Dear all,

I am analysing the impacts of dung beetles (treatment) on livestock productivity (outcome) using Difference-in-Differences. I have panel data from 1960 to 1980, and my geographical units are Local Government Areas (LGAs). My sample size is 94 LGAs. I have five treatments (five dung beetle species) with presence/absence and abundance (treatment intensity). However, each species was introduced at a different year into the LGAs, spreading over time. So I have multiple time periods, e.g. in 1974, species 1 was present in an LGA, then in 1978, species 2 arrived into the same LGA. So while some LGAs might have the five species at some point in time, others will only have one species or none.

The problems/questions are:
  1. When I look at presence/absence of all species together (dummy_general), there are very few control areas (<10 LGAs). So, I am unsure what is the best way to deal when I have a low number of control areas - at some point, most LGAs had at least one beetle species even if in low numbers. In this case, would be better to look at treatment intensity instead? Or even combine dummy with treatment intensity (abundance)? If so, would you be able to help me with the code to include both dummy + treatment intensity?
Currently, my code is very simple:

xtdidregress(livestock_productivity) (dummy_general), group(lga_id) time (year)

xtdidregress(livestock_productivity) (abundance, continuous), group(lga_id) time (year)


2. What is the best way to deal with the parallel trend assumption when there are multiple periods and multiple treatments?

Here is a sample of my data.

[ATTACH=CONFIG]temp_24297_1633598381923_800[/ATTACH] Thanks a lot for your help!