Hello everyone,
I currently have a problem that I don't know how to solve. To summarize my research: I investigate whether founding-CEO dismissal in VC-backed firms has an effect on firm performance. Firm performance is measured by using the runway time between the next round of financing and controlled by the revenue, total assets, and employees. My independent variable is CEO_Change_VC_Influence and my Dependent variable is FollowUpFunding_Months. I want to control this effect with the variables: revenue, total assets, and employees. For these last three variables, the annual increase/decrease is indicated in percentage terms from the years 2010 to 2018 and thus divided over 24 columns (3 variables x 8 time dimensions (2010>2011, 2011>2012 ... 2017>2018)). The problem that now arises: if for instance a CEO got dismissed in 2014, how am I able to compute the difference in revenue, total assets, and employees before and after this CEO change.
How do you suggest to run analysis here? I have added my dataset so feel free to have a look at it.
Greetings,
Vincent
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