The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Are Online and Offline Prices Similar? Evidence from Large Multi-Channel Retailers
Open accessAbstract
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)
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“The adherence between online and offline price levels for multichannel retailers has already been proven across multiple countries (Cavallo, 2017(Cavallo, , 2018)).”
From Sanctions and Russian online prices (2024) · cites this paper as Cavallo, 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Frictionless commerce? A comparison of Internet and conventional retailers
Brynjolfsson, E., & Smith, M. D. (2000) · Management Science · doi:10.1287/mnsc.46.4.563.12061 · Cited by 2,498
Five Facts about Prices: A Reevaluation of Menu Cost Models *
Nakamura, E., & Steinsson, J. (2008) · The Quarterly Journal of Economics · doi:10.1162/qjec.2008.123.4.1415 · Cited by 1,526
Brynjolfsson, E., Hu, Y. (., & Simester, D. (2011) · Management Science · doi:10.1287/mnsc.1110.1371 · Cited by 847
Search, Obfuscation, and Price Elasticities on the Internet
(2009) · Econometrica · doi:10.3982/ecta5708 · Cited by 562
Price dispersion and differentiation in online travel: An empirical investigation
Clemons, E. K., Hann, I.-H., & Hitt, L. M. (2002) · Management Science · doi:10.1287/mnsc.48.4.534 · Cited by 481
Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com
Chevalier, J. A., & Goolsbee, A. (2003) · Quantitative Marketing and Economics · doi:10.1023/a:1024634613982 · Cited by 459
The Billion Prices Project: Using Online Prices for Measurement and Research
Cavallo, A. F., & C, R. R. B. (2016) · The Journal of Economic Perspectives · doi:10.1257/jep.30.2.151 · Cited by 302
Self-citationRetail Strategies on the Web: Price and Non–price Competition in the Online Book Industry
Clay, K. B., Krishnan, R., Wolff, E., & Fernandes, D. (2002) · Journal of Industrial Economics · doi:10.1111/1467-6451.00181 · Cited by 296
Browse‐and‐Switch: Retail‐Online Competition under Value Uncertainty
Balakrishnan, A., Sundaresan, S., & Zhang, B. (2013) · Production and Operations Management · doi:10.1111/poms.12165 · Cited by 291
Detecting price and search discrimination on the internet
Mikians, J., Gyarmati, L., Erramilli, V., & Laoutaris, N. (2012) · Proceedings of the 11th ACM Workshop on Hot Topics in Networks · doi:10.1145/2390231.2390245 · Cited by 244
Will the growth of multi-channel retailing diminish the pricing efficiency of the web?
Tang, F.-F., & Xing, X. (2001) · Journal of Retailing · doi:10.1016/s0022-4359(01)00049-5 · Cited by 227
Income Differences and Prices of Tradables: Insights from an Online Retailer
Simonovska, I. (2010) · The Review of Economic Studies · doi:10.1093/restud/rdv015 · Cited by 219
THE MORPHOLOGY OF PRICE DISPERSION
Kaplan, G., & Menzio, G. (2015) · International Economic Review · doi:10.1111/iere.12134 · Cited by 210
Online and official price indexes: Measuring Argentina’s inflation
Cavallo, A. (2013) · Journal of Monetary Economics · doi:10.1016/j.jmoneco.2012.10.002 · Cited by 204
Self-citationThe Real Effects of Monetary Shocks in Sticky Price Models: A Sufficient Statistic Approach
Álvarez, F., Bihan, H. L., & Lippi, F. (2016) · American Economic Review · doi:10.1257/aer.20140500 · Cited by 170
Currency Unions, Product Introductions, and the Real Exchange Rate
Cavallo, A., Neiman, B., & Rigobón, R. (2014) · The Quarterly Journal of Economics · doi:10.1093/qje/qju008 · Cited by 157
Self-citationTalavera, O., & Gorodnichenko, Y. (2015) · RePEc: Research Papers in Economics · Cited by 157
Using Internet Data for Economic Research
Edelman, B. G. (2012) · The Journal of Economic Perspectives · doi:10.1257/jep.26.2.189 · Cited by 115
Tax Sensitivity and Home State Preferences in Internet Purchasing
Ellison, G., & Ellison, S. F. (2009) · American Economic Journal Economic Policy · doi:10.1257/pol.1.2.53 · Cited by 98
Brynjolfsson, E., Dick, A. A., & Smith, M. D. (2009) · Quantitative Marketing and Economics · doi:10.1007/s11129-009-9079-7 · Cited by 96
Crowd-assisted search for price discrimination in e-commerce: first results
Mikians, J., Gyarmati, L., Erramilli, V., & Laoutaris, N. (2013) · Proceedings of the ninth ACM conference on Emerging networking experiments and technologies · doi:10.1145/2535372.2535415 · Cited by 82
Xing, X., Yang, Z., & Tang, F. (2006) · Journal of Interactive Marketing · doi:10.1002/dir.20058 · Cited by 62
Price Stickiness in the US and Europe Revisited: Evidence from Internet Prices*
Lünnemann, P., & Wintr, L. (2011) · Oxford Bulletin of Economics and Statistics · doi:10.1111/j.1468-0084.2011.00657.x · Cited by 46
The Price Impact of Joining a Currency Union: Evidence from Latvia
Cavallo, A., Neiman, B., & Rigobón, R. (2015) · IMF Economic Review · doi:10.1057/imfer.2015.13 · Cited by 38
Self-citationThe FEWS Index: Fixed Effects with a Window Splice
Krsinich, F. (2016) · Journal of Official Statistics · doi:10.1515/jos-2016-0021 · Cited by 32
Distance and Political Boundaries: Estimating Border Effects under Inequality Constraints
Borráz, F., Cavallo, A. F., C, R. R. B., & Zipitría, L. (2015) · International Journal of Finance & Economics · doi:10.1002/ijfe.1517 · Cited by 27
Self-citation
Flagged first, then by citations
Research works printed but not linked: 7
- Brynjolfsson Erik, 2013, MIT Sloan Management Review, 54, 152
- Brynjolfsson Erik, 2001, Massachusetts Institute of Technology Sloan Working Paper, 4208
- Fitzgerald Drew, 2013, Wall Street Journal
- 10.1257/aer.20141127 · DOI · Paper page
- Horrigan Michael W, 2013, Amstat News
- Mattioli Dana, 2012, Wall Street Journal
- Valentino-DeVries Jennifer, 2012, Wall Street Journal
Cited by
Sorted by citations
Uniform Pricing in U.S. Retail Chains*
DellaVigna, S., & Gentzkow, M. A. (2019) · The Quarterly Journal of Economics · doi:10.1093/qje/qjz019 · Cited by 411
Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform
Brynjolfsson, E., Hui, X., & Liu, M. (2019) · Management Science · doi:10.1287/mnsc.2019.3388 · Cited by 408
Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform
Brynjolfsson, E., Hui, X., & Liu, M. (2018) · doi:10.3386/w24917 · Cited by 408
Hult, G. T. M., Sharma, P. N., Morgeson, F. V., & Zhang, Y. (2018) · Journal of Retailing · doi:10.1016/j.jretai.2018.10.003 · Cited by 350
Tariff Pass-Through at the Border and at the Store: Evidence from US Trade Policy
Cavallo, A. F., Gopinath, G., Neiman, B., & Tang, J. (2021) · American Economic Review Insights · doi:10.1257/aeri.20190536 · Cited by 303
Self-citation
Metadata
- Authors
- Cavallo, A.
- Affiliations
- National Bureau of Economic Research (US)
- Corresponding author
- Cavallo, Alberto
- ORCID
- Cavallo, Alberto
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2017-01-01
- Volume
- 107
- Issue
- 1
- Pages
- 283-303
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W2335991931
- Cited by
- 336
- References
- 26
- Citations by year
- 2026: 28 · 2025: 42 · 2024: 38 · 2023: 47 · 2022: 37 · 2021: 42 · 2020: 37 · 2019: 31 · 2018: 18 · 2017: 15
- FWCI
- 45.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Economic Review (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economics of Agriculture and Food Markets
- Social Sciences › Decision Sciences › Management Science and Operations Research › Supply Chain and Inventory Management
- Keywords
- online prices, price synchronization, multichannel retailing, price measurement, price changes, consumer price statistics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review