United Nations Economic Commission for EuropeStatistical DivisionUnited Nations Economic Commission for EuropeStatistical Division
PPI and XMPI Compilation
Seminar on challenges in economic StatisticsTehran, Iran
November 2008
Presentation by Carsten Boldsen Hansen, UNECE([email protected])
November 2008 UNECE Statistical Division Slide 2
Overview
1. The PPI family
2. PPI in an open market economy
3. Export and import price indices (XMPI)
4. International recommendations
5. Future challenges
November 2008 UNECE Statistical Division Slide 3
1. The PPI family
Producer price indices
Output PPIs Input PPIs
PPI – Production for the domestic market
PPI – Production for export
PPI – Total production
PPI – Input from the domestic market
PPI – Total input
PPI – Input from imports
November 2008 UNECE Statistical Division Slide 4
2. PPI in an open market economy
Coverage of production and establishments:
The statistical unit for the PPI should be the “output generating entity”, the establishment, as outlined in the SNA
Traditionally, one would like the PPI to cover the production on the economic territory
Economic globalization makes the identification of the statistical unit and the scope of the PPI still more difficult in practice!
November 2008 UNECE Statistical Division Slide 5
2. PPI in an open market economy
The situation today:Most PPIs limited to the industrial sector, including manufacturing, mining and energy
Agriculture and services are excluded
Services - .i.e. transport, communication, medical care, trade, business services - grow in importance.
It becomes still more problematic to leave services out
Many countries are progressively developing PPIs for services
EU member countries are required to compile PPIs for the services producing industries.
The non-observed economy – often excluded but may be important
November 2008 UNECE Statistical Division Slide 6
2. PPI in an open market economy
Challenges of economic globalization:OutsourcingGoods for processingMerchantingVirtual corporationsMultinational enterprises (MNEs)
E-commerce
Makes the production of statistics, also the PPI,more difficult – and more challenging!
November 2008 UNECE Statistical Division Slide 7
2. PPI in an open market economy
Goods for processing – current treatment
Goods for processing – new SNA/BOP convention
Finished Goods
Service included in Finished Goods
Goods for processing Company A Company B
Country X Country Y
Cash = value of service
Finished Goods
Cash = value of service
Processing Service
Goods for processing Company A Company B
Country X Country Y
November 2008 UNECE Statistical Division Slide 8
2. PPI in an open market economy
Merchanting
An enterprise in country A buys goods in country B
The goods never enter country A but are sold to country C
The ownership moves from B to A and from A to C
NA will look for values of flows according to change in ownership
What will the PPI compilers do?
Merchanting
(International Wholesaler)
Inventories
Customer Supplier
Country A
Country B Country C
November 2008 UNECE Statistical Division Slide 9
2. PPI in an open market economy
The challenges of globalization
The traditional coverage and relevance of PPI is questioned
How to decide which production activities to include- in principle- in practice
The treatment of “globalized” production may also depends on the different purposes of PPI
If such activities are included, how should they be price followed?
There are no easy or general answers to these questions
November 2008 UNECE Statistical Division Slide 10
2. PPI in an open market economy
The prices:
For the PPI it should be the prices received by the producer, i.e. basic prices (SNA) excluding taxes plus subsidiesInput PPIs: The price actually paid by the purchaser, including taxes net of subsidies, i.e. purchasers‘ prices
Transfer pricesBecomes more common as (international) trade is growing and posses serious measurement problemsOften they do not reflect real market prices. In such cases:
☞ Use estimated or imputed prices, or☞ Exclude the transfer prices from the index
November 2008 UNECE Statistical Division Slide 11
2. PPI in an open market economy
Some recommendations
Decide on the target of the PPI – what should in principle be covered, and ensure a clear delineation
Try in practice to be as close to the target as possible
The relationship and coherence with other statistics, notably the national accounts, should also be considered.
Cooperate with national accounts, and other areas:
- may provide weighting data- may use PPI for deflation
November 2008 UNECE Statistical Division Slide 12
3. Import and export price indices
Ten basic steps to develop XMPIs:
1. Defining the objective, scope and conceptual basis2. Deciding on the coverage and classification3. Deriving the weighting patterns of the indices4. Designing the samples for the indices5. Collecting and editing the prices6. Adjusting for changes in quality7. Calculating the indices8. Disseminating the indices9. Maintaining samples of reporters and commodities10. Reviewing and reweighting the indices
November 2008 UNECE Statistical Division Slide 13
3. Import and export price indices
1) Defining objective, scope and conceptual basis of the indexConsult with stakeholders and usersConsider coherence with other data (national accounts and BOP)
2) Deciding on the coverage and classification structures of the indicesExamine data sources for weights and prices (trade statistics, customs data)Decide on the actual coverage of goods and services.Select classification
November 2008 UNECE Statistical Division Slide 14
3. Import and export price indices
The most commonly used classifications are:
Harmonized System of Commodity Description and Coding (HS) Standard International Trade Classification (SITC) Central Commodity Classification (CPC]) International Standard Industrial Classification of All Economic Activities (ISIC) The European classification of economic activities (NACE)
November 2008 UNECE Statistical Division Slide 15
3. Import and export price indices
3) Deriving the weighting patterns of the indices
Select the level at which to form the elementary aggregates
A relatively high level of aggregation - e.g. 4-digit product or industry group – gives better discretion to select replacements, introduce new products and maintain the sample
Weights aims to be representative for the period in which they are used
Some normalizing or smoothing over more years may be appropriate to avoid irregular or extreme weights
November 2008 UNECE Statistical Division Slide 16
3. Import and export price indices
4) Designing the samples for the indices
Identify the sample frame - a listing of the population of units from which to select. Data sources for a frame include:
- Customs data, - Statistical business registers, - trade organizations, - commercially maintained lists, - Registers (company registers, taxation records- Telephone directory “yellow pages,”
Select the establishments from the frame by- Purposive/judgmental sampling
- Probability sampling
Take market conditions/concentration into account
November 2008 UNECE Statistical Division Slide 17
3. Import and export price indices
5) Collecting and editing the prices
Initialize collection from a company through a personal visit, by telephone, Internet, fax or mail contact, or some combination Select the products to be price-followed
- should be representative of the whole elementary aggregateDecide on the time of price recording
- point-in-time: a specific day- period-in-time: a period of days
Use specification pricing- require well-specified product descriptions- should include all price determining characteristics- when characteristics change, adjustment should be made
Follow actual market transaction pricesConversion into domestic currency
November 2008 UNECE Statistical Division Slide 18
3. Import and export price indices
6) Adjusting for quality changes
Use well-specified & detailed product descriptionsSelect products expected to remain on the market for some timeApply quality adjustment when replacements take place
7) Calculating the index
Decide on index calculation formulas for elementary and higher-level indicesUnit value indices should be used only for strictly homogenous groups of products
November 2008 UNECE Statistical Division Slide 19
3. Import and export price indices
8) Disseminating the index
Disseminate long-term fixed base indices and 12-months rates of changesConsult with user needsProblems with confidentiality for detailed levels in XMPIs
9) Maintaining the sample of companies and products
Ensure procedures are in place to monitor and update the sample on a regular basisSome sectors are more dynamic and needs more careful and regular monitoringWeights within elementary indices needs also be updated
November 2008 UNECE Statistical Division Slide 20
3. Import and export price indices
10) Reviewing and reweighting the index
Decide on the frequency of re-weightingEvery 3 or 5 years may adequate under stable market conditionsThe more dynamic markets, the greater need for frequent update of the weightsThe greater variation in price changes, the greater need for frequent update of the weights
November 2008 UNECE Statistical Division Slide 21
5. Future Challenges for PPI and XMPI
Exercise 3:
Discuss the following questions and list your answers
a) What will be the main challenges in the calculation of CPI and PPl in your country the next 5-10 years?
b) What will be the likely obstacles – and can you propose any way in which to overcome these?
November 2008 UNECE Statistical Division Slide 22
4. International recommendations
Producer Price Index Manual. Theory and Practice (2004). www.imf.org/external/np/sta/tegppi/index.htm
Export and Import Price index Manual – forthcoming. Draft available on www.imf.org/external/np/sta/tegeipi/index.htm
Methodology of short-term business statistics. Interpretation and guidelines. Available online from Eurostat’s webpage
The Voorburg Group on Services Statistics. Webpage: http://www4.statcan.ca/english/voorburg/
Methodological Guide for Developing Producer Price Indices for Services. Eurostat, 2005. Available from Eurostat and OECD web
Handbook on price and volume measures in national accounts. Available from Eurostat website
November 2008 UNECE Statistical Division Slide 23
5. Future Challenges for PPI and XMPI
Organisation of the statistical production process
Application of international comparable classifications (COICOP, NACE, ISIC, HS)
Index calculation methods
Integration of CPI, PPI and XMPI calculation, administrative and IT-systems?
Optimization of samples
Dissemination of data and metadata