Forecasting Aggregated Vector ARMA Processes

Forecasting Aggregated Vector ARMA Processes

Author: Helmut Lütkepohl

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 336

ISBN-13: 3642615848

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This study is concerned with forecasting time series variables and the impact of the level of aggregation on the efficiency of the forecasts. Since temporally and contemporaneously disaggregated data at various levels have become available for many countries, regions, and variables during the last decades the question which data and procedures to use for prediction has become increasingly important in recent years. This study aims at pointing out some of the problems involved and at pro viding some suggestions how to proceed in particular situations. Many of the results have been circulated as working papers, some have been published as journal articles, and some have been presented at conferences and in seminars. I express my gratitude to all those who have commented on parts of this study. They are too numerous to be listed here and many of them are anonymous referees and are therefore unknown to me. Some early results related to the present study are contained in my monograph "Prognose aggregierter Zeitreihen" (Lutkepohl (1986a)) which was essentially completed in 1983. The present study contains major extensions of that research and also summarizes the earlier results to the extent they are of interest in the context of this study.


A Companion to Economic Forecasting

A Companion to Economic Forecasting

Author: Michael P. Clements

Publisher: John Wiley & Sons

Published: 2008-04-15

Total Pages: 616

ISBN-13: 140517191X

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A Companion to Economic Forecasting provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.


Multivariate Time Series Analysis and Applications

Multivariate Time Series Analysis and Applications

Author: William W. S. Wei

Publisher: John Wiley & Sons

Published: 2019-03-18

Total Pages: 536

ISBN-13: 1119502853

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An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.


Handbook of Economic Forecasting

Handbook of Economic Forecasting

Author: G. Elliott

Publisher: Elsevier

Published: 2006-07-14

Total Pages: 1071

ISBN-13: 0444513957

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Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.


The Theory and Practice of Econometrics

The Theory and Practice of Econometrics

Author: George G. Judge

Publisher: John Wiley & Sons

Published: 1991-01-16

Total Pages: 1062

ISBN-13: 047189530X

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This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.


Disaggregation in Econometric Modelling (Routledge Revivals)

Disaggregation in Econometric Modelling (Routledge Revivals)

Author: Terry Barker

Publisher: Routledge

Published: 2014-02-04

Total Pages: 271

ISBN-13: 1317829182

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In this book, first published in 1990, leading theorists and applied economists address themselves to the key questions of aggregation. The issues are covered both theoretically and in wide-ranging applications. Of particular intrest is the optimal aggregation of trade data, the need for micro-modelling when imoprtant non-linearities are present (for example, tax exhaustion in modelling company behaviour) and the use of a micro-model to stimulate labour supply behaviour in a macro-model of the Netherlands.


Contemporary Biostatistics with Biopharmaceutical Applications

Contemporary Biostatistics with Biopharmaceutical Applications

Author: Lanju Zhang

Publisher: Springer

Published: 2019-07-11

Total Pages: 339

ISBN-13: 303015310X

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This edited volume presents current research in biostatistics with emphasis on biopharmaceutical applications. Featuring contributions presented at the 2017 ICSA Applied Statistics Symposium held in Chicago, IL on June 25 to 28, 2017, this book explores timely topics that have a high potential impact on statistical methodology and future research in biostatistics and biopharmaceuticals. The theme of this conference was Statistics for a New Generation: Challenges and Opportunities, in recognition of the advent of a new generation of statisticians. The conference attracted statisticians working in academia, government, and industry; domestic and international statisticians. From the conference, the editors selected 28 high-quality presentations and invited the speakers to prepare full chapters for this book. These contributions are divided into four parts: Part I Biostatistical Methodology, Part II Statistical Genetics and Bioinformatics, Part III Regulatory Statistics, and Part IV Biopharmaceutical Research and Applications. Featuring contributions on topics such as statistics in genetics, bioinformatics, biostatistical methodology, and statistical computing, this book is beneficial to researchers, academics, practitioners and policy makers in biostatistics and biopharmaceuticals.


Comparative Performance of U.S. Econometric Models

Comparative Performance of U.S. Econometric Models

Author: Lawrence Robert Klein

Publisher: Oxford University Press, USA

Published: 1991

Total Pages: 338

ISBN-13: 0195057724

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Each year, a number of different economic groups in the USA use their own econometric models to forecast what will happen to the economy in the coming year. This volume consists of chapters by distinguished economists comparing the different models now being used.


Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis

Author: Lutz Kilian

Publisher: Cambridge University Press

Published: 2017-11-23

Total Pages: 758

ISBN-13: 1108195288

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Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.