Difference between two slopes

I have a dataset with yearly levels of corruption in a number of countries, as well as whether they changed their government that year.

year, corruption, change of president
2001, 5, 0
2002, 7, 1
2003, 8, 0
etc.


I want to test whether corruption is affected by a change in power (defined as the election of a new president who isn't part of the same political party as the previous one).

The idea is to either look at the slope of corruption/year for the two years leading into the election, and the two years after, e.g. $t-2$, $t-1$ and $t$ for the before slope.

The other idea is to look at the average level of corruption three years before and after.

The rate might make more sense since there are more things that affect corruption and different countries may be on different trajectories. However, there could also be some benefit to just looking at average levels three years before and after.

Any thoughts on which one I should look at, and also how to go about measuring this?

• @Alexander, are you interested in the change in the level of corruption or are you interested in detecting a change in the rate of increase or decrease of corruption? They're quite different questions. – cardinal Feb 13 '11 at 16:06
• @cardinal The rate, thanks for asking. I should have been more clear on that. – sandstrom Feb 13 '11 at 21:08
• @Alexander, that seems unintuitive on the surface---at least to me. Is there reason to believe that levels of corruption generally trend rather than stay constant at some level? Just curious, as I have no domain knowledge there at all. :) – cardinal Feb 13 '11 at 21:15
• Corruption is an area where there is little data, since it's hard to measure. You may be right, in that there isn't any good reason to think it's trending. However, changes could be caused by things other change a new president, though that isn't the same as trending I guess. Also, I've edited the question a bit, since my first comment. I realized I'm not sure if it's best to look at the rate or the change. – sandstrom Feb 13 '11 at 21:22
• @Alexander, interesting. I can imagine it's not an easy thing to measure. My guess is that the more corrupt, and less transparent, the government, the harder a precise measurement becomes. You should also be careful of trying to conclude causality as well, as, e.g., the current situation in Egypt could end up demonstrating. – cardinal Feb 13 '11 at 21:25