Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

Essays in Honor of Halbert L. White Jr

  • Xiaohong Chen
  • Norman R. Swanson

Table of contents

  1. Front Matter
    Pages i-xxxiii
  2. S. Borağan Aruoba, Francis X. Diebold, Jeremy Nalewaik, Frank Schorfheide, Dongho Song
    Pages 1-25
  3. Richard M. Golden, Steven S. Henley, Halbert White, T. Michael Kashner
    Pages 145-177
  4. Christian Haefke, Leopold Sögner
    Pages 179-208
  5. David F. Hendry, Grayham E. Mizon
    Pages 219-240
  6. Stefan Hoderlein, Halbert White
    Pages 275-297
  7. Atsushi Inoue, Barbara Rossi, Lu Jin
    Pages 299-330
  8. Hiroaki Kaido, Halbert White
    Pages 331-361
  9. Igor Kheifets, Carlos Velasco
    Pages 363-382
  10. Chang-Ching Lin, Shinichi Sataka
    Pages 383-410
  11. Esfandiar Maasoumi, Levent Bulut
    Pages 411-436
  12. James G. MacKinnon
    Pages 437-461
  13. Christopher F. Parmeter, Jeffrey S. Racine
    Pages 463-488
  14. Dimitris N. Politis, Dimitrios D. Thomakos
    Pages 489-525

About this book

Introduction

This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Editors and affiliations

  • Xiaohong Chen
    • 1
  • Norman R. Swanson
    • 2
  1. 1.Yale UniversityNew HavenUSA
  2. 2.NEW BRUNSWICKUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-1653-1
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Business and Economics
  • Print ISBN 978-1-4614-1652-4
  • Online ISBN 978-1-4614-1653-1
  • About this book