Econometrics With Partial Identification
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Econometrics With Partial Identification
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Author : Francesca Molinari
language : en
Publisher:
Release Date : 2019
Econometrics With Partial Identification written by Francesca Molinari and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Econometrics has traditionally revolved around point identi cation. Much effort has been devoted to finding the weakest set of assumptions that, together with the available data, deliver point identifi cation of population parameters, finite or infi nite dimensional that these might be. And point identifi cation has been viewed as a necessary prerequisite for meaningful statistical inference. The research program on partial identifi cation has begun to slowly shift this focus in the early 1990s, gaining momentum over time and developing into a widely researched area of econometrics. Partial identification has forcefully established that much can be learned from the available data and assumptions imposed because of their credibility rather than their ability to yield point identifi cation. Within this paradigm, one obtains a set of values for the parameters of interest which are observationally equivalent given the available data and maintained assumptions. I refer to this set as the parameters' sharp identifi cation region. Econometrics with partial identi fication is concerned with: (1) obtaining a tractable characterization of the parameters' sharp identification region; (2) providing methods to estimate it; (3) conducting test of hypotheses and making con fidence statements about the partially identi fied parameters. Each of these goals poses challenges that differ from those faced in econometrics with point identifi cation. This chapter discusses these challenges and some of their solution. It reviews advances in partial identifi cation analysis both as applied to learning (functionals of) probability distributions that are well-defi ned in the absence of models, as well as to learning parameters that are well-defi ned only in the context of particular models. The chapter highlights a simple organizing principle: the source of the identi fication problem can often be traced to a collection of random variables that are consistent with the available data and maintained assumptions. This collection may be part of the observed data or be a model implication. In either case, it can be formalized as a random set. Random set theory is then used as a mathematical framework to unify a number of special results and produce a general methodology to conduct econometrics with partial identi fication.
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.
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.
Single Equation Instrumental Variable Models
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Author : Konrad Smolinski
language : en
Publisher:
Release Date : 2011
Single Equation Instrumental Variable Models written by Konrad Smolinski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Econometrics categories.
Over the last decade, substantial interest in theoretical econometrics and microeconometrics has been directed towards nonparametric models. Much work has been devoted to the development of novel identification and estimation technieques and in particular, to the identifying power of econometric models under various types of restrictions. Notable attention has been focused on the conditional independence restriction and instrumental variable methods for both continuous and discrete data problems. This immense effort has led to tremendous outcomes in terms of theoretical findings and most importantly, new empirical practices. Nowadays, we face an apparent emphasis on minimal restrictions of nuisance parameters of the model, with a focus on specific structural features at the same time. New models permit the relaxation of implausible restrictions frequently superimposed unwillingly in empirical analysis of plain old econometric models. In this spirit, recent developments in microeconometrics have given rise to increasing interest in partially identified models. In these models, for the credibility of claims, the feature of interest is bounded to a set rather then constituting of a point in the space of parameters or functions. This in turn has its own place in economic practice. Among many appealing and commonly investigated economic circumstances, partial identification frequently arises in econometric inquiry when researchers are faced with discrete data, omnipresent in survey studies. Examples consider a very general class of the limited information discrete outcome models with endogeneity when very little is known about the genesis of the process generating endogenous variable. This thesis contributes to the aforementioned line of research and seeks to address a somewhat limited, but I believe important, range of issues in a great depth. These issues are concerned with the specification of identified sets in so-called single equation models with endogeneity. We achieve identification via instrumental variable restrictions and focus on discrete outcomes as well as discrete endogenous variables. Our focus on discrete, ordered outcome models complements the vast majority of research on econometric design under continuous variation. The latter, even though theoretically sound, often becomes practically infeasible. We believe that this study provides a level of unity to the partial identification framework as a whole and makes steps forward in understanding some aspects of single equation instrumental variable models under discrete variation.
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.
Random Sets In Econometrics
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Author : Ilya Molchanov
language : en
Publisher: Cambridge University Press
Release Date : 2018-04-12
Random Sets In Econometrics written by Ilya Molchanov and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-12 with Business & Economics categories.
This is the first full-length study of how the theory of random sets can be applied in econometrics.
Handbook Of Econometrics
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Author :
language : en
Publisher: Elsevier
Release Date : 2020-11-25
Handbook Of Econometrics written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Business & Economics categories.
Handbook of Econometrics, Volume 7A, examines recent advances in foundational issues and "hot" topics within econometrics, such as inference for moment inequalities and estimation of high dimensional models. With its world-class editors and contributors, it succeeds in unifying leading studies of economic models, mathematical statistics and economic data. Our flourishing ability to address empirical problems in economics by using economic theory and statistical methods has driven the field of econometrics to unimaginable places. By designing methods of inference from data based on models of human choice behavior and social interactions, econometricians have created new subfields now sufficiently mature to require sophisticated literature summaries. Presents a broader and more comprehensive view of this expanding field than any other handbook Emphasizes the connection between econometrics and economics Highlights current topics for which no good summaries exist
Average Treatment Effect Bounds With An Instrumental Variable Theory And Practice
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Author : Carlos A. Flores
language : en
Publisher: Springer
Release Date : 2018-09-29
Average Treatment Effect Bounds With An Instrumental Variable Theory And Practice written by Carlos A. Flores and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-29 with Business & Economics categories.
This book reviews recent approaches for partial identification of average treatment effects with instrumental variables in the program evaluation literature, including Manski’s bounds, bounds based on threshold crossing models, and bounds based on the Local Average Treatment Effect (LATE) framework. It compares these bounds across different sets of assumptions, surveys relevant methods to assess the validity of these assumptions, and discusses estimation and inference methods for the bounds. The book also reviews some empirical applications employing bounds in the program evaluation literature. It aims to bridge the gap between the econometric theory on which the different bounds are based and their empirical application to program evaluation.