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I'm writing a paper on investment firms and their relationship with a sustainable finance initiative. I'm using a panel dataset with 307 investors, 125 of them signed this sustainable initiative.

I would like to add in a section in which I test which variables might be driving them to sign this initiative.

I believe I should use logit regression for this, but having not used these extensively, I'm looking for some guidance.

Currently the data looks like this:

investor year activity country region strategy signatory
123 IM 2002 4.45 France europe VC 1
123 IM 2003 3.2 France europe VC 1
123 IM 2004 7.8 France europe VC 1
Aegon 2005 5.4 Netherlands europe BY 0
Aegon 2006 4.2 Netherlands europe BY 0
Aegon 2007 1.3 Netherlands europe BY 0

As you can see the signatory variable is a binary, and I would be looking to test variables such as country or region against it.

Any tips would be appreciated!

Rory

R Wd
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1 Answers1

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You can use the glm function in R. Following is an example with country and activity variables as independent variables:

# Assuming that your dataframe name is df
my_logit <- glm(signatory ~ activity + country, family = 'binomial', data=df)
# Check the output summary
summary(my_logit)
Muhammad Rasel
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