R help - Apr 2014 - purtest and missing values (plm-package)

Hello R-Community,

 

I have quarterly panel-data and not surprisingly missing values, in a few
variables, which are differently distributed around the panel.

Now I want to run different unit-root tests.

 

For ADF on the pooled data set, I chose CADF-package, which can determine the
number of lags automa. by SIC and handles missing values. (I hope this is the
right one )

 

Secondly I want to run an LLC and IPS test specificially for the panel data
(Levin, Lin & Chu –test and Im, Pesaran & Shin-test ) for which I use
the purtest function, from plm-package.

But I don´t know how to apply it, if my series contains missing values ( so only
a error-message is created)

 
> purtest(data.plm,data=data.plm, test = "levinlin",exo =
"none",lags ="SIC")
Fehler in lm.fit(X, y) : NA/NaN/Inf in 'x'

Zusätzlich: Warnmeldung:

In Ops.factor(object[2:length(object)], object[1:(length(object) -  :

  - not meaningful for factors

 

So my Question is:

1.       Is there a way to handle the missing values? 

2.       Do I just omit them? And if, is there a way to integrate this by adding
an ” na.omit” into the function ?

 

 

To make it easier explaining the way of proceeding, a reproducible example could
be:

 

data("Grunfeld", package = "plm")

y <- data.frame(split(Grunfeld$inv, Grunfeld$firm))

purtest(y, pmax = 4, exo = "none", test =
"levinlin",lags=”SIC”) # works no missing data

 

# add an NA

 

data("Grunfeld", package = "plm") 

x <−data.frame(split(Grunfeldinv, Grunfeld$firm))

Grunfeldinv[2]<−NA

purtest(x, pmax = 4, exo = "none", test =
"levinlin",lags=”SIC”) # Error in lm.fit(X, x) : NA/NaN/Inf in
'x'

 

Thanks for your hints and suggestions! 

Katie

 


	[[alternative HTML version deleted]]

Because, my inbox shows a "cutted-email-version", once again:

Hello R-Community,

I have quarterly panel-data and not surprisingly missing values, in a few
variables, which are differently distributed around the panel.
Now I want to run different unit-root tests.

For ADF on the pooled data set, I chose CADF-package, which can determine the
number of lags automa. by SIC and handles missing values. (I hope this is the
right one )

Secondly I want to run an LLC and IPS test specificially for the panel data
(Levin, Lin & Chu ?test and Im, Pesaran & Shin-test ) for which I use
the purtest function, from plm-package.
But I don?t know how to apply it, if my series contains missing values ( so only
a error-message is created)
> purtest(data.plm,data=data.plm, test = "levinlin",exo =
"none",lags ="SIC")
Fehler in lm.fit(X, y) : NA/NaN/Inf in 'x'
Zus?tzlich: Warnmeldung:
In Ops.factor(object[2:length(object)], object[1:(length(object) -  :
  - not meaningful for factors

So my Question is:
1.	Is there a way to handle the missing values? 
2.	Do I just omit them? And if, is there a way to integrate this by adding an ?
na.omit? into the function ?


To make it easier explaining the way of proceeding, a reproducible example could
be:

data("Grunfeld", package = "plm")
y <- data.frame(split(Grunfeld$inv, Grunfeld$firm))
purtest(y, pmax = 4, exo = "none", test =
"levinlin",lags=?SIC?) # works no missing data

# add an NA

data("Grunfeld", package = "plm") 
x <?data.frame(split(Grunfeldinv, Grunfeld$firm))
Grunfeldinv[2]<?NA
purtest(x, pmax = 4, exo = "none", test =
"levinlin",lags=?SIC?) # Error in lm.fit(X, x) : NA/NaN/Inf in
'x'

Thanks for your hints and suggestions! 
Katie


-----Urspr?ngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im
Auftrag von Katharina Mersmann
Gesendet: Freitag, 25. April 2014 15:53
An: r-help at r-project.org
Betreff: [R] purtest and missing values (plm-package)

Hello R-Community,

 

I have quarterly panel-data and not surprisingly missing values, in a few
variables, which are differently distributed around the panel.

Now I want to run different unit-root tests.

 

For ADF on the pooled data set, I chose CADF-package, which can determine the
number of lags automa. by SIC and handles missing values. (I hope this is the
right one )

 

Secondly I want to run an LLC and IPS test specificially for the panel data
(Levin, Lin & Chu b