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...data? Nevertheless you should be able to follow my subsequent thoughts: # I should be able to get my (time- and sectionally) demeaned series as follows: res1<-plm(x~c+v,data=pdata_frame, effect="twoways", model="within", na.action=na.omit)) dem_yt<-pmodel.response(res) demXt<-model.matrix(res) # Given the demeaned series, I need to set the first observation(s) in each cross-section to NA in order to avoid inter-sectional links in the lagged residuals (i.e. in the MA component). #Note: Delete the first n observations per section for a MA(n) regression. For me, an MA...

...utput, references etc., although of course I trust D.B.'s opinion. For variables x,c,d,and e in object pdata_frame, I find that all sd() are reasonably similar both among the cross-sections as well as among the variables. However, I find that extracting the demeaned data from plm(), variables demXt$d and demXt$e (i.e. the demeaned variables) have sd()s that are very small compared to those of dem_yt and demXt$c (approx. by factor 1e-15). I extract the demeaned data as follows: dem_yt<-pmodel.response(res) demXt<-model.matrix(res) How is this possible? What is it that plm() does with...