If it is -xtreg, fe-, then the non-cluster robust VCE is not available, and if you specify -vce (robust)-, Stata automatically uses -vce (cluster ID)- instead (assuming ID is the panel … Robust and cluster–robust standard errors ; Panel-corrected standard errors (PCSE) for linear cross-sectional models. However, the bloggers make the issue a bit more complicated than it really is. Microeconometrics using stata (Vol. The linear model examples use clustered school data on IQ and language ability, and longitudinal state-level data on Aid to Families with Dependent Children (AFDC). Unlike the pooled cross sections, the observations for the same cross section unit (panel, entity, cluster) in general are dependent. In selecting a method to be used in analyzing clustered data the user must think carefully about the nature of their data and the assumptions underlying each of the … Stata has since changed its default setting to always compute clustered error in panel FE with the robust option. Stata provides an estimate of rho in the xtreg output. The intent is to show how the various cluster approaches relate to one another. type: xtset country year delta: 1 unit time variable: year, 1990 to 1999 panel variable: country (strongly balanced). Setting panel data: xtset The Stata command to run fixed/random effecst is xtreg. This page was created to show various ways that Stata can analyze clustered data. Getting around that restriction, one might be tempted to. xtreg health retired , re // + time-constant explanatory variable . Yes, this topic can be confusing. The standard regress command in Stata only allows one-way clustering. // declare panel data structure . Before using xtregyou need to set Stata to handle panel data by using the command xtset. Models for Clustered and Panel Data We will illustrate the analysis of clustered or panel data using three examples, two dealing with linear models and with with logits models. Rho is the intraclass correlation coefficient, which tells you the percent of variance in the dependent variable that is at the higher level of the data hieracrchy (here the individual). xtreg health retired female i.wave, re cluster(id) xtset country year If that value is anywhere north of .01, that's a good indication that you should be concerned about clustering. 04 Jan 2018, 10:35. xtset id wave // RE . In Stata: vce(cluster clustvar).Whereclustvar is a variable that identifies the groups in which onobservables are allowed to correlate. Thus cluster-robust statistics that account for … This will group countries that follow similar timepaths for your 6 variables. College Station, TX: Stata press.' You don't say what kind of panel regression you are doing, though since you are concerned about heteroscedasticity and autocorrelation, I'll guess you're running -xtreg-. 2). It is not meant as a way to select a particular model or cluster approach for your data. I would reshape wide so each year's data is its own variable and then cluster. There have been several posts about computing cluster-robust standard errors in R equivalently to how Stata does it, for example (here, here and here). Create a group identifier for the interaction of your two levels of clustering; Run regress and cluster by the newly created group identifier Hello Stata-listers: I am a bit puzzled by some regression results I obtained using -xtreg, re- and -regress, cluster()- on the same sample. xtreg health retired female , re // + cluster robust inference & period effect . Panel Data Panel data is obtained by observing the same person, firm, county, etc over several periods. Try something like this in Stata: reshape wide var@1 var@2 var@3 var@4 var@5 var@6, i (country) j (year); cluster … Onobservables are stata panel cluster to correlate anywhere north of.01, that 's good. A way to select a particular model or cluster approach for your 6 variables then... 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