350—Appendix B. Command Reference
See “Equation” (p. 157), “Pool” (p. 171), “System” (p. 184), and “Var” (p. 190) for a complete description of these objects, including a list of saved results. See also Appendix C, “Special Expression Reference”, on page 565, for special terms that may be used in ls specifications.
makecoint |
Var Proc |
|
|
Create group containing the estimated cointegrating relations from a VEC.
Syntax
Var Proc: |
var_name.makecoint [group_name] |
The series contained in the group are given names of the form “COINTEQ##”, where ## are numbers such that “COINTEQ##” is the next available unused name.
If you provide a name for the group in parentheses after the keyword, EViews will quietly create the named group in the workfile. If you do not provide a name, EViews will open an untitled group window if the command is executed from the command line, otherwise no group will be created.
This proc will return an error message unless you have estimated an error correction model using the var object.
Examples
var vec1.ec(b,2) 1 4 y1 y2 y3
vec1.makecoint gcoint
The first line estimates a VEC with 2 cointegrating relations. The second line creates a group named GCOINT which contains the two estimated cointegrating relations. The two cointegrating relations will be stored as series named COINTEQ01 and COINTEQ02 (if these names have not yet been used in the workfile).
Cross-references
See Chapter 24, “Vector Autoregression and Error Correction Models”, on page 719 of the
User’s Guide for details.
See also coint (p. 245).
makeendog—351
makederivs |
Equation Proc |
|
|
Make a group containing individual series which hold the derivatives of the equation specification.
Syntax
Equation Proc: |
equation_name.makederivs(options) [ser1 ser2 ...] |
If desired, enclose the name of a new group object to hold the series in parentheses following the command name.
The argument specifying the names of the series is also optional. If not provided, EViews will name the series “DERIV##” where ## is a number such that “DERIV##” is the next available unused name. If the names are provided, the number of names must match the number of target series.
Cross-references
See Chapter 25, “State Space Models and the Kalman Filter”, on page 751 of the User’s Guide for details on state space estimation.
See also derivs (p. 273), grads (p. 315), makegrads (p. 353).
makeendog |
Sspace Proc | System Proc | Var Proc |
|
|
Make a group out of the endogenous series.
Syntax
Object Proc: |
object_name.makeendog name |
Following the keyword makeendog, you should provide a name for the group to hold the endogenous series. If you do not provide a name, EViews will create an untitled group.
Note that in endog and makeendog are no longer supported for model objects. See instead, makegroup (p. 355).
Examples
var1.makeendog grp_v1
creates a group named GRP_V1 that contains the endogenous series in VAR1.
352—Appendix B. Command Reference
Cross-references
See also endog (p. 285) and makegroup (p. 355).
makefilter |
Sspace Proc |
|
|
Create a “Kalman filter” sspace object.
Creates a new sspace object with all estimated parameter values substituted out of the specification. This procedure allows you to use the structure of the sspace without reference to estimated coefficients or the estimation sample.
Syntax
Sspace Proc: |
sspace_name.makefilter [filter_name] |
If you provide a name for the sspace object in parentheses after the keyword, EViews will quietly create the named object in the workfile. If you do not provide a name, EViews will open an untitled sspace window if the command is executed from the command line.
Examples
ss1.makefilter kfilter
creates a new sspace object named KFILTER, containing the specification in SS1 with estimated parameter values substituted for coefficient elements.
Cross-references
See Chapter 25, “State Space Models and the Kalman Filter”, on page 751 of the User’s Guide for details on state space models.
See also makesignals (p. 361) and makestates (p. 362).
makegarch |
Equation Proc |
|
|
Generate conditional variance series.
Saves the estimated conditional variance (from an equation estimated using ARCH) as a named series.
Syntax
Equation Proc: |
eq_name.makegarch series1_name [@ series2_name] |
makegrads—353
You should provide a name for the saved conditional standard deviation series following the makegarch keyword. If you do not provide a name, EViews will name the series using the next available name of the form “GARCH##” (if GARCH01 already exists, it will be named GARCH02, and so on).
For component GARCH equations, the permanent component portion of the conditional variance may be saved by adding "@" followed by a series name.
Examples
equation eq1.arch sp c
eq1.makegarch cvar
plot cvar^.5
estimates a GARCH(1,1) model, saves the conditional variance as a series named CVAR, and plots the conditional standard deviation. If you merely wish to view a plot of the conditional standard deviation without saving the series, use the garch (p. 308) view.
The commands
equation eq1.arch(cgarch) sp c
eq1.makegarch cvar @ pvar
first estimates a Component GARCH model and then saves both the conditional variance and the permanent component portion of the conditional variance in the series CVAR and PVAR, respectively.
Cross-references
See Chapter 20, “ARCH and GARCH Estimation”, on page 599 of the User’s Guide for a discussion of GARCH models.
See also arch (p. 206), archtest (p. 210), and garch (p. 308).
makegrads |
Equation Proc | Logl Proc | Sspace Proc |
|
|
Make a group containing individual series which hold the gradients of the objective function.
Syntax
Object Proc: |
object_name.makegrads(options) [ser1 ser2 ...] |
The argument specifying the names of the series is also optional. If the argument is not provided, EViews will name the series “GRAD##” where ## is a number such that