help xtabond dialog: xtabond
also see: xtabond postestimation
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Title
[XT] xtabond -- Arellano-Bond linear dynamic panel-data estimation
Syntax
xtabond depvar [indepvars] [if] [in] [, options]
options description
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Model
noconstant suppress constant term
diffvars(varlist) already-differenced exogenous variables
inst(varlist) additional instrument variables
lags(#) use # lags of dependent variable as
covariates; default is lags(1)
maxldep(#) maximum lags of dependent variable for use as
instruments
maxlags(#) maximum lags of predetermined and endogenous
variables for use as instruments
twostep compute the two-step estimator instead of the
one-step estimator
Predetermined
pre(varlist[...]) predetermined variables; can be specified more
than once
Endogenous
endogenous(varlist[...]) endogenous variables; can be specified more
than once
SE/Robust
vce(vcetype) vcetype may be gmm or robust
Reporting
level(#) set confidence level; default is level(95)
artests(#) use # as maximum order for AR tests; default
is artests(2)
display_options control spacing
+ coeflegend display coefficients' legend instead of
coefficient table
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+ coeflegend does not appear in the dialog box.
A panel variable and a time variable must be specified; use xtset; see
[XT] xtset.
indepvars and all varlists, except pre(varlist[...]) and endogenous(
varlist[...]), may contain time-series operators; see tsvarlist. The
specification of depvar may not contain time-series operators.
by, statsby, and xi are allowed; see prefix.
See [XT] xtabond postestimation for features available after estimation.
Menu
Statistics > Longitudinal/panel data > Dynamic panel data (DPD) >
Arellano-Bond estimation
Description
Linear dynamic panel-data models include p lags of the dependent variable
as covariates and contain unobserved panel-level effects, fixed or
random. By construction, the unobserved panel-level effects are
correlated with the lagged dependent variables, making standard
estimators inconsistent. Arellano and Bond (1991) derived a consistent
generalized method of moments (GMM) estimator for the parameters of this
model; xtabond implements this estimator.
This estimator is designed for datasets with many panels and few periods,
and it requires that there be no autocorrelation in the idiosyncratic
errors. For a related estimator that uses additional moment conditions,
but still requires no autocorrelation in the idiosyncratic errors, see
[XT] xtdpdsys. For estimators that allow for some autocorrelation in the
idiosyncratic errors, at the cost of a more complicated syntax, see [XT]
xtdpd.
Options
+-------+
----+ Model +------------------------------------------------------------
noconstant; see [R] estimation options.
diffvars(varlist) specifies a set of variables that already have been
differenced to be included as strictly exogenous covariates.
inst(varlist) specifies a set of variables to be used as additional
instruments. These instruments are not differenced by xtabond before
including them in the instrument matrix.
lags(#) sets p, the number of lags of the dependent variable to be
included in the model. The default is p=1.
maxldep(#) sets the maximum number of lags of the dependent variable that
can be used as instruments. The default is to use all T_i-p-2 lags.
maxlags(#) sets the maximum number of lags of the predetermined and
endogenous variables that can be used as instruments. For
predetermined variables, the default is to use all T_i-p-1 lags of
these endogenous variables. For endogenous variables, the default is
to use all T_i-p-2 lags of these variables.
twostep specifies that the two-step estimator be calculated.
+---------------+
----+ Predetermined +----------------------------------------------------
pre(varlist [, lagstruct(prelags, premaxlags)]) specifies that a set of
predetermined variables be included in the model. Optionally, one
may specify that prelags lags of the specified variables also be
included. The default for prelags is 0. Specifying premaxlags sets
the maximum number of further lags of the predetermined variables
that can be used as instruments. The default is to include T_i-p-1
lagged levels as instruments for predetermined variables. You may
specify as many sets of predetermined variables as you need within
the standard Stata limits on matrix size. Each set of predetermined
variables may have its own number of prelags and premaxlags.
+------------+
----+ Endogenous +-------------------------------------------------------
endogenous(varlist [, lagstruct(endlags, endmaxlags)]) specifies that a
set of endogenous variables be included in the model. Optionally,
one may specify that endlags lags of the specified variables also be
included. The default for endlags is 0. Specifying endmaxlags sets
the maximum number of further lags of the endogenous variables that
can be used as instruments. The default is to include T_i-p-2 lagged
levels as instruments for endogenous variables. You may specify as
many sets of endogenous variables as you need within the standard
Stata limits on matrix size. Each set of endogenous variables may
have its own number of endlags and endmaxlags.
+-----------+
----+ SE/Robust +--------------------------------------------------------
vce(vcetype) specifies the type of standard error reported, which
includes types that are derived from asymptotic theory and that are
robust to some kinds of misspecification; see [XT] xtabond.
vce(gmm), the default, uses the conventionally derived variance
estimator for generalized method of moments estimation.
vce(robust) uses the robust estimator. After one-step estimation,
this is the Arellano-Bond robust VCE estimator. After two-step
estimation, this is the WC-robust estimator of Windmeijer.
+-----------+
----+ Reporting +--------------------------------------------------------
level(#); see [R] estimation options.
artests(#) specifies the maximum order of the autocorrelation test to be
calculated. The tests are reported by estat abond; see [XT] xtabond
postestimation. Specifying the order of the highest test at
estimation time is more efficient than specifying it to estat abond,
because estat abond must refit the model to obtain the test
statistics. The maximum order must be less than or equal to the
number of periods in the longest panel. The default is artests(2).
display_options: vsquish; see [R] estimation options.
The following option is available with xtabond but is not shown in the
dialog box:
coeflegend; see [R] estimation options.
Examples
Setup
. webuse abdata
Basic model with two lags of dependent variable included as regressors
. xtabond n l(0/1).w l(0/2).(k ys) yr1980-yr1984, lags(2)
. xtabond n l(0/1).w l(0/2).(k ys) yr1980-yr1984, lags(2) vce(robust)
. xtabond n l(0/1).w l(0/2).(k ys) yr1980-yr1984, lags(2) twostep
Treat w and k as predetermined and include w, L.w, k, L.k, and L2.k as
additional regressors
. xtabond n l(0/2).ys yr1980-yr1984, lags(2) pre(w, lag(1,.)) pre(k,
lag(2,.))
Treat L.w and L2.k as endogenous and include w, L.w, k, L.k, and L2.k as
additional regressors
. xtabond n l(0/2).ys yr1980-yr1984, lags(2) endogenous(w, lag(1,.))
endogenous(k, lag(2,.))
Saved results
xtabond saves the following in e():
Scalars
e(N) number of observations
e(N_g) number of groups
e(df_m) model degrees of freedom
e(g_max) largest group size
e(g_min) smallest group size
e(g_avg) average group size
e(t_max) maximum time in sample
e(t_min) minimum time in sample
e(chi2) model chi-squared statistic
e(arm#) test for autocorrelation of order #
e(artests) number of AR tests computed
e(sig2) estimate of sigma_epsilon^2
e(rss) sum of squared differenced residuals
e(sargan) Sargan test statistic
e(rank) rank of e(V)
e(zrank) rank of instrument matrix
Macros
e(cmd) xtdpd
e(cmdline) command as typed
e(depvar) name of dependent variable
e(twostep) twostep, if specified
e(ivar) variable denoting groups
e(tvar) time variable
e(vce) vcetype specified in vce()
e(vcetype) title used to label Std. Err.
e(system) system, if system estimator
e(hascons) hascons, if specified
e(transform) specified transform
e(engine) xtdpd
e(div_odvars) differenced variables used as standard instruments
for differenced equation and not for level
equation
e(div_olvars) level variables used as standard instruments for
differenced equation and not for level equation
e(liv_olvars) level variables used as standard instruments for
level equation and not for differenced equation
e(div_dvars) differenced variables used as standard instruments
for differenced equation
e(div_lvars) level variables used as standard instruments for
differenced equation
e(liv_lvars) level variables used as standard instruments for
level equation
e(dgmmiv_vars) variables used to create GMM-type instruments for
differenced equation
e(dgmmiv_flag) first lags of variables used to create GMM-type
instruments for differenced equation
e(dgmmiv_llag) last lags of variables used to create GMM-type
instruments for differenced equation
e(lgmmiv_vars) variables used to create GMM-type instruments for
level equation
e(lgmmiv_flag) first lags used to create GMM-type instruments for
level equation
e(diffvars) already differenced variables
e(datasignature) checksum from datasignature
e(properties) b V
e(estat_cmd) program used to implement estat
e(predict) program used to implement predict
e(marginsok) predictions allowed by margins
Matrices
e(b) coefficient vector
e(V) variance-covariance matrix of the estimators
Functions
e(sample) marks estimation sample
Results e(div_odvars), e(div_olvars), e(liv_olvars), e(div_dvars),
e(div_lvars), e(liv_lvars), e(dgmmiv_vars), e(dgmmiv_flag),
e(dgmmiv_llag), e(lgmmiv_vars), and e(lgmmiv_flag) describe the
instruments used by xtabond. These results are rarely of interest; see
the options of [XT] xtdpd for more details.
Reference
Arellano, M., and S. Bond. 1991. Some tests of specification for panel
data: Monte Carlo evidence and an application to employment
equations. Review of Economic Studies 58: 277-297.
Also see
Manual: [XT] xtabond
Help: [XT] xtabond postestimation;
[XT] xtset; [XT] xtdpd, [XT] xtdpdsys, [XT] xtivreg, [XT] xtreg,
> [XT] xtregar
