Time Series Data Analysis Using EViews

Contents
Preface
List Of Tables
List Of Figures

Chapter 1: Eviews Workfile And Descriptive Data Analysis
1.1 What Is The Eviews Workfile?
1.2 Basic Options In Eviews
1.3 Creating A Workfile
1.4 Illustrative Data Analysis
1.5 Special Notes And Comments
1.6 Statistics As A Sample Space

Chapter 2: Continuous Growth Models
2.1 Introduction
2.2 Classical Growth Models
2.3 Autoregressive Growth Models
2.4. Residual Tests
2.5 Bounded Autoregressive Growth Models
2.6 Lagged Variables Or Autoregressive Growth Models
2.7 Polynomial Growth Model
2.8. Growth Models With Exogenous Variables
2.9. A Taylor Series Approximation Model
2.10 Alternative Univariate Growth Models
2.11 Multivariate Growth Models
2.12. Multivariate Ar(P) Glm With Trend
2.13. Generalized Multivariate Models With Trend
2.14 Special Notes And Comments
2.15 Alternative Multivariate Models With Trend
2.16. Generalized Multivariate Models
With Time-Related-Effects

Chapter 3: Discontinuous Growth Models
3.1 Introduction
3.2. Piecewise Growth Models
3.3 Piecewise S-Shape Growth Models
3.4 Two-Pieces Polynomial Bounded Growth Models
3.5 Discontinuous Translog Linear Ar(1) Growth Models
3.6 Alternative Discontinuous Growth Models
3.7 Stability Test
3.8 Generalized Discontinuous Models With Trend
3.9 General Two-Pieces Models With Time-Related Effects
3.10. Multivariate Models By States And Time Periods
10.2 Not Recommended Models

Chapter 4: Seemingly Causal Models
4.1 Introduction
4.2 Statistical Analysis Based On Single Time Series
4.3 Bivariate Seemingly Causal Models
4.4 Trivariate Seemingly Causal Models
4.5 System Equations Based On Trivariate Time Series
4.6. General System Of Equations
4.7 Seemingly Causal Models With Dummy Variables
4.8. General Discontinuous Seemingly Causal Models
4.9. Additional Selected Seemingly Causal Models
4.10. Final Notes In Developing Models

Chapter 5: Special Cases Of Regression Models
5.1. Introduction
5.2 Specific

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.