Time Series Data Analysis Using EViews
, by Agung, I. Gusti NgurahNote: Supplemental materials are not guaranteed with Rental or Used book purchases.
- ISBN: 9780470823675 | 0470823674
- Cover: Hardcover
- Copyright: 10/31/2008
This book is a practical guide to selecting and applying the most appropriate time series model and analysis of data sets using EViews. After introducing EViews workfiles and how to carry out descriptive data analysis, the book goes on to describe various models in detail (continuous growth, discontinuous growth, seemingly causal models, special cases of regression models, ARCH and GARCH models), all illustrated with a rich variety of examples and accompanied by helpful notes. Additional testing hypotheses are also explored and finally extension to a general form of nonlinear time series model is examined. Designed as a special guide for students and less experienced researchers it is a perfect complement to more theoretical books presenting statistical or econometric models for time series data.
I Gusti Ngurah Agung is a Lecturer and Academic Advisor at the Graduate School of Management, Faculty of Economics at the University of Indonesia. He has been teaching mathematical statistics and applied statistics since 1960 at the Makassar Public University as well as Hassanudin University, Makassar, and since 2006 at the Graduate School of Planning, Strategy and Public Policy, University of Indonesia. Agung has authored more than 10 pocket books in applied statistics (in Indonesian). He holds a BSc in Mathematical Education from Hassanudin University, a Masters in Mathematics from the New Mexico State University and a second Masters in mathematical statistics as well as a PhD in biostatistics from the University of North Carolina at Chapel Hill.
Contents | |
Preface | |
List Of Tables | |
List Of Figures | |
Eviews Workfile And Descriptive Data Analysis | |
What Is The Eviews Workfile? | |
Basic Options In Eviews | |
Creating A Workfile | |
Creating A Workfile Using Eviews 5 Or 6 | |
Creating Workfile Using Eviews 4 | |
Illustrative Data Analysis | |
Basic Descriptive Statistical Summary | |
Box Plots And Outliers | |
Descriptive Statistics By Groups | |
Graphs Over Times | |
Means Seasonal Growth Curve | |
Correlation Matrix | |
Special Notes And Comments | |
Statistics As A Sample Space | |
Continuous Growth Models | |
Introduction | |
Classical Growth Models | |
Autoregressive Growth Models | |
First-Order Autoregressive Growth Models | |
Ar(P) Growth Models | |
Residual Tests | |
Hypothesis Of No Serial Correlation | |
Hypothesis Of Homogeneous Residual Term | |
Hypothesis Of The Normality Assumption | |
Correlogram Q-Statistic | |
Bounded Autoregressive Growth Models | |
Lagged Variables Or Autoregressive Growth Models | |
The White Estimation Method | |
The Newey-West Hac Estimation Method | |
The Akaike Information And Schwarz Criterions | |
Mixed Lagged Variables-Autoregressive Growth Models | |
Polynomial Growth Model | |
Basic Polynomial Growth Models | |
Special Polynomial Growth Models | |
Growth Models With Exogenous Variables | |
A Taylor Series Approximation Model | |
Alternative Univariate Growth Models | |
A More General Growth Model | |
Translog Additive Growth Models | |
Some Comments | |
Growth Model Having Interaction-Factors | |
Trigonometric Growth Models | |
Multivariate Growth Models | |
The Classical Multivariate Growth Model | |
Modified Multivariate Growth Models | |
Ar(1) Multivariate General Growth Models | |
The S-Shape Multivariate Ar(1) General Growth Models | |
Multivariate Ar(P) Glm With Trend | |
Generalized Multivariate Models With Trend | |
The Simplest Multivariate Autoregressive Model | |
Multivariate Autoregressive Model With Two-Way Interactions | |
Multivariate Autoregressive Model With Three-Way Interactions | |
Special Notes And Comments | |
The True Population Model | |
Near singular matrix | |
öTo Test Or Notö The Assumptions Of The Error Terms | |
Alternative Multivariate Models With Trend | |
The Lagged Endogenous Variables - First Autoregressive Model With Trend | |
The Lagged Endogenous Variables-First Autoregressive Model With Exogenous Variables And Trend | |
A Mixed Lagged Variables û First Autoregressive Model With Trend | |
Generalized Multivariate Models | |
With Time-Related-Effects | |
Discontinuous Growth Models | |
Introduction | |
Piecewise Growth Models | |
Two-Pieces Classical Growth Models | |
Piecewise S-Shape Growth Models | |
Two-Pieces Linear Growth Models | |
Two-Pieces Polynomial Bounded Growth Models | |
Two-Pieces Quadratic Growth Models | |
A Two-Pieces Third-Degree Bounded Growth Model | |
A Two-Pieces Generalized Exponential Growth Model | |
Discontinuous Translog Linear Ar(1) Growth Models | |
Alternative Discontinuous Growth Models | |
Stability Test | |
ChowÆS Breakpoint Test | |
ChowÆS Forecast Test | |
Generalized Discontinuous Models With Trend | |
General Two-Pieces Univariate Models With Trend | |
Special Notes And Comments | |
General Two-Pieces Multivariate Models With Trend | |
General Two-Pieces Models With Time-Related Effects | |
Multivariate Models By States And Time Periods | |
Alternative Models | |
Not Recommended Models | |
Seemingly Causal Models | |
Introduction | |
Statistical Analysis Based On Single Time Series | |
The Mean Model | |
The Cell-Means Models | |
The Lagged-Variables Models | |
Autoregressive Models | |
Lagged-Variables-Autoregressive Models | |
Bivariate Seemingly Causal Models | |
The Simplest Seemingly Causal Models | |
Simplest Models In Three Dimensional Space | |
General Univariate LVAR(p,q) Seemingly Causal Model | |
Trivariate Seemingly Causal Models | |
Simple Models In Three Dimensional Space | |
System Equations Based On Trivariate Time Series | |
General System Of Equations | |
Seemingly Causal Models With Dummy Variables | |
Homogeneous Time Series Models | |
Heterogeneous Time Series Models | |
General Discontinuous Seemingly Causal Models | |
Additional Selected Seemingly Causal Models | |
A Third Degree Polynomial Function | |
A Three Dimensional Bounded Semilog Linear Model | |
Time Series Cobb-Douglas Models | |
Ces Time Series Models | |
Final Notes In Developing Models | |
ExpertsÆ Judgment | |
Other Unexpected Models | |
Special Cases Of Regression Models | |
Introduction | |
Specific Cases Of Growth Curve Models | |
Basic Polynomial Model | |
An Ar(1) Regression Model | |
Heteroskedasticity-Consistent Covariance (White) | |
Seemingly Causal Models | |
Autoregressive Models | |
Lagged Variable Models | |
The Basic Lagged-Variables Model | |
And The Autoregresive Model | |
Some Notes | |
Generalized Lagged Variable-Autoregressive Model | |
Cases Based On The Us Domestic Price Of Copper | |
Graphical Representation | |
Seemingly Causal Model | |
Simplest Seemingly Causal Models | |
Generalized Translog Linear Model | |
Constant Elasticity Of Substitution Models | |
Models For The First Difference Of An Endogenous Variable | |
Unexpected Findings | |
Multivariate Linear Seemingly Causal Models | |
Return Rate Models | |
Cases Based On The Basics Workfile | |
Var And System Estimation Methods | |
Introduction | |
The Var Models | |
The Basic Var Model | |
The Var Models With Exogenous Variables | |
Cases Based On The Demo_Modified Workfile | |
The Var Models With Dummy Variables | |
Selected Var Models Based On The Us Domestic Price Of Copper Data | |
Application Of Continuous Var Models With Trend | |
Application Of The Var Seemingly Causal Models | |
The Vector Error Correction Models | |
The Basic Vec Model | |
General Equation Of The Basic Vec Models | |
The Vec Models With Exogenous Variables | |
Some Notes And Comments | |
Special Notes And Comments | |
Instrumental Variables Models | |
Introduction | |
Should We Apply Instrumental Models? | |
Residual Analysis In Developing Instrumental Models | |
Testing Hypothesis Corresponding To The Instrumental Models | |
Graphical Representation Of The Residual Series | |
System Equation With Instrumental Variables | |
Selected Cases Based On The Us_Dpoc Data | |
Intrumentals Models With Time-Related-Effects | |
Intrumental Seemingly Causal Models | |
Multivariate Instrumental Models, Based On The Us_Dpoc | |
Simple Multivariate Instrumental Models | |
Multivariate Instrumental Models | |
Further Extension Of The Instrumental Models | |
Arch Models | |
Introduction | |
The Options Of Arch Models | |
Simple Arch Models | |
Simple Arch Models | |
Special Notes On The Arch Models | |
Acrh Models With Exogenous Variables | |
Arch Models With One Exogenous Variable | |
Arch Models With Two Exogenous Variables | |
Advanced Arch Models | |
Alternative Garch Variance Series | |
General Garch Variance Series For The Garch/Tarch Model | |
General Garch Variance Series For The Egarch Model | |
General Garch Variance Series For The Parch Model | |
General Garch Variance Series For The Component Arch(1,1) Model | |
Special Notes On The Garch Variance Series | |
Additional Testing Hypotheses | |
Introduction | |
The Unit Root Tests | |
Simple Unit Root Test | |
Comments On The Unit Root Tests | |
The Omitted Variables Tests | |
Redundant Variables Test (Rv-Test) | |
Non-Nested Test (Nn-Test) | |
The RamseyÆS Reset Test | |
Nonlinear Least Squares Models | |
Introduction | |
Classical Growth Models | |
Generalized Cobb-Douglas Models | |
Cases Based On The Demo.Wf1 | |
Cases Based On The Basic.Wf1 | |
Cases Based On The Us_Dpoc Data | |
Generalized Ces Models | |
Special Notes And Comments | |
Other Nls Models | |
Cases Based On The Demo.Wf1 | |
Nonparametric Estimation Methods | |
What Is The Nonparamtric Data Analysis | |
Basic Moving Average Estimates | |
Simple Moving Average Estimates | |
The Weighted Moving Average Estimates | |
Measuring The Best Fit Model | |
Advanced Moving Average Models | |
The Moving Average Models | |
The Arma Models With Covariates | |
11.5. Nonparametric Regression Based On Time Series | |
The HardleÆS Moving Average Models | |
The Nearest Neighbor Fit | |
Mathematical Background Of The Nearest Neighbor Fit | |
The Local Polynomial Kernel Fit Regression | |
Nonparametric Growth Models | |
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