Hi everyone, i have a question regarding my dataset and would be grateful for any help:
I have a dataset i downloaded online that gives me information about variables like Pool size, Dealvolume etc. Every observation is a different tranche that is part of a deal (a deal may contain multiple tranches). The Tranches are included at the time the deal is launched. The dataset contains every Tranches from the last 10 years. From my understanding panel data is data collected at multiple times. The problem of understanding i have is that every observation (tranche) is just collected once, at launched data. Although the dataset contains observations over the last 10 years, so i collect data over time (-> panel data) but not for the same entities, because a tranche is part of a deal that is observed when the deal launches. So looking at tranches in year 1 and year 4 they're not the same tranches, as they are part of a deal.
I hope i managed to explain what i mean. I have problems to distinguish if it's a panel data or a pooled cross sectional data or maybe something else?
Help is really much appreciated. Kind regards.
Hi Nasim,
Panel data (or longitudinal data) is a combination of both time series data and cross-sectional data. It looks at how the subjects (firms, individuals, etc.) change over a time series.
If I correctly understand, the unit of analysis (subject) is the tranche in your research. But, you have only one observation per each tranche. Consequently, you do not have panel data.
If you had some historical observations (t1, t2, t4…) for your unit of analysis (SAME tranche), you would create an unbalanced panel dataset.
Hi Aspotolos, thanks for your clarification. Yes you’re right I have one observation per tranche and I have every tranches of the last 10 years. That’s why I assume I’ve a pooled cross sectional dataset?
Can you confirm this or am I missing something?
Thank you very much
Basically, cross-sectional is a data which is collected from all the subjects at the same time. Here, you have observations from different time periods. However, I think that you can run your models considering that you have cross-sectional analysis.
Further, I would try to run the models for each year and then compare the results for possible differences...