Hello David. Usually I'd ask for a reproducible example (see the posting guide), but as I routinely check my results against Stata, this time I think I know what happens already.
There are two issues here: one is cluster-robust covariance estimation, which in Stata is done through 'vce(cluster <groupvar>)' (or 'vce(robust)') and you correctly performed in R/plm by specifying 'method="arellano"' in vcovHC; the second is small sample correction, which is where R/plm and Stata differ slightly. Stata: Stata's help is opaque in this respect, or I am not smart enough to read it. Cameron, Gelbach and Miller (2006), "Robust inference with multi-way clustering" (http://www.nber.org/papers/t0327) on page 8 state it weights the residuals by sqrt(G/(G-1)*(N-1)/(N-K)) where G is the number of clusters and N the number of obs. in each. plm: In 'plm' the standard HC0-HC4 small sample corrections from the non-clustering literature are used instead: see a survey in Zeileis (2004) "Econometric Computing with HC and HAC Covariance Matrix Estimators" here http://www.jstatsoft.org/v11/i10/ so that re: your question, 1) there is currently in R/plm no _exact_ counterpart to the small-sample correction used in Stata's xtreg under the option 'vce(cluster <groupvar>)'. 2) HC1 is actually the closest cousin, weighing obs. by a function of sample size (while in HC0 weights are all =1 and from HC2 on they are based on the hat matrix), yet this function is a different one: GN/(GN-K) instead of G(N-1)/((G-1)/(N-K)) I have recently been working on a more general version of vcovHC including this stuff, should be out "soon". In the meantime, if I get around to do it, I'll send you a quick hack of vcovHC doing the correction the Stata way: but I can't promise :^) Best, Giovanni Giovanni Millo, PhD Research Dept., Assicurazioni Generali SpA Via Machiavelli 4, 34132 Trieste (Italy) tel. +39 040 671184 fax +39 040 671160 ######################## original message ############################# Message: 49 Date: Mon, 12 Mar 2012 00:55:46 -0400 From: "David A. Kim" <david_...@hms.harvard.edu> To: r-help@r-project.org Subject: [R] Replicating Stata's xtreg clustered SEs in R Message-ID: <CAC=kL6L34JC3bPq=praeputzjkeo2ywvavevljkb_vka7v6...@mail.gmail.com> Content-Type: text/plain; charset=ISO-8859-1 I'm trying to replicate a time-series cross-sectional analysis (countries over years) with SEs clustered by country. ?The original analysis was done in Stata 10 with: xtreg [DV] [IVs] fe cluster(country). Using plm() in R (cran.r-project.org/web/packages/plm/index.html), I've replicated the coefficients. I sought to estimate country-clustered SEs with vcovHC(), and tried a variety of options, but couldn't exactly replicate the published (i.e., Stata 10's) SEs. In R, vcovHC(x, method="arellano", type="HC1", cluster="group") came closest to Stata's SEs (differing at the 3rd decimal place or so). Does anyone happen to know what method cluster() for Stata's xtreg uses to calculate clustered SEs for panel data, and/or how this could be implemented equivalently in R? ?Any help would be much appreciated. Many thanks in advance, David ######################## end original message ############################# Ai sensi del D.Lgs. 196/2003 si precisa che le informazi...{{dropped:12}} ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
