Data and code for: The Common-Probability Auction Puzzle

Principal Investigator(s): View help for Principal Investigator(s) Kathleen Ngangoue, UCLA Anderson; Andrew Schotter, NYU

Version: View help for Version V1

Name	File Type	Size	Last Modified
ExpAll			03/10/2023 09:37:PM
ExpI			03/10/2023 09:37:PM
ExpII			03/10/2023 09:37:PM
ExpIII			03/10/2023 09:37:PM
ExpIIIb			03/10/2023 09:37:PM
ExpIV			03/10/2023 09:37:PM
graphs			03/10/2023 09:48:PM
ReadMe.pdf	application/pdf	477.3 KB	03/10/2023 04:36:PM
Runme.do	text/plain	1.6 KB	03/10/2023 04:36:PM
config.do	text/plain	1 KB	03/10/2023 04:36:PM

Project Citation:

Ngangoue, Kathleen, and Schotter, Andrew. Data and code for: The Common-Probability Auction Puzzle. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-05-22. https://doi.org/10.3886/E184041V1

Project Description

Summary: This paper presents a puzzle of the behavior of experimental subjects in what we call common-probability auctions. In common-value auctions, uncertainty is defined over values, while in common-probability auctions, uncertainty is defined over probabilities. We find that in contrast to the substantial overbidding found in common-value auctions, bidding in strategically equivalent common-probability auctions is consistent with Nash equilibrium. In order to explain our results, we run treatments to identify whether our observed difference stems from the way our subjects estimate the value of the object they are bidding for in a competitive environment rather than the way they bid conditional on these valuations. We conclude it is the former.

Scope of Project

Subject Terms: auction; uncertainty; winner's curse; common value

JEL Classification:
      C70 Game Theory and Bargaining Theory: General
      C90 Design of Experiments: General
      D44 Auctions
      D81 Criteria for Decision-Making under Risk and Uncertainty

Geographic Coverage: USA

Time Period(s): 2018 – 2020

Collection Date(s): 2018 – 2020

Universe: students at New York University

Data Type(s): experimental data

Methodology

Data Source: experimental data (new collection)

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Published Versions

V1 [2023-05-22]

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