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the claim

Web-scraped data can accurately construct consumer price indices

the verdict
SUPPORTED
the evidence backs this
Recorded sources
7 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that web-scraped data can accurately construct consumer price indices?

Yes. Multiple studies demonstrate that web-scraped data can be effectively utilized to construct and forecast consumer price indices, yielding results comparable to traditional scanner and survey data.

Verdict: SUPPORTED · 7 sources for, 0 against · Last checked

The analysis

The retrieved literature consistently supports the assertion that web-scraped data can be used to construct consumer price indices. Multiple studies (such as papers 1, 3, 5, 7, 8, and 10) show that online price data, when paired with appropriate index formulas (like GEKS or hedonic adjustments) and weighting techniques (such as those in paper 4), produce price indices that align closely with traditional official statistics or scanner benchmarks. None of the papers refute this capacity; rather, they explore methodological challenges like high churn rates or weighting estimation and successfully offer solutions.

Evidence for · 7
Tracking and modelling prices using web‐scraped price microdata: towards automated daily consumer price index forecasting
2018
The authors demonstrate that web-scraped price microdata can be successfully modeled to track and forecast consumer price indices more frequently.
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Powell, B., Nason, G., Elliott, D., Mayhew, M., Davies, J., & Winton, J. (2018). Tracking and modelling prices using web‐scraped price microdata: towards automated daily consumer price index forecasting. doi.org. https://doi.org/10.1111/rssa.12314

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More for · 6
Comparing Price Indices of Clothing and Footwear for Scanner Data and Web Scraped Data
2019
The study compares web-scraped and scanner data for clothing and footwear, finding small overall differences in price indices.
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Chessa, A. & Griffioen, R. (2019). Comparing Price Indices of Clothing and Footwear for Scanner Data and Web Scraped Data. doi.org. https://doi.org/10.24187/ecostat.2019.509.1984

Estimating Weights for Web-Scraped Data in Consumer Price Indices
2022
The article proposes methods for estimating expenditure weights from web-scraped data to construct accurate weighted item-level price indices.
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Ayoubkhani, D. & Thomas, H. (2022). Estimating Weights for Web-Scraped Data in Consumer Price Indices. doi.org. https://doi.org/10.2478/jos-2022-0002

Web scraped data in consumer price indices
2023
The paper demonstrates methods for aggregating daily web-scraped price data to determine monthly prices used by statistical institutes for CPI.
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Knížat, P. (2023). Web scraped data in consumer price indices. doi.org. https://doi.org/10.3233/sji-220115

Assessing the effect of new data sources on the consumer price index: a deterministic approach to uncertainty and sensitivity
2022
The empirical study assesses the impact of incorporating scraped data into consumer price indices and highlights its role in price dynamics analysis.
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Białek, J., Panek, T., & Zwierzchowski, J. (2022). Assessing the effect of new data sources on the consumer price index: a deterministic approach to uncertainty and sensitivity. doi.org. https://doi.org/10.2478/stattrans-2022-0027

The use of web-scraped data to analyze the dynamics of footwear prices
2021
The study confirms the feasibility of using web-scraped data from online shops to calculate price indices like GEKS and chained indexes.
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Juszczak, A. (2021). The use of web-scraped data to analyze the dynamics of footwear prices. doi.org. https://doi.org/10.22367/jem.2021.43.12

Research on the improvement of CPI basic classification index compilation method in digital economy.
2025
The authors construct an improved price index model using web-scraped mobile phone and laptop data to compile reliable price indices in the digital economy.
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Z, D. & J, D. (2025). Research on the improvement of CPI basic classification index compilation method in digital economy.. doi.org. https://doi.org/10.1371/journal.pone.0322465

Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 8204 Aug 2026
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