Nonparametric Approaches to Auctions

Abstract

This chapter discusses structural econometric approaches to auctions. Remarkably, much of what can be learned from auction data can be learned without restrictions beyond those derived from the relevant economic model. This enables us to take a nonparametric perspective in discussing how the structure of auction models can be combined with observables to uncover (or test hypotheses about) primitives of interest in auction markets. We focus on first-price sealed-bid and ascending auctions, including extensions to Dutch auctions, Internet auctions, multi-unit auctions, and multi-object auctions. We consider a wide range of underlying structures of bidder demand and information, as well as a variety of types of data one may encounter in applications. We discuss identification and testable restrictions of these models and present a variety of estimation approaches.

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