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Two Essays On Time Series Econometrics Multiple Time Series Analysis Of The Asian Crisis And Estimation And Inference Of The Nonstationary Structural Vector Autoregressive Model
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Book Synopsis Two Essays on Time Series Econometrics: Multiple Time Series Analysis of the Asian Crisis and Estimation and Inference of the Nonstationary Structural Vector Autoregressive Model by : Siyan Wang
Download or read book Two Essays on Time Series Econometrics: Multiple Time Series Analysis of the Asian Crisis and Estimation and Inference of the Nonstationary Structural Vector Autoregressive Model written by Siyan Wang and published by . This book was released on 2001 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Two Essays on the Time Series Econometrics by : Siyan Wang
Download or read book Two Essays on the Time Series Econometrics written by Siyan Wang and published by . This book was released on 2001 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays in Time Series Econometrics by : Christian Kascha
Download or read book Three Essays in Time Series Econometrics written by Christian Kascha and published by . This book was released on 2007 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis New Introduction to Multiple Time Series Analysis by : Helmut Lütkepohl
Download or read book New Introduction to Multiple Time Series Analysis written by Helmut Lütkepohl and published by Springer Science & Business Media. This book was released on 2007-07-26 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the new and totally revised edition of Lütkepohl’s classic 1991 work. It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it.
Book Synopsis Introduction to Multiple Time Series Analysis by : Helmut Lütkepohl
Download or read book Introduction to Multiple Time Series Analysis written by Helmut Lütkepohl and published by Springer Science & Business Media. This book was released on 1993-08-13 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Book Synopsis Time Series Econometrics by : Klaus Neusser
Download or read book Time Series Econometrics written by Klaus Neusser and published by Springer. This book was released on 2018-05-30 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Introduction to Modern Time Series Analysis by : Gebhard Kirchgässner
Download or read book Introduction to Modern Time Series Analysis written by Gebhard Kirchgässner and published by Springer Science & Business Media. This book was released on 2012-10-08 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated.
Book Synopsis Essays in Time Series Econometrics by : Fei Han
Download or read book Essays in Time Series Econometrics written by Fei Han and published by . This book was released on 2012 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three chapters dealing with different topics in time series econometrics including generalized method of moments (GMM) estimation and vector autoregressions (VAR). These econometric models have revolutionized empirical research in macroeconomics. Previous work by Hansen and Singleton (1982) showed that the GMM method can be applied to estimate nonlinear rational expectations models in a simple way that the models need not even be solved. The seminal work of Sims (1980) has demonstrated how VAR models can be used for macroeconomic forecasting and policy analysis. The objective of this dissertation is to provide some new econometric tools for applied research in macroeconomics using time series data. The first chapter develops an asymptotic theory for the GMM estimator in nonlinear econometric models with integrated regressors and instruments. We establish consistency and derive the limiting distribution of the GMM estimator for asymptotically homogeneous regression functions. The estimator is consistent under fairly general conditions, and the convergence rates are determined by the degree of the asymptotic homogeneity of regression functions. Similar to linear regressions, we find that the limiting distribution is generally biased and non-Gaussian, and that instruments themselves cannot eliminate the bias even when they are strictly exogenous. Therefore, GMM yields inefficient estimates and invalid $t$- and chi-square test statistics in general. By implementing the fully modified method developed by Phillips and Hansen (1990), we obtain an efficient GMM estimator which has an unbiased and mixed normal limiting distribution. In the second chapter, we develop a novel shock identification strategy in the context of two-country/block structural vector autoregressive (SVAR) models to identify the transmission of credit shocks. Specifically, we investigate how credit shocks originating in the U.S. or euro area affect domestic economic activity in emerging Asia. Shocks within each block are identified using sign restrictions, whereas shocks across the two blocks are identified using a recursive structure (block Cholesky decomposition). This strategy not only enables us to distinguish the external credit shock from the other structural shocks, but also captures the responses of the domestic country. The main findings include that the transmission of credit shocks across countries through the channel of credit contagion is fast and protracted. The adverse effects of external credit tightening are mitigated by domestic credit policy easing in China, but lead to significant decreases in credit and GDP growth in the other emerging Asian countries. We also find that the external credit shocks play a non-negligible role in driving economic fluctuations in emerging Asia, although the role is smaller in China. In the last chapter, we use a global vector autoregressive (GVAR) model to forecast the principal macroeconomic indicators of the original five ASEAN member countries (i.e. Indonesia, Malaysia, Philippines, Singapore, and Thailand). The GVAR model is a compact model of the world economy designed to explicitly model the economic and financial interdependencies at national and international levels. Our GVAR model covers twenty countries which are grouped into nine countries/regions. After applying vector error correction model (VECM) to estimate parameters in the GVAR, we generate twelve one-quarter-ahead forecasts of real GDP growth, inflation, short-term interest rates, real exchange rates, real equity prices, and world commodity prices over the period 2009Q1-2011Q4, with four out-of-sample forecasts during 2009Q1-2009Q4. Forecast evaluation based on the panel Diebold-Mariano (DM) tests shows that the forecasts of our GVAR model tend to outperform those of country-specific VAR models, especially for short-term interest rates and real equity prices. These results suggest that the interdependencies among countries in the global financial market play an important role in macroeconomic forecasting.
Book Synopsis Dissertation Abstracts International by :
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2002 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Time Series Econometrics by : Helmut Lütkepohl
Download or read book Applied Time Series Econometrics written by Helmut Lütkepohl and published by Cambridge University Press. This book was released on 2004-08-02 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Analysis of Economic Time Series by : Marc Nerlove
Download or read book Analysis of Economic Time Series written by Marc Nerlove and published by Academic Press. This book was released on 2014-05-10 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of Economic Time Series: A Synthesis integrates several topics in economic time-series analysis, including the formulation and estimation of distributed-lag models of dynamic economic behavior; the application of spectral analysis in the study of the behavior of economic time series; and unobserved-components models for economic time series and the closely related problem of seasonal adjustment. Comprised of 14 chapters, this volume begins with a historical background on the use of unobserved components in the analysis of economic time series, followed by an Introduction to the theory of stationary time series. Subsequent chapters focus on the spectral representation and its estimation; formulation of distributed-lag models; elements of the theory of prediction and extraction; and formulation of unobserved-components models and canonical forms. Seasonal adjustment techniques and multivariate mixed moving-average autoregressive time-series models are also considered. Finally, a time-series model of the U.S. cattle industry is presented. This monograph will be of value to mathematicians, economists, and those interested in economic theory, econometrics, and mathematical economics.
Book Synopsis New Developments in Time Series Econometrics by : Jean-Marie Dufour
Download or read book New Developments in Time Series Econometrics written by Jean-Marie Dufour and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :Evžen Kočenda Publisher :Charles University in Prague, Karolinum Press ISBN 13 :8024631997 Total Pages :220 pages Book Rating :4.0/5 (246 download)
Book Synopsis Elements of Time Series Econometrics: an Applied Approach by : Evžen Kočenda
Download or read book Elements of Time Series Econometrics: an Applied Approach written by Evžen Kočenda and published by Charles University in Prague, Karolinum Press. This book was released on 2015-12-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the numerous tools for the econometric analysis of time series. The text is designed with emphasis on the practical application of theoretical tools. Accordingly, material is presented in a way that is easy to understand. In many cases intuitive explanation and understanding of the studied phenomena are offerd. Essential concepts are illustrated by clear-cut examples. The attention of readers is drawn to numerous applied works where the use of specific techniques is best illustrated. Such applications are chiefly connected with issues of recent economic transition and European integration. The outlined style of presentation makes the book also a rich source of references. The text is divided into five major sections. The first section, “The Nature of Time Series”, gives an introduction to time series analysis. The second section, “Difference Equations”, describes briefly the theory of difference equations with an emphasis on results that are important for time series econometrics. The third section, “Univariate Time Series”, presents the methods commonly used in univariate time series analysis, the analysis of time series of one single variable. The fourth section, “Multiple Time Series”, deals with time series models of multiple interrelated variables. The fifth section “Panel Data and Unit Root Tests”, deals with methods known as panel unit root tests that are relevant to issues of convergence. Appendices contain an introduction to simulation techniques and statistical tables. Kniha přináší soubor základních i pokročilých technik a postupů používaných v ekonometrické analýze časových řad. Kniha klade důraz na umožnění efektivního použití popsaných technik v aplikovaném ekonomickém výzkumu. Toho je dosaženo tím, že teoretické základy popsané ekonometrie jsou prezentovány spolu s intuitivním vysvětlením problematiky a jednotlivé techniky jsou ilustrovány na výsledcích současného výzkumu a to především v kontextu procesu nedávné ekonomické transformace a současné evropské integrace. Toto pojetí z knihy činí nejen učebnici v klasickém smyslu, ale také užitečný referenční zdroj neboť odkazy v knize spojují klasickou i moderní ekonometrickou literaturu se soudobými aplikacemi, na nichž je použití jednotlivých technik jasně pochopitelné. Mnohá použití vycházejí z bohaté předchozí práce autorů v oboru. Text knihy je rozdělen do pěti hlavních částí. První část, “The Nature of Time Series”, přináší úvod do analýzy časových řad a popis jejich nejdůležitějších charakteristik, vlastností a procesů. Druhá část, “Difference Equations”, stručně popisuje teorii diferenciálních rovnic s důrazem na aspekty, které jsou klíčové v ekonometrii časových řad. Třetí část, “Univariate Time Series”, poměrně rozsáhle popisuje techniky, které se používají při analýze jednotlivých časových řad bez jejich vzájemené interakce a zahrnuje jak lineární tak nelineární modelované struktury. Čtvrtá část, “Multiple Time Series”, popisuje modely které umožňují analýzu několika časových řad a jejich vzájemných interakcí. Pátá část “Panel Data and Unit Root Tests”, zahrnuje některé techniky postavené na panelových datech, jež k průřezovým datům přidávají časovou dimenzi a vztahují se k analýze konvergence. Závěr knihy je doplněn o úvod do simulační techniky a statistické tabulky
Book Synopsis Introduction to Multiple Time Series Analysis by : Helmut Lütkepohl
Download or read book Introduction to Multiple Time Series Analysis written by Helmut Lütkepohl and published by Springer. This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Book Synopsis Multivariate Modelling of Non-Stationary Economic Time Series by : John Hunter
Download or read book Multivariate Modelling of Non-Stationary Economic Time Series written by John Hunter and published by Springer. This book was released on 2017-05-08 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.
Book Synopsis Time Series and Panel Data Econometrics by : M. Hashem Pesaran
Download or read book Time Series and Panel Data Econometrics written by M. Hashem Pesaran and published by OUP Oxford. This book was released on 2015-10-01 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.
Book Synopsis Notes on Economic Time Series Analysis: System Theoretic Perspectives by : Masanao Aoki
Download or read book Notes on Economic Time Series Analysis: System Theoretic Perspectives written by Masanao Aoki and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: In seminars and graduate level courses I have had several opportunities to discuss modeling and analysis of time series with economists and economic graduate students during the past several years. These experiences made me aware of a gap between what economic graduate students are taught about vector-valued time series and what is available in recent system literature. Wishing to fill or narrow the gap that I suspect is more widely spread than my personal experiences indicate, I have written these notes to augment and reor ganize materials I have given in these courses and seminars. I have endeavored to present, in as much a self-contained way as practicable, a body of results and techniques in system theory that I judge to be relevant and useful to economists interested in using time series in their research. I have essentially acted as an intermediary and interpreter of system theoretic results and perspectives in time series by filtering out non-essential details, and presenting coherent accounts of what I deem to be important but not readily available, or accessible to economists. For this reason I have excluded from the notes many results on various estimation methods or their statistical properties because they are amply discussed in many standard texts on time series or on statistics.
