Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/309825 
Year of Publication: 
2018
Citation: 
[Journal:] Eurostat Review on National Accounts and Macroeconomic Indicators (EURONA) [ISSN:] 1977-978X [Issue:] 1 [Year:] 2018 [Pages:] 79-94
Publisher: 
Publications Office of the European Union, Luxembourg
Abstract: 
The use of automated algorithms allows online shops to change product prices at short notice, depending on various parameters; this type of price-setting is known as dynamic pricing. At present, roughly 10 000 online prices are collected each month by the German Federal Statistical Office (FSO) for the German consumer price index (CPI) and the harmonised index of consumer prices (HICP), but in many cases only one price is observed each month for each product, usually at a given point in time. Dynamic pricing poses a potential challenge to consumer price statistics: to capture the correct monthly average price and to process volatile prices. To understand this challenge, a study on dynamic pricing was conducted in 2017. It was limited to products and online shops that were included in the CPI/HICP sample and used web scraping to collect prices.
Subjects: 
consumer price index
harmonised index of consumer prices
dynamic pricing
online price collection
web scraping
Document Type: 
Article

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