by the CBCH. A PPI indicator that excludes copper effects on its volatility is not published. The NSI’s website provides a comprehensive description of CPI metadata but only a summary of the PPI metadata and no detailed PPI time series. Macroeconomic statistics are made available simultaneously to all users. Unpublished, nonconfidential data are made available to users on request.

10. To enrich the basis for the assessment, the mission elicited the views of selected users of macroeconomic statistics. With the assistance of the CBCH and the NSI, a users’ survey was conducted (with 50 respondents), and meetings were held with selected users. Most users were satisfied with the methodological soundness, timely dissemination, accessibility, and frequency of official macroeconomic statistics. However, they identified some areas where there is scope for improvement. In particular, it appears that the PPI lacks credibility and is not much used. The coverage and detail of GFS and PPI are seen as insufficient, and some users did not know whether an early release calendar for GFS existed and was met. A number of users indicated that the information on revisions on NA, PPI, GFS, and BOP could be improved. They also found somewhat difficult the access to metadata on NA, PPI, and GFS. Some users expressed an interest in more detailed and longer time series on NA, BOP, PPI, the monthly index of economic activity (IMACEC), and GFS. A considerable number of users emphasized the need for data on household income distribution, average prices by industry, volume of sales by industry, and reliable and consistent series on employment statistics.

II. Assessment by Agency and Dataset

11. Assessment of the quality of six macroeconomic datasets—NA, CPI, PPI, GFS, monetary, and BOP statistics—were conducted using the DQAF July 2003. 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-d. 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.

Chile: Data Quality Assessment Framework July 2003—Summary Results

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 1.

Chile: 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
		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		LO	O	LO	LO	O	LO
0.2	Resources		O	LNO	LNO	LO	O	O
0.3	Relevance		LO	LO	LNO	LO	LO	LO
0.4	Other quality management		O	O	O	O	O	O
1.	Assurances of integrity
1.1	Professionalism		O	LO	LO	O	O	O
1.2	Transparency		O	O	O	O	O	O
1.3	Ethical standards		O	O	O	O	O	O
2.	Methodological soundness
2.1	Concepts and definitions		O	LO	O	O	O	O
2.2	Scope		LO	LNO	O	LO	O	O
2.3	Classification/sectorization		LO	LNO	LO	LNO	LO	LO
2.4	Basis for recording		LO	LO	LO	LO	O	LO
3.	Accuracy and reliability
3.1	Source data		LO	LO	O	LO	O	O
3.2	Assessment of source data		LO	LO	O	O	O	O
3.3	Statistical techniques		LO	LO	LO	O	O	O
3.4	Assessment and validation of intermediate data and statistical outputs		LO	O	O	LO	LO	O
3.5	Revision studies		O	LO	LO	O	O	O
4.	Serviceability
4.1	Periodicity and timeliness		O	O	O	O	O	O
4.2	Consistency		O	O	O	LO	O	O
4.3	Revision policy and practice		O	O	O	O	O	O
5.	Accessibility
5.1	Data accessibility		LO	LO	LO	O	O	O
5.2	Metadata accessibility		O	O	O	O	O	O
5.3	Assistance to users		O	O	O	LO	O	O

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.

View Table

Table 1.

Chile: 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
		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		LO	O	LO	LO	O	LO
0.2	Resources		O	LNO	LNO	LO	O	O
0.3	Relevance		LO	LO	LNO	LO	LO	LO
0.4	Other quality management		O	O	O	O	O	O
1.	Assurances of integrity
1.1	Professionalism		O	LO	LO	O	O	O
1.2	Transparency		O	O	O	O	O	O
1.3	Ethical standards		O	O	O	O	O	O
2.	Methodological soundness
2.1	Concepts and definitions		O	LO	O	O	O	O
2.2	Scope		LO	LNO	O	LO	O	O
2.3	Classification/sectorization		LO	LNO	LO	LNO	LO	LO
2.4	Basis for recording		LO	LO	LO	LO	O	LO
3.	Accuracy and reliability
3.1	Source data		LO	LO	O	LO	O	O
3.2	Assessment of source data		LO	LO	O	O	O	O
3.3	Statistical techniques		LO	LO	LO	O	O	O
3.4	Assessment and validation of intermediate data and statistical outputs		LO	O	O	LO	LO	O
3.5	Revision studies		O	LO	LO	O	O	O
4.	Serviceability
4.1	Periodicity and timeliness		O	O	O	O	O	O
4.2	Consistency		O	O	O	LO	O	O
4.3	Revision policy and practice		O	O	O	O	O	O
5.	Accessibility
5.1	Data accessibility		LO	LO	LO	O	O	O
5.2	Metadata accessibility		O	O	O	O	O	O
5.3	Assistance to users		O	O	O	LO	O	O

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.

Chile: Assessment of Data Quality—Dimensions 0 and 1—National Statistics Institute

Table 2a.

Chile: Assessment of Data Quality—Dimensions 0 and 1—National Statistics Institute

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment The NSI operates under an adequate legal framework. The legislation supporting CPI and PPI compilation is established in Law 17374 of 1970, which guarantees the confidentiality of individual reporters’ data (breach of confidentiality has a criminal punishment, Art. 29 and 30). The Law does not specify the responsibility of the NSI to compile source data for national accounts purposes. Statistical reporting is mandatory according to the Law (penalties specified in Art. 22 act as an effective deterrent, even though in some cases these seem to be low). Statistics are reviewed periodically by the National Statistics Commission (composed by the NSI, several public entities, universities, and representatives from the private sector and labor unions). The commission facilitates data sharing and coordination among statistics producing agencies, and also makes recommendations on processes and methodologies, but coordination is insufficient. Resources The price statistics program lacks adequate staff, facilities, and computing resources. Insufficient staff precludes attaining a well-diversified outlet sample, a continuous analysis and implementation of methodological improvements, and appropriate quality adjustments to price statistics. Computers and compilation software are outdated. In the event of no access to the NSI’s facilities, compilation of the CPI would not be possible. Office space and equipment are not adequate (more space, a cooling system, and telephone lines are required). Resources to update regularly the business register and to conduct and validate surveys for national accounts statistics are also insufficient. Relevance The NSI has periodic meetings with the CBCH to identify emerging CPI requirements, but there is no structured consultation process for the PPI. Public knowledge on the PPI is scant and index credibility is low. The NSI seeks to implement international standards that should better attend users’ needs. Other quality management The NSI is quality conscious. Staff has been trained on quality management systems. Although the NSI has not implemented an externally recognized process to focus on quality, it is planning to implement an ISO 9001:2000 quality management system on the CPI by December 2007 and on the PPI by December 2008.

Professionalism Law 17374 of 1970 recognizes the independence of the NSI to determine the methodology, release dates, design of surveys, and use of definitions. Data gathering is objective and impartial. The NSI Director is appointed by the President of the Republic from a group proposed by the Civil Service Council. Deputy directors are elected by the director from a group proposed by the aforementioned Council. However, the short tenure in both cases (three years plus one possible renewal) and discretion for removal are not supportive of professional independence. Hirings and promotions are based on relevant aptitude, but there is a significant legal rigidity to terminate contracts with nonperforming staff members. Transparency The terms and conditions under which the statistics are produced and disseminated are available to the public. Government officials outside the NSI have no access to the data before public release. However, a vulnerability within the NSI is that staff from the Corporate Image Department (which does not belong to the Price Statistics Department) has access to CPI and PPI results prior to their release. Major methodological changes are usually announced to the public in advance. Ethical standards The Administrative Statute Law, Law 18834 of 1989, details the public servants obligations and prohibitions, and forbids specific activities to avoid conflict of interest. Penalties are specified in cases of noncompliance

View Table

Table 2a.

Chile: Assessment of Data Quality—Dimensions 0 and 1—National Statistics Institute

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment The NSI operates under an adequate legal framework. The legislation supporting CPI and PPI compilation is established in Law 17374 of 1970, which guarantees the confidentiality of individual reporters’ data (breach of confidentiality has a criminal punishment, Art. 29 and 30). The Law does not specify the responsibility of the NSI to compile source data for national accounts purposes. Statistical reporting is mandatory according to the Law (penalties specified in Art. 22 act as an effective deterrent, even though in some cases these seem to be low). Statistics are reviewed periodically by the National Statistics Commission (composed by the NSI, several public entities, universities, and representatives from the private sector and labor unions). The commission facilitates data sharing and coordination among statistics producing agencies, and also makes recommendations on processes and methodologies, but coordination is insufficient. Resources The price statistics program lacks adequate staff, facilities, and computing resources. Insufficient staff precludes attaining a well-diversified outlet sample, a continuous analysis and implementation of methodological improvements, and appropriate quality adjustments to price statistics. Computers and compilation software are outdated. In the event of no access to the NSI’s facilities, compilation of the CPI would not be possible. Office space and equipment are not adequate (more space, a cooling system, and telephone lines are required). Resources to update regularly the business register and to conduct and validate surveys for national accounts statistics are also insufficient. Relevance The NSI has periodic meetings with the CBCH to identify emerging CPI requirements, but there is no structured consultation process for the PPI. Public knowledge on the PPI is scant and index credibility is low. The NSI seeks to implement international standards that should better attend users’ needs. Other quality management The NSI is quality conscious. Staff has been trained on quality management systems. Although the NSI has not implemented an externally recognized process to focus on quality, it is planning to implement an ISO 9001:2000 quality management system on the CPI by December 2007 and on the PPI by December 2008.

Professionalism Law 17374 of 1970 recognizes the independence of the NSI to determine the methodology, release dates, design of surveys, and use of definitions. Data gathering is objective and impartial. The NSI Director is appointed by the President of the Republic from a group proposed by the Civil Service Council. Deputy directors are elected by the director from a group proposed by the aforementioned Council. However, the short tenure in both cases (three years plus one possible renewal) and discretion for removal are not supportive of professional independence. Hirings and promotions are based on relevant aptitude, but there is a significant legal rigidity to terminate contracts with nonperforming staff members. Transparency The terms and conditions under which the statistics are produced and disseminated are available to the public. Government officials outside the NSI have no access to the data before public release. However, a vulnerability within the NSI is that staff from the Corporate Image Department (which does not belong to the Price Statistics Department) has access to CPI and PPI results prior to their release. Major methodological changes are usually announced to the public in advance. Ethical standards The Administrative Statute Law, Law 18834 of 1989, details the public servants obligations and prohibitions, and forbids specific activities to avoid conflict of interest. Penalties are specified in cases of noncompliance

Table 2b.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Budget Directorate of the Ministry of Finance

Table 2b.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Budget Directorate of the Ministry of Finance

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment The Annual Budget Laws (Decree-Law 1263 of 1975 and Decree with Legal Power 106 of 1960) set a general framework for budgetary planning, execution, and reporting applicable to central government units, and provide the DIPRES of the MOF with the legal authority to compile and disseminate GFS. More recently, the Law of Fiscal Responsibility (Law 20128 of 2006) empowers the DIPRES to collect data on transactions regulated by the Reserved Copper Law (Law 13196 of 1976), both for stocks and flows. The Law on Municipalities (Decree with Legal Power 1/18695 of 2006) and the Law on Municipal Resources (Decree 2385 of 1996) set the responsibility of local governments regarding the preparation of annual financial statements, and reporting to the Office of the Comptroller General (OCG). There is room for improvement in data sharing and coordination among the various units involved in the compilation process. GFS are compiled using mostly publicly available data. Resources At present, the number of staff devoted to produce GFS is barely adequate. In the medium term, additional resources may be necessary to complete the migration to the GFSM2001 methodology. Most staff is well trained in the GFSM 2001. Physical resources are adequate. Relevance The DIPRES monitors the relevance of GFS through informal contacts with other departments and data users through e-mail inquiries, personal contacts, and press conferences. However, there are no user advisory groups. Other quality management Quality is a main concern for GFS production. Beginning in 2007, the DIPRES will be audited using the ISO 9001:2000 international quality standard.

Professionalism. The Administrative Statute (Law 18834 of 1989) and the Law of Administrative Probity (Law 19653 of 1999) assist in ensuring impartiality in the work of civil servants. Professionalism is actively promoted and supported within the organization through external and on-the-job staff training. Statisticians are free from political influence in choosing data sources and methods for compiling GFS, and changes to statistical processes are not influenced by political considerations. The DIPRES is entitled to comment and respond to misused or misinterpreted fiscal statistics. Transparency Laws and regulations governing the compilation and dissemination of GFS are freely available to the public, with the exception of the Reserved Copper Law. No government officials outside the DIPRES have access to the data before they are released to the public, and the data are made available simultaneously to all interested parties. Ethical standards Aside from the Administrative Statute and the Law of Administrative Probity, several codes of conduct governing the behavior of the central government and local government employees ensure that data compilation and dissemination are performed according to strictly professional considerations.

View Table

Table 2b.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Budget Directorate of the Ministry of Finance

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment The Annual Budget Laws (Decree-Law 1263 of 1975 and Decree with Legal Power 106 of 1960) set a general framework for budgetary planning, execution, and reporting applicable to central government units, and provide the DIPRES of the MOF with the legal authority to compile and disseminate GFS. More recently, the Law of Fiscal Responsibility (Law 20128 of 2006) empowers the DIPRES to collect data on transactions regulated by the Reserved Copper Law (Law 13196 of 1976), both for stocks and flows. The Law on Municipalities (Decree with Legal Power 1/18695 of 2006) and the Law on Municipal Resources (Decree 2385 of 1996) set the responsibility of local governments regarding the preparation of annual financial statements, and reporting to the Office of the Comptroller General (OCG). There is room for improvement in data sharing and coordination among the various units involved in the compilation process. GFS are compiled using mostly publicly available data. Resources At present, the number of staff devoted to produce GFS is barely adequate. In the medium term, additional resources may be necessary to complete the migration to the GFSM2001 methodology. Most staff is well trained in the GFSM 2001. Physical resources are adequate. Relevance The DIPRES monitors the relevance of GFS through informal contacts with other departments and data users through e-mail inquiries, personal contacts, and press conferences. However, there are no user advisory groups. Other quality management Quality is a main concern for GFS production. Beginning in 2007, the DIPRES will be audited using the ISO 9001:2000 international quality standard.

Professionalism. The Administrative Statute (Law 18834 of 1989) and the Law of Administrative Probity (Law 19653 of 1999) assist in ensuring impartiality in the work of civil servants. Professionalism is actively promoted and supported within the organization through external and on-the-job staff training. Statisticians are free from political influence in choosing data sources and methods for compiling GFS, and changes to statistical processes are not influenced by political considerations. The DIPRES is entitled to comment and respond to misused or misinterpreted fiscal statistics. Transparency Laws and regulations governing the compilation and dissemination of GFS are freely available to the public, with the exception of the Reserved Copper Law. No government officials outside the DIPRES have access to the data before they are released to the public, and the data are made available simultaneously to all interested parties. Ethical standards Aside from the Administrative Statute and the Law of Administrative Probity, several codes of conduct governing the behavior of the central government and local government employees ensure that data compilation and dissemination are performed according to strictly professional considerations.

Table 2c.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Central Bank of Chile

Table 2c.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Central Bank of Chile

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment Provisions for producing statistics are included in the Law 18840 of 1989 (Basic Constitutional Act of the Central Bank of Chile). Article 53 states that “the Bank shall timely compile and publish the main macroeconomic statistics, including those of a monetary and foreign exchange character, balance of payments and national accounts …” The National Statistics Compilation Plan assigns the CBCH the task of compiling and disseminating NA, monetary, and BOP statistics. Article 53 establishes mandatory data reporting by public entities to the CBCH. Although there are no legal precepts empowering the CBCH to require private institutions to respond solely to statistical data requests, there is broad cooperation of the private sector with the CBCH. Article 40 of the CBCH’s Basic Consitutional Act empowers it to demand from the private sector information on foreign exchange transactions. Confidentiality of the reported data is guaranteed by Article 66 and the CBCH’s By-Laws. The CBCH has special agreements with various institutions for data sharing, in particular with the NSI, the SBFI, the National Custom Service (NCS), the Internal Tax Service (ITS), and the National Tourism Service (SERNATUR). Resources Human resources dedicated to compile and disseminate macroeconomic statistics are adequate in number and professional qualifications. Staff attend courses and training programs offered by international organizations, graduate programs abroad, and internships in recognized statistical agencies. Compensation levels are competitive. Computing resources, physical infrastructure, and funding are adequate. NA uses a data model and a database application to compile statistics. BOP is working on such an application. A data warehouse application would make the database application more effective. Measures are in place to monitor the cost-effectiveness of the statistical programs and to detect needs for improvements. Relevance The CBCH does not have formal mechanisms to consult data users about their information needs. However, users can submit questions and feedback on series and the database to the CBCH’s website. The CBCH showed its commitment to improving the country’s macroeconomic statistics by participating in statistical meetings and seminars organized by international and regional organizations. Other quality management The CBCH has a long tradition of producing high-quality macroeconomic statistics and strives to maintain high standards of quality using modern technology. Among the objectives of its 2006-2008 strategic plan is to contribute to an understanding of economic and financial affairs by preparing and broadcasting relevant reports, studies, and statistics. Results of studies produced by the CBCH are disseminated to the general public.

Professionalism By Constitution, the CBCH is an autonomous institution of a technical nature with its own capital (Chapter XII). This provision guarantees the professional independence of the CBCH, ensuring that macroeconomic statistics are compiled following strict technical criteria and free from outside interference. The CBCH’s management promotes professionalism with a continuous training program and by receiving technical assistance from other countries and international organizations. The CBCH monitors media coverage of macroeconomic statistics. When statistics are misinterpreted or misused, the CBCH provides comments and clarifications through its Communications Management Office. Transparency The CBCH disseminates its statistics in a timely manner and provides advance release calendars, which are strictly followed. No government officials outside the CBCH have access to the data before their release to the public. Documentation is available on the terms and conditions and the methodology used for NA, BOP, and monetary statistics. Data released to the public are clearly identified as products of the CBCH. Major changes in the conceptual framework, source data, and statistical techniques of macroeconomic statistics are announced in advance. Ethical standards The CBCH’s Personnel By-Laws provide guidelines for CBCH employees. In addition, the Ethics Code (March 2003) establishes clear standards describing the procedures that the organization and its staff must follow when potential conflict of interest situations arise (Section II, 1). It also includes clear ethical standards on measures to be adopted to prevent the misuse or misinterpretation of statistics (Section II, 2). Compliance with the Code is facilitated by a culture of solid ethical standards.

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Table 2c.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Central Bank of Chile

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment Provisions for producing statistics are included in the Law 18840 of 1989 (Basic Constitutional Act of the Central Bank of Chile). Article 53 states that “the Bank shall timely compile and publish the main macroeconomic statistics, including those of a monetary and foreign exchange character, balance of payments and national accounts …” The National Statistics Compilation Plan assigns the CBCH the task of compiling and disseminating NA, monetary, and BOP statistics. Article 53 establishes mandatory data reporting by public entities to the CBCH. Although there are no legal precepts empowering the CBCH to require private institutions to respond solely to statistical data requests, there is broad cooperation of the private sector with the CBCH. Article 40 of the CBCH’s Basic Consitutional Act empowers it to demand from the private sector information on foreign exchange transactions. Confidentiality of the reported data is guaranteed by Article 66 and the CBCH’s By-Laws. The CBCH has special agreements with various institutions for data sharing, in particular with the NSI, the SBFI, the National Custom Service (NCS), the Internal Tax Service (ITS), and the National Tourism Service (SERNATUR). Resources Human resources dedicated to compile and disseminate macroeconomic statistics are adequate in number and professional qualifications. Staff attend courses and training programs offered by international organizations, graduate programs abroad, and internships in recognized statistical agencies. Compensation levels are competitive. Computing resources, physical infrastructure, and funding are adequate. NA uses a data model and a database application to compile statistics. BOP is working on such an application. A data warehouse application would make the database application more effective. Measures are in place to monitor the cost-effectiveness of the statistical programs and to detect needs for improvements. Relevance The CBCH does not have formal mechanisms to consult data users about their information needs. However, users can submit questions and feedback on series and the database to the CBCH’s website. The CBCH showed its commitment to improving the country’s macroeconomic statistics by participating in statistical meetings and seminars organized by international and regional organizations. Other quality management The CBCH has a long tradition of producing high-quality macroeconomic statistics and strives to maintain high standards of quality using modern technology. Among the objectives of its 2006-2008 strategic plan is to contribute to an understanding of economic and financial affairs by preparing and broadcasting relevant reports, studies, and statistics. Results of studies produced by the CBCH are disseminated to the general public.

Professionalism By Constitution, the CBCH is an autonomous institution of a technical nature with its own capital (Chapter XII). This provision guarantees the professional independence of the CBCH, ensuring that macroeconomic statistics are compiled following strict technical criteria and free from outside interference. The CBCH’s management promotes professionalism with a continuous training program and by receiving technical assistance from other countries and international organizations. The CBCH monitors media coverage of macroeconomic statistics. When statistics are misinterpreted or misused, the CBCH provides comments and clarifications through its Communications Management Office. Transparency The CBCH disseminates its statistics in a timely manner and provides advance release calendars, which are strictly followed. No government officials outside the CBCH have access to the data before their release to the public. Documentation is available on the terms and conditions and the methodology used for NA, BOP, and monetary statistics. Data released to the public are clearly identified as products of the CBCH. Major changes in the conceptual framework, source data, and statistical techniques of macroeconomic statistics are announced in advance. Ethical standards The CBCH’s Personnel By-Laws provide guidelines for CBCH employees. In addition, the Ethics Code (March 2003) establishes clear standards describing the procedures that the organization and its staff must follow when potential conflict of interest situations arise (Section II, 1). It also includes clear ethical standards on measures to be adopted to prevent the misuse or misinterpretation of statistics (Section II, 2). Compliance with the Code is facilitated by a culture of solid ethical standards.

Table 2d.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Superintendency of Banks and Financial Institutions

Table 2d.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Superintendency of Banks and Financial Institutions

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment The General Banking Act (Decree with Force of Law-DFL 3 of 1997) defines the SBFI as an autonomous institution, with full legal capacity, in charge of the supervision of the Banco Estado, the banking enterprises, and the financial entities whose control is not otherwise entrusted by the law to a different institution (Articles 1 and 2). Article 16 of DFL 3 of 1997 indicates that “…the Superintendent shall have the right to request from the institutions subject to his supervision, any information, document, or book that, in his opinion, may be necessary for purposes of control or statistics.” Penalties for not complying with the instructions issued by the SBFI are foreseen in Article 19 of DFL 3 of 1997. The confidentiality of the information provided to the SBFI is guaranteed by Article 7 of DFL 3 of 1997. Several agreements of collaboration between the SBFI and the CBCH are in place, under the umbrella of Article 53 of Law 18840/89. The SBFI forwards electronically to the CBCH daily and monthly data received from other depository corporations (ODCs), via dedicated encrypted lines. Resources Human, technical, and financial resources are generally adequate. Salaries in the SBFI are regulated by the scale of public supervisory institutions and are higher than the rest of the public sector. However, they are lower than salaries paid by the private banking sector, inducing a higher than desirable personnel turnover. Relevance The SBFI’s main function is to collect data for supervisory purposes. Nevertheless, it has always demonstrated willingness to accommodate the CBCH’s emerging data needs for the compilation of monetary statistics, requesting additional information from the ODCs when necessary. Other quality management The SBFI’s authorities are aware that continued efforts are needed to improve the quality of its statistical products.

Professionalism The SBFI 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. Staff of the SBFI regularly attend meetings and participate in international courses offered by other supervisory agencies and central banks. Transparency The legal terms and conditions for collecting data for supervisory purposes are specified in the relevant laws, which are available on the SBFI’s website. According to Article 14 of DFL 3 of 1997, the Minister of Finance may have access to information on entities supervised by the SBFI, but this provision refers basically to cases of financial insolvency and does not affect published monetary data. On its website, the SBFI disseminates data on its supervised institutions, such as balance sheets, financial statements, interest rates, and composition of deposits and loans. Ethical standards Through internal staff bulletins, SBFI staff is made aware of its rights and obligations. Special attention is paid to the confidentiality of the information received by the SBFI, with concrete instructions on the ways to protect it.

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Table 2d.

Chile: Assessment of Data Quality—Dimensions 0 and 1—Superintendency of Banks and Financial Institutions

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment The General Banking Act (Decree with Force of Law-DFL 3 of 1997) defines the SBFI as an autonomous institution, with full legal capacity, in charge of the supervision of the Banco Estado, the banking enterprises, and the financial entities whose control is not otherwise entrusted by the law to a different institution (Articles 1 and 2). Article 16 of DFL 3 of 1997 indicates that “…the Superintendent shall have the right to request from the institutions subject to his supervision, any information, document, or book that, in his opinion, may be necessary for purposes of control or statistics.” Penalties for not complying with the instructions issued by the SBFI are foreseen in Article 19 of DFL 3 of 1997. The confidentiality of the information provided to the SBFI is guaranteed by Article 7 of DFL 3 of 1997. Several agreements of collaboration between the SBFI and the CBCH are in place, under the umbrella of Article 53 of Law 18840/89. The SBFI forwards electronically to the CBCH daily and monthly data received from other depository corporations (ODCs), via dedicated encrypted lines. Resources Human, technical, and financial resources are generally adequate. Salaries in the SBFI are regulated by the scale of public supervisory institutions and are higher than the rest of the public sector. However, they are lower than salaries paid by the private banking sector, inducing a higher than desirable personnel turnover. Relevance The SBFI’s main function is to collect data for supervisory purposes. Nevertheless, it has always demonstrated willingness to accommodate the CBCH’s emerging data needs for the compilation of monetary statistics, requesting additional information from the ODCs when necessary. Other quality management The SBFI’s authorities are aware that continued efforts are needed to improve the quality of its statistical products.

Professionalism The SBFI 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. Staff of the SBFI regularly attend meetings and participate in international courses offered by other supervisory agencies and central banks. Transparency The legal terms and conditions for collecting data for supervisory purposes are specified in the relevant laws, which are available on the SBFI’s website. According to Article 14 of DFL 3 of 1997, the Minister of Finance may have access to information on entities supervised by the SBFI, but this provision refers basically to cases of financial insolvency and does not affect published monetary data. On its website, the SBFI disseminates data on its supervised institutions, such as balance sheets, financial statements, interest rates, and composition of deposits and loans. Ethical standards Through internal staff bulletins, SBFI staff is made aware of its rights and obligations. Special attention is paid to the confidentiality of the information received by the SBFI, with concrete instructions on the ways to protect it.

Table 3a.

Chile: Assessment of Data Quality—Dimensions 2 to 5—National Accounts

Table 3a.

Chile: Assessment of Data Quality—Dimensions 2 to 5—National Accounts

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions NA are compiled following the 1993 SNA. Scope The 1993 SNA tables and accounts, specified by the Intersecretariat Working Group on National Accounts (ISWGNA) as minimum requirements, are compiled on a regular basis. The accounts cover annual and quarterly gross domestic product (GDP) by the production and expenditure approaches at current and constant 2003 prices, annual supply-and-use tables, an input-output matrix for the base year, and the set of accounts by institutional sectors up to the financial account. Indirect estimates on nonobserved activities are derived by applying the commodity flow approach. Delimitation of production and assets boundaries are in line with the 1993 SNA with some exceptions, such as the treatment of mineral exploration, agricultural work in progress, and own-account production in some activities. Free zones and workers who work part of the year in other countries are included. Classification/sectorization National classifications of economic activities and products are broadly consistent with the International Standard Industrial Classification (ISIC) Rev. 3 and the Central Product Classification (CPC), respectively. There are some deviations, in particular the classification of copper derivatives in mining. The classification of the functions of government (COFOG) is not used to classify government expenditure and the classification of individual consumption by purpose (COICOP) is not applied for classifying household final consumption expenditure. Improvements are under development. Basis for recording Transactions are recorded on an accrual basis, except for agricultural products. Transactions between establishments from the same enterprise are recorded on a gross basis.	Source data The NSI’s business register is partially updated and the update is not done regularly. The UBS is conducted every 10 years, instead of five years. Although the NSI conducts some important surveys, the CBCH conducts complementary surveys. The data available for agriculture, fishing, some services, and quarterly estimates are limited in scope. However, income tax and VAT records are used to fill in the gaps. Source data reasonably approximate national accounts’ requirements and their coverage is satisfactory. The timeliness of the NSI’s source data could be further improved. Assessment of source data Appropriate measures are taken to validate most source data. The NSIs lack of resources to properly validate the data in a timely manner limits the potential use of some surveys for NA. Scientific sampling techniques are not used for most of the surveys. No information is available for sampling and nonsampling errors for the HBS and most business surveys. Statistical techniques Statistical techniques are broadly appropriate with some minor deviations. GDP compilation is mainly based on supply-and-use tables and changes in inventories are residuals. The double-deflation method is used to estimate around half of value added. There are only some explicit estimates on nonobserved activities for the benchmark year. The base year has been recently updated to 2003. The Denton method is used for benchmarking quarterly and annual figures. Quarterly GDP data are seasonally adjusted. 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 the corresponding documentation prepared.	Periodicity and timeliness Preliminary GDP data meet SDDS recommendations on periodicity and timeliness. Consistency NA series are consistent from 2003 to 2006. Previous series are consistent for the period 1996-2005. Intertemporal and internal consistency of GDP figures are verified in the supply-and-use tables. Net lending/borrowing by institutional sector is derived independently from the capital accounts and financial accounts and is reconciled. Differences between NA and GFS are reconcilable. BOP statistics and NA are broadly consistent. Revision policy and practice Preliminary data are clearly identified. There is a preannounced calendar of revisions. The base year has been changed every seven to 10 years, and there is a plan to update it every five years. Documentation on analysis of regular and major revisions is prepared and made public.	Data accessibility NA are disseminated in a clear manner but with insufficient detail, in hard copy and on the CBCH’s website. An advance release calendar gives a 12-month-ahead notice of the precise release dates. NA are released simultaneously to all users and customized tabulations are provided upon request. Metadata accessibility Detailed updated metadata are available in special publications and on the CBCH’s website. Metadata are also available on the IMF’s DSBB, although need updating. Assistance to users A specific contact person is not indicated in publications, on the CBCH’s website, or on the DSBB. However, users can address queries to an e-mail address on the CBCH’s website and through the Communications Management Office. A catalog of CBCH’s publications is available on its website. Users can subscribe to an e-system to be notified on economic statistics.

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Table 3a.

Chile: Assessment of Data Quality—Dimensions 2 to 5—National Accounts

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions NA are compiled following the 1993 SNA. Scope The 1993 SNA tables and accounts, specified by the Intersecretariat Working Group on National Accounts (ISWGNA) as minimum requirements, are compiled on a regular basis. The accounts cover annual and quarterly gross domestic product (GDP) by the production and expenditure approaches at current and constant 2003 prices, annual supply-and-use tables, an input-output matrix for the base year, and the set of accounts by institutional sectors up to the financial account. Indirect estimates on nonobserved activities are derived by applying the commodity flow approach. Delimitation of production and assets boundaries are in line with the 1993 SNA with some exceptions, such as the treatment of mineral exploration, agricultural work in progress, and own-account production in some activities. Free zones and workers who work part of the year in other countries are included. Classification/sectorization National classifications of economic activities and products are broadly consistent with the International Standard Industrial Classification (ISIC) Rev. 3 and the Central Product Classification (CPC), respectively. There are some deviations, in particular the classification of copper derivatives in mining. The classification of the functions of government (COFOG) is not used to classify government expenditure and the classification of individual consumption by purpose (COICOP) is not applied for classifying household final consumption expenditure. Improvements are under development. Basis for recording Transactions are recorded on an accrual basis, except for agricultural products. Transactions between establishments from the same enterprise are recorded on a gross basis.	Source data The NSI’s business register is partially updated and the update is not done regularly. The UBS is conducted every 10 years, instead of five years. Although the NSI conducts some important surveys, the CBCH conducts complementary surveys. The data available for agriculture, fishing, some services, and quarterly estimates are limited in scope. However, income tax and VAT records are used to fill in the gaps. Source data reasonably approximate national accounts’ requirements and their coverage is satisfactory. The timeliness of the NSI’s source data could be further improved. Assessment of source data Appropriate measures are taken to validate most source data. The NSIs lack of resources to properly validate the data in a timely manner limits the potential use of some surveys for NA. Scientific sampling techniques are not used for most of the surveys. No information is available for sampling and nonsampling errors for the HBS and most business surveys. Statistical techniques Statistical techniques are broadly appropriate with some minor deviations. GDP compilation is mainly based on supply-and-use tables and changes in inventories are residuals. The double-deflation method is used to estimate around half of value added. There are only some explicit estimates on nonobserved activities for the benchmark year. The base year has been recently updated to 2003. The Denton method is used for benchmarking quarterly and annual figures. Quarterly GDP data are seasonally adjusted. 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 the corresponding documentation prepared.	Periodicity and timeliness Preliminary GDP data meet SDDS recommendations on periodicity and timeliness. Consistency NA series are consistent from 2003 to 2006. Previous series are consistent for the period 1996-2005. Intertemporal and internal consistency of GDP figures are verified in the supply-and-use tables. Net lending/borrowing by institutional sector is derived independently from the capital accounts and financial accounts and is reconciled. Differences between NA and GFS are reconcilable. BOP statistics and NA are broadly consistent. Revision policy and practice Preliminary data are clearly identified. There is a preannounced calendar of revisions. The base year has been changed every seven to 10 years, and there is a plan to update it every five years. Documentation on analysis of regular and major revisions is prepared and made public.	Data accessibility NA are disseminated in a clear manner but with insufficient detail, in hard copy and on the CBCH’s website. An advance release calendar gives a 12-month-ahead notice of the precise release dates. NA are released simultaneously to all users and customized tabulations are provided upon request. Metadata accessibility Detailed updated metadata are available in special publications and on the CBCH’s website. Metadata are also available on the IMF’s DSBB, although need updating. Assistance to users A specific contact person is not indicated in publications, on the CBCH’s website, or on the DSBB. However, users can address queries to an e-mail address on the CBCH’s website and through the Communications Management Office. A catalog of CBCH’s publications is available on its website. Users can subscribe to an e-system to be notified on economic statistics.

Table 3b.

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

Table 3b.

Chile: 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 The CPI uses concepts and definitions that broadly correspond to international practices and the recommendations of the CPI Manual, 2004. However, the CPI basket includes interest rates on consumption loans and mortgage payments, with a treatment inconsistent with best practices (the weight of both items in the basket adds up to about 3.6 percent). Scope The CPI measures the change in prices of a fixed basket of goods and services representative of the final consumption expenditures of households of Greater Santiago (about 40 percent of Chile’s population), not including other cities and rural areas. The NSI is conducting a new national HBS and there are plans to update the CPI base with the expenditure results from this survey by December 2008. Classification/sectorization The CPI is based on a domestic classification that closely corresponds with COICOP but some departures hinder international comparisons (e.g., food category includes restaurants and alcoholic beverages; education is bundled with recreational services). Goods and services are classified in eight groups, 41 subgroups, 156 articles, 482 products, and more than 1,300 varieties. The domestic classification of educational services splits in different product payments for the same service, producing a potential downward bias in the index (education services weight in the index is 6.2 percent). Basis for recording CPFs weights are based on consumption expenditure valued at the purchaser’s prices. Product specifications include relevant price determining characteristics. However, expenditure estimates for used cars follow an erroneous netting procedure that yields a relatively high index weight for this item (1.1 percent).	Source data The CPI basket and weight structure is based on the results of the 1996-1997 HBS. Assessment of source data There are various validation procedures for the source data. However, there are no established procedures to verify the HBS response consistency with other sources of information. Statistical techniques Data compilation procedures are sound, and appropriate statistical methods are used to handle missing prices. New products are introduced in the sample as they gain market share, but a similar treatment for outlets is lacking. Adjustments for quality differences are not made (except for computers with a procedure that requires revision) leading potentially to an index bias with the introduction of new products and services. Assessment and validation of intermediate data and statistical outputs Intermediate results and statistical outputs are regularly assessed and validated. The thresholds for investigating unusual movements of index components is invariant to the item’s particular characteristics, leading to under- or overvalidation of results (confirmed information is included). Revision studies The NSI has not conducted long-term trend studies for revision patterns of the HBS, leading to infrequent weight structure revisions (the HBS has been levied on 10-year cycles).	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 Statistics are consistent within the dataset and over time. Methodological notes identify and explain main breaks in time series as well as the adjustments made to maintain consistency over time. Unusual changes in price statistics trends are not explained in the press release, hindering understanding to CPI users. Revision policy and practice The CPI is final upon its first release.	Data accessibility CPI statistics are punctually published on a preannounced schedule. The statistics are not presented in a way that facilitates proper interpretation and meaningful comparisons. Appropriate analysis of current-period developments is not included with the press release. Data dissemination formats hinder redissemination and analysis of inflationary trends. Metadata accessibility The NSI has a comprehensive description of the CPI metadata on its website. Assistance to users Adequate assistance is given to users.

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Table 3b.

Chile: 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 The CPI uses concepts and definitions that broadly correspond to international practices and the recommendations of the CPI Manual, 2004. However, the CPI basket includes interest rates on consumption loans and mortgage payments, with a treatment inconsistent with best practices (the weight of both items in the basket adds up to about 3.6 percent). Scope The CPI measures the change in prices of a fixed basket of goods and services representative of the final consumption expenditures of households of Greater Santiago (about 40 percent of Chile’s population), not including other cities and rural areas. The NSI is conducting a new national HBS and there are plans to update the CPI base with the expenditure results from this survey by December 2008. Classification/sectorization The CPI is based on a domestic classification that closely corresponds with COICOP but some departures hinder international comparisons (e.g., food category includes restaurants and alcoholic beverages; education is bundled with recreational services). Goods and services are classified in eight groups, 41 subgroups, 156 articles, 482 products, and more than 1,300 varieties. The domestic classification of educational services splits in different product payments for the same service, producing a potential downward bias in the index (education services weight in the index is 6.2 percent). Basis for recording CPFs weights are based on consumption expenditure valued at the purchaser’s prices. Product specifications include relevant price determining characteristics. However, expenditure estimates for used cars follow an erroneous netting procedure that yields a relatively high index weight for this item (1.1 percent).	Source data The CPI basket and weight structure is based on the results of the 1996-1997 HBS. Assessment of source data There are various validation procedures for the source data. However, there are no established procedures to verify the HBS response consistency with other sources of information. Statistical techniques Data compilation procedures are sound, and appropriate statistical methods are used to handle missing prices. New products are introduced in the sample as they gain market share, but a similar treatment for outlets is lacking. Adjustments for quality differences are not made (except for computers with a procedure that requires revision) leading potentially to an index bias with the introduction of new products and services. Assessment and validation of intermediate data and statistical outputs Intermediate results and statistical outputs are regularly assessed and validated. The thresholds for investigating unusual movements of index components is invariant to the item’s particular characteristics, leading to under- or overvalidation of results (confirmed information is included). Revision studies The NSI has not conducted long-term trend studies for revision patterns of the HBS, leading to infrequent weight structure revisions (the HBS has been levied on 10-year cycles).	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 Statistics are consistent within the dataset and over time. Methodological notes identify and explain main breaks in time series as well as the adjustments made to maintain consistency over time. Unusual changes in price statistics trends are not explained in the press release, hindering understanding to CPI users. Revision policy and practice The CPI is final upon its first release.	Data accessibility CPI statistics are punctually published on a preannounced schedule. The statistics are not presented in a way that facilitates proper interpretation and meaningful comparisons. Appropriate analysis of current-period developments is not included with the press release. Data dissemination formats hinder redissemination and analysis of inflationary trends. Metadata accessibility The NSI has a comprehensive description of the CPI metadata on its website. Assistance to users Adequate assistance is given to users.

Table 3c.

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

Table 3c.

Chile: 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 Output weights are determined according to internationally accepted standards. Output estimates are compiled at a sufficient level of industrial and commodity detail. Scope The PPI includes producer prices for six categories: agriculture, livestock and forestry; mining; fishing; manufacturing; electricity, gas and water; and construction. The index does not cover services. Monthly surveys are used to collect prices for about 4,000 specific goods in 738 establishments. Classification/sectorization The PPI is built on classification systems consistent with internationally accepted standards. Institutional units and transactions are classified according to the 1993 SNA. ISIC, rev. 3 is used to classify the economic activities of establishments and enterprises. Products are classified with the CPC ver. 1.0. An exception is the classification of copper extraction and copper manufacturing products, which departs from international classification to conform to CBCH national accounts. Basis for recording Procedures to value flows and stocks, timing rules to record flows, and net weights are in accordance with the 1993 SNA. However, survey design does not allow registry of copper prices on accrual.	Source data Comprehensive data collection programs provide source data. Source data approximates the definitions, scope, classification, valuation and time of recording required in the PPI. The data collection provides timely receipt of the data (respondents are aware of reporting deadlines). In general, sample design ensures proper representation of the population scope. However, the sample does not include information from firms of less than 10 employees (which are not covered in the business registry), enterprises within free zones, and household unincorporated enterprises. Export and domestic prices are considered but are not weighted according to sales. Assessment of source data The NSI has a Methodology Department (not within the Price Statistics Department) that routinely reviews censuses and surveys. Prices are constantly examined for consistency with other data sources. Statistical techniques Sound imputation techniques are used to handle missing prices in agriculture, and livestock and forestry. However, in the other PPI economic categories missing prices are carried forward, a practice that should be discontinued. Adjustments for quality differences are not made, leading potentially to an inappropriate introduction of new products and services. In addition, the copper price recollection procedure increases quality induced volatility since price quotes are derived directly from contracts that adjust the international price with quality variations of the metal. Assessment and validation of intermediate data and statistical outputs Intermediate results and statistical outputs are regularly assessed and validated. The thresholds for investigating unusual movements of index components is invariant to particular characteristics. Revision studies Sources of errors are not routinely investigated.	Periodicity and timeliness The PPI is published on a monthly basis within five working days after the end of the month, meeting SDDS requirements. Consistency Statistics are consistent within the dataset and over time. Unusual changes in price statistics trends are not explained in the press release, hindering understanding to PPI users. Revision policy and practice The PPI is final upon its first release.	Data accessibility PPI statistics are punctually published on a preannounced schedule. The statistics are not presented in a way that facilitates proper interpretation and meaningful comparisons. Appropriate analysis of current-period developments is not included with the press release. Data dissemination formats hinder redissemination and analysis of inflationary trends. A PPI indicator that excludes copper effects on its volatility is not published. In addition, detailed product price series are not available at the NSI’s website. Metadata accessibility A summary of PPI methodology is published on the NSI’s website, but the full-fledged version is not available. Assistance to users Adequate assistance is given to users.

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Table 3c.

Chile: 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 Output weights are determined according to internationally accepted standards. Output estimates are compiled at a sufficient level of industrial and commodity detail. Scope The PPI includes producer prices for six categories: agriculture, livestock and forestry; mining; fishing; manufacturing; electricity, gas and water; and construction. The index does not cover services. Monthly surveys are used to collect prices for about 4,000 specific goods in 738 establishments. Classification/sectorization The PPI is built on classification systems consistent with internationally accepted standards. Institutional units and transactions are classified according to the 1993 SNA. ISIC, rev. 3 is used to classify the economic activities of establishments and enterprises. Products are classified with the CPC ver. 1.0. An exception is the classification of copper extraction and copper manufacturing products, which departs from international classification to conform to CBCH national accounts. Basis for recording Procedures to value flows and stocks, timing rules to record flows, and net weights are in accordance with the 1993 SNA. However, survey design does not allow registry of copper prices on accrual.	Source data Comprehensive data collection programs provide source data. Source data approximates the definitions, scope, classification, valuation and time of recording required in the PPI. The data collection provides timely receipt of the data (respondents are aware of reporting deadlines). In general, sample design ensures proper representation of the population scope. However, the sample does not include information from firms of less than 10 employees (which are not covered in the business registry), enterprises within free zones, and household unincorporated enterprises. Export and domestic prices are considered but are not weighted according to sales. Assessment of source data The NSI has a Methodology Department (not within the Price Statistics Department) that routinely reviews censuses and surveys. Prices are constantly examined for consistency with other data sources. Statistical techniques Sound imputation techniques are used to handle missing prices in agriculture, and livestock and forestry. However, in the other PPI economic categories missing prices are carried forward, a practice that should be discontinued. Adjustments for quality differences are not made, leading potentially to an inappropriate introduction of new products and services. In addition, the copper price recollection procedure increases quality induced volatility since price quotes are derived directly from contracts that adjust the international price with quality variations of the metal. Assessment and validation of intermediate data and statistical outputs Intermediate results and statistical outputs are regularly assessed and validated. The thresholds for investigating unusual movements of index components is invariant to particular characteristics. Revision studies Sources of errors are not routinely investigated.	Periodicity and timeliness The PPI is published on a monthly basis within five working days after the end of the month, meeting SDDS requirements. Consistency Statistics are consistent within the dataset and over time. Unusual changes in price statistics trends are not explained in the press release, hindering understanding to PPI users. Revision policy and practice The PPI is final upon its first release.	Data accessibility PPI statistics are punctually published on a preannounced schedule. The statistics are not presented in a way that facilitates proper interpretation and meaningful comparisons. Appropriate analysis of current-period developments is not included with the press release. Data dissemination formats hinder redissemination and analysis of inflationary trends. A PPI indicator that excludes copper effects on its volatility is not published. In addition, detailed product price series are not available at the NSI’s website. Metadata accessibility A summary of PPI methodology is published on the NSI’s website, but the full-fledged version is not available. Assistance to users Adequate assistance is given to users.

Table 3d.

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

Table 3d.

Chile: 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 Concepts and definitions are broadly consistent with the GFSM 2001 methodology. Since 2003, the DIPRES has documented and published the official migration plan to adopt the GFSM 2001. Scope Institutional and transactional coverage for the general government are incomplete. GFS do not cover universities and ancillary units serving local governments. Central government debt excludes accrued interest on debt instruments, liabilities related to the Reserved Copper Law, and the stock of recognition bonds, even though supplementary data are disseminated separately for the latter. Classification/sectorization Sectorization is broadly in line with the GFSM 2001. However, significant deviations exist in national classification practices. Aggregates that do not conform to the GFSM 2001 framework are copper revenues, subsidies and grants, capital transfers, and financing transactions. Basis for recording Tax revenues are recorded on a cash basis. Interest of indexed debt instruments do not include changes in principal due to fluctuations of the index.	Source data Source data are complete and timely to allow the compilation of GFS. The Integrated Financial Management System (SIGFE) provides comprehensive accounting records for the budgetary central government. However, stock data on financial assets and liabilities are recorded at face value. For extrabudgetary central government, source data are collected by the DIPRES directly from each unit. For local governments, source data are provided to the DIPRES by the OCG. Debt GFS are compiled using the Treasury’s accounting records. Assessment of source data Built-in software cross checks are used to monitor data accuracy. Statistical techniques Data compilation is mostly computerized. Assessment and validation of intermediate data and statistical outputs The process for validating data is not well established. Revision studies GFS data are final when first published.	Periodicity and timeliness GFS meet the SDDS standards. Notwithstanding, Chile is taking a flexibility option for the timeliness of central government operations. Consistency The same concepts and classifications are used for monthly, quarterly, and annual GFS. Consistent time series are available from 1990, except for monthly data that are available from 2003. GFS are not internally consistent due to differences in source data and valuation methods used to compile debt flows and stocks. Discrepancies between GFS and national accounts are explained by differences in coverage, sectorization, and classification; while a different residence criteria accounts for the inconsistency between the GFS and the BOP. Revision policy and practice A revision policy has not been explicitly articulated. However, major revisions associated with methodological changes are well documented and disseminated.	Data accessibility The GFS disseminated on the DIPRES’s website are presented in a clear manner. All publications are released according to a regular and preannounced schedule, most of them in Excel-readable-format. The publications are made available simultaneously to all users. Statistics not routinely disseminated are made available to users upon request. Metadata accessibility The concepts, scope, classification, basis for recording, data sources, and methodologies for GFS are widely documented by the DIPRES, and are available in several publications, on its website, as well as on the DSBB. Assistance to users Contact persons and details for each subject field are publicized in the metadata on the DSBB. Catalogs of publications are not available to users of statistics.

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Table 3d.

Chile: 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 Concepts and definitions are broadly consistent with the GFSM 2001 methodology. Since 2003, the DIPRES has documented and published the official migration plan to adopt the GFSM 2001. Scope Institutional and transactional coverage for the general government are incomplete. GFS do not cover universities and ancillary units serving local governments. Central government debt excludes accrued interest on debt instruments, liabilities related to the Reserved Copper Law, and the stock of recognition bonds, even though supplementary data are disseminated separately for the latter. Classification/sectorization Sectorization is broadly in line with the GFSM 2001. However, significant deviations exist in national classification practices. Aggregates that do not conform to the GFSM 2001 framework are copper revenues, subsidies and grants, capital transfers, and financing transactions. Basis for recording Tax revenues are recorded on a cash basis. Interest of indexed debt instruments do not include changes in principal due to fluctuations of the index.	Source data Source data are complete and timely to allow the compilation of GFS. The Integrated Financial Management System (SIGFE) provides comprehensive accounting records for the budgetary central government. However, stock data on financial assets and liabilities are recorded at face value. For extrabudgetary central government, source data are collected by the DIPRES directly from each unit. For local governments, source data are provided to the DIPRES by the OCG. Debt GFS are compiled using the Treasury’s accounting records. Assessment of source data Built-in software cross checks are used to monitor data accuracy. Statistical techniques Data compilation is mostly computerized. Assessment and validation of intermediate data and statistical outputs The process for validating data is not well established. Revision studies GFS data are final when first published.	Periodicity and timeliness GFS meet the SDDS standards. Notwithstanding, Chile is taking a flexibility option for the timeliness of central government operations. Consistency The same concepts and classifications are used for monthly, quarterly, and annual GFS. Consistent time series are available from 1990, except for monthly data that are available from 2003. GFS are not internally consistent due to differences in source data and valuation methods used to compile debt flows and stocks. Discrepancies between GFS and national accounts are explained by differences in coverage, sectorization, and classification; while a different residence criteria accounts for the inconsistency between the GFS and the BOP. Revision policy and practice A revision policy has not been explicitly articulated. However, major revisions associated with methodological changes are well documented and disseminated.	Data accessibility The GFS disseminated on the DIPRES’s website are presented in a clear manner. All publications are released according to a regular and preannounced schedule, most of them in Excel-readable-format. The publications are made available simultaneously to all users. Statistics not routinely disseminated are made available to users upon request. Metadata accessibility The concepts, scope, classification, basis for recording, data sources, and methodologies for GFS are widely documented by the DIPRES, and are available in several publications, on its website, as well as on the DSBB. Assistance to users Contact persons and details for each subject field are publicized in the metadata on the DSBB. Catalogs of publications are not available to users of statistics.

Table 3e.

Chile: Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

Table 3e.

Chile: Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions Chile’s monetary statistics are in line with the methodology of the MFSM. Scope Coverage of the depository corporations (DC) survey is complete, including the CBCH, commercial banks, the state-owned Banco Estado, credit unions, and mutual funds. Classification/sectorization The classification and sectorization of financial instruments follow the methodology of the MFSM. However, securities issued by the CBCH and liabilities of mutual funds are not sectorized. Basis for recording Monetary statistics are produced on an accrual basis, which is consistent with the MFSM. Accounts in foreign currency are converted into national currency at the end of the month using the CBCH’s “observed” exchange rate, which is an average of the mid-point exchange rate of the interbank market. Three nonmaterial departures from the MFSM methodology are: (1) financial instruments are valued at the lower of amortized cost or market prices, rather than at market prices, (2) interest is not accrued on nonperforming loans, but recorded in memorandum accounts, and (3) gold holdings at the CBCH are recorded using an average of the daily prices of the last three months, rather than the quotation of the closing day.	Source data The DC survey is based on the consolidated balance sheets of the CBCH and ODCs. The ODCs report daily preliminary data to the CBCH and on a monthly basis their balance sheets together with additional sectorized data to the SBFI, which in turn forwards these to the CBCH. Assessment of source data Data are transmitted electronically from the ODCs to the SBFI and from the SBFI to the CBCH, minimizing the risk for error. Data are validated by the SBFI, including interbank positions. Statistical techniques Monetary data are based on the balance sheets of the CBCH and ODCs. The monetary and financial statistics group (GEMF) uses additional data to sectorize ODCs’ data. In processing source data, the GEMF runs standardized macros. Assessment and validation of intermediate data and statistical output In addition to the cross-checks performed on source data by the SBFI, the GEMF analyzes the daily data and investigates large and unexplained fluctuations. However, the GEMF does not validate the aggregated interbank positions, holdings of securities by ODCs, or monetary data against fiscal data. Revision studies The CBCH has produced some revisions in its monetary statistics, such as the recent changes in the definitions of monetary aggregates. These revisions are documented and, when appropriate, published in the CBCH Estudios Económicos Estadísticos.	Periodicity and timeliness Monetary statistics are disseminated on the 7th and 23rd day after the reference month, in full compliance with SDDS requirements. Consistency Monetary data are disseminated in consistent historical series. Data on the CBCH and ODC survey are internally consistent. The GEMF routinely cross-checks data on net foreign assets with the data on the international investment position (IIP). The GEMF does not reconcile monetary data on net credit to government with fiscal data. Inconsistencies were detected in the aggregated interbank positions originated in the lack of sectorization of mutual funds’ liabilities. Revision policy and practice Monetary data are published as provisional for two months, and then substituted by final data. Provisional data and their revisions are clearly identified.	Data accessibility Data are presented in an aggregated form with methodological notes. The CBCH publishes, and complies with, an advance release calendar for monetary data. Data are posted on the CBCH’s website—ensuring simultaneous access by all users—and published in the CBCH’s Boletín Mensual, and its annual Síntesis Monetaria y Financiera. Metadata accessibility Chile has posted its monetary metadata on the IMF’s DSBB since February 1997. The CBCH’s website provides a link to the country page on the DSBB. Assistance to users Information on the contact person for monetary statistics is available on the DSBB. Users’ requests and comments may be channeled through the CBCH’s website. There is a catalog with the CBCH’s publications, documents, and other services to users, including frequency and prices.

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Table 3e.

Chile: Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions Chile’s monetary statistics are in line with the methodology of the MFSM. Scope Coverage of the depository corporations (DC) survey is complete, including the CBCH, commercial banks, the state-owned Banco Estado, credit unions, and mutual funds. Classification/sectorization The classification and sectorization of financial instruments follow the methodology of the MFSM. However, securities issued by the CBCH and liabilities of mutual funds are not sectorized. Basis for recording Monetary statistics are produced on an accrual basis, which is consistent with the MFSM. Accounts in foreign currency are converted into national currency at the end of the month using the CBCH’s “observed” exchange rate, which is an average of the mid-point exchange rate of the interbank market. Three nonmaterial departures from the MFSM methodology are: (1) financial instruments are valued at the lower of amortized cost or market prices, rather than at market prices, (2) interest is not accrued on nonperforming loans, but recorded in memorandum accounts, and (3) gold holdings at the CBCH are recorded using an average of the daily prices of the last three months, rather than the quotation of the closing day.	Source data The DC survey is based on the consolidated balance sheets of the CBCH and ODCs. The ODCs report daily preliminary data to the CBCH and on a monthly basis their balance sheets together with additional sectorized data to the SBFI, which in turn forwards these to the CBCH. Assessment of source data Data are transmitted electronically from the ODCs to the SBFI and from the SBFI to the CBCH, minimizing the risk for error. Data are validated by the SBFI, including interbank positions. Statistical techniques Monetary data are based on the balance sheets of the CBCH and ODCs. The monetary and financial statistics group (GEMF) uses additional data to sectorize ODCs’ data. In processing source data, the GEMF runs standardized macros. Assessment and validation of intermediate data and statistical output In addition to the cross-checks performed on source data by the SBFI, the GEMF analyzes the daily data and investigates large and unexplained fluctuations. However, the GEMF does not validate the aggregated interbank positions, holdings of securities by ODCs, or monetary data against fiscal data. Revision studies The CBCH has produced some revisions in its monetary statistics, such as the recent changes in the definitions of monetary aggregates. These revisions are documented and, when appropriate, published in the CBCH Estudios Económicos Estadísticos.	Periodicity and timeliness Monetary statistics are disseminated on the 7th and 23rd day after the reference month, in full compliance with SDDS requirements. Consistency Monetary data are disseminated in consistent historical series. Data on the CBCH and ODC survey are internally consistent. The GEMF routinely cross-checks data on net foreign assets with the data on the international investment position (IIP). The GEMF does not reconcile monetary data on net credit to government with fiscal data. Inconsistencies were detected in the aggregated interbank positions originated in the lack of sectorization of mutual funds’ liabilities. Revision policy and practice Monetary data are published as provisional for two months, and then substituted by final data. Provisional data and their revisions are clearly identified.	Data accessibility Data are presented in an aggregated form with methodological notes. The CBCH publishes, and complies with, an advance release calendar for monetary data. Data are posted on the CBCH’s website—ensuring simultaneous access by all users—and published in the CBCH’s Boletín Mensual, and its annual Síntesis Monetaria y Financiera. Metadata accessibility Chile has posted its monetary metadata on the IMF’s DSBB since February 1997. The CBCH’s website provides a link to the country page on the DSBB. Assistance to users Information on the contact person for monetary statistics is available on the DSBB. Users’ requests and comments may be channeled through the CBCH’s website. There is a catalog with the CBCH’s publications, documents, and other services to users, including frequency and prices.

Table 3f.

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

Table 3f.

Chile: 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 BOP broadly follow the BPM5. Resident units are defined in conformity with the BPM5. In 2002, the CBCH completed the implementation of the BPM5 and migrated balance of payments data to the BPM5 from 1996 onwards. Scope BOP is broadly consistent with international standards. No significant amounts of unrecorded activities are deemed to occur. Classification/sectorization Is broadly in line with the BPM5 guidelines. Reverse investment on FDI are an exception. Basis for recording For the most part, transactions/stock data are valued at market prices. In general, transactions are recorded on an accrual basis in accordance with the BPM5. However, there are some areas where accounting is done on a different basis: (1) loan liabilities of public sector and private sector, which are recorded on a cash basis, (2) portfolio and other investment income are generally recorded on a cash basis for liabilities and on an accrual basis for assets, (3) unrequited transfers, such as grants, are recorded when foreign exchange is converted into the national currency (pesos), and (4) external trade is recorded according to customs documents. Entries of income are registered on accrual basis with the exceptions of external debt. Gross and net transactions are recorded in accordance with the BPM5.	Source data These are broadly adequate to compile balance of payments. Main sources include (1) the CBCH’s Summary of International Exchange Regulations, (2) customs data, (3) balance sheets, (4) administrative data, and (5) surveys and estimates. These data are supplemented or validated with information from enterprises, foreign agencies, and international financial institutions. Assessment of source data Source data are routinely assessed, including for surveys used by the Balance of Payments and External Debt Department (DBPDE). Statistical techniques Robust and efficient techniques are used by the DBPDE to adjust data derived from primary sources to improve quality, coverage, and timelines. Also estimates are used to adjust data in case of nonresponse or missing data. Assessment and validation of intermediate data and statistical output In most cases, where database management procedures exist, computerized edit checks are used to identify coding and other errors in data source. Statistical discrepancies are assessed and validated with available datasets. Revision studies The DBPDE routinely carries out revisions of balance of payments data to improve its statistics. The CBCH also publishes on its website studies on specific related topics and explanations of the causes of revisions.	Periodicity and timelines BOP and international investment position (IIP) statistics meet SDDS requirements. Also partial data are published: weekly (external trade), semi-monthly (reserve assets), and monthly (financial account flows). Consistency Balance of payments data are broadly consistent internally and overtime (annual data since 1996 and quarterly data since 2002). BOP statistics are consistent with the IIP and monetary statistics. An effort was also made to carry out a full reconciliation with national accounts statistics. However, these are not consistent with external debt statistics, which value the portfolio liabilities on a nominal basis. Revision policy and practice Data are provisional when first released. Revisions follow the announced calendar on the Boletín Mensual. Quarterly data of the calendar year are revised each time a new quarter is released. Annual revisions are carried out in March of the following two years. The public is informed of major changes in methodology on the CBCH’s publications.	Data accessibility Data are disseminated in accordance with the BPM5 standard components. Quarterly release is made under the analytical presentation, and the annual version on a detailed presentation. Data are made available to all users at the same time on the CBCH’s website and released on a preannounced schedule. Metadata accessibility Concepts, methodology, and data sources for balance of payments compilation are available on the CBCH’s website, in the Balance of Payments of Chile publication (annual), as well as on the IMF’s DSBB. Assistance to users It is adequate. Publications available on the CBCH’s website provide an institutional contact point. For specific balance of payments statistics, users’ contact points are provided on the DSBB.

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Table 3f.

Chile: 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 BOP broadly follow the BPM5. Resident units are defined in conformity with the BPM5. In 2002, the CBCH completed the implementation of the BPM5 and migrated balance of payments data to the BPM5 from 1996 onwards. Scope BOP is broadly consistent with international standards. No significant amounts of unrecorded activities are deemed to occur. Classification/sectorization Is broadly in line with the BPM5 guidelines. Reverse investment on FDI are an exception. Basis for recording For the most part, transactions/stock data are valued at market prices. In general, transactions are recorded on an accrual basis in accordance with the BPM5. However, there are some areas where accounting is done on a different basis: (1) loan liabilities of public sector and private sector, which are recorded on a cash basis, (2) portfolio and other investment income are generally recorded on a cash basis for liabilities and on an accrual basis for assets, (3) unrequited transfers, such as grants, are recorded when foreign exchange is converted into the national currency (pesos), and (4) external trade is recorded according to customs documents. Entries of income are registered on accrual basis with the exceptions of external debt. Gross and net transactions are recorded in accordance with the BPM5.	Source data These are broadly adequate to compile balance of payments. Main sources include (1) the CBCH’s Summary of International Exchange Regulations, (2) customs data, (3) balance sheets, (4) administrative data, and (5) surveys and estimates. These data are supplemented or validated with information from enterprises, foreign agencies, and international financial institutions. Assessment of source data Source data are routinely assessed, including for surveys used by the Balance of Payments and External Debt Department (DBPDE). Statistical techniques Robust and efficient techniques are used by the DBPDE to adjust data derived from primary sources to improve quality, coverage, and timelines. Also estimates are used to adjust data in case of nonresponse or missing data. Assessment and validation of intermediate data and statistical output In most cases, where database management procedures exist, computerized edit checks are used to identify coding and other errors in data source. Statistical discrepancies are assessed and validated with available datasets. Revision studies The DBPDE routinely carries out revisions of balance of payments data to improve its statistics. The CBCH also publishes on its website studies on specific related topics and explanations of the causes of revisions.	Periodicity and timelines BOP and international investment position (IIP) statistics meet SDDS requirements. Also partial data are published: weekly (external trade), semi-monthly (reserve assets), and monthly (financial account flows). Consistency Balance of payments data are broadly consistent internally and overtime (annual data since 1996 and quarterly data since 2002). BOP statistics are consistent with the IIP and monetary statistics. An effort was also made to carry out a full reconciliation with national accounts statistics. However, these are not consistent with external debt statistics, which value the portfolio liabilities on a nominal basis. Revision policy and practice Data are provisional when first released. Revisions follow the announced calendar on the Boletín Mensual. Quarterly data of the calendar year are revised each time a new quarter is released. Annual revisions are carried out in March of the following two years. The public is informed of major changes in methodology on the CBCH’s publications.	Data accessibility Data are disseminated in accordance with the BPM5 standard components. Quarterly release is made under the analytical presentation, and the annual version on a detailed presentation. Data are made available to all users at the same time on the CBCH’s website and released on a preannounced schedule. Metadata accessibility Concepts, methodology, and data sources for balance of payments compilation are available on the CBCH’s website, in the Balance of Payments of Chile publication (annual), as well as on the IMF’s DSBB. Assistance to users It is adequate. Publications available on the CBCH’s website provide an institutional contact point. For specific balance of payments statistics, users’ contact points are provided on the DSBB.

III. Staff’s Recommendations⁴

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