170—Appendix A. Object, View and Procedure Reference
and statistics computed for the rows of a matrix:
matrix rowmat=@transpose(copymat)
rowmat.stats
You can use explicit indices to refer to matrix elements:
scalar diagsum=cov1(1,1)+cov1(2,2)+cov(3,3)
Model
Set of simultaneous equations used for forecasting and simulation.
Model Declaration
model .................. |
declare model object (p. 370). |
Declare an object by entering the keyword model, followed by a name:
model mymod
declares an empty model named MYMOD. To fill MYMOD, open the model and edit the specification view, or use the append view. Note that models are not used for estimation of unknown parameters.
See also the section on model keywords in “Text View” on page 797 of the User’s Guide.
Model Views
block ................... |
display model block structure (p. 223). |
eqs....................... |
view of model organized by equation (p. 287). |
label .................... |
view or set label information for the model (p. 330). |
msg ..................... |
display model solution messages (p. 371). |
text ...................... |
show text showing equations in the model (p. 508). |
trace .................... |
view of trace output from model solution (p. 512). |
vars ..................... |
view of model organized by variable (p. 529). |
Model Procs
addassign............. |
assign add factors to equations (p. 198). |
addinit ................. |
initialize add factors (p. 199). |
append................. |
append a line of text to a model (p. 205). |
control ................. |
solve for values of control variable so that target matches trajec- |
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tory (p. 248). |
displayname......... |
set display name (p. 276). |
exclude ................ |
specifies (or merges) excluded series to the active scenario |
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(p. 289). |
|
Pool—171 |
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makegraph............ |
make graph object showing model series (p. 354). |
makegroup ........... |
make group out of model series and display dated data table |
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(p. 355). |
merge ................... |
merge objects into the model (p. 368). |
override ................ |
specifies (or merges) override series to the active scenario |
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(p. 382). |
scenario................ |
set the active, alternate, or comparison scenario (p. 438). |
solve..................... |
solve the model (p. 475). |
solveopt ................ |
set solve options for model (p. 476). |
spec...................... |
display the text specification view (p. 479). |
unlink .................. |
break links in specification (p. 519). |
update .................. |
update model specification (p. 520). |
Model Examples
The commands:
model mod1
mod1.append y=324.35+x
mod1.append x=-234+7.3*z
mod1.solve(m=100,c=.008)
create, specify, and solve the model MOD1.
The command:
mod1(g).makegraph gr1 x y z
plots the endogenous series X, Y, and Z, in the active scenario for model MOD1.
Pool
Pooled time series, cross-section object. Used when working with data with both time series and cross-section structure.
Pool Declaration
pool...................... |
declare pool object (p. 408). |
To declare a pool object, use the pool keyword, followed by a pool name, and optionally, a list of pool members. Pool members are short text identifiers for the cross section units:
pool mypool
pool g7 _can _fr _ger _ita _jpn _us _uk
172—Appendix A. Object, View and Procedure Reference
Pool Methods
ls ......................... |
estimate linear regression models including cross-section weighted |
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least squares, and fixed and random effects models (p. 345). |
tsls....................... |
linear two-stage least squares (TSLS) regression models (p. 515). |
Pool Views
cellipse ................ |
Confidence ellipses for coefficient restrictions (p. 236). |
coefcov ................ |
coefficient covariance matrix (p. 244). |
describe ............... |
calculate pool descriptive statistics (p. 274). |
fixedtest ............... |
test significance of estimates of fixed effects (p. 299). |
label .................... |
label information for the pool object (p. 330). |
output.................. |
table of estimation results (p. 380). |
ranhaus ............... |
Hausman test for correlation between random effects and regres- |
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sors (p. 413). |
representations..... |
text showing equations in the model (p. 417). |
residcor................ |
residual correlation matrix (p. 421). |
residcov ............... |
residual covariance matrix (p. 421). |
resids ................... |
table or graph of residuals for each pool member (p. 422). |
results.................. |
table of estimation results (p. 423). |
sheet.................... |
spreadsheet view of series in pool (p. 469). |
testadd ................. |
likelihood ratio test for adding variables to pool equation (p. 500) |
testdrop ............... |
likelihood ratio test for dropping variables from pool equation |
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(p. 503) |
uroot.................... |
panel unit root test on a pool series (p. 522). |
wald .................... |
Wald coefficient restriction test (p. 530). |
Pool Procs
add ...................... |
add cross section members to pool (p. 198). |
define .................. |
define cross section identifiers (p. 272). |
delete................... |
delete pool series (p. 272). |
displayname......... |
set display name (p. 276). |
drop..................... |
drop cross section members from pool (p. 281). |
fetch .................... |
fetch series into workfile using a pool (p. 291). |
genr..................... |
generate pool series using the “?” (p. 308). |
makegroup........... |
create a group of series from a pool (p. 355). |
makemodel .......... |
creates a model object from the estimated pool (p. 358). |
makeresids........... |
make series containing residuals from pool (p. 359). |
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Pool—173 |
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|
makestats ............. |
make descriptive statistic series (p. 363). |
makesystem .......... |
creates a system object from the pool for other estimation methods |
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(p. 365). |
read...................... |
import pool data from disk (p. 414). |
store ..................... |
store pool series in database/bank files (p. 490). |
updatecoefs........... |
update coefficient vector from pool (p. 521). |
write .................... |
export pool data to disk (p. 545). |
Pool Data Members |
|
String Values |
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@idname(i) .......... |
i-th cross-section identifier. |
@idnameest(i)...... |
i-th cross-section identifier for estimated equation |
Scalar Values |
|
@aic..................... |
Akaike information criterion. |
@coefcov(i,j) ....... |
covariance of coefficients i and j. |
@coefs(i).............. |
coefficient i. |
@dw .................... |
Durbin-Watson statistic. |
@effects(i)............ |
estimated fixed or random effect for the i-th cross-section member |
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(only for fixed or random effects). |
@f........................ |
F-statistic. |
@logl ................... |
log likelihood. |
@meandep ........... |
mean of the dependent variable. |
@ncoef................. |
total number of estimated coefficients. |
@ncross ............... |
total number of cross sectional units. |
@ncrossest ........... |
number of cross sectional units in last estimated pool equation. |
@r2...................... |
R-squared statistic. |
@rbar2................. |
adjusted R-squared statistic. |
@regobs ............... |
total number of observations in regression. |
@schwarz ............ |
Schwarz information criterion. |
@sddep ................ |
standard deviation of the dependent variable. |
@se...................... |
standard error of the regression. |
@ssr..................... |
sum of squared residuals. |
@stderrs(i) ........... |
standard error for coefficient i. |
@totalobs ............. |
total number of observations in the pool. For a balanced sample |
|
this is “@regobs*@ncrossest”. |
@tstats(i) ............. |
t-statistic value for coefficient i. |