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在stata中用h xtmpg命令，得到：
Title
xtpmg -- Pooled Mean-Group, Mean-Group, and Dynamic Fixed Effects
Models
Syntax
xtpmg depvar [indepvars] [if] [in] [, options]
options description
-------------------------------------------------------------------------
Model
lr(varlist) terms to be included in long-run cointegrating
vector (Note the difference in sign from
Pesaran's specification)
noconstant suppresses constant term
cluster(varname) adjust standard errors for intragroup correlation
ec(string) name of newly created error-correction term
constraints(string) constraints to be applied to the model
replace overwrite error correction term, if it exists
full display all panel regressions for MG and PMG
models
pmg|mg|fe specifies the panel data specification. pmg
estimates Pesaran's Pooled Mean-Group Model, mg
estimates the Mean-Group Model, and fe
estimates the Dynamic Fixed Effects Model. pmg
is the default.
Maximum Likelihood Options
Only valid with pmg.
technique(algorithm) specifies the ml maximization technique
difficult will use a different stepping algorithm in
non-concave regions of the likelihood see
See ml model_options for a description of available options.
Reporting
level(#) set confidence level; default is level(95)
-------------------------------------------------------------------------
You must tsset your data before using xtpmg; see tsset.
varlists may contain time-series operators; see tsvarlist.
Description
xtpmg aids in the estimation of large N and large T panel-data models
where nonstationarity may be a concern. In addition to the traditional
dynamic fixed effects models, xtpmg allows for the pooled mean group and
mean group estimators. Consider the model
d.y_it = phi*(y_(it-1)+beta*x_(it)) + d.y_(it-1)a_1+... + y_(it-p)a_p +
d.x_(it)b_1+...+d.x_(it-q)b_q + e_(it) i={(1,...,N};
t={(1,...,T_i)},
where
phi is the error correction speed of adjustment parameter to be estimated
beta is a (k X 1) vector of parameters
a_1,...,a_p are p parameters to be estimated
x_(it) is a (1 X k) vector of covariates
b_1,...,b_q are q parameters to be estimated
and e_(it) is the error term. The assumed distribution of the error term
depends on the model estimated.
Options
+-------+
----+ Model +------------------------------------------------------------
constraints(constraints), noconstant; see estimation options. (Note:
Constraints are applied post-estimation)
lr(varlist) specifies the variables to be included in the cointegrating
vector. For identification purposes, the first listed variable will
have its coefficient normalized to 1.
ec(string) specifies the name of a new variable to be created in the
dataset to hold the error-correction term. The default is __ec.
cluster(varname); see estimation options.
replace replaces the error correction variable in memory, if it exists.
full displays all panel estimation output (for the mean-group and pooled
mean-group models).
pmg|mg|fe selects the desired estimation procedure. pmg estimates the
pooled mean-group model where the long-run effects, beta, are
constrained to be equal across all panels. The short-run
coefficients, including phi, are allowed to differ across panels. mg
estimates the mean-group model where the coefficients of the model
are calculated from the unweighted average of the unconstrained,
fully heterogeneous model. fe estimates the dynamic fixed effects
model where all parameters, except intercepts, are constrained to be
equal across panels. pmg is the default.
+----------------------------+
----+ Maximum Likelihood Options +---------------------------------------
technique(algorithm) specifies ml optimization technique. See ml
model_options for more information. The bhh algorithm is not
allowed. This option is only valid with the pmg model.
level(#); see estimation options.
Examples
. xtpmg d.c d.y d.pi, lr(l.c y pi) full
. xtpmg d.c d(1/2).y d.pi if year>1962, ec(ec) lr(l.c y pi) mg replace
. xtpmg d.c d.y d.pi, lr(l.c y pi) fe
. cons def 1 [ec]y=.75
. xtpmg d.c d.y d.pi, lr(l.c y pi) mg const(1) replace ec(ec)
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