2017年-IMF国际货币组织全球_Uganda_Technical_Assistance_Report„Report_on_the_Price_Statistics_Mission_IMF_Country_Report_No_17295_September_2017_33页_663kb

Uganda: Technical Assistance Report on Prices Statistics Mission

Core Content

This report summarizes the findings and recommendations from a technical assistance mission to Uganda conducted by the International Monetary Fund (IMF) from June 30 to July 18, 2014. The mission aimed to assist the Uganda Bureau of Statistics (UBOS) in finalizing the rebased Producer Price Index (PPI) and developing Export and Import Price Indices (XMPI). The report outlines the methodology, data sources, and implementation strategies for both indices, along with training and program development recommendations.

Main Objectives

• Finalize the rebased PPI
• Develop Export and Import Price Indices (XMPI)
• Enhance data collection and dissemination processes
• Streamline methodologies and procedures for better accuracy and serviceability

Key Findings and Recommendations

PPI Development

• Conceptual Basis: The new PPI was based on the 2008 System of National Accounts (SNA) and the international PPI Manual. It includes mining, quarrying, manufacturing, and electricity/water industries, with plans to extend to agriculture and major service sectors in the future.
• Pricing Point: Ex-factory, ex-mine, etc., using basic prices (excluding trade and transport margins and VAT).
• Index Scope: Covers both domestic usage and exports, requiring separate price collection for these segments.
• Aggregation Methodology:
  • First level: 4-digit ISIC class level
  • Elementary Aggregate (EA) indices calculated using the Jevons geometric mean formula
  • Higher levels aggregated using the Laspeyres formula with weights derived from the 2009-10 Supply Use Tables (SUT)
• Base Period: 2009-10 SUT used as the weighting base
• Rebasing Frequency: Proposed to be done every 5 years using the latest finalized SUT
• Sampling:
  • 28 4-digit ISIC classes selected as the index basket
  • Initial sample size of 250 manufacturing establishments reduced to 176 after re-selection
  • Annual review of the sample is recommended using the Uganda Business Register
• Data Collection:
  • Monthly price indicators collected from a new Producer Price Survey (PPS)
  • Retrospective data collection from March 2013 to March 2014
  • A streamlined questionnaire was introduced for better timeliness and user-friendliness
• Training: Conducted for PPI and XMPI teams on price index concepts, compilation methods, and survey procedures

XMPI Development

• Conceptual Basis: XMPI is a hybrid index combining Customs unit values for homogeneous commodities and survey-based prices for heterogeneous items.
• Pricing Points:
  • Export Price Index (XPI): Free on Board (FOB)
  • Import Price Index (MPI): Cost, Insurance, and Freight (CIF)
• Index Scope: Actual transaction prices for merchandise trade
• Aggregation Methodology:
  • First level: 8-digit HS level
  • EA indices calculated using the Jevons geometric mean formula
• Reference Period: Tentatively set to 2012, but may be adjusted based on funding and timeline
• Data Sources:
  • Customs unit values for homogeneous commodities
  • Survey-based prices from the Import Price Survey (MPS) for heterogeneous items
• Sampling and Initialization:
  • A program of initialization interviews was delayed due to corporate funding cuts
  • Business rules for sample selection were developed
  • The mission focused on developing the MPI due to its complexity
• Dissemination Strategy:
  • Monthly indices to be published starting from April 2013
  • Indices to be linked to the current PPI where possible
  • Long-term goal: Coordinate PPI, CPI, and national accounts on a common reference base

Main Views

• The PPI and XMPI projects are critical for improving inflation monitoring and economic analysis in Uganda.
• The PPI is expected to serve as a leading indicator of downstream inflation, complementing the CPI.
• The XMPI is more complex due to the heterogeneity of imported goods and the challenges of obtaining historical price data.
• The use of the Jevons geometric mean is recommended for EA indices due to its suitability for price index calculations.
• The current PPI Excel-based system will be modified to support XMPI compilation, enhancing its functionality.
• Streamlining data collection procedures and improving sample representativeness are essential for data accuracy and reliability.

Key Information

• Mission Period: June 30 – July 18, 2014
• Prepared By: David Collins, Prices Expert, East AFRITAC
• Project: Prices Statistics STA_UGA_2013_05
• Base Period for PPI: 2009-10 SUT
• Reference Period for XMPI: Tentatively 2012
• Data Sources:
  • PPI: Producer Price Survey (PPS)
  • XMPI: Customs unit values and Import Price Survey (MPS)
• Sampling Criteria:
  • 90% cut-off for large industries (≥5% of total weight)
  • 70% cut-off for medium and small industries
• Dissemination Goals:
  • Publish separate indices for total sales, exports, and domestic sales
  • Publish at least at the 2-digit ISIC level
  • Coordinate with the SDDS for timely data release
• Training Program:
  • Covered price index concepts, compilation methodology, and survey procedures
  • Provided guidance on splicing and linking index series

Appendices

• Appendix I: PPI Project Tasks and Timetable
• Appendix II: XMPI Project Tasks and Timetable
• Appendix III: MPS Field Interviewers Instructions
• Appendix IV: Introductory Letter to Importers
• Appendix V: Interview Guide
• Appendix VI: Example of a Generic MPS Questionnaire
• Appendix VII: PPI/XMPI Training Program Outline

Conclusion

The mission highlighted the need for improved data collection, streamlined methodologies, and enhanced training to ensure the accuracy, reliability, and serviceability of the PPI and XMPI. The focus on monthly data collection and a common reference base period for both indices aims to improve their utility for economic analysis and policy-making. The development of the XMPI, particularly the MPI, requires careful attention to data availability and sampling techniques, with a clear plan for implementation and future extension.