Nonparametric and Semiparametric Methods in Econometrics and Statistics
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Nonparametric and Semiparametric Methods in Econometrics and Statistics Proceedings of the Fifth International Symposium in Economic Theory and Econometrics ... in Economic Theory and Econometrics) by

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Published by Cambridge University Press .
Written in English

Subjects:

  • Econometrics,
  • Statistical methods,
  • Economic History,
  • Business & Economics,
  • Mathematics,
  • Probability & Statistics - General,
  • Business/Economics,
  • Economics,
  • Business & Economics / Economic History,
  • Econometrics--Congresses,
  • Congresses,
  • Mathematical statistics

Book details:

Edition Notes

ContributionsWilliam A. Barnett (Editor), James Powell (Editor), George E. Tauchen (Editor)
The Physical Object
FormatHardcover
Number of Pages507
ID Numbers
Open LibraryOL7738445M
ISBN 100521370906
ISBN 109780521370905

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“This book is intended to introduce graduate students and researchers to nonparametric and semiparametric methods and their applications to econometrics. all results are stated with the appropriate conditions and the role of the conditions is : Paperback. "Nonparametric and Semiparametric Methods in Econometrics and Statistics gives a fairly thorough picture of recent advances in nonparametric and semiparametric analysis. It provides insight on recently solved problems in this area and also points towards some of the yet-unresolved issues."Author: William A. Barnett. Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. These methods are applicable to a wide variety of estimation problems in empirical economics and other fields, Manufacturer: Springer. : Nonparametric and Semiparametric Methods in Econometrics and Statistics: Proceedings of the Fifth International Symposium in Economic Theory and Symposia in Economic Theory and Econometrics): William A. Barnett, James Powell, George E. Tauchen: Books.

Nonparametric and Semiparametric Methods in Econometrics and Statistics: Proceedings of the Fifth International Symposium in Economic Theory and Econometrics Volume 5 of International Symposia in Economic Theory and Econometrics, ISSN Editors: William A. Barnett, James Powell, George E. Tauchen: Edition: illustrated: Publisher. Inference based on convenient but incorrect assumptions about functional forms and distributions can be highly misleading. Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference. Nonparametric Econometrics: Theory and Practice Qi Li, Jeffrey Scott Racine Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. This books systematically and thoroughly covers a vast literature on the nonparametric and semiparametric statistics and econometrics that has evolved over the last five decades. Within this framework, this is the first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics, e.g., regression function.

Nonparametric and semiparametric methods potentially offer considerable reward to applied researchers, owing to the methods' ability to adapt to many unknown features of the data. Professors Pagan and Ullah provide intuitive explanations of difficult concepts, heuristic developments of theory, and empirical examples emphasizing the usefulness Cited by: Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems. Until recently, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis.   Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fullyCited by: Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data — nominal and.