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EBookClubs

Read Books & Download eBooks Full Online

Book Vector Error Correction Models with Stationary and Nonstationary Variables

Download or read book Vector Error Correction Models with Stationary and Nonstationary Variables written by Pu Chen and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vector error correction models (VECM) have become a standard tool in empirical economics for analysing nonstationary time series data because they combine two key concepts in economics: equilibrium and dynamic adjustment in one single model. The current standard VECM procedure is restricted to time series data with the same degree of integration, i.e. all I(1) variables. Time series data with different degrees of integration, on the other hand, are frequently encountered in empirical studies, necessitating the simultaneous handling of I(1) and I(0) time series. In this paper, the standard VECM is extended to accommodate mixed I(1) and I(0) variables. The mixed VECM conditions are derived, and a test and estimation of the mixed VECM are presented as a result.

Book The Power of Cointegration Tests

Download or read book The Power of Cointegration Tests written by Jeroen J. M. Kremers and published by . This book was released on 1992 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Likelihood based Inference in Cointegrated Vector Autoregressive Models

Download or read book Likelihood based Inference in Cointegrated Vector Autoregressive Models written by Søren Johansen and published by Oxford University Press, USA. This book was released on 1995 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is concerned with the statistical analysis of multivariate systems of non-stationary time series of type I. It applies the concepts of cointegration and common trends in the framework of the Gaussian vector autoregressive model.

Book The Effects of Monetary Policy in the US  The Vector Error Correction Model  VECM  compared to the Structural Autoregressive Model  SVAR

Download or read book The Effects of Monetary Policy in the US The Vector Error Correction Model VECM compared to the Structural Autoregressive Model SVAR written by Colin Tissen and published by GRIN Verlag. This book was released on 2017-10-13 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paper (undergraduate) from the year 2017 in the subject Mathematics - Applied Mathematics, grade: 8.5, , course: Empirical Econometrics II, language: English, abstract: This paper investigates the effects of monetary policy in the US by comparing a system of equations – estimated from a VECM (vector error correction model) – to a SVAR (structural autoregressive) model. Vector error-correction models are used when there exists long-run equilibrium relation-ships between non-stationary data integrated of the same order. Those models imply that the stationary transformations of the variables adapt to disequilibria between the non-stationary variables in the model. In contrast, SVAR models focus on the contemporaneous interdependence between the variables. The authors apply these two methods on a model with a contractionary monetary policy which affects the short-term interest rate. Following Sims and Zha the authors use a shock to the Treasury Bill rate instead of a shock to the Federal Funds rate. The paper continues as follows. First, a description of the data is given. Secondly, it presents a system of equations built from the LSE approach, aiming at macroeconomic simulations. Thirdly, it compares results obtained from the previous part to those obtained using SVAR impulse response functions (IRFs) identified with sign restrictions. The paper focuses on the impact of the simulated policies or monetary shocks on GDP and its growth rate.

Book Using R for Principles of Econometrics

Download or read book Using R for Principles of Econometrics written by Constantin Colonescu and published by Lulu.com. This book was released on 2017-12-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.

Book Cointegration and Long Horizon Forecasting

Download or read book Cointegration and Long Horizon Forecasting written by Mr.Peter F. Christoffersen and published by International Monetary Fund. This book was released on 1997-05-01 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imposing cointegration on a forecasting system, if cointegration is present, is believed to improve long-horizon forecasts. Contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures. In fact, simple univariate Box-Jenkins forecasts are just as accurate. Our results highlight a potentially important deficiency of standard forecast accuracy measures—they fail to value the maintenance of cointegrating relationships among variables—and we suggest alternatives that explicitly do so.

Book Introductory Econometrics for Finance

Download or read book Introductory Econometrics for Finance written by Chris Brooks and published by Cambridge University Press. This book was released on 2008-05-22 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.

Book The Econometric Analysis of Non Stationary Spatial Panel Data

Download or read book The Econometric Analysis of Non Stationary Spatial Panel Data written by Michael Beenstock and published by Springer. This book was released on 2019-03-27 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph deals with spatially dependent nonstationary time series in a way accessible to both time series econometricians wanting to understand spatial econometics, and spatial econometricians lacking a grounding in time series analysis. After charting key concepts in both time series and spatial econometrics, the book discusses how the spatial connectivity matrix can be estimated using spatial panel data instead of assuming it to be exogenously fixed. This is followed by a discussion of spatial nonstationarity in spatial cross-section data, and a full exposition of non-stationarity in both single and multi-equation contexts, including the estimation and simulation of spatial vector autoregression (VAR) models and spatial error correction (ECM) models. The book reviews the literature on panel unit root tests and panel cointegration tests for spatially independent data, and for data that are strongly spatially dependent. It provides for the first time critical values for panel unit root tests and panel cointegration tests when the spatial panel data are weakly or spatially dependent. The volume concludes with a discussion of incorporating strong and weak spatial dependence in non-stationary panel data models. All discussions are accompanied by empirical testing based on a spatial panel data of house prices in Israel.

Book Introduction to Econometrics

Download or read book Introduction to Econometrics written by James H. Stock and published by Prentice Hall. This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For courses in Introductory Econometrics Engaging applications bring the theory and practice of modern econometrics to life. Ensure students grasp the relevance of econometrics with Introduction to Econometrics-the text that connects modern theory and practice with motivating, engaging applications. The Third Edition Update maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. This program provides a better teaching and learning experience-for you and your students. Here's how: Personalized learning with MyEconLab-recommendations to help students better prepare for class, quizzes, and exams-and ultimately achieve improved comprehension in the course. Keeping it current with new and updated discussions on topics of particular interest to today's students. Presenting consistency through theory that matches application. Offering a full array of pedagogical features. Note: You are purchasing a standalone product; MyEconLab does not come packaged with this content. If you would like to purchase both the physical text and MyEconLab search for ISBN-10: 0133595420 ISBN-13: 9780133595420. That package includes ISBN-10: 0133486877 /ISBN-13: 9780133486872 and ISBN-10: 0133487679/ ISBN-13: 9780133487671. MyEconLab is not a self-paced technology and should only be purchased when required by an instructor.

Book Analysis of Integrated and Cointegrated Time Series with R

Download or read book Analysis of Integrated and Cointegrated Time Series with R written by Bernhard Pfaff and published by Springer Science & Business Media. This book was released on 2008-09-03 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.

Book Multivariate Time Series Analysis

Download or read book Multivariate Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2013-11-11 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.

Book Private Investment in Developing Countries

Download or read book Private Investment in Developing Countries written by International Monetary Fund and published by International Monetary Fund. This book was released on 1990-04-01 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper analyzes the effects of several policy and other macro-economic variables on the ratio of private investment to GDP in developing countries. Using data for a sample of 23 developing countries over the period 1975-87, the econometric evidence indicates that the rate of private investment is positively related to the real growth rate of GDP, public sector investment, and to a lesser extent the level of per capita GDP, while it is negatively related to domestic inflation, the debt service ratio, the debt-to-GDP ratio, and high real interest rates. There is also some indication that all but the last of these variables had a greater impact before the onset of the debt crisis in 1982, while the debt-to-GDP ratio (a measure of a country’s debt overhang) has become more important since then.

Book Multiple Time Series Models

Download or read book Multiple Time Series Models written by Patrick T. Brandt and published by SAGE. This book was released on 2007 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.

Book Multivariate Tests for Time Series Models

Download or read book Multivariate Tests for Time Series Models written by Jeff B. Cromwell and published by SAGE. This book was released on 1994 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Which time series test should researchers choose to best describe the interactions among a set of time series variables? Providing guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests.

Book Unit Roots  Cointegration  and Structural Change

Download or read book Unit Roots Cointegration and Structural Change written by G. S. Maddala and published by Cambridge University Press. This book was released on 1998 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of unit roots, cointegration and structural change from a best-selling author.

Book Time Series Econometrics

Download or read book Time Series Econometrics written by Klaus Neusser and published by Springer. This book was released on 2016-06-14 with total page 421 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.