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Non-nested Tests for Instrumental Variable Regression Models with Differing Conditioning Sets

Non-nested Tests for Instrumental Variable Regression Models with Differing Conditioning Sets PDF Author: R. J. Smith
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description


Non-nested Tests for Instrumental Variable Regression Models with Differing Conditioning Sets

Non-nested Tests for Instrumental Variable Regression Models with Differing Conditioning Sets PDF Author: R. J. Smith
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description


Non-nested Tests for Instrumental Variable Regression Models with Differing Conditioning Sets

Non-nested Tests for Instrumental Variable Regression Models with Differing Conditioning Sets PDF Author: Richard J. Smith
Publisher:
ISBN:
Category :
Languages : en
Pages : 24

Book Description


Contents of Recent Economics Journals

Contents of Recent Economics Journals PDF Author:
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 388

Book Description


Advanced Econometric Methods

Advanced Econometric Methods PDF Author: Thomas B. Fomby
Publisher: Springer Science & Business Media
ISBN: 1441987460
Category : Business & Economics
Languages : en
Pages : 637

Book Description
This book had its conception in 1975in a friendly tavern near the School of Businessand PublicAdministration at the UniversityofMissouri-Columbia. Two of the authors (Fomby and Hill) were graduate students of the third (Johnson), and were (and are) concerned about teaching econometrics effectively at the graduate level. We decided then to write a book to serve as a comprehensive text for graduate econometrics. Generally, the material included in the bookand itsorganization have been governed by the question, " Howcould the subject be best presented in a graduate class?" For content, this has meant that we have tried to cover " all the bases " and yet have not attempted to be encyclopedic. The intended purpose has also affected the levelofmathematical rigor. We have tended to prove only those results that are basic and/or relatively straightforward. Proofs that would demand inordinant amounts of class time have simply been referenced. The book is intended for a two-semester course and paced to admit more extensive treatment of areas of specific interest to the instructor and students. We have great confidence in the ability, industry, and persistence of graduate students in ferreting out and understanding the omitted proofs and results. In the end, this is how one gains maturity and a fuller appreciation for the subject in any case. It is assumed that the readers of the book will have had an econometric methods course, using texts like J. Johnston's Econometric Methods, 2nd ed.

Non-nested Tests for Errors-in-variables Models

Non-nested Tests for Errors-in-variables Models PDF Author: Mahmood A. Bodla
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 434

Book Description


Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation PDF Author: Kenneth Train
Publisher: Cambridge University Press
ISBN: 0521766559
Category : Business & Economics
Languages : en
Pages : 399

Book Description
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

British Reports, Translations and Theses

British Reports, Translations and Theses PDF Author: British Library. Document Supply Centre
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 592

Book Description


Statistical modeling : a fresh approach

Statistical modeling : a fresh approach PDF Author: Daniel Theodore Kaplan
Publisher:
ISBN: 9780983965879
Category : Mathematical statistics
Languages : en
Pages : 388

Book Description
"Statistical Modeling: A Fresh Approach introduces and illuminates the statistical reasoning used in modern research throughout the natural and social sciences, medicine, government, and commerce. It emphasizes the use of models to untangle and quantify variation in observed data. By a deft and concise use of computing coupled with an innovative geometrical presentation of the relationship among variables. A Fresh Approach reveals the logic of statistical inference and empowers the reader to use and understand techniques such as analysis of covariance that appear widely in published research but are hardly ever found in introductory texts."-- book cover

The Null Distribution of Non-nested Tests with Nearly Orthogonal Regression Models

The Null Distribution of Non-nested Tests with Nearly Orthogonal Regression Models PDF Author: Leo Michelis
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 35

Book Description


Robustness Tests for Quantitative Research

Robustness Tests for Quantitative Research PDF Author: Eric Neumayer
Publisher: Cambridge University Press
ISBN: 1108415393
Category : Business & Economics
Languages : en
Pages : 269

Book Description
This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.