Recent advances and future directions in causality, prediction, and specification analysis : essays in honor of Halbert L. White Jr. / / Xiaohong Chen, Norman R. Swanson, editors

• Pubblicazione: New York, : Springer, 2012, c2013
• Descrizione fisica: 1 online resource (xxxiii, 560 pages) : illustrations, portraits
• Disciplina: 621.382; 621.382/2
• Soggetto topico: Econometrics - Asymptotic theory; Causation; Prediction theory
• Altri autori: ChenXiaohong SwansonNorman R
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Improving U.S. GDP measurement : a forecast combination perspective / S. Boragan Aruoba ... [et al.] -- Identification without exogeneity under equiconfounding in linear recursive structural systems / Karim Chalak -- Optimizing robust conditional moment tests : an estimating function approach / Yi-Ting Chen and Chung-Ming Kuan -- Asymptotic properties of penalized M estimators with time series observations / Xiaohong Chen and Zhipeng Liao -- A survey of recent advances in forecast accuracy comparison testing, with an extension to stochastic dominance / Valentina Corradi and Norman R. Swanson -- New directions in information matrix testing : eigenspectrum tests / Richard M. Golden ... [et al.] -- Bayesian analysis and model selection of GARCH models with additive jumps / Christian Haefke and Leopold Sogner -- Hal White : time at MIT and early days of research / Jerry Hausman -- Open-model forecast-error taxonomies / David F. Hendry and Grayham E. Mizon -- Heavy-tail and plug-in robust consistent conditional moment tests of functional form / Jonathan B. Hill ; Nonparametric identification in dynamic nonseparable panel data models / Stefan Hoderlein and Halbert White -- Consistent model selection : over rolling windows / Atsushi Inoue, Barbara Rossi and Lu Jin -- Estimating misspecified moment inequality models / Hiroaki Kaido and Halbert White -- Model adequacy checks for discrete choice dynamic models / Igor Kheifets and Carlos Velasco -- On long-run covariance matrix estimation with the truncated flat kernel / Chang-Ching Lin and Shinichi Sataka -- Predictability and specification in models of exchange rate determination / Esfandiar Maasoumi and Levent Bulut -- Thirty years of heteroskedsticity-robust inference / James G. MacKinnon -- Smooth constrained frontier analysis / Christopher F. Parmeter and Jeffrey S. Racine -- No VaS transformations : flexible inference for volatility forecasting / Dimitris N. Politis and Dimitrios D. Thomakos -- Regression efficacy and the curse of dimensionality / Maxwell B. Stinchcombe and David M. Drukker.
• Sommario/riassunto: 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.
• Titolo autorizzato: Recent advances and future directions in causality, prediction, and specification analysis
• ISBN: 1-4614-1653-1
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910438072503321
• Lo trovi qui: Univ. Federico II