Econometric Model Specification: Consistent Model Specification Tests And Semi-nonparametric Modeling And Inference

Bierens Herman J

ISBN 10: 9814740500 / ISBN 13: 9789814740500

Published by World Scientific Pub Co Inc, 2017

About this Item

Seller Inventory # 395205521

Bibliographic Details

• Title: Econometric Model Specification: Consistent Model Specification Tests And Semi-nonparametric Modeling And Inference
• Publisher: World Scientific Pub Co Inc
• Publication Date: 2017
• Language: English
• ISBN 10: 9814740500
• ISBN 13: 9789814740500
• Binding: Hardcover
• Condition: Used

About this title

Synopsis

Econometric Model Specification reviews and extends the author's papers on consistent model specification testing and semi-nonparametric modeling and inference. This book consists of two parts. The first part discusses consistent tests of functional form of regression and conditional distribution models, including a consistent test of the martingale difference hypothesis for time series regression errors. In the second part, semi-nonparametric modeling and inference for duration and auction models are considered, as well as a general theory of the consistency and asymptotic normality of semi-nonparametric sieve maximum likelihood estimators. Moreover, this volume also contains addendums and appendices that provide detailed proofs and extensions of all the results. It is uniquely self-contained and is a useful source for students and researchers interested in model specification issues.

From the Back Cover

Econometric Model Specification reviews and extends the studies on consistent model specification testing and semi-nonparametric modeling and inference. This book consists of four parts. The first part discusses about consistent tests of functional form of regression and conditional distribution models. The second part studies Martingale difference hypothesis for time series regression errors. In the third part, semi-nonparametric modeling and inference for duration and auction models are considered. The last part provides insights into consistency and asymptotic normality of sieve maximum likelihood estimators. Moreover, this volume also contains addendums that provide detailed proofs of all the results. It is uniquely self-contained and a useful source for students and researchers interested in model specification issues.