› › New Developments In Time Series Econometrics

New Developments in Time Series Econometrics

Author : Jean-Marie Dufour

Publisher : Springer Science & Business Media

Page : 248 pages

File Size : 18,22 MB

Release : 2012-12-06

Category : Business & Economics

ISBN : 3642487424

Get eBook

Book Description

This book contains eleven articles which provide empirical applications as well as theoretical extensions of some of the most exciting recent developments in time-series econometrics. The papers are grouped around three broad themes: (I) the modeling of multivariate times series; (II) the analysis of structural change; (III) seasonality and fractional integration. Since these themes are closely inter-related, several other topics covered are also worth stressing: vector autoregressive (VAR) models, cointegration and error-correction models, nonparametric methods in time series, and fractionally integrated models. Researchers and students interested in macroeconomic and empirical finance will find in this collection a remarkably representative sample of recent work in this area.



Time Series Econometrics

Author : Klaus Neusser

Publisher : Springer

Page : 421 pages

File Size : 40,16 MB

Release : 2016-06-14

Category : Business & Economics

ISBN : 331932862X

Get eBook

Book Description

This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.



Introduction to Modern Time Series Analysis

Author : Gebhard Kirchgässner

Publisher : Springer Science & Business Media

Page : 288 pages

File Size : 44,37 MB

Release : 2008-08-27

Category : Business & Economics

ISBN : 9783540687351

Get eBook

Book Description

This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.



Time Series Econometrics

Author : Pierre Perron

Publisher :

Page : pages

File Size : 25,24 MB

Release : 2018

Category : Econometrics

ISBN : 9789813237896

Get eBook

Book Description

Part I. Unit roots and trend breaks -- Part II. Structural change



Applied Time Series Econometrics

Author : Helmut Lütkepohl

Publisher : Cambridge University Press

Page : 351 pages

File Size : 42,68 MB

Release : 2004-08-02

Category : Business & Economics

ISBN : 1139454730

Get eBook

Book Description

Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.



Recent Advances in Time Series Forecasting

Author : Dinesh C.S. Bisht

Publisher : CRC Press

Page : 183 pages

File Size : 34,94 MB

Release : 2021-09-08

Category : Mathematics

ISBN : 1000433846

Get eBook

Book Description

Future predictions are always a topic of interest. Precise estimates are crucial in many activities as forecasting errors can lead to big financial loss. The sequential analysis of data and information gathered from past to present is call time series analysis. This book covers the recent advancements in time series forecasting. The book includes theoretical as well as recent applications of time series analysis. It focuses on the recent techniques used, discusses a combination of methodology and applications, presents traditional and advanced tools, new applications, and identifies the gaps in knowledge in engineering applications. This book is aimed at scientists, researchers, postgraduate students and engineers in the areas of supply chain management, production, inventory planning, and statistical quality control.



Forecasting Economic Time Series

Author : C. W. J. Granger

Publisher : Academic Press

Page : 353 pages

File Size : 30,33 MB

Release : 2014-05-10

Category : Business & Economics

ISBN : 1483273245

Get eBook

Book Description

Economic Theory, Econometrics, and Mathematical Economics, Second Edition: Forecasting Economic Time Series presents the developments in time series analysis and forecasting theory and practice. This book discusses the application of time series procedures in mainstream economic theory and econometric model building. Organized into 10 chapters, this edition begins with an overview of the problem of dealing with time series possessing a deterministic seasonal component. This text then provides a description of time series in terms of models known as the time-domain approach. Other chapters consider an alternative approach, known as spectral or frequency-domain analysis, that often provides useful insights into the properties of a series. This book discusses as well a unified approach to the fitting of linear models to a given time series. The final chapter deals with the main advantage of having a Gaussian series wherein the optimal single series, least-squares forecast will be a linear forecast. This book is a valuable resource for economists.



The Econometric Analysis of Seasonal Time Series

Author : Eric Ghysels

Publisher : Cambridge University Press

Page : 258 pages

File Size : 15,56 MB

Release : 2001-06-18

Category : Business & Economics

ISBN : 9780521565882

Get eBook

Book Description

Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.



Advances in Time Series Data Methods in Applied Economic Research

Author : Nicholas Tsounis

Publisher : Springer

Page : 0 pages

File Size : 49,43 MB

Release : 2018-12-12

Category : Business & Economics

ISBN : 9783030021931

Get eBook

Book Description

This conference proceedings volume presents advanced methods in time series estimation models that are applicable various areas of applied economic research such as international economics, macroeconomics, microeconomics, finance economics and agricultural economics. Featuring contributions presented at the 2018 International Conference on Applied Economics (ICOAE) held in Warsaw, Poland, this book presents contemporary research using applied econometric method for analysis as well as country specific studies with potential implications on economic policy. Applied economics is a rapidly growing field of economics that combines economic theory with econometrics to analyse economic problems of the real world usually with economic policy interest. ICOAE is an annual conference started in 2008 with the aim to bring together economists from different fields of applied economic research in order to share methods and ideas. Approximately 150 papers are submitted each year from about 40 countries around the world. The goal of the conference and the enclosed papers is to allow for an exchange of experiences with different applied econometric methods and to promote joint initiatives among well-established economic fields such as finance, agricultural economics, health economics, education economics, international trade theory and management and marketing strategies. Featuring global contributions, this book will be of interest to researchers, academics, professionals and policy makers in the field of applied economics and econometrics.



Time Series Econometrics

Author : John D. Levendis

Publisher : Springer

Page : 409 pages

File Size : 29,93 MB

Release : 2019-01-31

Category : Business & Economics

ISBN : 3319982826

Get eBook

Book Description

In this book, the author rejects the theorem-proof approach as much as possible, and emphasize the practical application of econometrics. They show with examples how to calculate and interpret the numerical results. This book begins with students estimating simple univariate models, in a step by step fashion, using the popular Stata software system. Students then test for stationarity, while replicating the actual results from hugely influential papers such as those by Granger and Newbold, and Nelson and Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot and Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Finally, students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger. The book contains many worked-out examples, and many data-driven exercises. While intended primarily for graduate students and advanced undergraduates, practitioners will also find the book useful.