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Bayesian estimation of bidding process and bidder’s preference under shape restrictions

Dong Li (), Luya Wang () and Ximing Wu
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Luya Wang: The Capital University of Economics and Business
Ximing Wu: Texas A&M University

Empirical Economics, 2021, vol. 60, issue 1, No 7, 157-176

Abstract: Abstract This paper applies a novel nonparametric estimator to the modeling of auctions subject to shape restrictions. In particular, we employ a Bayesian estimator with a Gaussian process prior parameterized by a spectral representation. We use squared Gaussian processes to model the functional derivatives and therefore are able to impose global shape restrictions. Our first application is the estimation of a monotonically increasing bidding process of online auctions. The second application concerns the estimation of bidders’ risk-averse latent preferences in sealed-bid timber auctions. The results show that the shape-constrained estimator not only ensures the conformity with economic theories but also improves estimation precision.

Keywords: Bayesian estimation; Auctions; Shape restrictions; Squared Gaussian processes (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s00181-020-01932-1

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