stata panel cluster

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-. 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). 04 Jan 2018, 10:35. 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 … xtset id wave // RE . xtset country year 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. 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). 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 … 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). In Stata: vce(cluster clustvar).Whereclustvar is a variable that identifies the groups in which onobservables are allowed to correlate. Stata provides an estimate of rho in the xtreg output. Thus cluster-robust statistics that account for … I would reshape wide so each year's data is its own variable and then cluster. 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 . College Station, TX: Stata press.' Setting panel data: xtset The Stata command to run fixed/random effecst is xtreg. xtreg health retired female i.wave, re cluster(id) Getting around that restriction, one might be tempted to. // declare panel data structure . type: xtset country year delta: 1 unit time variable: year, 1990 to 1999 panel variable: country (strongly balanced). 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 that value is anywhere north of .01, that's a good indication that you should be concerned about clustering. Robust and cluster–robust standard errors ; Panel-corrected standard errors (PCSE) for linear cross-sectional models. Hello Stata-listers: I am a bit puzzled by some regression results I obtained using -xtreg, re- and -regress, cluster()- on the same sample. The standard regress command in Stata only allows one-way clustering. However, the bloggers make the issue a bit more complicated than it really is. Unlike the pooled cross sections, the observations for the same cross section unit (panel, entity, cluster) in general are dependent. 2). Create a group identifier for the interaction of your two levels of clustering; Run regress and cluster by the newly created group identifier Before using xtregyou need to set Stata to handle panel data by using the command xtset. Stata has since changed its default setting to always compute clustered error in panel FE with the robust option. This page was created to show various ways that Stata can analyze clustered data. The intent is to show how the various cluster approaches relate to one another. Yes, this topic can be confusing. Microeconometrics using stata (Vol. 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.

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