EU-SILC

[Lydia Palumbo]

Hello!

I am dealing with EU-SILC dataset, which is a rotational panel, as you might know. 

I have data from 2004 to 2014. However, individuals were not observed for the same time period, since the design of the 

panel requires that they are observed only for a time span and then dropped and substituted by other units. 

My question is the following: if I implement a random effect model, could there be a problem of non random missing data, 

since people are removed from my sample because of the precise decision of not following them anymore?

Thank you and best, 

Lydia

[Jonathan Bartlett]

Hi Lydia

In this situation the missingness is by design, which is a good thing in the sense that you know how the missingness comes about. How you handle the fact the individuals were only in the cohort for a portion of the total time I think will depend on what analysis you want to run. E.g. Do you want to run an analysis on the calendar time scale across the whole cohort period? Or an analysis on the time scale where time zero is when the individual joined the cohort.

[Lydia Palumbo]

Thank you very much for your answer. I would like to do a cohort
period analysis. I thought about putting an indicator for the year of
entry, but it seems too simplistic to me.

2016-10-12 19:18 GMT+01:00 'Jonathan Bartlett' via Missing Data
<missin...@googlegroups.com>:

> Hi Lydia
>
> In this situation the missingness is by design, which is a good thing in the sense that you know how the missingness comes about. How you handle the fact the individuals were only in the cohort for a portion of the total time I think will depend on what analysis you want to run. E.g. Do you want to run an analysis on the calendar time scale across the whole cohort period? Or an analysis on the time scale where time zero is when the individual joined the cohort.
>

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