Teach Yourself Econometric Data Analysis with EViews
Teach Yourself Econometric Data Analysis with EViews

Author: Chukwuemeka Tiptop Okoro

Publisher:

Published: 2020-05-18

Total Pages: 250

ISBN-13:

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There is a large group of people in a variety of fields, including finance, economics, accounting, science, mathematics, engineering, statistics, and public policy who need to understand some basic concepts of time series analysis and forecasting. Analyzing time-series data and forecasting future values of a time series are among the most important problems that analysts face in many fields. But to Successfully analyze this time series data requires that the analyst interact with computer software because the techniques and algorithms are just not suitable to manual calculations.This book has been written with the aim of solving this problems by providing a step-by-step guide to economic and financial econometrics using EViews. It contains a brief overviews of the concepts of econometric models, and data analysis techniques followed by procedures of how they can be implemented in EViews. This book is written as a compendium for undergraduate and graduate students in economics, finance, statistics and accounting. It can also serve as a guide for researchers and practitioners who desire to use EViews for analyzing financial data. This book may be used as a textbook companion for post graduate level courses in time series analysis, empirical finance, statistics and financial econometrics. Since, many organizations can improve their effectiveness and business results by making better short-to-medium term forecasts, this book should be useful to a wide variety of professionals. Topics Covered with examples Include: Chapter 1: Introduction to EViews. Chapter 2: Descriptive Statistics and Preliminary Tests. Chapter 3: Running Regression Analysis in EViews. Chapter 4: Forecasting Using Regression Models. Chapter 5: Economic Forecasting using ARIMA Modelling. Chapter 6: Volatility Modeling: ARCH, GARCH and EGARCH Models. An Introduction to Financial Econometrics. Chapter 7: Vector Autoregressive (VAR) Model. An Introduction to Macroeconometrics. Chapter 8: Vector Error Correction Model (VECM). Chapter 9: Autoregressive Distributed Lag Model (ARDL). Chapter 10: Panel Data Analysis

Time Series Data Analysis Using EViews
Time Series Data Analysis Using EViews

Author: I. Gusti Ngurah Agung

Publisher: John Wiley & Sons

Published: 2011-08-31

Total Pages: 502

ISBN-13: 1118176308

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Do you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometric models for time series data. The procedures introduced are easily extendible to cross-section data sets. The author: Provides step-by-step directions on how to apply EViews software to time series data analysis Offers guidance on how to develop and evaluate alternative empirical models, permitting the most appropriate to be selected without the need for computational formulae Examines a variety of times series models, including continuous growth, discontinuous growth, seemingly causal, regression, ARCH, and GARCH as well as a general form of nonlinear time series and nonparametric models Gives over 250 illustrative examples and notes based on the author's own empirical findings, allowing the advantages and limitations of each model to be understood Describes the theory behind the models in comprehensive appendices Provides supplementary information and data sets An essential tool for advanced undergraduate and graduate students taking finance or econometrics courses. Statistics, life sciences, and social science students, as well as applied researchers, will also find this book an invaluable resource.

Introduction to Econometrics
Introduction to Econometrics

Author: James H. Stock

Publisher: Prentice Hall

Published: 2015

Total Pages: 0

ISBN-13: 9780133486872

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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.

Economic and Financial Modelling with EViews
Economic and Financial Modelling with EViews

Author: Abdulkader Aljandali

Publisher: Springer

Published: 2018-10-22

Total Pages: 293

ISBN-13: 3319929852

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This practical guide in Eviews is aimed at practitioners and students in business, economics, econometrics, and finance. It uses a step-by-step approach to equip readers with a toolkit that enables them to make the most of this widely used econometric analysis software. Statistical and econometrics concepts are explained visually with examples, problems, and solutions. Developed by economists, the Eviews statistical software package is used most commonly for time-series oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. The package provides convenient ways to enter or upload data series, create new series from existing ones, display and print series, carry out statistical analyses of relationships among series, and manipulate results and output. This highly hands-on resource includes more than 200 illustrative graphs and tables and tutorials throughout. Abdulkader Aljandali is Senior Lecturer at Coventry University in London. He is currently leading the Stochastic Finance Module taught as part of the Global Financial Trading MSc. His previously published work includes Exchange Rate Volatility in Emerging Markers, Quantitative Analysis, Multivariate Methods & Forecasting with IBM SPSS Statistics and Multivariate Methods and Forecasting with IBM® SPSS® Statistics. Dr Aljandali is an established member of the British Accounting and Finance Association and the Higher Education Academy. Motasam Tatahi is a specialist in the areas of Macroeconomics, Financial Economics, and Financial Econometrics at the European Business School, Regent’s University London, where he serves as Principal Lecturer and Dissertation Coordinator for the MSc in Global Banking and Finance at The European Business School-London.

Principles of Econometrics
Principles of Econometrics

Author: Sankar Kumar Bhaumik

Publisher: OUP India

Published: 2015

Total Pages: 0

ISBN-13: 9780198098539

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Principles of Econometrics: A Modern Approach Using EViews is ideal for beginners in econometrics. It covers the undergraduate syllabi on econometrics taught at universities in India and abroad. Additionally, it introduces some advanced topics, such as panel data models, models with dummy dependent variable, and time series econometrics, which are important for empirical researchers in economics and other branches of social sciences. The book provides an applicational perspective to the subject of econometrics. It discusses the most modern tools of econometrics intuitively and uses simple algebra to establish results. For applications of the tools of econometrics, this book makes extensive use of data sets drawn from Indian sources and EViews software package. The steps followed in applications of EViews are systematically described, and the interpretations of results obtained from such applications are provided to help students acquire skills for econometric analysis. Written in lucid language and style, this book presents econometrics as an enjoyable and easy-to-learn subject for students of all categories. The book will be especially useful for students and researchers in economics, commerce, and management.

Advanced Time Series Data Analysis
Advanced Time Series Data Analysis

Author: I. Gusti Ngurah Agung

Publisher: John Wiley & Sons

Published: 2019-03-18

Total Pages: 538

ISBN-13: 1119504716

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Introduces the latest developments in forecasting in advanced quantitative data analysis This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable. Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers. Presents models that are all classroom tested Contains real-life data samples Contains over 350 equation specifications of various time series models Contains over 200 illustrative examples with special notes and comments Applicable for time series data of all quantitative studies Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.

Econometric Analysis of Cross Section and Panel Data, second edition
Econometric Analysis of Cross Section and Panel Data, second edition

Author: Jeffrey M. Wooldridge

Publisher: MIT Press

Published: 2010-10-01

Total Pages: 1095

ISBN-13: 0262232588

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The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

Econometric Analysis of Panel Data
Econometric Analysis of Panel Data

Author: Badi Baltagi

Publisher: John Wiley & Sons

Published: 2008-06-30

Total Pages: 239

ISBN-13: 0470518863

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Written by one of the world's leading researchers and writers in the field, Econometric Analysis of Panel Data has become established as the leading textbook for postgraduate courses in panel data. This new edition reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book. These programs will be made available via an accompanying website which will also contain solutions to end of chapter exercises that will appear in the book. The text has been fully updated with new material on dynamic panel data models and recent results on non-linear panel models and in particular work on limited dependent variables panel data models.

Applied Econometrics with R
Applied Econometrics with R

Author: Christian Kleiber

Publisher: Springer Science & Business Media

Published: 2008-12-10

Total Pages: 229

ISBN-13: 0387773185

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R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.