scholarly journals Identification of the distribution of valuations in an incomplete model of English auctions

2015 ◽  
Author(s):  
Adam Rosen ◽  
Andrew Chesher
Keyword(s):  
English Auctions ◽  
Incomplete Model

scholarly journals Inference with an Incomplete Model of English Auctions

2003 ◽  
Vol 111 (1) ◽  
pp. 1-51 ◽  
Author(s):  
Philip A. Haile ◽  
Elie Tamer
Keyword(s):  
English Auctions ◽  
Incomplete Model

Effects of incomplete parameterization on full-wavefield viscoelastic seismic data for petrophysical reservoir properties

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. O9-O17 ◽  
Author(s):  
Upendra K. Tiwari ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Input Data ◽  
Elastic Model ◽  
Quality Factors ◽  
Noise Levels ◽  
Reservoir Properties ◽  
Estimated Parameters ◽  
Model Parameterization ◽  
The Earth ◽  
Incomplete Model

In inversion of viscoelastic full-wavefield seismic data, the choice of model parameterization influences the uncertainties and biases in estimating seismic and petrophysical parameters. Using an incomplete model parameterization results in solutions in which the effects of missing parameters are attributed erroneously to the parameters that are included. Incompleteness in this context means assuming the earth is elastic rather than viscoelastic. The inclusion of compressional and shear-wave quality factors [Formula: see text] and [Formula: see text] in inversion gives better estimates of reservoir properties than the less complete (elastic) model parameterization. [Formula: see text] and [Formula: see text] are sensitive primarily to fluid types and saturations. The parameter correlations are sensitive also to the model parameterization. As noise increases in the viscoelastic input data, the resolution of the estimated parameters decreases, but the parameter correlations are relatively unaffected by modest noise levels.

In vivoquantitation of metabolites with an incomplete model function

2009 ◽  
Vol 20 (10) ◽  
pp. 104032 ◽  
Author(s):  
E Popa ◽  
E Capobianco ◽  
R de Beer ◽  
D van Ormondt ◽  
D Graveron-Demilly
Keyword(s):  
Model Function ◽  
Incomplete Model

scholarly journals Projection of Private Values in Auctions

2021 ◽  
Vol 111 (10) ◽  
pp. 3256-3298
Author(s):  
Tristan Gagnon-Bartsch ◽  
Marco Pagnozzi ◽  
Antonio Rosato
Keyword(s):  
Allocative Efficiency ◽  
Reserve Price ◽  
English Auctions ◽  
Common Value ◽  
Private Values ◽  
Optimal Reserve ◽  
Intensity Of Competition

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)

scholarly journals Dynamic Logic for Data-aware Systems: Decidability Results

2017 ◽  
Author(s):  
Francesco Belardinelli ◽  
Andreas Herzig
Keyword(s):  
Model Checking ◽  
Dynamic Logic ◽  
English Auctions ◽  
First Order ◽  
Formal Framework ◽  
Data Content ◽  
Order Extension

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.

Prospects for Social Reporting in the United States: A Receding Horizon

1987 ◽  
Vol 8 (x) ◽  
pp. 251-261
Author(s):  
Richard C. Rockwell
Keyword(s):  
Social Sciences ◽  
United States ◽  
Real World ◽  
The United States ◽  
Social Reporting ◽  
Social Scientists ◽  
Scientific Advance ◽  
The Real ◽  
Incomplete Model ◽  
The Social

This essay sets forth the thesis that social reporting in the United States has suffered from an excess of modesty among social scientists. This modesty might be traceable to an incomplete model of scientific advance. one that has an aversion to engagement with the real world. The prospects for social reporting in the United States would be brighter if reasonable allowances were to be made for the probable scientific yield of the social reporting enterprise itself. This yield could support and improve not only social reporting but also many unrelated aspects of the social sciences.

Shouldn’t a Model “Know” Its Own ID?: Banks Can Significantly Improve Their Model Discipline by Embedding One Critical Piece of Information

2018 ◽  
Keyword(s):  
Source Code ◽  
Geographic Region ◽  
Financial Industry ◽  
Legal Entity ◽  
Root Cause ◽  
Model Source ◽  
Actual Model ◽  
Incomplete Model ◽  
Embedded Model

The unique IDs that firms assign to all important models typically appear in just three places: model documents, validation documents, and model inventory databases. Where the IDs do not, as a rule, appear is within the actual model source code. Incomplete model inventory information (including usage) is a chronic issue throughout the financial industry. Few firms can accurately answer such vexing questions as how many times each model in inventory was executed during the last year, which models exhibit significant seasonality, which models are used in each geographic region or legal entity, or whether any unvalidated models were used during the last year on any firm computer. This article will demonstrate that a root cause of model usage opacity is, unfortunately, that most models do not actually know who they are. This article will further explain how software-embedded model IDs can be leveraged to increase transparency and address some of the most difficult questions that may be posed about model usage.

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