help sureg dialog: sureg
also see: sureg postestimation
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Title
[R] sureg -- Zellner's seemingly unrelated regression
Syntax
Basic syntax
sureg (depvar1 varlist1) (depvar2 varlist2) ... (depvarN varlistN) [
if] [in] [weight]
Full syntax
sureg ([eqname1:] depvar1a [depvar1b ... =] varlist1 [, noconstant])
([eqname2:] depvar2a [depvar2b ... =] varlist2 [, noconstant])
...
([eqnameN:] depvarNa [depvarNb ... =] varlistN [, noconstant])
[if] [in] [weight] [, options]
Explicit equation naming (eqname:) cannot be combined with multiple
dependent variables in an equation specification.
options description
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Model
isure iterate until estimates converge
constraints(constraints) apply specified linear constraints
df adj.
small report small-sample statistics
dfk use small-sample adjustment
dfk2 use alternate adjustment
Reporting
level(#) set confidence level; default is level(95)
corr perform Breusch-Pagan test
nocnsreport do not display constraints
display_options control spacing and display of omitted
variables and base and empty cells
Optimization
optimization_options control the optimization process; seldom used
+ noheader suppress header table from above coefficient
table
+ notable suppress coefficient table
+ coeflegend display coefficients' legend instead of
coefficient table
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+ noheader, notable, and coeflegend do not appear in the dialog box.
varlist1, ..., varlistN may contain factor variables; see fvvarlist. You
must have the same levels of factor variables in all equations that
have factor variables.
depvar and the varlists may contain time-series operators; see tsvarlist.
bootstrap, by, jackknife, rolling, and statsby are allowed; see prefix.
Weights are not allowed with the bootstrap prefix.
aweights are not allowed with the jackknife prefix.
aweights and fweights are allowed, see weight.
See [R] sureg postestimation for features available after estimation.
Menu
Statistics > Linear models and related > Multiple-equation models >
Seemingly unrelated regression
Description
sureg fits seemingly unrelated regression models (Zellner 1962; Zellner
and Huang 1962; Zellner 1963). The acronyms SURE and SUR are often used
for the estimator.
Options
+-------+
----+ Model +------------------------------------------------------------
isure specifies that sureg iterate over the estimated disturbance
covariance matrix and parameter estimates until the parameter
estimates converge. Under seemingly unrelated regression, this
iteration converges to the maximum likelihood results. If this
option is not specified, sureg produces two-step estimates.
constraints(constraints); see [R] estimation options.
+---------+
----+ df adj. +----------------------------------------------------------
small specifies that small-sample statistics be computed. It shifts the
test statistics from chi-squared and Z statistics to F statistics and
t statistics. Although the standard errors from each equation are
computed using the degrees of freedom for the equation, the degrees
of freedom for the t statistics are all taken to be those for the
first equation.
dfk specifies the use of an alternate divisor in computing the covariance
matrix for the equation residuals. As an asymptotically justified
estimator, sureg by default uses the number of sample observations
(n) as a divisor. When the dfk option is set, a small-sample
adjustment is made and the divisor is taken to be sqrt((n - k_i) * (n
- k_j)), where k_i and k_j are the number of parameters in equations
i and j, respectively.
dfk2 specifies the use of an alternate divisor in computing the
covariance matrix for the equation residuals. When the dfk2 option
is set, the divisor is taken to be the mean of the residual degrees
of freedom from the individual equations.
+-----------+
----+ Reporting +--------------------------------------------------------
level(#); see [R] estimation options.
corr displays the correlation matrix of the residuals between equations
and performs a Breusch-Pagan test for independent equations; that is,
the disturbance covariance matrix is diagonal.
nocnsreport; see [R] estimation options.
display_options: noomitted, vsquish, noemptycells, baselevels,
allbaselevels; see [R] estimation options.
+--------------+
----+ Optimization +-----------------------------------------------------
optimization_options control the iterative process that minimizes the sum
of squared errors when isure is specified. These options are seldom
used.
iterate(#) specifies the maximum number of iterations. When the
number of iterations equals #, the optimizer stops and presents
the current results, even if the convergence tolerance has not
been reached. The default value of iterate(#) is the current
value of set maxiter, which is iterate(16000) if maxiter has not
been changed.
trace adds to the iteration log a display of the current parameter
vector.
nolog suppresses the display of the iteration log.
tolerance(#) specifies the tolerance for the coefficient vector.
When the relative change in the coefficient vector from one
iteration to the next is less than or equal to #, the
optimization process is stopped. tolerance(1e-6) is the default.
The following options are available with sureg but are not shown in the
dialog box:
noheader suppresses display of the header reporting F statistics,
R-squared, and root mean squared error above the coefficient table.
notable suppresses display of the coefficient table.
coeflegend; see [R] estimation options.
Examples
Setup
. sysuse auto
Fit seemingly unrelated regression model
. sureg (price foreign weight length) (mpg foreign weight) (displ
foreign weight)
Using a shorthand syntax
. sureg (price foreign weight length) (mpg displ = foreign weight)
Using global macros
. global price (price foreign weight length)
. global mpg (mpg foreign weight)
. global displ (displ foreign weight)
. sureg $price $mpg $displ
With constraints
. constraint 1 [price]foreign = [mpg]foreign
. constraint 2 [price]foreign = [displacement]foreign
. sureg (price foreign length) (mpg displacement = foreign weight),
const(1 2)
Saved results
sureg saves the following in e():
Scalars
e(N) number of observations
e(k) number of parameters in system
e(k_eq) number of equations
e(k_autoCns) number of base, empty, and omitted constraints
e(mss_#) model sum of squares for equation #
e(df_m#) model degrees of freedom for equation #
e(rss_#) residual sum of squares for equation #
e(df_r) total residual degrees of freedom
e(r2_#) R-squared for equation #
e(F_#) F statistic for equation # (small only)
e(rmse_#) root mean squared error for equation #
e(dfk2_adj) divisor used with VCE when dfk2 specified
e(ll) log likelihood
e(chi2_#) chi-squared for equation #
e(p_#) significance for equation #
e(cons_#) 1 if equation # has a constant 0 otherwise
e(k_eform) number of leading equations appropriate for eform output
e(chi2_bp) Breusch-Pagan chi-squared
e(df_bp) degrees of freedom for Breusch-Pagan chi-squared test
e(cons_#) 1 when equation # has a constant; 0, otherwise
e(rank) rank of e(V)
e(ic) number of iterations
Macros
e(cmd) sureg
e(cmdline) command as typed
e(method) sure or isure
e(depvar) names of dependent variables
e(exog) names of exogenous variables
e(eqnames) names of equations
e(wtype) weight type
e(wexp) weight expression
e(corr) correlation structure
e(small) small
e(dfk) alternate divisor (dfk or dfk2 only)
e(properties) b V
e(predict) program used to implement predict
e(marginsok) predictions allowed by margins
e(marginsnotok)
predictions disallowed by margins
e(asbalanced) factor variables fvset as asbalanced
e(asobserved) factor variables fvset as asobserved
Matrices
e(b) coefficient vector
e(Cns) constraints matrix
e(Sigma) Sigma hat matrix
e(V) variance-covariance matrix of the estimators
Functions
e(sample) marks estimation sample
Reference
Zellner, A. 1962. An efficient method of estimating seemingly unrelated
regressions and tests for aggregation bias. Journal of the American
Statistical Association 57: 348-368.
------. 1963. Estimators for seemingly unrelated regression equations:
Some exact finite sample results. Journal of the American
Statistical Association 58: 977-992.
Zellner, A., and D. S. Huang. 1962. Further properties of efficient
estimators for seemingly unrelated regression equations.
International Economic Review 3: 300-313.
Also see
Manual: [R] sureg
Help: [R] sureg postestimation;
[R] mvreg, [R] nlsur, [R] reg3, [R] regress, [TS] dfactor
