Working Paper: NBER ID: w20523
Authors: Dominic Coey; Bradley Larsen; Kane Sweeney
Abstract: We introduce a simple and robust approach to answering two key questions in empirical auction analysis: discriminating between models of entry and quantifying the revenue gains from improving auction design. The approach builds on Bulow and Klemperer (1996), connecting their theoretical results to empirical work. It applies in a broad range of information settings and auction formats without requiring instruments or estimation of a complex structural model. We demonstrate the approach using US timber and used-car auction data.
Keywords: Auction Design; Bidding Behavior; Revenue Analysis
JEL Codes: C10; D44; L10; L13; L40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Bidder Exclusion Effect (D44) | Expected Decrease in Revenue (F69) |
| Exclusion of a Single Bidder (D44) | Decrease in Revenue (D49) |
| Number of Bidders (D44) | Independence of Valuations (D46) |
| Expected Revenue Drop (D49) | Probability of Excluded Bidder Being Highest (D44) |