Collection of prices of recreational goods and electronic and electrical appliances in the EU David Mair, Head of Unit on Consumer Markets, DG SANCO for the Conference Statistical architecture for consumer prices Luxembourg October 2009

1.The objectives of the study 2.Contractor and his offer 3.Description of the source data 4.Problems encountered and solutions taken 5.Deficiencies of data and collection Contents

The objectives of the study Collection of prices of goods that are: Comparable and substituable from a consumer perspective (not necessarily identical models) Representative: product (may be represented by different substituable models) shall be for sale in the overwhelming majority of the Member States and have significant market share within the product group

Contractor and his offer GfK Marketing Services Ltd., London Monthly or bi-monthly syndicated collection of prices by models in shops Collection covers max 21 countries (Austria, Belgium, Bulgaria, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom) For some categories and some countries data not collected or confidential (if 1 or 2 sellers only)

10 product groups covered by the offer Recreational goods and household electronics Flat screen TVs Digital cameras Mp3 Notebooks Refrigerators Filter Coffee makers Irons Microwave ovens Vacuum cleaners Washing machines

Description of the source data Syndicated collection – number of shops: for consumer electronics from 247 in Slovenia to in Germany for household appliances from 390 in Slovenia to in Italy for mobile computers from 550 in Ireland to 7510 in Germany Other shops: extrapolation from the sample – problem of sample choice Prices calculated as sales/units sold (»natural average » of prices)

Description of the source collection of prices cont. Sales channels cuts available: Consumer electronics shops/Mass Merchants; online/offline No regional structure Monthly/bimonthly collection (depending on type of product) Problem of seasonality not solved Problem of confidentiality in particular cases (e.g. exclusive distributors)

Problems encountered Period to choose – annual chosen, to avoid seasonality bias Number of models (from for digital cameras to for mobile computers) – scattered nature of the market Comparability vs. representativity: very few models actually sold across Europe

Solution to comparability vs representativity 2 levels of comparability – models and « technical segments » (groups of models of the same features) 3 levels of representativity (sold in all countries, in most, in big majority) The « most adequate » (sufficiently covering the market) selection chosen as principal

Problem of structural differences Situation: in any aggregate (average price per category, per group of models) strong impact of structures Solution: weighted structures (by European average structure, by the structure of the complementing channel) or fixed prices (« technicity index ») Problem: « holes » (Swiss cheese) – models of groups of models missing in a country of sales channel

Deficiencies of the collection – quality of data Sample of points of sales not randomly drawn. Not possible to estimate margins of errors Some countries not covered Problem of seasonality not solved Problem of calculation of prices out of sales and units sold Impact of structure of sales Impact of “bundles” (e.g. computers for 1 euro) Products returned –sales may be negative

Deficiencies of the collection – coverage and power relations Only 2 providers of datasets – Nielsen, GfK monopolist position vs. distributed clients impact on price of service clients should be collective (Eurostat?) Only some sectors covered Nielsen – groceries GfK - electronics

Thank you DG SANCO consumer website