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Handbook of Computational Econometrics

ISBN: 978-0-470-74890-9

August 2009

514 pages

Description
Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations.

This book:

  • Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies.
  • Brings together contributions from leading researchers.
  • Develops the techniques needed to carry out computational econometrics.
  • Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation.

This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels.

About the Author

Erricos Kontoghiorghes is Associate Professor at the School of Economics and Management in Nicosia, Cyprus, and holds a visiting professorship at Birkbeck College since 2003. He has authored and edited seven books. He is a Co-Editor of the journal Computational Statistics & Data Analysis, Associate Editor of the journal Computational Management Science (Springer), and was Editor-in-Chief of the Handbook Series of Computing and Statistics with Applications.

Professor David Besley is Professor at the Department of Economics Boston College, USA. He has written many articles and holds editorial positions for several journals including Computational Economics and is the Associate Editor for Econometrics, Computational Statistics and Data Analysis and International Journal of Forecasting.