- •Table of Contents
- •What’s New in EViews 5.0
- •What’s New in 5.0
- •Compatibility Notes
- •EViews 5.1 Update Overview
- •Overview of EViews 5.1 New Features
- •Preface
- •Part I. EViews Fundamentals
- •Chapter 1. Introduction
- •What is EViews?
- •Installing and Running EViews
- •Windows Basics
- •The EViews Window
- •Closing EViews
- •Where to Go For Help
- •Chapter 2. A Demonstration
- •Getting Data into EViews
- •Examining the Data
- •Estimating a Regression Model
- •Specification and Hypothesis Tests
- •Modifying the Equation
- •Forecasting from an Estimated Equation
- •Additional Testing
- •Chapter 3. Workfile Basics
- •What is a Workfile?
- •Creating a Workfile
- •The Workfile Window
- •Saving a Workfile
- •Loading a Workfile
- •Multi-page Workfiles
- •Addendum: File Dialog Features
- •Chapter 4. Object Basics
- •What is an Object?
- •Basic Object Operations
- •The Object Window
- •Working with Objects
- •Chapter 5. Basic Data Handling
- •Data Objects
- •Samples
- •Sample Objects
- •Importing Data
- •Exporting Data
- •Frequency Conversion
- •Importing ASCII Text Files
- •Chapter 6. Working with Data
- •Numeric Expressions
- •Series
- •Auto-series
- •Groups
- •Scalars
- •Chapter 7. Working with Data (Advanced)
- •Auto-Updating Series
- •Alpha Series
- •Date Series
- •Value Maps
- •Chapter 8. Series Links
- •Basic Link Concepts
- •Creating a Link
- •Working with Links
- •Chapter 9. Advanced Workfiles
- •Structuring a Workfile
- •Resizing a Workfile
- •Appending to a Workfile
- •Contracting a Workfile
- •Copying from a Workfile
- •Reshaping a Workfile
- •Sorting a Workfile
- •Exporting from a Workfile
- •Chapter 10. EViews Databases
- •Database Overview
- •Database Basics
- •Working with Objects in Databases
- •Database Auto-Series
- •The Database Registry
- •Querying the Database
- •Object Aliases and Illegal Names
- •Maintaining the Database
- •Foreign Format Databases
- •Working with DRIPro Links
- •Part II. Basic Data Analysis
- •Chapter 11. Series
- •Series Views Overview
- •Spreadsheet and Graph Views
- •Descriptive Statistics
- •Tests for Descriptive Stats
- •Distribution Graphs
- •One-Way Tabulation
- •Correlogram
- •Unit Root Test
- •BDS Test
- •Properties
- •Label
- •Series Procs Overview
- •Generate by Equation
- •Resample
- •Seasonal Adjustment
- •Exponential Smoothing
- •Hodrick-Prescott Filter
- •Frequency (Band-Pass) Filter
- •Chapter 12. Groups
- •Group Views Overview
- •Group Members
- •Spreadsheet
- •Dated Data Table
- •Graphs
- •Multiple Graphs
- •Descriptive Statistics
- •Tests of Equality
- •N-Way Tabulation
- •Principal Components
- •Correlations, Covariances, and Correlograms
- •Cross Correlations and Correlograms
- •Cointegration Test
- •Unit Root Test
- •Granger Causality
- •Label
- •Group Procedures Overview
- •Chapter 13. Statistical Graphs from Series and Groups
- •Distribution Graphs of Series
- •Scatter Diagrams with Fit Lines
- •Boxplots
- •Chapter 14. Graphs, Tables, and Text Objects
- •Creating Graphs
- •Modifying Graphs
- •Multiple Graphs
- •Printing Graphs
- •Copying Graphs to the Clipboard
- •Saving Graphs to a File
- •Graph Commands
- •Creating Tables
- •Table Basics
- •Basic Table Customization
- •Customizing Table Cells
- •Copying Tables to the Clipboard
- •Saving Tables to a File
- •Table Commands
- •Text Objects
- •Part III. Basic Single Equation Analysis
- •Chapter 15. Basic Regression
- •Equation Objects
- •Specifying an Equation in EViews
- •Estimating an Equation in EViews
- •Equation Output
- •Working with Equations
- •Estimation Problems
- •Chapter 16. Additional Regression Methods
- •Special Equation Terms
- •Weighted Least Squares
- •Heteroskedasticity and Autocorrelation Consistent Covariances
- •Two-stage Least Squares
- •Nonlinear Least Squares
- •Generalized Method of Moments (GMM)
- •Chapter 17. Time Series Regression
- •Serial Correlation Theory
- •Testing for Serial Correlation
- •Estimating AR Models
- •ARIMA Theory
- •Estimating ARIMA Models
- •ARMA Equation Diagnostics
- •Nonstationary Time Series
- •Unit Root Tests
- •Panel Unit Root Tests
- •Chapter 18. Forecasting from an Equation
- •Forecasting from Equations in EViews
- •An Illustration
- •Forecast Basics
- •Forecasting with ARMA Errors
- •Forecasting from Equations with Expressions
- •Forecasting with Expression and PDL Specifications
- •Chapter 19. Specification and Diagnostic Tests
- •Background
- •Coefficient Tests
- •Residual Tests
- •Specification and Stability Tests
- •Applications
- •Part IV. Advanced Single Equation Analysis
- •Chapter 20. ARCH and GARCH Estimation
- •Basic ARCH Specifications
- •Estimating ARCH Models in EViews
- •Working with ARCH Models
- •Additional ARCH Models
- •Examples
- •Binary Dependent Variable Models
- •Estimating Binary Models in EViews
- •Procedures for Binary Equations
- •Ordered Dependent Variable Models
- •Estimating Ordered Models in EViews
- •Views of Ordered Equations
- •Procedures for Ordered Equations
- •Censored Regression Models
- •Estimating Censored Models in EViews
- •Procedures for Censored Equations
- •Truncated Regression Models
- •Procedures for Truncated Equations
- •Count Models
- •Views of Count Models
- •Procedures for Count Models
- •Demonstrations
- •Technical Notes
- •Chapter 22. The Log Likelihood (LogL) Object
- •Overview
- •Specification
- •Estimation
- •LogL Views
- •LogL Procs
- •Troubleshooting
- •Limitations
- •Examples
- •Part V. Multiple Equation Analysis
- •Chapter 23. System Estimation
- •Background
- •System Estimation Methods
- •How to Create and Specify a System
- •Working With Systems
- •Technical Discussion
- •Vector Autoregressions (VARs)
- •Estimating a VAR in EViews
- •VAR Estimation Output
- •Views and Procs of a VAR
- •Structural (Identified) VARs
- •Cointegration Test
- •Vector Error Correction (VEC) Models
- •A Note on Version Compatibility
- •Chapter 25. 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
- •Chapter 26. 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
- •Part VI. Panel and Pooled Data
- •Chapter 27. 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
- •Chapter 28. Working with Panel Data
- •Structuring a Panel Workfile
- •Panel Workfile Display
- •Panel Workfile Information
- •Working with Panel Data
- •Basic Panel Analysis
- •Chapter 29. Panel Estimation
- •Estimating a Panel Equation
- •Panel Estimation Examples
- •Panel Equation Testing
- •Estimation Background
- •Appendix A. Global Options
- •The Options Menu
- •Print Setup
- •Appendix B. Wildcards
- •Wildcard Expressions
- •Using Wildcard Expressions
- •Source and Destination Patterns
- •Resolving Ambiguities
- •Wildcard versus Pool Identifier
- •Appendix C. Estimation and Solution Options
- •Setting Estimation Options
- •Optimization Algorithms
- •Nonlinear Equation Solution Methods
- •Appendix D. Gradients and Derivatives
- •Gradients
- •Derivatives
- •Appendix E. Information Criteria
- •Definitions
- •Using Information Criteria as a Guide to Model Selection
- •References
- •Index
- •Symbols
- •.DB? files 266
- •.EDB file 262
- •.RTF file 437
- •.WF1 file 62
- •@obsnum
- •Panel
- •@unmaptxt 174
- •~, in backup file name 62, 939
- •Numerics
- •3sls (three-stage least squares) 697, 716
- •Abort key 21
- •ARIMA models 501
- •ASCII
- •file export 115
- •ASCII file
- •See also Unit root tests.
- •Auto-search
- •Auto-series
- •in groups 144
- •Auto-updating series
- •and databases 152
- •Backcast
- •Berndt-Hall-Hall-Hausman (BHHH). See Optimization algorithms.
- •Bias proportion 554
- •fitted index 634
- •Binning option
- •classifications 313, 382
- •Boxplots 409
- •By-group statistics 312, 886, 893
- •coef vector 444
- •Causality
- •Granger's test 389
- •scale factor 649
- •Census X11
- •Census X12 337
- •Chi-square
- •Cholesky factor
- •Classification table
- •Close
- •Coef (coefficient vector)
- •default 444
- •Coefficient
- •Comparison operators
- •Conditional standard deviation
- •graph 610
- •Confidence interval
- •Constant
- •Copy
- •data cut-and-paste 107
- •table to clipboard 437
- •Covariance matrix
- •HAC (Newey-West) 473
- •heteroskedasticity consistent of estimated coefficients 472
- •Create
- •Cross-equation
- •Tukey option 393
- •CUSUM
- •sum of recursive residuals test 589
- •sum of recursive squared residuals test 590
- •Data
- •Database
- •link options 303
- •using auto-updating series with 152
- •Dates
- •Default
- •database 24, 266
- •set directory 71
- •Dependent variable
- •Description
- •Descriptive statistics
- •by group 312
- •group 379
- •individual samples (group) 379
- •Display format
- •Display name
- •Distribution
- •Dummy variables
- •for regression 452
- •lagged dependent variable 495
- •Dynamic forecasting 556
- •Edit
- •See also Unit root tests.
- •Equation
- •create 443
- •store 458
- •Estimation
- •EViews
- •Excel file
- •Excel files
- •Expectation-prediction table
- •Expected dependent variable
- •double 352
- •Export data 114
- •Extreme value
- •binary model 624
- •Fetch
- •File
- •save table to 438
- •Files
- •Fitted index
- •Fitted values
- •Font options
- •Fonts
- •Forecast
- •evaluation 553
- •Foreign data
- •Formula
- •forecast 561
- •Freq
- •DRI database 303
- •F-test
- •for variance equality 321
- •Full information maximum likelihood 698
- •GARCH 601
- •ARCH-M model 603
- •variance factor 668
- •system 716
- •Goodness-of-fit
- •Gradients 963
- •Graph
- •remove elements 423
- •Groups
- •display format 94
- •Groupwise heteroskedasticity 380
- •Help
- •Heteroskedasticity and autocorrelation consistent covariance (HAC) 473
- •History
- •Holt-Winters
- •Hypothesis tests
- •F-test 321
- •Identification
- •Identity
- •Import
- •Import data
- •See also VAR.
- •Index
- •Insert
- •Instruments 474
- •Iteration
- •Iteration option 953
- •in nonlinear least squares 483
- •J-statistic 491
- •J-test 596
- •Kernel
- •bivariate fit 405
- •choice in HAC weighting 704, 718
- •Kernel function
- •Keyboard
- •Kwiatkowski, Phillips, Schmidt, and Shin test 525
- •Label 82
- •Last_update
- •Last_write
- •Latent variable
- •Lead
- •make covariance matrix 643
- •List
- •LM test
- •ARCH 582
- •for binary models 622
- •LOWESS. See also LOESS
- •in ARIMA models 501
- •Mean absolute error 553
- •Metafile
- •Micro TSP
- •recoding 137
- •Models
- •add factors 777, 802
- •solving 804
- •Mouse 18
- •Multicollinearity 460
- •Name
- •Newey-West
- •Nonlinear coefficient restriction
- •Wald test 575
- •weighted two stage 486
- •Normal distribution
- •Numbers
- •chi-square tests 383
- •Object 73
- •Open
- •Option setting
- •Option settings
- •Or operator 98, 133
- •Ordinary residual
- •Panel
- •irregular 214
- •unit root tests 530
- •Paste 83
- •PcGive data 293
- •Polynomial distributed lag
- •Pool
- •Pool (object)
- •PostScript
- •Prediction table
- •Principal components 385
- •Program
- •p-value 569
- •for coefficient t-statistic 450
- •Quiet mode 939
- •RATS data
- •Read 832
- •CUSUM 589
- •Regression
- •Relational operators
- •Remarks
- •database 287
- •Residuals
- •Resize
- •Results
- •RichText Format
- •Robust standard errors
- •Robustness iterations
- •for regression 451
- •with AR specification 500
- •workfile 95
- •Save
- •Seasonal
- •Seasonal graphs 310
- •Select
- •single item 20
- •Serial correlation
- •theory 493
- •Series
- •Smoothing
- •Solve
- •Source
- •Specification test
- •Spreadsheet
- •Standard error
- •Standard error
- •binary models 634
- •Start
- •Starting values
- •Summary statistics
- •for regression variables 451
- •System
- •Table 429
- •font 434
- •Tabulation
- •Template 424
- •Tests. See also Hypothesis tests, Specification test and Goodness of fit.
- •Text file
- •open as workfile 54
- •Type
- •field in database query 282
- •Units
- •Update
- •Valmap
- •find label for value 173
- •find numeric value for label 174
- •Value maps 163
- •estimating 749
- •View
- •Wald test 572
- •nonlinear restriction 575
- •Watson test 323
- •Weighting matrix
- •heteroskedasticity and autocorrelation consistent (HAC) 718
- •kernel options 718
- •White
- •Window
- •Workfile
- •storage defaults 940
- •Write 844
- •XY line
- •Yates' continuity correction 321
Chapter 4. Object Basics
At the heart of the EViews design is the concept of an object. In brief, objects are collections of related information and operations that are bundled together into an easy-to-use unit. Virtually all of your work in EViews will involve using and manipulating various objects.
EViews holds all of its objects in object containers. You can think of object containers as filing cabinets or organizers for the various objects with which you are working. The most important object container in EViews is the workfile, which is described in Chapter 3, “Workfile Basics”, beginning on page 49.
The remainder of this chapter describes basic techniques for working with objects in a workfile. While you may at first find the idea of objects to be a bit foreign, the basic concepts are easy to master and will form the foundation for your work in EViews. But don’t feel that you have to understand all of the concepts the first time through. If you wish, you can begin working with EViews immediately, developing an intuitive understanding of objects and workfiles as you go.
Subsequent chapters will provide a more detailed description of working with the various types of objects and other types of object containers.
What is an Object?
Information in EViews is stored in objects. Each object consists of a collection of information related to a particular area of analysis. For example, a series object is a collection of information related to a set of observations on a particular variable. An equation object is a collection of information related to the relationship between a collection of variables.
Note that an object need not contain only one type of information. For example, an estimated equation object contains not only the coefficients obtained from estimation of the equation, but also a description of the specification, the variance-covariance matrix of the coefficient estimates, and a variety of statistics associated with the estimates.
Associated with each type of object is a set of views and procedures which can be used with the information contained in the object. This association of views and procedures with the type of data contained in the object is what we term the object oriented design of EViews.
The object oriented design simplifies your work in EViews by organizing information as you work. For example, since an equation object contains all of the information relevant to an estimated relationship, you can move freely between a variety of equation specifications simply by working with different equation objects. You can examine results, perform
74—Chapter 4. Object Basics
hypothesis and specification tests, or generate forecasts at any time. Managing your work is simplified since only a single object is used to work with an entire collection of data and results.
This brief discussion provides only the barest introduction to the use of objects. The remainder of this section will provide a more general description of EViews objects. Subsequent chapters will discuss series, equations, and other object types in considerable detail.
Object Data
Each object contains various types of information. For example, series, matrix, vector, and scalar objects, all contain mostly numeric information. In contrast, equations and systems contain complete information about the specification of the equation or system, and the estimation results, as well as references to the underlying data used to construct the estimates. Graphs and tables contain numeric, text, and formatting information.
Since objects contain various kinds of data, you will want to work with different objects in different ways. For example, you might wish to compute summary statistics for the observations in a series, or you may want to perform forecasts based upon the results of an equation. EViews understands these differences and provides you with custom tools, called views and procedures, for working with an object’s data.
Object Views
There is more than one way to examine the data in an object. Views are tabular and graphical windows that provide various ways of looking at the data in an object.
For example, a series object has a spreadsheet view, which shows the raw data, a line graph view, a bar graph view, a histogram-and-statistics view, and a correlogram view. Other views of a series include distributional plots, QQ-plots, and kernel density plots.
Series views also allow you to compute simple hypothesis tests and statistics for various subgroups of your sample.
An equation object has a representation view showing the equation specification, an output view containing estimation results, an actual-fitted-residual view containing plots of fitted values and residuals, a covariance view containing the estimated coefficient covariance matrix, and various views for specification and parameter tests.
Views of an object are displayed in the object’s window. Only one window can be opened for each object and each window displays only a single view of the object at a time. You can change views of an object using the View menu located in the object window’s toolbar or the EViews main menu.
Perhaps the most important thing to remember about views is that views normally do not change data outside the object. Indeed, in most cases, changing views only changes the display format for the data, and not the data in the object itself.
What is an Object?—75
Object Procedures
Most EViews objects also have procedures, or procs. Like views, procedures often display tables or graphs in the object’s window. Unlike views, however, procedures alter data, either in the object itself or in another object.
Many procedures create new objects. For example, a series object contains procedures for smoothing or seasonally adjusting time series data and creating a new series containing the smoothed or adjusted data. Equation objects contain procedures for generating new series containing the residuals, fitted values, or forecasts from the estimated equation.
You select procedures from the Proc menu on the object’s toolbar or from the EViews main menu.
Object Types
The most common objects in EViews are series and equation objects. There are, however, a number of different types of objects, each of which serves a unique function. Most objects are represented by a unique icon which is displayed in the object container (workfile or database) window. The basic object icons are given by:
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Equation |
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Rowvector |
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Table |
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Graph |
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Sample |
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Text |
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Valmap |
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Series |
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Matrix |
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Vector |
Despite the fact that they are also objects, object containers do not have icons since they cannot be placed in other object containers—thus, workfiles and databases do not have icons since they cannot be placed in other workfiles or databases.
Note also that there are special icons that correspond to special versions of the objects:
Auto-updating Series
Group data and definitions (in databases)
76—Chapter 4. Object Basics
Undefined Link
If you set a series object to be auto-updating (see “Auto-Updating Series” on page 149), EViews will use the special icon to indicate that the series depends upon a formula. In contrast, an auto-updating alpha series (which we imagine to be less common) uses the original alpha icon, with an orange color to indicate the presence of a formula.
When group data are stored in databases, you will be given the option of storing the group definition (list of series names) alone, or both the group definition and the series contained in the group (see “Store, Fetch, and Copy of Group Objects” on page 272). If the latter are stored, the standard group icon will be modified, with the “+” indicating the additional presence of the series data.
Lastly, a link object (see “Series Links” on page 177), is always in one of three states, depending upon the definition contained in the link. If the link is to a numeric source series, the link object be displayed using a series icon, since it may be used as though it were an ordinary series, with a distinctive pink color used to indicate that the object depends on linked data. If the link is to an alpha source series, the link will show up as an alpha series icon, again in pink. If, however, the link object is unable to locate the source series, EViews will display the “?” icon indicating that the series type is unknown.
Basic Object Operations
Creating Objects
To create an object, you must first make certain that you have an open workfile container and that its window is active. Next, select Object/New Object… from the main menu. Until you have created or loaded a workfile, this selection is unavailable. After you click on the Object/New Object… menu entry, you will see the New Object dialog box.
You can click on the type of object you want, optionally provide a name for the object, and then click on OK. For some object types, a second dialog box will open prompting you to describe your object in more detail. For most objects, however, the object window will open immediately.
For example, if you select Equation, you will see a dialog box prompting you for additional information. Alternatively, if you click on Series and then select OK, you will see an object window (series window) displaying the spreadsheet view of an UNTITLED series.
Basic Object Operations—77
We will discuss object windows in greater detail in “The Object Window” on page 78.
Objects can also be created by applying procedures to other objects or by freezing an object view (see “Freezing Objects” on page 83).
Selecting Objects
Creating a new object will
not always be necessary. Instead, you may want to work with an existing object. One of the fundamental operations in EViews is selecting one or more objects from the workfile directory.
The easiest way to select objects is to point-and-click, using the standard Windows conventions for selecting contiguous or multiple items if necessary (“Selecting and Opening Items” on page 20). Keep in mind that if you are selecting a large number of items, you may find it useful to use the display filter before beginning to select items.
In addition, the View button in the workfile toolbar provides convenient selection shortcuts:
•Select All selects all of the objects in the workfile with the exception of the C coefficient vector and the RESID series.
•Deselect All eliminates any existing selections.
Note that all of the selected objects will be highlighted.
Opening Objects
Once you have selected your object or objects, you will want to open your selection, or create a new object containing the selected objects. You can do so by double clicking anywhere in the highlighted area.
If you double click on a single selected object, you will open an object window.
If you select multiple graphs or series and double click, a pop-up menu appears, giving you the option of creating and opening new objects (group, equation, VAR, graph) or displaying each of the selected objects in its own window.
Note that if you select multiple graphs and double click or select View/Open as One Window, all of the graphs will be merged into a single graph and displayed in a single window.