- •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
794—Chapter 26. Models
below, making sure that the active scenario is set to Scenario 1, and the comparison scenario is set to Baseline. Again set the sample to 1995Q1 to 2005Q4. The following graph should be displayed:
The simulation results suggest that the cut in the money supply causes a substantial increase in interest rates, which creates a small reduction in investment and a relatively minor drop in income and consumption. Overall, the predicted effects of changes in the money supply on the real economy are relatively minor in this model.
This concludes the discussion of our example model. The
remainder of this chapter provides detailed information about working with particular features of the EViews model object.
Building a Model
Creating a Model
The first step in working with a model is to create the model object itself. There are several different ways of creating a model:
•You can create an empty model by using Object/New Object… and then choosing Model, or by performing the same operation using the right mouse button menu from inside the workfile window.
•You can select a list of estimation objects in the workfile window (equations, VARs, systems), and then select Open as Model from the right mouse button menu. This item will create a model which contains the equations from the selected objects as links.
Building a Model—795
•You can use the Make model procedure from an estimation object to create a model containing the equation or equations in that object.
Adding Equations to the Model
The equations in a model can be classified into two types: linked equations and inline equations. Linked equations are equations that import their specification from other objects in the workfile. Inline equations are contained inside the model as text.
There are a number of ways to add equations to your model:
•To add a linked equation: from the workfile window, select the object which contains the equation or equations you would like to add to the model, then copy-and- paste the object into the model equation view window.
•To add an equation using text: select Insert… from the right mouse button menu. In the text box titled: Enter one or more lines…, type in one or more equations in standard EViews format. You can also add linked equations from this dialog by typing a colon followed by the name of the object you would like to link to, for example “:EQ1”, because this is the text form of a linked object.
In an EViews model, the first variable that appears in an equation will be considered the endogenous variable for that equation. Since each endogenous variable can be associated with only one equation, you may need to rewrite your equations to ensure that each equation begins with a different variable. For example, say we have an equation in the model:
x / y = z
EViews will associate the equation with the variable X. If we would like the equation to be associated with the variable Y, we would have to rewrite the equation:
1 / y * x = z
Note that EViews has the ability to handle simple expressions involving the endogenous variable. You may use functions like LOG, D, and DLOG on the left-hand side of your equation. EViews will normalize the equation into explicit form if the Gauss-Seidel method is selected for solving the model.
Removing equations from the model
To remove equations from the model, simply select the equations using the mouse in Equation view, then use Delete from the right mouse button menu to remove the equations.
Both adding and removing equations from the model will change which variables are considered endogenous to the model.
796—Chapter 26. Models
Updating Links in the Model
If a model contains linked equations, changes to the specification of the equations made outside the model can cause the equations contained in the model to become out of date. You can incorporate these changes in the model by using Proc/Link/Update All Links.
Alternatively, you can update just a single equation using the Proc/Link/Update Link item from the right mouse button menu. Links are also updated when a workfile is reloaded from disk.
Sometimes, you may want to sever equations in the model from their linked objects. For example, you may wish to see the entire model in text form, with all equations written in place. To do this, you can use the Proc/Link/Break All Links procedure to convert all linked equations in the model into inline text. You can convert just a single equation by selecting the equation, then using Break Link from the right mouse button menu.
When a link is broken, the equation is written in text form with the unknown coefficients replaced by their point estimates. Any information relating to uncertainty of the coefficients will be lost. This will have no effect on deterministic solutions to the model, but may alter the results of stochastic simulations if the Include coefficient uncertainty option has been selected.
Working with the Model Structure
As with other objects in EViews, we can look at the information contained in the model object in several ways. Since a model is a set of equations that describe the relationship between a set of variables, the two primary views of a model are the equation view and the variable view. EViews also provides two additional views of the structure of the model: the block view and the text view.
Equation View
The equation view is used for displaying, selecting, and modifying the equations contained in the model. An example of the equation view can be seen on page 783.
Each line of the window is used to represent either a linked object or an inline text equation. Linked objects will appear similarly to how they do in the workfile, with an icon representing their type, followed by the name of the object. Even if the linked object contains many equations, it will use only one line in the view. Inline equations will appear with a “TXT” icon, followed by the beginning of the equation text in quotation marks.
The remainder of the line contains the equation number, followed by a symbolic representation of the equation, indicating which variables appear in the equation.
Any errors in the model will appear as red lines containing an error message describing the cause of the problem.
Working with the Model Structure—797
You can open any linked objects directly from the equation view. Simply select the line representing the object using the mouse, then choose Open Link from the right mouse button menu.
The contents of a line can be examined in more detail using the equation properties dialog. Simply select the line with the mouse, then choose Properties… from the right mouse button menu. Alternatively, simply double click on the object to call up the dialog.
For a link to a single equation, the dialog shows the functional form of the equation, the values of any estimated coefficients, and the standard error of the equation residual from the estimation. If the link is to an object containing many equations, you can move between the different equations imported from the object using the Endogenous list box at the top of the dialog. For an inline equation, the dialog simply shows the text of the equation.
The Edit Equation or Link Specification button allows you to edit the text of an inline equation or to modify a link to point to an object with a different name. A link is represented in text form as a colon followed by the name of the object. Note that you cannot modify the specification of a linked object from within the model object, you must work directly with the linked object itself.
In the bottom right of the dialog, there are a set of fields that allow you to set the stochastic properties of the residual of the equation. If you are only performing deterministic simulations, then these settings will not affect your results in any way. If you are performing stochastic simulations, then these settings are used in conjunction with the solution options to determine the size of the random innovations applied to this equation.
The Stochastic with S.D. option for Equation type lets you set a standard deviation for any random innovations applied to the equation. If the standard deviation field is blank or is set to “NA”, then the standard deviation will be estimated from the historical data. The Identity option specifies that the selected equation is an identity, and should hold without error even in a stochastic simulation. See “Stochastic Options” on page 810 below for further details.
798—Chapter 26. Models
The equation properties dialog also gives you access to the property dialogs for the endogenous variable and add factor associated with the equation. Simply click on the appropriate tab. These will be discussed in greater detail below.
Variable View
The variable view is used for adjusting options related to variables and for displaying and editing the series associated with the model (see the discussion in “An Example Model” (p. 784)). The variable view lists all the variables contained in the model, with each line representing one variable. Each line begins with an icon classifying the variable as endogenous, exogenous or an add factor. This is followed by the name of the variable, the equation number associated with the variable, and the description of the variable. The description is read from the associated series in the workfile.
Note that the names and types of the variables in the model are determined fully by the equations of the model. The only way to add a variable or to change the type of a variable in the model is to modify the model equations.
You can adjust what is displayed in the variable view in a number of ways. By clicking on the Filter/Sort button just above the variable list, you can choose to display only variables that match a certain name pattern, or to display the variables in a particular order. For example, sorting by type of variable makes the division into endogenous and exogenous variables clearer, while sorting by override highlights which variables have been overridden in the currently active scenario.
The variable view also allows you to browse through the dependencies between variables in the model by clicking on the Dependencies button. Each equation in the model can be thought of as a set of links that connect other variables in the model to the endogenous variable of the equation. Starting from any variable, we can travel up the links, showing all the endogenous variables that this variable directly feeds into, or we can travel down the links, showing all the variables upon which this variable directly depends. This may sometimes be useful when trying to find the cause of unexpected behavior. Note, however, that in a simultaneous model, every endogenous variable is indirectly connected to every other variable in the same block, so that it may be hard to understand the model as a whole by looking at any particular part.
You can quickly view or edit one or more of the series associated with a variable by double clicking on the variable. For several variables, simply select each of them with the mouse then double click inside the selected area.
Block Structure View
The block structure view of the model analyzes and displays any block structure in the dependencies of the model.
Working with the Model Structure—799
Block structure refers to whether the model can be split into a number of smaller parts, each of which can be solved for in sequence. For example, consider the system:
block 1 |
x = y + 4 |
|
|
|
y = 2*x – 3 |
|
|
block 2 |
z = x + y |
|
|
Because the variable Z does not appear in either of the first two equations, we can split this equation system into two blocks: a block containing the first two equations, and a block containing the third equation. We can use the first block to solve for the variables X and Y, then use the second block to solve for the variable Z. By using the block structure of the system, we can reduce the number of variables we must solve for at any one time. This typically improves performance when calculating solutions.
Blocks can be classified further into recursive and simultaneous blocks. A recursive block is one which can be written so that each equation contains only variables whose values have already been determined. A recursive block can be solved by a single evaluation of all the equations in the block. A simultaneous block cannot be written in a way that removes feedback between the variables, so it must be solved as a simultaneous system. In our example above, the first block is simultaneous, since X and Y must be solved for jointly, while the second block is recursive, since Z depends only on X and Y, which have already been determined in solving the first block.
The block structure view displays the structure of the model, labeling each of the blocks as recursive or simultaneous. EViews uses this block structure whenever the model is solved. The block structure of a model may also be interesting in its own right, since reducing the system to a set of smaller blocks can make the dependencies in the system easier to understand.
Text View
The text view of a model allows you to see the entire structure of the model in a single screen of text. This provides a quick way to input small models, or a way to edit larger models using copy-and-paste.
The text view consists of a series of lines. In a simple model, each line simply contains the text of one of the inline equations of the model. More complicated models may contain one of more of the following:
•A line beginning with a colon “:” represents a link to an external object. The colon must be followed by the name of an object in the workfile. Equations contained in the external object will be imported into the model whenever the model is opened, or when links are updated.