Hello,
I am currently writing a thesis on the performance of mutual in general. I have collected mutual funds from various countries in Europe, and I have a question relating to one of my sub-analyses. I am hoping to do a regression to see if there are any country-specific factors that affects my dependent variable, which is a HmL variable (the difference in performance) between highly ESG rated mutual funds and low ESG rated mutual funds.
To clarify, my dataset includes a time period of four years, equal to 48 months, and it additionally includes 11 countries, which makes my dataset a paneldata. So in total, I have 48 months of HmL observations for country 1, 48 months of HmL observations for country 2, etc. etc. Furthermore, I have country factors in my dataset such as GDP per capita, AuM, market share, etc.
I am unsure how to perform the best regression on this paneldata-set. I am not interested in any time-effects, but rather country-effects. I was contemplating using a fixed effects model, or else including dummy variables for each country and when running the whole dataset, then excluding one of the 11 dummies to be able to interpret my results.
My supervisor is not very good at guiding me through this, so I was hoping someone in here could help me with this problem.
I look forward to receiving some feedback!
Best,
Kamilla
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