Using data from "WebsiteX", one of the largest online marketplaces in the world, we estimate a structural model of sponsored search auctions where bidders have heterogeneous click-through curves. Unlike earlier studies, our model accommodates two stylized empirical facts: the advertiser...

This paper studies identification and estimation of first-price auctions if the bidders face ambiguity about the distribution of valuations. Ambiguity is modeled using Gilboa and Schmeidler's (1989) Maxmin Expected Utility preferences. We exploit variation in the number of bidders to identify...

We estimate demand for personal computer processors using structural estimation of valuations and data from Internet multi-object discriminatory auctions. Three models of bidding and a suitable econometric procedure are used to compute the parameters that govern the distribution of the buyers'...

In this paper we propose a two-step semiparametric procedure to estimate first-price auction models. In the first-step, we estimate the bid density and distribution using local polynomial method, and recover a sample of (pseudo) private values. In the second-step, we apply the method of moments...

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...

The paper presents conditions for non-parametric identification of a joint distribution when the marginal distributions are identified and the joint distribution is only identified for a subset of the domain. This result is applied to sealed bid auctions where bidders face competing auctions for...

This paper shows point identification in first-price auction models with risk aversion and unobserved auction heterogeneity by exploiting multiple bids from each auction and variation in the number of bidders. The required exclusion restriction is shown to be consistent with a large class of...

This paper reviews recent developments in nonparametric identification of measurement error models and their applications in applied microeconomics, in particular, in empirical industrial organization and labor economics. Measurement error models describe mappings from a latent distribution to...