Object Reference : Object View and Procedure Reference : Var
  
 
append
Append a specification line to a var.
Syntax
var_name.append(options) text
Type the text to be added after the append keyword. You must specify the restrictions type option.
Options
One of the following options is required when using append as a var proc:
 
svar
Text for identifying restrictions for structural VAR.
coint
Text for restrictions on the cointegration relations and/or adjustment coefficients.
VEC Restrictions
Restrictions may be placed on the coefficients B(r, k) of the r-th cointegrating relation and on the adjustment coefficients, where A(k, r) is the coefficient of the r-th cointegrating relation in the k-th VEC equation. Restrictions are entered in a comma separated list of the form:
B(r, k) = value
and
A(k, r) = value
SVAR Restrictions
SVAR text restriction expressions involve linear equations or use a function-like syntax to specify restrictions on one or more matrix elements for the , , , and .
For direct restrictions on elements of the matrices, the EViews text syntax requires that the canonical structural matrix names are preceded by “@”, as in “@A”, or “@F”, to avoid ambiguity with workfile objects, e.g., scalars or matrix object elements.
EViews also offers function-like expressions that concisely specify popular sets of SVAR restrictions. In the following list, the token can be substituted with any of the canonical matrices , , , and . The canonical names should not be preceded by “@” in this context since there is no potential workfile object ambiguity in the function argument(s).
 
@X = mat
Use mat as a pattern matrix for matrix X, e.g., “@a=mat1”, “@b = @mat2”.
@vec(X)=, , , ...
Restricts all elements of matrix X similar using the specified pattern matrix (provided in list form). Element ordering matches the vectorization of the matrix, i.e., the elements of the first column, followed by the second column, followed by the third column, etc.
@diag(X)
Restricts X to be a diagonal matrix, i.e., off-diagonal elements are zero. The diagonal elements are unrestricted.
@diag(X) = n
Restricts X to be a diagonal matrix with elements on the diagonal restricted to be n.
@lower(X)
Restricts X to be a lower triangular matrix, i.e., elements above the diagonal are zero.
@unitlower(X)
Restricts X to be a unit lower triangular matrix, i.e., elements above the diagonal are zero and elements on the diagonal are one.
@upper(X)
Restricts X to be an upper triangular matrix, i.e., elements below the diagonal are zero.
@unitupper(X)
Restricts X to be a unit upper triangular matrix, i.e., elements below the diagonal are zero and elements on the diagonal are one.
@row(X, r) = n
Restricts the elements in row r of X to equal n.
@col(X, c) = n
Restricts the elements in column c of X equal n.
Examples
var v
v.append(coint) b(1,1)=1
v.ec(restrict) 1 4 x y
First a VEC, V, is declared, then a restriction is appended to V, finally V is estimated with that restriction imposed.
var v
v.ls 1 3 y1 y2 y3
v.append(svar) @a(1,1) = 2.5
v.append(svar) @b(2,2) = @b(3,3) / 2
v.append(svar) @a(1,1) + @a(2,1) = 1
v.append(svar) @a(1,2) = 3 * @b(3,3)
v.append(svar) @s(1,1) + @s(2,2) - @f(3,3) = 1.5
v.svar
For an SVAR, we first estimate the VAR, then append restrictions then perform SVAR estimation.
Using a text expression equivalent to a pattern matrix:
v1.append(svar) @vec(s) = na, na, na, 0, na, na, 0, 0, na
v1.svar
Using a text expression with specialized function:
v1.append(svar) @lower(s)
v1.svar
Cross-references
See also Var::cleartext.