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Файл:EViews Guides BITCH / EV72.pdf
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- •Preface
- •Part IV. Basic Single Equation Analysis
- •Chapter 18. Basic Regression Analysis
- •Equation Objects
- •Specifying an Equation in EViews
- •Estimating an Equation in EViews
- •Equation Output
- •Working with Equations
- •Estimation Problems
- •References
- •Chapter 19. Additional Regression Tools
- •Special Equation Expressions
- •Robust Standard Errors
- •Weighted Least Squares
- •Nonlinear Least Squares
- •Stepwise Least Squares Regression
- •References
- •Chapter 20. Instrumental Variables and GMM
- •Background
- •Two-stage Least Squares
- •Nonlinear Two-stage Least Squares
- •Limited Information Maximum Likelihood and K-Class Estimation
- •Generalized Method of Moments
- •IV Diagnostics and Tests
- •References
- •Chapter 21. Time Series Regression
- •Serial Correlation Theory
- •Testing for Serial Correlation
- •Estimating AR Models
- •ARIMA Theory
- •Estimating ARIMA Models
- •ARMA Equation Diagnostics
- •References
- •Chapter 22. Forecasting from an Equation
- •Forecasting from Equations in EViews
- •An Illustration
- •Forecast Basics
- •Forecasts with Lagged Dependent Variables
- •Forecasting with ARMA Errors
- •Forecasting from Equations with Expressions
- •Forecasting with Nonlinear and PDL Specifications
- •References
- •Chapter 23. Specification and Diagnostic Tests
- •Background
- •Coefficient Diagnostics
- •Residual Diagnostics
- •Stability Diagnostics
- •Applications
- •References
- •Part V. Advanced Single Equation Analysis
- •Chapter 24. ARCH and GARCH Estimation
- •Basic ARCH Specifications
- •Estimating ARCH Models in EViews
- •Working with ARCH Models
- •Additional ARCH Models
- •Examples
- •References
- •Chapter 25. Cointegrating Regression
- •Background
- •Estimating a Cointegrating Regression
- •Testing for Cointegration
- •Working with an Equation
- •References
- •Binary Dependent Variable Models
- •Ordered Dependent Variable Models
- •Censored Regression Models
- •Truncated Regression Models
- •Count Models
- •Technical Notes
- •References
- •Chapter 27. Generalized Linear Models
- •Overview
- •How to Estimate a GLM in EViews
- •Examples
- •Working with a GLM Equation
- •Technical Details
- •References
- •Chapter 28. Quantile Regression
- •Estimating Quantile Regression in EViews
- •Views and Procedures
- •Background
- •References
- •Chapter 29. The Log Likelihood (LogL) Object
- •Overview
- •Specification
- •Estimation
- •LogL Views
- •LogL Procs
- •Troubleshooting
- •Limitations
- •Examples
- •References
- •Part VI. Advanced Univariate Analysis
- •Chapter 30. Univariate Time Series Analysis
- •Unit Root Testing
- •Panel Unit Root Test
- •Variance Ratio Test
- •BDS Independence Test
- •References
- •Part VII. Multiple Equation Analysis
- •Chapter 31. System Estimation
- •Background
- •System Estimation Methods
- •How to Create and Specify a System
- •Working With Systems
- •Technical Discussion
- •References
- •Vector Autoregressions (VARs)
- •Estimating a VAR in EViews
- •VAR Estimation Output
- •Views and Procs of a VAR
- •Structural (Identified) VARs
- •Vector Error Correction (VEC) Models
- •A Note on Version Compatibility
- •References
- •Chapter 33. State Space Models and the Kalman Filter
- •Background
- •Specifying a State Space Model in EViews
- •Working with the State Space
- •Converting from Version 3 Sspace
- •Technical Discussion
- •References
- •Chapter 34. Models
- •Overview
- •An Example Model
- •Building a Model
- •Working with the Model Structure
- •Specifying Scenarios
- •Using Add Factors
- •Solving the Model
- •Working with the Model Data
- •References
- •Part VIII. Panel and Pooled Data
- •Chapter 35. Pooled Time Series, Cross-Section Data
- •The Pool Workfile
- •The Pool Object
- •Pooled Data
- •Setting up a Pool Workfile
- •Working with Pooled Data
- •Pooled Estimation
- •References
- •Chapter 36. Working with Panel Data
- •Structuring a Panel Workfile
- •Panel Workfile Display
- •Panel Workfile Information
- •Working with Panel Data
- •Basic Panel Analysis
- •References
- •Chapter 37. Panel Estimation
- •Estimating a Panel Equation
- •Panel Estimation Examples
- •Panel Equation Testing
- •Estimation Background
- •References
- •Part IX. Advanced Multivariate Analysis
- •Chapter 38. Cointegration Testing
- •Johansen Cointegration Test
- •Single-Equation Cointegration Tests
- •Panel Cointegration Testing
- •References
- •Chapter 39. Factor Analysis
- •Creating a Factor Object
- •Rotating Factors
- •Estimating Scores
- •Factor Views
- •Factor Procedures
- •Factor Data Members
- •An Example
- •Background
- •References
- •Appendix B. Estimation and Solution Options
- •Setting Estimation Options
- •Optimization Algorithms
- •Nonlinear Equation Solution Methods
- •References
- •Appendix C. Gradients and Derivatives
- •Gradients
- •Derivatives
- •References
- •Appendix D. Information Criteria
- •Definitions
- •Using Information Criteria as a Guide to Model Selection
- •References
- •Appendix E. Long-run Covariance Estimation
- •Technical Discussion
- •Kernel Function Properties
- •References
- •Index
- •Symbols
- •Numerics
Part IX. Advanced Multivariate Analysis
The following chapters describe specialized tools for multivariate analysis:
•Chapter 38. “Cointegration Testing,” on page 685 documents testing for the presence of cointegrating relationships among non-stationary variables in non-panel and panel settings.
•Chapter 39. “Factor Analysis,” on page 705 describes tools for multivariate analysis using factor analysis.
General tools for multivariate analysis using the group object, including summary statistics, covariance analysis and principal components, are discussed in Chapter 12. “Groups,” beginning on page 379 of User’s Guide I.
684—Part IX. Advanced Multivariate Analysis
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