PanelNaOmit: PanelNaOmit

In PooledMeanGroup: Pooled Mean Group Estimation of Dynamic Heterogenous Panels

Description

Prepares a panel data set for further calculations by eliminating "NA" and modifying quantity or a vector of the number of time series observations in each group

Usage

PanelNaOmit(dataset, quantity)

Arguments

dataset	a panel data set in the form of stacked time series, containing variables of long-run and short-run relationships (i.e., including differentiated and lagged variables from DiffPanel or LagPanel)
quantity	a vector of the number of time series observations in each group; in practice, it takes the form c(T1,...Tn) since the PMG allows the numbers of time series observations to differ freely across groups (if the number of time series observations in each group is the same, then c(T,...,T) and T=T1=T2=...=Tn

Details

Eliminates "NA" and modifies quantity or a vector of the number of time series observations in each group

Value

$dataset	panel data set for further calculations modified by eliminating "NA"
$quantity	modified vector of the number of time series observations in each group

Author(s)

Lech Kujawski, Piotr Zientara

Examples

# first import DataExp, i=1...9, T1=T2=...T9=35
data(DataExp)
DataExp[1:5,]
# then prepare lags and diffs using LagPanel and DiffPanel
y10=data.frame(y10=DataExp[,1], row.names=row.names(DataExp))
cpi=data.frame(cpi=DataExp[,7], row.names=row.names(DataExp))
dy10=DiffPanel(variable=y10, quantity=rep(35,9))
dopeness=DiffPanel(variable=DataExp[,6], quantity=rep(35,9))
ly10=LagPanel(variable=y10, quantity=rep(35,9))
diip=DiffPanel(variable=DataExp[,11], quantity=rep(35,9))
dcrisk=DiffPanel(variable=DataExp[,9], quantity=rep(35,9))
ldcrisk=LagPanel(variable=dcrisk, quantity=rep(35,9))
dcpi=DiffPanel(variable=DataExp[,7], quantity=rep(35,9))
ddcpi=DiffPanel(variable=dcpi, quantity=rep(35,9))
ldebt=LagPanel(variable=DataExp[,4], quantity=rep(35,9))
# create homogenous preliminary dataset (containing "NA") after DiffPanel, LagPanel
dataPanel=cbind(y10, dy10, ly10, DataExp[,6], dopeness, diip,
DataExp[,11], ldcrisk, DataExp[,9], ddcpi, DataExp[,7])
dataPanel=data.frame(dataPanel)
names(dataPanel)=c("y10", "dy10", "ly10", "openess", "dopeness", "diip",
"iip", "ldcrisk", "crisk", "ddcpi", "cpi")
dataPanel[1:5,]
# prepare dataset and quantity for PMG or optimPMG functions using PanelNaOmit
dataPanel=PanelNaOmit(dataset=dataPanel, quantity=rep(35,9))
dataPanel$dataset[1:5,]
dataPanel$quantity

PooledMeanGroup documentation built on May 2, 2019, 12:40 p.m.