Only Time Fixed Effects for Cross-Sectional Data

Hi Talkstats-Community. I have been browsing around but couldnt find an answer to my problem. Hopefully you might be able to help me on this.

I have a dataset with funds that were launched in the last 40 years and the final performance that they achieved until they were liquidated. This means I have their latest performance as of today (most were liquidated anyway, the others will be ignored), which means 1 measure per fund. I am going to analyze the performance persistence of the fund managers responsible for the funds.

From what I see this is a cross-sectional dataset (only 1 performance measurement per fund) but with funds that were started in different years. As I am only going to analyze US funds (no industry differentiation) I dont think I would need Entity fixed effects/dummies for the fundmanagers or location. I would still need Year fixed effects/dummies though because they were running over different periods of time and I would therefore like to differentiate by launch year.

My problem is:
-Am I right about this being cross-sectional data or is this an unbalanced panel?
-Would applying the year dummy make this a fixed effects model?
-As the fixed effects model seems to be usually applied to panel data it seems there is not a possibility to just run yearly fixed effects but also entity fixed effects are needed. I found something on another thread:

"The unobserved effects model is modeled as: y=Xb+u where u=c(i)+a(t)+v(it) . A one-way error model assumes a(t)=0 while a two-way error allows for a∈ℝ"

If the one-way model only considers entity effects it wouldnt be applicable as I dont need entity differentiation. Is there a way of having a one-way model that only considers Year Fixed Effects/Dummies, without applying any fixed entity effects?

Thanks a lot in advance


Active Member
This is an unbalanced panel. You are allowed to use fixed effects for both entities and years. However, such "saturated" model is unlikely to be accurate. I would not be surprised if a model with

1) random intercept for each entity (random effect),
2) dummy variables for each year except for the reference one (fixed effect)

would be a good place to start. Many software packages have this implemented, including Stata and R (see the links).
Last edited: