Mean group common correlated effects estimator
rp=pccemg1(y,index,x)
y = a (nobs*nindiv x 1) matrix of all of the individual's observations vertically concatenated. This matrix must include in the first column the dependent variable, the independent variables must follow accordingly.
index = index vector that identifies each observation with an individual e.g. 1 (first 2 observations for individual # 1) 1 2 (next 1 observation for individual # 2) 3 (next 3 observations for individual # 3) 3 3
x = (nobs*nindinv x k) matrix of exogeneous variables
res = a tlist with
rp('meth')='CCEMG'
rp('y') = y data vector
rp('x') = x data matrix
rp('nobs') = nobs
rp('nvar') = nvars
rp('beta') = bhat
rp('betai') = individual regression coefficients
rp('w') = vector of individual weights
rp('yhat') = yhat
rp('resid') = residuals
rp('vcovar') = estimated variance-covariance matrix of the CCCEP estimators
rp('sige') = estimated variance of the residuals
rp('sigu') = sum of squared residuals
rp('ser') = standard error of the regression
rp('tstat') = t-stats (CCEP estimators and fixed effects)
rp('pvalue') = pvalue of the betas
rp('condindex') = multicolinearity cond index
rp('prescte') = boolean indicating the presence or absence of a constant in the regression