Abstract:
Combinatorial auctions are economically efficient mechanisms to allocate multiple, potentially synergistic or substitutable items. Despite their economic advantages, however, computational difficulties in implementation have kept them from becoming widely used. The literature has proposed several methods of circumventing the computational barriers combinatorial auctions pose. One such approach is the graphical valuations model presented by Daron Acemoglu in 2012. Ozan Candogan then designs a computationally feasible iterative auction using the graphical valuations model. This paper builds on the work presented in [Acemoglu et al. 2012] and [Candogan 2013] as well as the broader combinatorial auctions literature by presenting an analysis of the revenue performance of Candogan's iterative auction. In particular, this paper explores salient revenue and allocative efficiency results after implementing reserve prices in Candogan's auction mechanism.
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