• Corpus ID: 199668875

Nonparametric identification of first-price auction with unobserved competition: A density discontinuity framework

@article{Guerre2019NonparametricIO,
  title={Nonparametric identification of first-price auction with unobserved competition: A density discontinuity framework},
  author={Emmanuel Guerre and Yao Luo},
  journal={arXiv: Econometrics},
  year={2019}
}
We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders N. We show that, if the bidders observe N, the resulting discontinuities in the winning bid density can be used to identify the distribution of N. The private value distribution can be identified in a second step. A second class of models considers endogenously determined N, due to a reserve… 

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