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Bayesian Analysis and Uncertainty in Economic Theory

Bayesian Analysis and Uncertainty in Economic Theory
Author: Richard Michael Cyert
Publisher: Springer Science & Business Media
Total Pages: 278
Release: 2012-12-06
Genre: Business & Economics
ISBN: 9400931638

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We began this research with the objective of applying Bayesian methods of analysis to various aspects of economic theory. We were attracted to the Bayesian approach because it seemed the best analytic framework available for dealing with decision making under uncertainty, and the research presented in this book has only served to strengthen our belief in the appropriateness and usefulness of this methodology. More specif ically, we believe that the concept of organizational learning is funda mental to decision making under uncertainty in economics and that the Bayesian framework is the most appropriate for developing that concept. The central and unifying theme of this book is decision making under uncertainty in microeconomic theory. Our fundamental aim is to explore the ways in which firms and households make decisions and to develop models that have a strong empirical connection. Thus, we have attempted to contribute to economic theory by formalizing models of the actual pro cess of decision making under uncertainty. Bayesian methodology pro vides the appropriate vehicle for this formalization.


Uncertainty in Economic Theory

Uncertainty in Economic Theory
Author: Itzhak Gilboa
Publisher: Routledge
Total Pages: 584
Release: 2004-08-02
Genre: Business & Economics
ISBN: 1134344155

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This volume brings together important papers, coupled with new introductions, in the massively influential area of uncertainty in economic theory. Seminal papers are available together for the first time in book format, with new introductions and under the steely editorship of Itzhak Gilboa - this book is a useful reference tool for economists all over the globe.


Precision Theory

Precision Theory
Author: Ian M. Dobbs
Publisher:
Total Pages:
Release: 1985
Genre: Mathematical statistics
ISBN:

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Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics

Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics
Author: Nguyen Ngoc Thach
Publisher: Springer Nature
Total Pages: 865
Release: 2022-05-28
Genre: Technology & Engineering
ISBN: 3030986896

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This book overviews latest ideas and developments in financial econometrics, with an emphasis on how to best use prior knowledge (e.g., Bayesian way) and how to best use successful data processing techniques from other application areas (e.g., from quantum physics). The book also covers applications to economy-related phenomena ranging from traditionally analyzed phenomena such as manufacturing, food industry, and taxes, to newer-to-analyze phenomena such as cryptocurrencies, influencer marketing, COVID-19 pandemic, financial fraud detection, corruption, and shadow economy. This book will inspire practitioners to learn how to apply state-of-the-art Bayesian, quantum, and related techniques to economic and financial problems and inspire researchers to further improve the existing techniques and come up with new techniques for studying economic and financial phenomena. The book will also be of interest to students interested in latest ideas and results.


Bayesian Analysis in Economic Theory and Time Series Analysis

Bayesian Analysis in Economic Theory and Time Series Analysis
Author: Charles A. Holt
Publisher: North-Holland
Total Pages: 200
Release: 1980
Genre: Business & Economics
ISBN:

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Bidding for contract; A bayesian approach to the spectral analysis of stationary time series.


Bayesian Models in Economic Theory

Bayesian Models in Economic Theory
Author: Marcel Boyer
Publisher: North Holland
Total Pages: 336
Release: 1984
Genre: Business & Economics
ISBN:

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Principles of Uncertainty

Principles of Uncertainty
Author: Joseph B. Kadane
Publisher: CRC Press
Total Pages: 497
Release: 2020-11-25
Genre: Mathematics
ISBN: 1351683357

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Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. ... the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. ... A must-read for sure! —Christian Robert, CHANCE It's a lovely book, one that I hope will be widely adopted as a course textbook. —Michael Jordan, University of California, Berkeley, USA Like the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems. Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied


The Economics of Uncertainty. (PSME-2), Volume 2

The Economics of Uncertainty. (PSME-2), Volume 2
Author: Karl Hendrik Borch
Publisher: Princeton University Press
Total Pages: 236
Release: 2015-12-08
Genre: Business & Economics
ISBN: 1400874769

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Game theory has brought into economics an uncertainty principle similar to the one brought into physics by the quantum theory. Professor Barch's main purpose in this book is to show how one can construct realistic economic theories by taking uncertainty into account instead of dismissing it. He brings together a number of recent developments in different fields of economics and other social sciences in which uncertainty and chance play a central role and shows that they really constitute an entity. These developments include the revisions of utility, the introduction of game theory as a basic tool, and the view of the foundations of probability theory adopted by modern Bayesian statisticians. Originally published in 1968. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.


Bayesian Theory and Applications

Bayesian Theory and Applications
Author: Paul Damien
Publisher: Oxford University Press
Total Pages: 717
Release: 2013-01-24
Genre: Mathematics
ISBN: 0199695601

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This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.


Probability and Bayesian Statistics

Probability and Bayesian Statistics
Author: R. Viertl
Publisher: Springer Science & Business Media
Total Pages: 505
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461318858

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This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics and stochastic processes, to real applications in economics, reliability and hydrology. Also the question is raised if it is necessary to develop new techniques to model and analyze fuzzy observations in samples. The articles are arranged in alphabetical order according to the family name of the first author of each paper to avoid a hierarchical ordering of importance of the different topics. Readers interested in special topics can use the index at the end of the book as guide.