Before and After "Event Study" with Panel Data

#1
I'm currently writing my undergrad thesis. The topic i was given is "Political interest and participation before and after the german refugee crisis. An empirical investigation using mico-data from Germany".
Before my thesis, I wrote a paper about The Effect of Income on Political Participation using cross-sectional data for 2015. Now I want to write a new paper and build upon this by comparing two time periods using Panel Data and not only focus on income but all key determinants. I conducted a binary logistic regression with interest and participation as two separate dependent variables.
My starting question is: Does this require my to evaluate the impact of the crisis itself or basically just compare the key determinants of interest/participation before and after the crisis ? Would evaluating the impact (with DiD for example) be a whole different topic and therefore miss the scope of my thesis?
My professor explicitly told me to only use Data from before and after the crisis year.
I have Data for german individuals for the year 2013 and 2017. (before and after the crisis). The actual crisis year was in 2015. I do also have data for that year, but as i mentioned i shall only use before and after the event in my analysis.
What would be some appropriate steps/analysis to conduct in my case ? I have to write about 25 pages, so i'm afraid simply comparing the regressions before and after would not be enough ?
How would I go about this ? I have never worked with Panel Data and read about DID / fixed and random effects models but i'm not sure which method would be appropriate, and how to treat the "Event" of the crisis itself.
 
#2
I wanted to add my idea that I had so far:
The main crisis in 2015 only started after June 2015, and the individuals in my sample were interviewed randamoly throughout the year 2015. 75% of individuals were interviewed in the first half of 2015 and the remaining 25% in the second half.
I thought of using the people who were interviewed during the peak of the crisis (2nd half of 2015) as a treatment group and the individuals interviewed during the first half of 2015 as control group. Then, i also have data for 2017 where both groups were not treated.
My problem is that by doing this, I would use data from the crisis year itself...