Sample Spacings for Identification: The Case of English Auctions With Absentee Bidding

2020 ◽  
Author(s):  
Marleen Marra
2001 ◽  
Vol 30 (7) ◽  
pp. 1435-1470 ◽  
Author(s):  
Neeraj Misra ◽  
Edward C. van der Meulen
Keyword(s):  

2021 ◽  
Vol 111 (10) ◽  
pp. 3256-3298
Author(s):  
Tristan Gagnon-Bartsch ◽  
Marco Pagnozzi ◽  
Antonio Rosato

We explore how taste projection—the tendency to overestimate how similar others’ tastes are to one’s own—affects bidding in auctions. In first-price auctions with private values, taste projection leads bidders to exaggerate the intensity of competition and, consequently, to overbid—irrespective of whether values are independent, affiliated, or (a)symmetric. Moreover, the optimal reserve price is lower than the rational benchmark, and decreasing in the extent of projection and the number of bidders. With an uncertain common-value component, projecting bidders draw distorted inferences about others’ information. This misinference is stronger in second-price and English auctions, reducing their allocative efficiency compared to first-price auctions. (JEL D11, D44, D82, D83)


Author(s):  
Francesco Belardinelli ◽  
Andreas Herzig

We introduce a first-order extension of dynamic logic (FO-DL), suitable to represent and reason about the behaviour of Data-aware Systems (DaS), which are systems whose data content is explicitly exhibited in the system’s description. We illustrate the expressivity of the formal framework by modelling English auctions as DaS, and by specifying relevant properties in FO-DL. Most importantly, we develop an abstraction-based verification procedure, thus proving that the model checking problem for DaS against FO-DL is actually decidable, provided some mild assumptions on the interpretationdomain.


2010 ◽  
Vol 22 (8) ◽  
pp. 2208-2227 ◽  
Author(s):  
Intae Lee

While the sample-spacings-based density estimation method is simple and efficient, its applicability has been restricted to one-dimensional data. In this letter, the method is generalized such that it can be extended to multiple dimensions in certain circumstances. As a consequence, a multidimensional entropy estimator of spherically invariant continuous random variables is derived. Partial bias of the estimator is analyzed, and the estimator is further used to derive a nonparametric objective function for frequency-domain independent component analysis. The robustness and the effectiveness of the objective function are demonstrated with simulation results.


2019 ◽  
Vol 109 (5) ◽  
pp. 1911-1929 ◽  
Author(s):  
Dirk Bergemann ◽  
Benjamin Brooks ◽  
Stephen Morris

We revisit the revenue comparison of standard auction formats, including first-price, second-price, and English auctions. We rank auctions according to their revenue guarantees, i.e., the greatest lower bound of revenue across all informational environments, where we hold fixed the distribution of bidders’ values. We conclude that if we restrict attention to the symmetric affiliated models of Milgrom and Weber (1982) and monotonic pure-strategy equilibria, first-price, second-price, and English auctions are revenue guarantee equivalent: they have the same revenue guarantee, which is equal to that of the first-price auction as characterized by Bergemann, Brooks, and Morris (2017). If we consider all equilibria or if we allow more general models of information, then first-price auctions have a greater revenue guarantee than all other auctions considered. (JEL D44, D83)


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