This paper considers nonparametric identification of a two‐stage entry and bidding game we call the Affiliated‐Signal (AS) model. This model assumes that potential bidders have private values, observe signals of their values prior to entry, and then choose whether to undertake a costly entry...

This paper considers nonparametric identification of a two-stage entry and bidding model for auctions which we call the Affiliated-Signal (AS) model. This model assumes that potential bidders have private values, observe imperfect signals of their true values prior to entry, and choose whether...

In this paper, we propose a new class of asymptotically efficient estimators for moment condition models. These estimators share the same higher order bias properties as the generalized empirical likelihood estimators and once bias corrected, have the same higher order efficiency properties as...

Greece's debt-to-GDP ratio is reaching unsustainable levels. But why should the debt load of such a small country cause such outsized tremors in global financial markets?Greek debt may be relatively small, but a sufficient amount is held by a few major banks in Europe to cause disruptions to the...

Multiple prizes are usually awarded in contests (e.g., internal promotions, school admissions, sports, etc.) and players exert effort to increase their chances for winning a higher prize. A multi-prize contest model must provide each player's probabilities of winning each prize as functions of...

In this paper, we identify a set of axioms that is necessary and sufficient for axiomatizing the reverse nested lottery contest proposed by Fu, Lu and Wang (2014), which is the "mirror image" of the conventional nested lottery contest of Clark and Riis (1996). This paper thus provides an...

We establish the effort-maximizing rule of allocating heterogeneous prizes when contestants privately observe their effort efficiencies. With ex ante symmetric players and increasing virtual effort efficiency, an all pay auction maximizes the total expected effort.