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Merge pull request #6 from diana3135/contrib-diana3135-014
Add study_014: Davis et al. (2011) — Optimal Reserve Prices in Auctions
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studies/study_014/README.md

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# Do Auctioneers Pick Optimal Reserve Prices?
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**Authors:** Andrew M. Davis, Elena Katok, Anthony M. Kwasnica
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**Year:** 2011
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---
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## Description
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This study investigates how auctioneers set reserve prices in second-price sealed-bid auctions (described to sellers as English auctions). A well-established theoretical result, assuming risk neutrality of the seller, is that the optimal reserve price should not depend on the number of participating bidders (Roger B. Myerson 1981). In a set of controlled laboratory experiments, seller behavior often deviates from this theoretical benchmark.
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Specifically, this study tests the Cuberoot distribution treatment with bidder counts in {1, 4, 7, 10} under the NoInfo condition. Computerized bidders follow the weakly dominant strategy of bidding their private valuations, drawn from the Cuberoot distribution F(v) = (v/100)^(1/3) with mean 25 and support [0, 100]. The seller's personal valuation is zero, and the risk-neutral optimal reserve price is 42.
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The key finding: sellers systematically increase their reserve prices as the number of bidders grows (Pearson r = 0.42, p < .001), contrary to standard auction theory.
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LLM simulation baselines for this experiment are done and reported in [Feng et al., "Noise, Adaptation, and Strategy: Assessing LLM Fidelity in Decision-Making," EMNLP 2025](https://aclanthology.org/2025.emnlp-main.391.pdf). Baselines from GPT-4o and Claude Sonnet models are available in `benchmark/`.
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## Participants
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- **N:** 40
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- **Population:** University students
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## Replicated tests (human data)
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Due to the unavailability of the original human experiment data (Davis et al. 2011), we use the replicated experiment data (Davis et al. 2023) instead.
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- **Pearson correlation (reserve price vs. number of bidders)**
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Reported: r = 0.42, p < .001
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Significance level: 0.05
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## Effect sizes & auxiliary statistics
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- F1: Mean reserve prices by number of bidders (Cuberoot distribution, NoInfo):
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1 bidder: 14.85 (SD = 19.15, n = 716),
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4 bidders: 24.30 (SD = 17.90, n = 566),
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7 bidders: 32.93 (SD = 21.25, n = 458),
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10 bidders: 39.50 (SD = 25.12, n = 660).
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Overall: mean = 27.31, SD = 23.23, sell-through rate = 0.74, mean profit = 32.83.
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Risk-neutral optimal reserve price = 42.
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Raw data present in `ground_truth.json`.
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## Files
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**source/**
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- ground_truth.json
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- materials/auction_instructions.json
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- metadata.json
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- specification.json
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**scripts/**
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- config.py
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- evaluator.py
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- stats_lib.py
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- study_utils.py
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**benchmark/**
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- human_data/auction_human_data.csv
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- llm_data

studies/study_014/benchmark/human_data/auction_human_data.csv

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