An Introduction to the Structural Econometrics of Auction Data PDF Download

Author: Harry J. Paarsch
Publisher: MIT Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 454

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Book Description
Accompanying CD-ROM contains data and sample computer code for empirical problems.

Author: Matthew L. Gentry
Publisher: Foundations and Trends (R) in Econometrics
ISBN: 9781680834468
Category : Auctions
Languages : en
Pages : 244

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Book Description
Structural Econometrics of Auctions summarizes the structural econometric analysis of observational data from auctions.

Author: Christopher P. Adams
Publisher: CRC Press
ISBN: 1000282384
Category : Business & Economics
Languages : en
Pages : 399

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Book Description
Focuses on the assumptions underlying the algorithms rather than their statistical properties Presents cutting-edge analysis of factor models and finite mixture models. Uses a hands-on approach to examine the assumptions made by the models and when the models fail to estimate accurately Utilizes interesting real-world data sets that can be used to analyze important microeconomic problems Introduces R programming concepts throughout the book. Includes appendices that discuss many of the concepts introduced in the book, as well as measures of uncertainty in microeconometrics.

Author: Paul Milgrom
Publisher: Cambridge University Press
ISBN: 1139449168
Category : Business & Economics
Languages : en
Pages : 378

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Book Description
This book provides a comprehensive introduction to modern auction theory and its important new applications. It is written by a leading economic theorist whose suggestions guided the creation of the new spectrum auction designs. Aimed at graduate students and professionals in economics, the book gives the most up-to-date treatments of both traditional theories of 'optimal auctions' and newer theories of multi-unit auctions and package auctions, and shows by example how these theories are used. The analysis explores the limitations of prominent older designs, such as the Vickrey auction design, and evaluates the practical responses to those limitations. It explores the tension between the traditional theory of auctions with a fixed set of bidders, in which the seller seeks to squeeze as much revenue as possible from the fixed set, and the theory of auctions with endogenous entry, in which bidder profits must be respected to encourage participation.

Author: Eugene Choo
Publisher: Emerald Group Publishing
ISBN: 1783500530
Category : Business & Economics
Languages : en
Pages : 350

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Book Description
This volume focuses on recent developments in the use of structural econometric models in empirical economics. The first part looks at recent developments in the estimation of dynamic discrete choice models. The second part looks at recent advances in the area empirical matching models.

Author: Matthew Shum
Publisher: World Scientific
ISBN: 981310967X
Category : Business & Economics
Languages : en
Pages : 154

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Book Description
Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.

Author: David J. Salant
Publisher: MIT Press
ISBN: 0262028263
Category : Business & Economics
Languages : en
Pages : 199

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Book Description
A guide to modeling and analyzing auctions, with the applications of game theory and auction theory to real-world auction decision making. Auctions are highly structured market transactions primarily used in thin markets (markets with few participants and infrequent transactions). In auctions, unlike most other markets, offers and counteroffers are typically made within a structure defined by a set of rigid and comprehensive rules. Because auctions are essentially complex negotiations that occur within a fully defined and rigid set of rules, they can be analyzed by game theoretic models more accurately and completely than can most other types of market transactions. This book offers a guide for modeling, analyzing, and predicting the outcomes of auctions, focusing on the application of game theory and auction theory to real-world auction design and decision making. After a brief introduction to fundamental concepts from game theory, the book explains some of the more significant results from the auction theory literature, including the revenue (or payoff) equivalence theorem, the winner's curse, and optimal auction design. Chapters on auction practice follow, addressing collusion, competition, information disclosure, and other basic principles of auction management, with some discussion of auction experiments and simulations. Finally, the book covers auction experience, with most of the discussion centered on energy and telecommunications auctions, which have become the proving ground for many new auction designs. A clear and concise introduction to auctions, auction design, and auction strategy, this Primer will be an essential resource for students, researchers, and practitioners.

Author: Peter C. Cramton
Publisher: MIT Press (MA)
ISBN:
Category : Business & Economics
Languages : en
Pages : 678

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Book Description
A synthesis of theoretical and practical research on combinatorial auctions from the perspectives of economics, operations research, and computer science.

Author: Ajay Agrawal
Publisher: University of Chicago Press
ISBN: 0226833127
Category : Business & Economics
Languages : en
Pages : 172

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Book Description
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

Author: Jonas Peters
Publisher: MIT Press
ISBN: 0262037319
Category : Computers
Languages : en
Pages : 289

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Book Description
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.