Common correlated effects estimators
res=pcce(namey,arg1,...,argn)
* namey = a real (n x 1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes (this last case is the only one authorized if you are using a 'panel data' tlist, see below)
* arg1=
- either a 'panel data' tlist
- or an endogenous variable taking the form of a time series, a real (nx1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes
* arg2,...,argn=
- if first input of arg1,...,argn was a 'panel data' tlist then: other input are optional and can be:
.either 'x = name1;...;namep' where name1,...,namep are a subset of the names of the variables that are in the database
.the string 'nameid = name1,..., namen' where name1,... are names of individuals present in the database
.'yar=namear' the name of the AR endogenous variable in case of a dynamic panel data model that is in the database
- if arg1;was an endogenous variable then either:
.a time series
.a real (nxk) matrix
.a (kx1) string vector of names of time series, vectors or matrices
.the string 'id = v' where v is the vector of individuals attached to the y and x data (this argument must be present somewhere in the list of variables arguments)
.'yar = namear' the name of the AR endogeneous variable in case of a dynamic panel data model
- 'cce=xxx' type of common correlated effect estimators (dynamic or static, depending on the presence of an AR part)
.'meang' for the mean group (CCEMG)
.'pooled' for the pooled one (CCCEP)
- 'jackkn' if the user wants a half-panel jackknife correction for CCEMG estimator with dynamic panel
- 'wvec = xxx' a vector of individual weights for the CCEP estimator (optional, default = 1/#individuals)
- 'mglag = xxx' number of lags to filter residuals case of a CCEMG dynamic panel estimation (default int(T^(1/3)))
- the string 'noprint' if the user doesn't want the to print the results of the regression
* res = a tlist with
-res('meth') = 'panel with random effects'
-res('y') = y data vector
-res('x') = x data matrix
-res('nobs') = nobs
-res('nvar') = nvars
-res('beta') = bhat
-res('yhat') = yhat
-res('resid') = residuals
-res('vcovar') = estimated variance-covariance matrix of beta
-res('sige') = estimated variance of the residuals
-res('sige') = estimated variance of the residuals
-res('ser') = standard error of the regression
-res('tstat') = t-stats
-res('pvalue') = pvalue of the betas
-res('condindex') = multicolinearity cond index
-res('prescte') = boolean indicating the presence or absence of a constant in the regression
-res('rsqr') = rsquared
-res('rbar') = rbar-squared
-res('f') = F-stat for the nullity of coefficients other than the constant
-res('pvaluef') = its significance level