Working Paper: NBER ID: w17095
Authors: Daniel J. Henderson; John A. List; Daniel L. Millimet; Christopher F. Parmeter; Michael K. Price
Abstract: Nonparametric estimators provide a flexible means of uncovering salient features of auction data. Although these estimators are popular in the literature, many key features necessary for proper implementation have yet to be uncovered. Here we provide several suggestions for nonparamteric estimation of first-price auction models. Specifically, we show how to impose monotonicity of the equilibrium bidding strategy; a key property of structural auction models not guaranteed in standard nonparametric estimation. We further develop methods for automatic bandwidth selection. Finally, we discuss how to impose monotonicity in auctions with differering number of bidders, reserve prices, and auction-specific characteristics. Finite sample performance is examined using simulated data as well as experimental auction data.
Keywords: Nonparametric Estimation; First-Price Auctions; Monotonicity; Bandwidth Selection
JEL Codes: C12; C14; D44
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Imposing monotonicity on the estimated bidding strategy (D44) | More accurate estimations of the bid-value relationship (D44) |
| Using constraint weighted bootstrapping (C51) | Improved estimates of the bid-value relationship (D44) |
| Using constraint weighted bootstrapping (C51) | Optimal reserve prices (D44) |
| Automated bandwidth selection method (C45) | Enhanced accuracy of estimates (C51) |
| Constrained estimator (C51) | Better performance in terms of bias and variance (C52) |