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

 


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