Learning From Prices is a theoretical framework in experimental economics whereby agents update their beliefs and strategies in a market environment through the informational content embedded in observed price signals, distinguishing it from other learning models by its singular reliance on price data as the source of inference about underlying economic fundamentals or opponent behaviors.
297
Publications
17.9K
Citations
557
Authors
340
Institutions
Publications per year
2017–2026
84
Parents
Publications
297
Artificial Intelligence, Algorithmic Pricing, and Collusion
Emilio Calvano, Giacomo Calzolari, Vincenzo Denicolò et al. · American Economic Review · 2020 · 563 citations · Full text
1–5 of 297
Authors
557
- CH
7
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- DS
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1–5 of 557
Institutions
340
University of Pennsylvania
Philadelphia, United States
12 h-index
22 publications
1.2K citations
National Bureau of Economic Research
Cambridge, United States
12 h-index
17 publications
2K citations
Centre for Economic Policy Research
London, United Kingdom
11 h-index
14 publications
1.2K citations
University of Amsterdam
Amsterdam, The Netherlands
11 h-index
29 publications
1.8K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
13 publications
927 citations
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
16 publications
1K citations
University of Chicago
Chicago, United States
9 h-index
10 publications
954 citations
Columbia University
New York, United States
7 h-index
10 publications
1.2K citations
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Venues
- SSRN Electronic Journal
Repository · 42 publications · 1.4K citations
20
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- Management Science
11 publications · 1.1K citations
11
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- The RAND Journal of Economics
10 publications · 1.2K citations
10
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- The Review of Economic Studies
9 publications · 943 citations
9
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- American Economic Review
7 publications · 1K citations
7
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