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Dear R users, I have an unbalanced panel with an average of I=100 individuals and a total of T=1370 time intervals, i.e. T>>I. So far, I have been using the plm package. I wish to estimate a FE model like: res<-plm(x~c+v, data=pdata_frame, effect="twoways", model="within", na.action=na.omit) ?where c varies over i and t, and v represents an exogenous impact on x varying over time but not over i. I discover significant time effects comparing the above model with a plm(?,effect="individual", ?)-model (u...

...ontent-Type: text/plain; charset=UTF-8 Dear R Users, I have an unbalanced panel with (on average) approx. 100 individuals over 1370 time intervals (with individual time series of different lengths, varying between 60 and 1370 time intervals). I use the following model: res1<-plm(x~c+d+e,data=pdata_frame, effect="twoways", model="within", na.action=na.omit)) ## I have difficulty in understanding why you would want to introduce ca. 1470 incidental parameters... I'd rather go with a more parsimonious specification: a trend, AR(n) or else... I repeatedly get the following e...