The Billion Prices Project: Using Online Prices for Measurement and Research

Cavallo, Alberto; Rigobón, Roberto

doi:10.3386/w22111

Cited by 64 publications

(66 citation statements)

References 3 publications

(3 reference statements)

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“…One explanation may be that online prices adjust faster to shocks. That would be consistent with the unsynchronized price change results in this paper and the anticipation in online price indices documented in Cavallo and Rigobon (2016). Another potential reason is that location-specific sales or offline price dispersion may play a larger role than I can detect in these data.…”

Section: Discussionsupporting

confidence: 75%

“…Online prices are not only cheaper to collect, but they also provide information for all goods sold by each retailer, with many details per product, uncensored price spells, and can be collected on a high-frequency basis without any delays. Of course, there are also many potential disadvantages of using online data, including limited sector coverage and the lack of information on quantities, as we discuss in Cavallo and Rigobon (2016). But from a data-collection perspective, my results suggest that the online-offline price differences should not be a major source of concern.…”

Section: Discussionmentioning

confidence: 78%

“…In most cases, the robot was designed to use the website's search box to enter the product id obtained offline. For more general details on the BPP's online scraping methods, see Cavallo and Rigobon (2016).…”

Section: Collecting Online Prices On Each Retailer's Websitementioning

confidence: 99%

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Are Online and Offline Prices Similar? Evidence from Large Multi-Channel Retailers

Cavallo

2017

American Economic Review

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254

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Online prices are increasingly used for measurement and research applications, yet little is known about their relation to prices collected offline, where most retail transactions take place. I conduct the first large-scale comparison of prices simultaneously collected from the websites and physical stores of 56 large multi-channel retailers in 10 countries. I find that price levels are identical about 72 percent of the time. Price changes are not synchronized but have similar frequencies and average sizes. These results have implications for national statistical offices, researchers using online data, and anyone interested in the effect of the Internet on retail prices. (JEL D22, L11, L81, O14)

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 78%

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Are Online and Offline Prices Similar? Evidence from Large Multi-Channel Retailers

Cavallo

2017

American Economic Review

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254

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“…Scanner data also permit the analysis of prices recorded on-line and at the individual store level offering a wealth of new information. The Billion Prices Project at the Massachusetts Institute of Technology began recording scanner data in a number of countries in 2008 and surpassed its 'billion' label in under two years (see Cavallo and Rigobon, 2016).…”

Section: New Data New Developmentsmentioning

confidence: 99%

Forty Years of Price Transmission Research in the Food Industry: Insights, Challenges and Prospects

Lloyd¹

2016

J Agricultural Economics

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Price transmission refers to a process via which information is transmitted between participants in a market. Focusing on vertical markets such as the food chain, this Address considers developments in theory, methods and data that help economists understand how information is conveyed between food consumers and agricultural producers. Central to this understanding is the increasingly important role played by the food industry (retailing, manufacturing and processing) in price transmission. Not only is the food industry a major source of the price changes that producers and consumers face but it also mediates price signals originating in other parts of the food chain in increasingly nuanced ways, as revealed by highly detailed retail (‘scanner’) data that is becoming progressively available to researchers. While the speed, magnitude and asymmetry of price transmission are valuable descriptors of price adjustment in vertical markets, we should be wary of inferring too much about the competitive setting on the basis of prices alone. Theory‐consistent empirical models are a step in the right direction and represent a useful complement to the approaches developed in the New Empirical Industrial Organisation literature which address the issue of market power directly. Being the mechanism underlying food inflation, price transmission also has an important macro‐economic dimension, and concerns about competition surface here too. Given the rapidly changing nature of the food industry in many countries, the need to understand the forces shaping price transmission is as cogent as ever.

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“…These big data techniques have the potential to improve measurement of economic indicators. For example, Cavallo and Rigobon (2016) scrape the web to collect billions of prices for millions of products to construct prices 1 E.g. U.S. Economy Grew 1.4% in Fourth Quarter (http://www.bloomberg.com/news/articles/2016-03-25/u-seconomy-grew-1-4-in-fourth-quarter-supported-by-consumers), China's Economy Grew by 6.7% in First Quarter of 2016 (http://blogs.wsj.com/chinarealtime/2016/04/15/chinas-economy-grew-by-6-7-in-first-quarter-of-2016/).…”

Section: Introductionmentioning

confidence: 99%