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I have a dataset with yearly levels of corruption in a number of countries. year, corruption 2001, 5 2002, 7 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).

My take at this is to look at the slope in the corruption measure (∂corruption / ∂year) two years before and after the new president takes office. So any change change in slope after the new president (good or bad) is treated as a change. It's likely that some presidents will increase corruption, others reduce it and some will have no impact.

Any thoughts on a good statistical method to test this?

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Your question may have a better change to be answered here: stats.stackexchange.com –  eat Feb 13 '11 at 15:28
    
Thanks for the suggestion, will repost it there. Don't have enough points to move the question. –  user7033 Feb 13 '11 at 15:58
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