| pccep {plm} | R Documentation |
Common Corrleated Effects Pooled (CCEP) estimator for panel data with common factors (balanced or unbalanced)
pccep(formula, data, subset, na.action,
residuals = c("standard", "cce","ccemg"),
index = NULL, trend = FALSE, ...)
## S3 method for class 'pccep'
summary(object, ...)
## S3 method for class 'summary.pccep'
print(x,digits = max(3, getOption("digits") -
2), width = getOption("width"),...)
formula |
a symbolic description of the model to be estimated, |
object, x |
an object of class |
data |
a |
subset |
see |
na.action |
see |
residuals |
one of |
index |
the indexes, see |
trend |
logical specifying whether an individual-specific trend has to be included, |
digits |
digits, |
width |
the maximum length of the lines in the print output, |
... |
further arguments. |
pccep is a function for the estimation of linear panel models by the
Common Correlated Effects Pooled estimator, consistent under the
hypothesis of unobserved common factors and idiosyncratic factor
loadings; the CCEP estimator works by augmenting the model by
cross-sectional averages of the dependent variable and regressors in
order to account for the common factors, and adding individual
intercepts and possibly trends.
An object of class c("pccep","panelmodel") containing:
coefficients |
the vector of coefficients, |
residuals |
the vector of residuals, |
fitted.values |
the vector of fitted.values, |
vcov |
the covariance matrix of the coefficients, |
df.residual |
degrees of freedom of the residuals, |
model |
a data.frame containing the variables used for the estimation, |
call |
the call, |
sigma |
always |
indcoef |
the matrix of individual coefficients from separate time series regressions. |
Giovanni Millo
G. Kapetanios, M. Hashem Pesaran, T. Yamagata (2011), Panels with non-stationary multifactor error structures, Journal of Econometrics, 160(2), 326–348.
data("Produc", package = "plm")
ccepmod <- pccep(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc)
summary(ccepmod)