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). 2). 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-. 04 Jan 2018, 10:35. Yes, this topic can be confusing. Microeconometrics using stata (Vol. xtreg health retired female i.wave, re cluster(id) // declare panel data structure . Before using xtregyou need to set Stata to handle panel data by using the command xtset. xtset country year Panel Data Panel data is obtained by observing the same person, ﬁrm, county, etc over several periods. College Station, TX: Stata press.' Stata provides an estimate of rho in the xtreg output. The intent is to show how the various cluster approaches relate to one another. It is not meant as a way to select a particular model or cluster approach for your data. xtreg health retired , re // + time-constant explanatory variable . I would reshape wide so each year's data is its own variable and then cluster. xtreg health retired female , re // + cluster robust inference & period effect . Stata has since changed its default setting to always compute clustered error in panel FE with the robust option. The standard regress command in Stata only allows one-way clustering. Hello Stata-listers: I am a bit puzzled by some regression results I obtained using -xtreg, re- and -regress, cluster()- on the same sample. xtset id wave // RE . 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 … This will group countries that follow similar timepaths for your 6 variables. 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 … 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. Getting around that restriction, one might be tempted to. This page was created to show various ways that Stata can analyze clustered data. If that value is anywhere north of .01, that's a good indication that you should be concerned about clustering. 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). Unlike the pooled cross sections, the observations for the same cross section unit (panel, entity, cluster) in general are dependent. Robust and cluster–robust standard errors ; Panel-corrected standard errors (PCSE) for linear cross-sectional 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). However, the bloggers make the issue a bit more complicated than it really is. Thus cluster-robust statistics that account for … Setting panel data: xtset The Stata command to run fixed/random effecst is xtreg. type: xtset country year delta: 1 unit time variable: year, 1990 to 1999 panel variable: country (strongly balanced). 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