The UN has a convention against corruption (UNCAC) that has been signed by some 140 countries and ratified by most (link).
Transparency International publishes an annual report on corruption. They have data for most countries for the period 2000-2010, each country is given a score between zero and ten where ten is best (lowest level of corruption). There is usually a slight trend in the corruption score, indicating that there is some inertia in the level of corruption (link).
I want to test whether ratifying the convention has any positive effect on the level of corruption in the country.
My initial idea is to calculate the mean level of corruption 3 years before and after signing the treaty and using a students paired t-test to see if latter mean is significantly larger than the former.
Another approach, that I would know less about, is to use some kind of event model where dummy variables are used for the years after the convention is ratified.
What are your thoughts on this? Would the first approach work, is there anything I have overlooked? All feedback is appreciated.
I should note that this is a minor part of a course term paper. We weren't supposed to do anything quantitative, just a write-up on a topic of our choice. However I want to take a quick look at the statistics since data is readily available and I prefer to look at numbers if possible. Hence, I don't need the ideal PhD-level statistical model, just something quick and simple.