188—Appendix A. Object, View and Procedure Reference
displayname......... |
set display name (p. 276). |
save ..................... |
save table as CSV, tab-delimited ASCII text, RTF, or HTML file on |
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disk (p. 430). |
setfillcolor............ |
set the fill (background) color of a set of table cells (p. 453). |
setfont ................. |
set the font for the text in a set of table cells (p. 455). |
setformat ............. |
set the display format of a set of table cells (p. 456). |
setheight .............. |
set the row height in a set of table cells (p. 461). |
setindent.............. |
set the indentation for a set of table cells (p. 462). |
setjust.................. |
set the justification for a set of table cells (p. 463). |
setlines ................ |
set the line characteristics and borders for a set of table cells |
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(p. 465). |
setmerge .............. |
merge or unmerge a set of table cells (p. 466). |
settextcolor .......... |
set the text color in a set of table cells (p. 467). |
setwidth............... |
set the column width for a set of table cells (p. 468). |
Table Data Members
(i,j)...................... the (i,j)-th element of the table, formatted as a string.
Table Commands
setcell .................. |
format and fill in a table cell (p. 446). |
setcolwidth .......... |
set width of a table column (p. 447). |
setline.................. |
place a horizontal line in table (p. 464). |
Table Examples
table(5,5) mytable
%strval = mytable(2,3)
mytable(4,4) = "R2"
mytable(4,5) = @str(eq1.@r2)
Text
Text object.
Object for holding arbitrary text information.
Text Declaration
text ...................... |
declare text object (p. 508). |
To declare a text object, use the keyword text, followed by the object name:
text mytext
Valmap—189
Text Views
label |
.....................label information for the valmap object (p. 330). |
text....................... |
view contents of text object (p. 508). |
Text Examples
text mytext
[add text to the object]
mytext.text
Valmap
Valmap (value map).
Valmap Declaration
valmap ................. |
declare valmap object (p. 527). |
To declare a valmap use the keyword valmap, followed by a name |
|
valmap mymap |
|
Valmap Views |
|
label ..................... |
label information for the valmap object (p. 330). |
sheet .................... |
view table of map definitions (p. 469). |
stats...................... |
summary of map definitions (p. 487). |
usage.................... |
list of series and alphas which use the map (p. 527). |
Valmap Procs |
|
append ................. |
append a definition to a valmap (p. 205). |
displayname ......... |
set display name (p. 276). |
Valmap Examples
valmap b
b.append 0 no
b.append 1 yes
declares a valmap B, and adds two map definitions, mapping 0 to “no” and 1 to “yes”.
valmap txtmap
txtmap append "NM" "New Mexico"
txtmap append CA California
txtmap append "RI" "Rhode Island"
declares the valmap TXTMAP and adds three definitions.
190—Appendix A. Object, View and Procedure Reference
Var
Vector autoregression and error correction object.
Var Declaration
var....................... |
declare var estimation object (p. 528). |
To declare a var use the keyword var, followed by a name and, optionally, by an estimation specification:
var finvar
var empvar.ls 1 4 payroll hhold gdp
var finec.ec(e,2) 1 6 cp div r
Var Methods
ec ........................ |
estimate a vector error correction model (p. 282). |
ls ......................... |
estimate an unrestricted VAR (p. 345). |
Var Views
arlm..................... |
serial correlation LM test (p. 213). |
arroots ................. |
inverse roots of the AR polynomial (p. 215). |
coint .................... |
Johansen cointegration test (p. 245). |
correl ................... |
residual autocorrelations (p. 256). |
decomp................ |
variance decomposition (p. 270). |
endog .................. |
table or graph of endogenous variables (p. 285). |
impulse................ |
impulse response functions (p. 324). |
jbera .................... |
residual normality test (p. 327). |
label .................... |
label information for the var object (p. 330). |
laglen .................. |
lag order selection criteria (p. 331). |
output.................. |
table of estimation results (p. 380). |
qstats ................... |
residual portmanteau tests (p. 412). |
representations..... |
text describing var specification (p. 417). |
residcor................ |
residual correlation matrix (p. 421). |
residcov ............... |
residual covariance matrix (p. 421). |
resids ................... |
residual graphs (p. 422). |
results.................. |
table of estimation results (p. 423). |
testexog ............... |
exogeneity (Granger causality) tests (p. 504). |
testlags ................ |
lag exclusion tests (p. 506). |
white ................... |
White heteroskedasticity test (p. 542). |
Var—191
Var Procs
append ................. |
append restriction text (p. 205). |
cleartext................ |
clear restriction text (p. 242). |
displayname ......... |
set display name (p. 276). |
makecoint............. |
make group of cointegrating relations (p. 350). |
makeendog ........... |
make group of endogenous series (p. 351). |
makemodel........... |
make model from the estimated var (p. 358). |
makeresids ........... |
make residual series (p. 359). |
makesystem .......... |
make system from var (p. 365). |
svar ...................... |
estimate structural factorization (p. 494). |
Var Data Members
Scalar Values (individual level data)
@eqlogl(k) ........... |
log likelihood for equation k. |
@eqncoef(k)......... |
number of estimated coefficients in equation k. |
@eqregobs(k) ....... |
number of observations in equation k. |
@meandep(k)....... |
mean of the dependent variable in equation k. |
@r2(k) ................. |
R-squared statistic for equation k. |
@rbar2(k) ............ |
adjusted R-squared statistic for equation k. |
@sddep(k) ........... |
std. dev. of dependent variable in equation k. |
@se(k) ................. |
standard error of the regression in equation k. |
@ssr(k) ................ |
sum of squared residuals in equation k. |
a(i,j)..................... |
adjustment coefficient for the j-th cointegrating equation in the i- |
|
th equation of the VEC (where applicable). |
b(i,j)..................... |
coefficient of the j-th variable in the i-th cointegrating equation |
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(where applicable). |
c(i,j) ..................... |
coefficient of the j-th regressor in the i-th equation of the var, or |
|
the coefficient of the j-th first-difference regressor in the i-th equa- |
|
tion of the VEC. |
Scalar Values (system level data) |
|
@aic..................... |
Akaike information criterion for the system. |
@detresid ............. |
determinant of the residual covariance matrix. |
@hq ..................... |
Hannan-Quinn information criterion for the system. |
@logl ................... |
log likelihood for system. |
@ncoefs ............... |
total number of estimated coefficients in the var. |
@neqn ................. |
number of equations. |
192—Appendix A. Object, View and Procedure Reference
@regobs .............. |
number of observations in the var. |
@sc ..................... |
Schwarz information criterion for the system. |
@svarcvgtype....... |
Returns an integer indicating the convergence type of the struc- |
|
tural decomposition estimation: 0 (convergence achieved), 2 (fail- |
|
ure to improve), 3 (maximum iterations reached), 4 (no |
|
convergence—structural decomposition not estimated). |
@svaroverid......... |
over-identification LR statistic from structural factorization. |
@totalobs ............ |
sum of “@eqregobs” from each equation (“@regobs*@neqn”). |
Vectors and Matrices
@coefmat ............ |
coefficient matrix (as displayed in output table). |
@coefse ............... |
matrix of coefficient standard errors (corresponding to the output |
|
table). |
@cointse.............. |
standard errors of cointegrating vectors. |
@cointvec............ |
cointegrating vectors. |
@impfact ............. |
factorization matrix used in last impulse response view. |
@lrrsp ................. |
accumulated long-run responses from last impulse response view. |
@lrrspse .............. |
standard errors of accumulated long-run responses. |
@residcov............ |
(sym) covariance matrix of the residuals. |
@svaramat........... |
estimated A matrix for structural factorization. |
@svarbmat .......... |
estimated B matrix for structural factorization. |
@svarcovab ......... |
covariance matrix of stacked A and B matrix for structural factor- |
|
ization. |
@svarrcov............ |
restricted residual covariance matrix from structural factorization. |
Var Examples
To declare a var estimate a VEC specification and make a residual series:
var finec.ec(e,2) 1 6 cp div r
finec.makeresids
To estimate an ordinary var, to create series containing residuals, and to form a model based upon the estimated var:
var empvar.ls 1 4 payroll hhold gdp
empvar.makeresids payres hholdres gdpres
empvar.makemodel(inmdl) cp fcp div fdiv r fr
To save coefficients in a scalar: