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Scanner Data – next steps ahead

Scanner Data – next steps ahead. Berthold Feldmann – Eurostat Price statistics; purchasing power parities; housing statistics. Structure of the talk. Scanner data – a new paradigm Main lessons of the last two days Challenges Time table and conclusion. 2. Chapter 1. A new universe.

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Scanner Data – next steps ahead

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  1. Scanner Data – next steps ahead Berthold Feldmann – Eurostat Price statistics; purchasing power parities; housing statistics

  2. Structure of the talk • Scanner data – a new paradigm • Main lessons of the last two days • Challenges • Time table and conclusion 2

  3. Chapter 1 A new universe

  4. Scanner data as source for consumer price indices Expected advantages Better quality of indices Low response burden of enterprises Productivity gains of National Statistical Institutes Data can be used for other purposes Purchasing Power Parities Average price levels Advanced economic analysis (e.g. substitution rates) Regional breakdown of CPI/HICP 4

  5. Scanner data as source for consumer price indices Expected disadvantages Potential biases in CPI / HICP High investment costs (IT) Some rules of European Implementing Regulations may no longer be applicable Treatment of rebates Quality adjustment Direct collection of “price observations” • Together we have to check if rules laid down in legal acts need an adaptation 5

  6. Chapter 2 Lessons learnt in the Workshop

  7. Some general conclusions We are still at an early stage in the use of scanner data as a data source Several problems still need to be solved Scanner data appears quite promising for the collection of Multipurpose Consumer Price Statistics Scanner data cannot be used for all COICOP groups Scanner data offers high quality information of actual transactions 7

  8. Conclusions on discounts Discounts are an important stimulus for increased sales important for consumers Scanner data offers new opportunities for a more precise treatment of discounts compared to traditional price collection For HICP – the inclusion of all non-discriminatory price reductions should be the rule Precise recommendations should be drafted a.s.a.p. We might need to evaluate the existing regulatory framework on price reductions 8

  9. Practical experience The exchange of views and experiences between NSIs could save a lot of time Avoid reinventing the wheel Full support from the top management of retailers is mandatory Good collaboration with data providers is a key point More volatility and some short and medium term differences when changing the price concept (transaction price versus shelf price) Major challenge: high attrition rate (up to 30%) Promising results with the use of “internal” classifications as links between EAN and COICOP 9

  10. Computation methods From GEKS to RYGEKS From RYGEKS to imputed Tornquist RYGEKS Three different methods are tested for the imputation of prices for new and disappearing items Conclusion at the lowest level of computation we might need to go beyond Laspeyres ... ... Mainly used for benchmarking 10

  11. Chapter 3 Challenges

  12. Link EAN - COICOP • EAN differ from country to country • A high proportion of EAN have a life span of less than a year • This results in a high turnover rate of product types • Automating the link of EAN to COICOP level 5 or 6 is not a trivial task • In the long run a harmonisation of EAN across Europe would be desirable

  13. Use a sample or all data? Current practise differs between countries A harmonised approach should be achieved Advantages and disadvantages of the two approaches should be discussed carefully Using a sample is closer to the traditional price observations Using all data might offer new opportunities 13

  14. Automation of editing EAN data Problem of many products disappearing and others emerging within a year Practice of some advanced National Statistical Offices can give guidelines 14

  15. Weighted or not weighted average?(product level) Should quantity information be used at basic calculations? Quantities may show huge fluctuations A Europe-wide recommendation should be achieved 15

  16. Scanner data as a source for weights(level of product groups) Quantities from scanner data could be used as weights at the lowest level (COICOP 5 or 6) In any case, only annual averages should be used as weights According to Implementing Regulation no changing weights from month to month Volatility of the data? 16

  17. Further information collected Scanner data contains more than prices and quantities Product description is important for EAN – COICOP link Information on discounts may be useful for further data analysis for economic purposes 17

  18. Scanner data versus price collectors Different results are reported from the two alternative sources for consumer price indices A thorough analysis is required to explain these differences Algorithms to be found for possible bias in scanner data 18

  19. Legal obligations National law may set different obligations in different countries Are stores obliged to supply scanner data? Can European legislation help? COUNCIL REGULATION (EC) No 2166/1999 The statistical units … called upon by the Member States to cooperate in the collection or provision of basic information are obliged to give honest and complete information at the time it is requested and allow the organisations and institutions responsible for compiling official statistics, on request, to obtain information at the level of detail necessary ……… 19

  20. IT environment High investment costs to start the regular usage of scanner data Economies of scale possible if similar solutions are used in different countries 20

  21. Chapter 4 Provisional time table

  22. A proposal for a timetable • Continue intensive discussion among experts • Enhance transparency on current practice in all European countries • Eurostat will create an overview of current practice in summer 2012 • Discussion at the Working Group meeting in October 2012 • Meeting of the Task Force “Multipurpose price statistics” shall draft first recommendations in January 2013 • Incorporation of basic rules on the use of scanner data in the new HICP Regulation

  23. Conclusion • The use of scanner data offers several advantages for future price statistics (not only consumer price indices) • Some issue connected with the use of scanner data are not easy to solve and require a harmonised approach • The European legal framework might need to be assessed if some rules need an adaptation for the use of scanner data

  24. Thank you for your attention! Any Questions ?

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