What if panel data is unbalanced?
An unbalanced panel (e.g., the second dataset above) is a dataset in which at least one panel member is not observed every period. Therefore, if an unbalanced panel contains N panel members and T periods, then the following strict inequality holds for the number of observations (n) in the dataset: n < N×T.
What does unbalanced mean Stata?
Technical note The terms balanced and unbalanced are often used to describe whether a panel dataset is missing some observations. If a dataset does not contain a time variable, then panels are considered balanced if each panel contains the same number of observations; otherwise, the panels are unbalanced.
What is Areg Stata?
areg fits a linear regression absorbing one categorical factor. areg is designed for datasets with many groups, but not a number of groups that increases with the sample size. See the xtreg, fe command in [XT] xtreg for an estimator that handles the case in which the number of groups increases with the sample size.
Is an unbalanced panel a problem?
The main concern with unbalanced panel data is the question why the data is unbalanced. If observations are missing at random then this is not a problem – for a good explanation of what “missing at random” means, have a look at this answer by Peter Flom.
Can you use fixed effects with unbalanced panel data?
As Peterson said, you can run standard fixed effects models on your entire unbalanced data and still get estimates. You could also add a time fixed effect or even use a varying coefficient model.
Why is balanced panel data important?
Balanced data is preferred over unbalanced panels, because it allows an observation of the same unit (e.g., individual, company, person, etc.) in every time period (e.g., year, month, etc.), which reduces the noise introduced by unit (individual, etc.)
What is a strongly balanced panel?
balanced if each panel contains the same number of observations; otherwise, the panels are unbalanced. When the dataset contains a time variable, panels are said to be strongly balanced if each panel contains the. same time points, weakly balanced if each panel contains the same number of observations but not the same.
What is the difference between Areg and Xtreg?
In the areg procedure, you are estimating coefficients for each of your covariates plus each dummy variable for your groups. In the xtreg, fe procedure the R2 reported is obtained by only fitting a mean deviated model where the effects of the groups (all of the dummy variables) are assumed to be fixed quantities.
What does Xtset do in Stata?
xtset manages the panel settings of a dataset. You must xtset your data before you can use the other xt commands. xtset panelvar declares the data in memory to be a panel in which the order of observations is irrelevant.