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TLDR: I present a linear model for comparing the ease of operating a philanthropic organization in different countries. Make a copy and adjust the weights to your needs.

I am a researcher at the Center for Exploratory Altruism Research (CEARCH), but I created this tool in my own time as a personal project.

Why use it? Deciding which country to operate a charity in depends on lots of factors, some of which are fairly universal: the costs of operating, the availability of talent, and the risks of crime and corruption. This tool provides a quick way of assessing countries on these factors.

It won't be much use with more cause-specific factors like the global distribution of the problem you are trying to solve, your personal experience, or where your intervention is proven to work.

How to use it? Open the spreadsheet, make a copy and start experimenting! Some key information:

  • Lower scores are better. Each indicator is between 0 and 1
  • The total score is calculated by multiplying each indicator in the row by the relevant weight at the top of the column. You should change the weights according to your needs
  • If you find the scaling of the indicators too subjective, use the "ranking" version on the second tab
  • The "intervention effectiveness" indicators are proxies for how easy it is to help people (by tackling poverty, improving health) in the country. I leave these weights at zero by default.

What are the limitations?

  • The indicators are derived from hard data, but most of them are subjectively scaled
  • The hard data can be quite crap: the education data ranks Singapore's education level alongside Kyrgyzstan and Bulgaria.
  • The model provides very limited information on health/welfare outcomes in each country: if you are starting a malaria charity, you will need to find extra data on the incidence of malaria!
  • The weights are subjective
  • Some countries are missing (missing countries with population above 2 million are: Qatar, Eritrea, Kuwait, Palestine, Oman, Singapore, Libya, Hong Kong, Cuba, Cambodia, North Korea, Saudi Arabia)

Could this be better? Let me know if you think the tool could be upgraded. Double credit if you can link to a data source that could be added.

Some trends I noticed: In the comments I'll add some of my findings from playing around with the tool for an hour or so.




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Some quick observations:

  • Eastern Europe comes out well when economy, workforce and law are given equal weighting. They are helped by the scaling on the GBP and income indicators - in the “rankings” version, Western & Northern European start to compete
  • India and Philippines look better as the emphasis on economy increases
  • Weighting only on economy and law (cheap, stable countries) gives a top 5 of India, Rwanda, Georgia, Indonesia, Uzbekistan
  • With a double weighting on workforce, the top 5 are New Zealand, Australia, US, UK, Georgia
  • Georgia comes out looking surprisingly good. It appears to have flukey scores on education and crime.
  • I did some top 10 rankings with different ratings
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