Information Aggregation in Auctions with an Unknown Number of Bidders

Information aggregation, a key concern for uniform-price, common-value auctions with many bidders, has been characterized in models where bidders know exactly how many rivals they face. A model allowing for uncertainty over the number of bidders is essential for capturing a critical condition for information to aggregate: as the numbers of winning and losing bidders grow large, information aggregates if and only if uncertainty about the fraction of winning bidders vanishes. It is possible for the seller to impart this information by precommitting to a specified fraction of winning bidders, via a proportional selling policy. Intuitively, this makes the proportion of winners known, and thus provides all the information that bidders need to make winners curse corrections.information aggregation, common-value auctions, uncertain level of competition

Modeling elastic properties of polystyrene through coarse-grained molecular dynamics simulations

This paper presents an extended coarse-grained investigation of the elastic properties of polystyrene. In particular, we employ the well-known MARTINI force field and its modifications to perform extended molecular dynamics simulations at the $\mu$s timescale, which take slow relaxation processes of polystyrene into account, such that the simulations permit analyzing the bulk modulus, the shear modulus, and the Poisson ratio. We show that through the iterative modification of MARTINI force field parameters it turns out to be possible to affect the shear modulus and the bulk modulus of the system, making them closer to those values reported in the experiment.Comment: 29 pages, 8 figure