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st: Generating summary variables in TSCS data using values across long time periods


From   "Wallace, Geoffrey P" <[email protected]>
To   "[email protected]" <[email protected]>
Subject   st: Generating summary variables in TSCS data using values across long time periods
Date   Mon, 18 Jan 2010 08:39:41 -0500

Dear all,

I have two questions, which I believe are related, and deal with generating summary variables based on longer time periods using time-series cross-sectional data.

1. I’m using the Polity IV data set which gives national democracy scores in a country-year format.

As a measure of volatility I want to generate a variable that captures the standard deviation in a country’s polity score (polity2) in a moving window over 25-year periods. E.g. For Iraq in 1990 this would be the standard deviation in polity2 for 1965-1989, etc. I also want a similar measure looking at volatility in 25-year windows using future polity scores.

I have tried variants of the –egen- command like the following

.bysort ccode (year): egen sd(polity2) 

I believe this simply gives the standard deviation in polity2 across the entire time period for each country, but I cannot figure out how to specify by moving 25-year periods.

I was successful in using the –tssmooth ma- command to create a moving average variable over similar 25-year periods, but have not found a way to generate something similar for standard deviations, or alternative measures.

2. I also want to generate a dummy variable by country-year that equal “1” if a country achieved above a particular polity2 score “x” over the previous 25-year period. Is there a way to do so with using some form of the expression 
-if polity2[_n-1]>x … polity2[_n-25]>x- 

Is there a way to avoid specifying [_n-t] 25 separate times?

Any help on either issue would be greatly appreciated.

Best, Geoff



--
Geoffrey Wallace
Assistant Professor
Department of Political Science
1657 Patterson Office Tower
University of Kentucky
Lexington, KY 40506-0027
tel. 859-257-2709
fax. 859-257-7034
email. [email protected]
web. http://www.uky.edu/~gpwa223
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