Finally an RTutor problem set about insurance! It is about time given that Ulm University is ranked worldwide as the 2nd best non-business school for research in Risk, Management and Insurance and Actuarial Sciences:
Source: The UNL Global Research Rankings of Actuarial Science and Risk Management & Insurance
I know that is some blatant advertisement (for better advertisement take a look at this video), but it is nice to be proud of one’s department.
OK, admittedly I have not yet done research in insurance myself, but this post is also not about a standard insurance research topic. As part of her Master’s thesis Aditi Malani has created a very nice interactive RTutor problem set about the article “God Insures Those Who Pay? Formal Insurance and Religious Offerings in Ghana” by Emmanuelle Auriol, Julie Lassébie, Amma Panin, Eva Raiber, and Paul Seabright (QJE, 2020). Aditi writes in her introduction:
When sudden and unforeseen financial shocks decide to give us a surprise visit, it provides a little relief to have insurance against it. But what if you are living your life, as uncertain as it is, without being formally insured against the risks that might come knocking on your door? Whom do you rely on then? God?
Or perhaps on the church as God’s representatives on earth? But does this reversely mean that some people may become less engaged with the church if they get more formal insurance? Does the experimental economics toolkit allow to test this hypothesis?
To dig deeper into these questions and at the same time learn data analysis with R in an interactive fashion, you can take a look at the RTutor problem set on shinyapps.io:
https://aditi-malani.shinyapps.io/RTutorGodInsuresThoseWhoPay
or locally install the problem set, by following the installation guide at the problem set’s Github repository:
https://github.com/aditi-malani/RTutorGodInsuresThoseWhoPay
If you want to learn more about RTutor, try out other problem sets, or create a problem set yourself, take a look at the Github page
https://github.com/skranz/RTutor
or at the documentation
https://skranz.github.io/RTutor
Published on 16 Sep 2021 •