Partial Identification In Econometrics And Related Topics
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Partial Identification In Econometrics And Related Topics
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Author : Nguyen Ngoc Thach
language : en
Publisher: Springer Nature
Release Date :
Partial Identification In Econometrics And Related Topics written by Nguyen Ngoc Thach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Topics In Identification Limited Dependent Variables Partial Observability Experimentation And Flexible Modeling
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Author : Ivan Jeliazkov
language : en
Publisher: Emerald Group Publishing
Release Date : 2019-10-18
Topics In Identification Limited Dependent Variables Partial Observability Experimentation And Flexible Modeling written by Ivan Jeliazkov and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Business & Economics categories.
Volume 40B of Advances in Econometrics examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression.
Essays On Partial Identification In Econometrics And Finance
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Author : Alfred Galichon
language : en
Publisher:
Release Date : 2007
Essays On Partial Identification In Econometrics And Finance written by Alfred Galichon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
The second essay propose an alternative testing methodology with favorable computational properties, the "Dilation Bootstrap," a testing methodology based on probabilistic coupling representations of the empirical distribution.
Prediction And Causality In Econometrics And Related Topics
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Author : Nguyen Ngoc Thach
language : en
Publisher: Springer Nature
Release Date : 2021-07-26
Prediction And Causality In Econometrics And Related Topics written by Nguyen Ngoc Thach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-26 with Technology & Engineering categories.
This book provides the ultimate goal of economic studies to predict how the economy develops—and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.
Financial Econometrics Bayesian Analysis Quantum Uncertainty And Related Topics
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Author : Nguyen Ngoc Thach
language : en
Publisher: Springer Nature
Release Date : 2022-05-28
Financial Econometrics Bayesian Analysis Quantum Uncertainty And Related Topics written by Nguyen Ngoc Thach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-28 with Technology & Engineering categories.
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.
Microeconometrics
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Author : Steven Durlauf
language : en
Publisher: Springer
Release Date : 2016-06-07
Microeconometrics written by Steven Durlauf and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-07 with Literary Criticism categories.
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Identification Problems In The Social Sciences
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Author : Charles F. Manski
language : en
Publisher: Harvard University Press
Release Date : 1999-03-15
Identification Problems In The Social Sciences written by Charles F. Manski and has been published by Harvard University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-15 with Business & Economics categories.
This book provides a language and a set of tools for finding bounds on the predictions that social and behavioral scientists can logically make from nonexperimental and experimental data. The economist Charles Manski draws on examples from criminology, demography, epidemiology, social psychology, and sociology as well as economics to illustrate this language and to demonstrate the broad usefulness of the tools. There are many traditional ways to present identification problems in econometrics, sociology, and psychometrics. Some of these are primarily statistical in nature, using concepts such as flat likelihood functions and nondistinct parameter estimates. Manski's strategy is to divorce identification from purely statistical concepts and to present the logic of identification analysis in ways that are accessible to a wide audience in the social and behavioral sciences. In each case, problems are motivated by real examples with real policy importance, the mathematics is kept to a minimum, and the deductions on identifiability are derived giving fresh insights. Manski begins with the conceptual problem of extrapolating predictions from one population to some new population or to the future. He then analyzes in depth the fundamental selection problem that arises whenever a scientist tries to predict the effects of treatments on outcomes. He carefully specifies assumptions and develops his nonparametric methods of bounding predictions. Manski shows how these tools should be used to investigate common problems such as predicting the effect of family structure on children's outcomes and the effect of policing on crime rates. Successive chapters deal with topics ranging from the use of experiments to evaluate social programs, to the use of case-control sampling by epidemiologists studying the association of risk factors and disease, to the use of intentions data by demographers seeking to predict future fertility. The book closes by examining two central identification problems in the analysis of social interactions: the classical simultaneity problem of econometrics and the reflection problem faced in analyses of neighborhood and contextual effects.
Partial Identification Of Probability Distributions
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Author : Charles F. Manski
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-29
Partial Identification Of Probability Distributions written by Charles F. Manski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-29 with Mathematics categories.
The book presents in a rigorous and thorough manner the main elements of Charles Manski's research on partial identification of probability distributions. The approach to inference that runs throughout the book is deliberately conservative and thoroughly nonparametric. There is an enormous scope for fruitful inference using data and assumptions that partially identify population parameters.
Topics In Identification Limited Dependent Variables Partial Observability Experimentation And Flexible Modeling
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Author : Ivan Jeliazkov
language : en
Publisher: Emerald Group Publishing
Release Date : 2019-10-18
Topics In Identification Limited Dependent Variables Partial Observability Experimentation And Flexible Modeling written by Ivan Jeliazkov and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-18 with Business & Economics categories.
Volume 40B of Advances in Econometrics examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression.
Handbook Of Econometrics
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Author : James Joseph Heckman
language : en
Publisher: Elsevier
Release Date : 2007
Handbook Of Econometrics written by James Joseph Heckman and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Econometrics categories.
As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics. It is a tool for empirical discovery and policy analysis. The chapters in this volume embody this vision and either implement it directly or provide the tools for doing so. This vision is not shared by those who view econometrics as a branch of statistics rather than as a distinct field of knowledge that designs methods of inference from data based on models of human choice ...