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 âtest 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 â na.omitâ 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=âSICâ) # works no missing data # add an NA data("Grunfeld", package = "plm") x <âdata.frame(split(Grunfeldinv, Grunfeld$firm)) Grunfeldinv[2]<âNA purtest(x, pmax = 4, exo = "none", test = "levinlin",lags=âSICâ) # Error in lm.fit(X, x) : NA/NaN/Inf in 'x' Thanks for your hints and suggestions! Katie [[alternative HTML version deleted]]
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