2014年-IMF国际货币组织全球_Uruguay_Report_on_the_Observance_of_Standards_and_CodesData_Module_151页_988kb

报告摘要

Uruguay IMF Country Report No. 14/42 Summary

Core Content

This report is the Report on the Observance of Standards and Codes (ROSC)—Data Module for Uruguay, prepared by the IMF Statistics Department in February 2014. It evaluates Uruguay's macroeconomic statistics, particularly national accounts, consumer price index (CPI), and producer price index (PPI), against the Special Data Dissemination Standard (SDDS) and the IMF's Data Quality Assessment Framework (DQAF) 2012.

The report is based on data and information available up to January 23, 2014, and includes the authorities' response and detailed assessments. It is the first data ROSC report using the 2012 version of the DQAF, which reflects the latest methodological standards.

Main Observations

Uruguay has made significant improvements in statistical compilation and dissemination since the 1999–mid-2000 ROSC mission.
The country subscribed to the SDDS on February 12, 2004, and has been in compliance with its standards.
Timeliness is generally good for labor market, price, and international investment position data.
Flexibility in timeliness is used for general and central government operations, but not for real sector statistics.
The national accounts and price statistics are generally of good quality and meet user needs, though some areas require improvement.

Key Agencies

Central Bank of Uruguay (CBU): Compiles national accounts.
National Institute of Statistics (NIS): Compiles CPI and PPI.

Legal and Institutional Framework

The legal and institutional basis for statistics is sound and follows international good practice.
CBU is an independent agency with technical, administrative, and financial autonomy.
NIS is a public body responsible for national statistics and is subject to the Statistics Law (No. 16,616).
Both agencies have ethical standards that meet international norms.
Staff training and retention are challenges, particularly for the NIS.
There is no formal process for user feedback on statistical relevance.
Methodological changes are not always communicated in advance to users.

Methodological Soundness

National accounts conform to the System of National Accounts 1993 (1993 SNA), but there is a need to adopt the 2008 SNA and ISIC Rev. 4.
CPI and PPI follow international guidance, but have methodological gaps:
- CPI does not cover implicit rent or net acquisitions of owner-occupied dwellings.
- PPI does not cover services or exported output.
Classification systems used include ISIC Rev. 3, a national extension of ISIC, and national product classifications.
Recording basis for government revenue and expenditure is cash and obligation basis, deviating from the accrual basis required by the SNA.

Accuracy and Reliability

Source data for national accounts have limited accuracy, with outdated input-output ratios (from 1997) used for 60% of GDP calculations.
Household consumption is not independently derived, and inventory changes are obtained as residuals.
CPI and PPI have good source data due to well-designed surveys and advanced data capture technologies.
However, intermediate data and outputs are not validated with alternative sources.
Revision studies for national accounts are conducted during base year changes, but regular revisions to detect bias are not analyzed.
Weight updates for CPI and PPI are not analyzed for their impact.

Serviceability, Periodicity, and Timeliness

Periodicity and timeliness meet SDDS standards.
Consistency between national accounts and price statistics is good.
CPI shelter component should cover both renters and owner occupants.
Detailed national accounts data are only available up to 2008.
Quarterly GDP is compiled but not disseminated in a current prices approach.
Monthly economic activity index is not published.
Weight updates for CPI and PPI should be more regular and frequent.

Accessibility and User Support

Data and metadata are generally accessible.
User assistance is provided by both agencies.
Regular revision studies and user engagement could improve the quality of statistical products.
Metadata accessibility is good for CBU but limited for NIS.
CBU and NIS have good data accessibility but limited metadata accessibility.

Staff Recommendations

Improve source data coverage and validation for national accounts.
Adopt the 2008 SNA and ISIC Rev. 4 for national accounts.
Enhance the timeliness of weight updates for CPI and PPI.
Implement a regular schedule for updating the base year of national accounts.
Strengthen the quality management system at NIS.
Improve staff training and recruitment to maintain and enhance statistical capabilities.
Increase user consultation on the relevance and methodological changes of statistics.
Ensure transparency in methodological changes and statistical practices.

Tables Summary

Table 1: Summary results of the DQAF 2012 for the three datasets.
Table 2a–b: Assessments of prerequisites of quality and assurances of integrity for CBU and NIS.
Table 3a–c: Assessments of methodological soundness, accuracy and reliability, serviceability, and accessibility for the three datasets.

Conclusion

Uruguay has made notable progress in statistical compilation and dissemination since the 1999–mid-2000 assessment. The country meets SDDS standards and has good data quality in most areas. However, there are opportunities for improvement, particularly in source data validation, methodological transparency, and user engagement. The NIS and CBU are working to enhance their statistical practices, but staffing challenges and limited resources remain a concern. The DQAF 2012 is used to evaluate data quality, and the ROSC report provides a comprehensive overview of Uruguay's statistical performance.