R: Mean Groups (MG), Demeaned MG and CCE MG estimators
pmg
R Documentation
Mean Groups (MG), Demeaned MG and CCE MG estimators
Description
Mean Groups (MG), Demeaned MG (DMG) and Common Corrleated Effects MG
(CCEMG) estimators for heterogeneous panel models, possibly with
common factors (CCEMG)
Usage
pmg(formula, data, subset, na.action,
model = c("mg", "cmg", "dmg"),
index = NULL, trend = FALSE, ...)
## S3 method for class 'pmg'
summary(object, ...)
## S3 method for class 'summary.pmg'
print(x,digits = max(3, getOption("digits") -
2), width = getOption("width"),...)
Arguments
formula
a symbolic description of the model to be estimated,
object, x
an object of class pmg,
data
a data.frame,
subset
see lm,
na.action
see lm,
model
one of c("mg", "cmg", "dmg"),
index
the indexes, see pdata.frame,
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.
Details
pmg is a function for the estimation of linear panel models with
heterogeneous coeffcients by the Mean Groups
estimator. model="mg" specifies the standard Mean Groups
estimator, based on the average of individual time series
regressions. If model="dmg" the data are demeaned
cross-sectionally, which is believed to reduce the influence of common
factors (and is akin to what is done in homogeneous panels when
model="within" and effect="time". Lastly, if
model="cmg" then the CCEMG estimator is employed: this latter is
consistent under the hypothesis of unobserved common factors and
idiosyncratic factor loadings; it 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.
Value
An object of class c("pmg", "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 NULL, sigma is here only for
conmpatibility reasons (to allow using the same summary and
print methods as pggls),
indcoef
the matrix of individual coefficients from separate time
series regressions.
Author(s)
Giovanni Millo
References
M. Hashem Pesaran (2006), Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure, Econometrica, 74(4), pp. 967–1012.
Examples
data("Produc", package = "plm")
## Mean Groups estimator
mgmod <- pmg(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data = Produc)
summary(mgmod)
## demeaned Mean Groups
dmgmod <- pmg(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data =
Produc, model="dmg")
summary(dmgmod)
## Common Correlated Effects Mean Groups
ccemgmod <- pmg(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp, data
= Produc, model="cmg")
summary(ccemgmod)
providing 
.