coef—243
Cross-references
See Chapter 24, “Vector Autoregression and Error Correction Models”, on page 719 of the User’s Guide for a discussion of VARs.
See also append (p. 205).
close |
Command |
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Close object, program, or workfile.
Closing an object eliminates its window. If the object is named, it is still displayed in the workfile as an icon, otherwise it is deleted. Closing a program or workfile eliminates its window and removes it from memory. If a workfile has changed since you activated it, you will see a dialog box asking if you want to save it to disk.
Syntax
Command: |
close object_name |
Examples
close gdp graph1 table2
closes the three objects GDP, GRAPH1, and TABLE2.
lwage.hist
close lwage
opens the LWAGE window and displays the histogram view of LWAGE, then closes the window.
Cross-references
See Chapter 1, “Introduction”, on page 15 of the User’s Guide for a discussion of basic control of EViews.
coef |
Object Declaration |
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Declare a coefficient (column) vector. |
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Syntax |
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Command: |
coef(n) coef_name |
Follow the coef keyword with the number of coefficients in parentheses, and a name for the object. If you omit the number of coefficients, EViews will create a vector of length 1.
244—Appendix B. Command Reference
Examples
coef(2) slope
ls lwage = c(1)+slope(1)*edu+slope(2)*edu^2
The first line declares a coef object of length 2 named SLOPE. The second line estimates a least squares regression and stores the estimated slope coefficients in SLOPE.
arch(2,2) sp500 c
coef beta = c
coef(6) beta
The first line estimates a GARCH(2,2) model using the default coef vector C (note that the “C” in an equation specification refers to the constant term, a series of ones.) The second line declares a coef object named BETA and copies the contents of C to BETA (the “C” in the assignment statement refers to the default coef vector). The third line resizes BETA to “chop off” all elements except the first six. Note that since EViews stores coefficients with equations for later use, you will generally not need to perform this operation to save your coefficient vectors.
Cross-references
See “Coef” on page 155 for a full description of the coef object. See also vector (p. 529).
coefcov |
Equation View | Logl View | Pool View | Sspace View | System View |
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Coefficient covariance matrix.
Displays the covariances of the coefficient estimates for objects containing an estimated equation or equations.
Syntax
Object View: |
object_name.coefcov(options) |
Options
p |
Print the coefficient covariance matrix. |
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Examples
The set of commands:
equation eq1.ls lwage c edu edu^2 union
eq1.coefcov
coint—245
declares and estimates equation EQ1 and displays the coefficient covariance matrix in a window. To store the coefficient covariance matrix as a sym object, use “@coefcov”:
sym eqcov = eq1.@coefcov
Cross-references
See also coef (p. 243) and spec (p. 479).
coint |
Command || Group View | Var View |
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Johansen’s cointegration test.
Syntax
Command: |
coint(test_option,n,option) y1 y2 [y3 ... |
] |
Command: |
coint(test_option,n,option) y1 y2 [y3 ... |
] [@ x1 x2 x3 ...] |
Group View: |
group_name.coint(test_option,n,option) |
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Var View: |
var_name.coint(test_option,n,option) [@ x1 x2 x3 ...] |
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In command form, you should enter the coint keyword followed by a list of series or group names for you wish to test for cointegration. Each name should be separated by a space. To use exogenous variables, such as seasonal dummy variables, in the test, list the names after an “@”-sign.
When used as a group or var view, coint tests for cointegration among the series in the group or var. By default, if the var object contains exogenous variables, the cointegration test will use those exogenous variables; however, if you explicitly list the exogenous variables with an “@”-sign, then only the listed variables will be used in the test.
The EViews 5 output for cointegration tests now displays p-values for the rank test statistics. These p-values are computed using the response surface coefficients as estimated in MacKinnon, et. al. (1999). The 0.05 critical values are now based on the response surface coefficients from MacKinnon-Haug-Michelis. Note: the reported critical values assume no exogenous variables other than an intercept and trend.
Options
You must specify the test option followed by the number of lags n. You must choose one of the following six test options:
a |
No deterministic trend in the data, and no intercept or |
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trend in the cointegrating equation. |
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246—Appendix B. Command Reference
b |
No deterministic trend in the data, and an intercept but |
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no trend in the cointegrating equation. |
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c |
Linear trend in the data, and an intercept but no trend |
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in the cointegrating equation. |
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d |
Linear trend in the data, and both an intercept and a |
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trend in the cointegrating equation. |
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e |
Quadratic trend in the data, and both an intercept and a |
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trend in the cointegrating equation. |
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s |
Summarize the results of all 5 options (a-e). |
Other Options:
restrict |
Impose restrictions as specified by the append (coint) |
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proc. |
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m = integer |
Maximum number of iterations for restricted estimation |
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(only valid if you choose the restrict option). |
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c = scalar |
Convergence criterion for restricted estimation. (only |
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valid if you choose the restrict option). |
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save = mat_name |
Stores test statistics as a named matrix object. The |
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save= option stores a ( k + 1) × 4 matrix, where k is |
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the number of endogenous variables in the VAR. The |
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first column contains the eigenvalues, the second col- |
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umn contains the maximum eigenvalue statistics, the |
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third column contains the trace statistics, and the fourth |
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column contains the log likelihood values. The i-th row |
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of columns 2 and 3 are the test statistics for rank i − 1 . |
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The last row is filled with NAs, except the last column |
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which contains the log likelihood value of the unre- |
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stricted (full rank) model. |
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cvtype=ol |
Display 0.05 and 0.01 critical values from Osterwald- |
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Lenum (1992). |
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This option reproduces the output from version 4. The |
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default is to display critical values based on the |
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response surface coefficients from MacKinnon-Haug- |
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Michelis (1999). Note that the argument on the right |
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side of the equals sign are letters, not numbers 0-1). |
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