Inference for Identifiable Parameters in Partially Identified Econometric Models PDF Download
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Author: Joseph P. Romano
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
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Book Description
Author: Joseph P. Romano
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
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Book Description
Author: Azeem M. Shaikh
Publisher:
ISBN:
Category :
Languages : en
Pages : 194
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Book Description
Author: Joseph P. Romano
Publisher:
ISBN:
Category :
Languages : en
Pages : 41
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Book Description
Author: Paul Gustafson
Publisher: CRC Press
ISBN: 1439869405
Category : Mathematics
Languages : en
Pages : 196
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Book Description
Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts. Drawing on his many years of research in this area, the author presents a thorough overview of the statistical theory, properties, and applications of PIMs. The book first describes how reparameterization can assist in computing posterior quantities and providing insight into the properties of Bayesian estimators. It next compares partial identification and model misspecification, discussing which is the lesser of the two evils. The author then works through PIM examples in depth, examining the ramifications of partial identification in terms of how inferences change and the extent to which they sharpen as more data accumulate. He also explains how to characterize the value of information obtained from data in a partially identified context and explores some recent applications of PIMs. In the final chapter, the author shares his thoughts on the past and present state of research on partial identification. This book helps readers understand how to use Bayesian methods for analyzing PIMs. Readers will recognize under what circumstances a posterior distribution on a target parameter will be usefully narrow versus uselessly wide.
Author: Hiroaki Kaido
Publisher:
ISBN: 9781124030555
Category : Capital assets pricing model
Languages : en
Pages : 402
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Book Description
When a sample of data does not fully reveal the "true" data generating structure (or parameter) but gives information that bounds the set of observationally equivalent structures, an economic model is said to be partially identified. This dissertation develops and applies estimation and inference methods for economic models whose population features are only partially identified. In Chapter 1 (co-authored with Halbert White), I apply econometric techniques from the partial identification literature to address a fundamental problem in asset pricing theory. Namely, that the market price of risk is only identified as a set under incomplete markets. I construct a set estimator and confidence regions for the set of market risk prices. I further show that it is possible to test hypotheses of economic interest without fully identifying the market price of risk. The econometric techniques used in Chapter 1 are developed by Chapter 2 (co-authored with Halbert White). When the dimension of the parameter space is large, this is a particular challenge for set-valued estimators, as high dimensionality can create computational difficulties and seriously hamper the interpretation of estimation results. We study how the use of a natural two-stage extension of the Chernozhukov, Hong, and Tamer's (2007) (CHT) framework can exploit a priori knowledge about the data generating process to mitigate the problems otherwise associated with set estimation in high-dimensional parameter spaces. Chapter 3 unifies two general approaches recently proposed in the literature, the criterion function approach and support function approach. CHT develop a theory of set estimation and inference for the set [Theta]/I of parameter values that minimize a criterion function. The support function approach provides an alternative characterization of CHT's level-set estimator by its supporting hyperplanes. This results in an estimation and inference method that has the wide applicability of the criterion function approach and the computational tractability of the support function approach. By establishing the asymptotic distribution of the properly normalized support function of the level set estimator, I provide Wald-type inference tools to conduct tests regarding the identified set [Theta]/I and a point [Theta]0 in the identified set.
Author: Bo Honoré
Publisher: Cambridge University Press
ISBN: 1108243975
Category : Business & Economics
Languages : en
Pages : 381
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Book Description
This is the second of two volumes containing papers and commentaries presented at the Eleventh World Congress of the Econometric Society, held in Montreal, Canada in August 2015. These papers provide state-of-the-art guides to the most important recent research in economics. The book includes surveys and interpretations of key developments in economics and econometrics, and discussion of future directions for a wide variety of topics, covering both theory and application. These volumes provide a unique, accessible survey of progress on the discipline, written by leading specialists in their fields. The second volume addresses topics such as big data, macroeconomics, financial markets, and partially identified models.
Author: Victor Chernozhukov
Publisher:
ISBN:
Category :
Languages : en
Pages : 43
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Book Description
This paper provides confidence regions for minima of an econometric criterion function Q([mu]). The minima form a set of parameters, [Theta]I, called the identified set. In economic applications, [Theta]I represents a class of economic models that are consistent with the data. Our inference procedures are criterion function based and so our confidence regions, which cover [Theta]I with a prespecified probability, are appropriate level sets of Qn([mu]), the sample analog of Q([mu]). When [Theta]I is a singleton, our confidence sets reduce to the conventional confidence regions based on inverting the likelihood or other criterion functions. We show that our procedure is valid under general yet simple conditions, and we provide feasible resampling procedure for implementing the approach in practice. We then show that these general conditions hold in a wide class of parametric econometric models. In order to verify the conditions, we develop methods of analyzing the asymptotic behavior of econometric criterion functions under set identification and also characterize the rates of convergence of the confidence regions to the identified set. We apply our methods to regressions with in terval data and set identified method of moments problems. We illustrate our methods in an empirical Monte Carlo study based on Current Population Survey data. Keywords: Set estimator, level sets, interval regression, subsampling bootsrap. JEL Classifications: C13, C14, C21, C41, C51, C53.
Author: Econometric Society. World Congress
Publisher: Cambridge University Press
ISBN: 1108414982
Category : Econometrics
Languages : en
Pages : 381
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Book Description
"This is the first of two volumes containing papers and commentaries presented at the Eleventh World Congress of the Econometric Society, held in Montréal, Canada in August 2015. These papers provide state-of-the-art guides to the most important recent research in economics today. This book includes surveys and interpretations of key developments in economics and econometrics, and discussion of future directions for a wide variety of topics, covering both theory and application. These volumes provide a unique, accessible survey of progress on the discipline, written by leading specialists in their fields. The first volume includes theoretical and applied papers addressing topics such as dynamic mechanism design, agency problems, and networks"--
Author:
Publisher: Elsevier
ISBN: 0444636544
Category : Business & Economics
Languages : en
Pages : 594
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Book Description
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
Author: Qi Li
Publisher: Emerald Group Publishing
ISBN: 1849506248
Category : Business & Economics
Languages : en
Pages : 576
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Book Description
Contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. This work is suitable for those who wish to familiarize themselves with nonparametric methodology.
