Nonparametric estimation of first-price auctions with risk-averse bidders

Uncertainty about ex post realized values is an inherent component in many auction environments. In this article, we develop a structural framework to analyze auction data subject to ex post uncertainty as a pure risk. We consider a low‐price sealed‐bid auction model with heterogeneous bidders' preferences and ex post uncertainty. The uncertainty can be common to all bidders or idiosyncratic. We derive the model restrictions and study nonparametric and semiparametric identification of the model primitives under exogenous and endogenous participation. We then develop multistep nonparametric and semiparametric estimation procedures in both cases.

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“…Similarly, for

{\overset{V}{true}}_{1} false(\cdot false)

we obtain

0true prefixexp \int_{η}^{\cdot - π_{0}} 1 / {\hat{normalΛ}}_{1} (x) italicdx

, where

{\overset{Λ}{true}}_{1}^{- 1} false(1 / {\hat{H}}_{1} ({\overset{b}{true}}_{1 α}) false) = {\overset{b}{true}}_{1 α} - {\overset{b}{true}}_{0 α} + {\overset{Λ}{true}}_{0}^{- 1} false(1 / {\hat{H}}_{0} ({\overset{b}{true}}_{0 α}) false)

. See Guerre and Vuong () and Zincenko ().…”

Section: Identification and Estimationmentioning

confidence: 93%

Auctions with ex post uncertainty

Luo

Perrigne

Vuong

2018

The RAND J of Economics

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“…Potential bidders have independent private values, observe signals of their values prior to entry, and choose whether to incur a common-knowledge entry cost, with entrants learning their values and submitting bids. This framework nests many existing models as special cases, including the affiliated-signal (AS) models of Marmer, Shneyerov, and Xu (2013) and Gentry and Li (2014) (henceforth GL); the mixed-strategy entry model of Levin and Smith (1994); and models with risk averse bidders but exogenous entry including Guerre, Perrigne, and Vuong (2009) (henceforth GPV), Campo, Guerre, Perrigne, and Vuong (2011) (henceforth CGPV) and Zincenko (2018). It thus represents a natural focal point for researchers seeking to understand structural interactions between risk aversion and entry.…”

Section: Introductionmentioning

confidence: 80%

Identification and Inference in First-Price Auctions with Risk Averse Bidders and Selective Entry

Chen¹,

Gentry

et al. 2020

SSRN Journal

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We study identification and inference in first-price auctions with risk averse bidders and selective entry, building on a flexible entry and bidding framework we call the Affiliated Signal with Risk Aversion (AS-RA) model. Assuming that the econometrician observes either exogenous variation in the number of potential bidders (N) or a continuous instrument (z) shifting opportunity costs of entry, we provide a sharp characterization of the nonparametric restrictions implied by equilibrium bidding. Given variation in either competition or costs, this characterization implies that risk neutrality is nonparametrically testable in the sense that if bidders are strictly risk averse, then no risk neutral model can rationalize the data. In addition, if both instruments (discrete N and continuous z) are available, then the model primitives are nonparametrically point identified. We then explore inference based on these identification results, focusing on set inference and testing when primitives are set identified.

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“…To learn about bidders' risk averseness, we consider the Guerre, Perrigne, and Vuong (2009) approach. For estimation methods based on this approach, see Zincenko (2014) and Kim (2015). For other approaches, see, e.g., Lu and Perrigne (2008) for exploiting the exogenous change of auction format, Campo, Guerre, Perrigne, and Vuong (2011) for a semiparametric method and Fang and Tang (2014) for using entry behaviors.…”

Section: Related Literaturementioning

confidence: 99%

Unobserved heterogeneity in auctions under restricted stochastic dominance

Luo

2020

Journal of Econometrics

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We study the identification of first-price auctions with nonseparable unobserved heterogeneity. In particular, we extend Hu, McAdams, and Shum (2013) by relaxing the first-order stochastic dominance condition. Instead, we assume restricted stochastic dominance relations among the value quantile functions and show that the same relations pass to the bid quantile functions. An ordered tree summarizes these relations and provides a total ordering. Relying on the proposed restricted stochastic dominance ordering, we extend a list of identification results in the empirical auction literature.

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Nonparametric estimation of first-price auctions with risk-averse bidders

Cited by 24 publications

References 32 publications

Auctions with ex post uncertainty

Auctions with ex post uncertainty

Identification and Inference in First-Price Auctions with Risk Averse Bidders and Selective Entry

Unobserved heterogeneity in auctions under restricted stochastic dominance

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