Egypt’s military and constitution
Posted: February 12, 2011 Filed under: Research | Tags: democracy, egypt, predictions, regime stability Leave a comment »
Exercise Bright Star 2009
In 2003 we invaded Iraq with the hope that people would cheer in the streets. They didn’t. We occupied the country anyways and our presences was and generally is hated by the people.
Starting with the protests on National Police Day, January 25th, 2011, the Egyptian people went to the streets, largely peacefully, and removed Mubarak from power. Now the Egyptian military, hesitant, will have to get involved in running the country. But how many of Egypt’s last leaders have come from the military? Nasser, Sadat, Mubarak, … Read the rest of this entry »
Iraq counter-IED
Posted: February 8, 2011 Filed under: Iraq | Tags: counter-IED, Iraq, officer Leave a comment »
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A long time ago, in a place far away, I wrote this (pdf). Random thoughts on counter-IED in northern Iraq, and gripes about living there.
Not knowing, I was on my way to death from cancer at the time. Maybe that’s why I wasn’t positive.
In retrospect I have to also admit even more how much more difficult the combat arms soldiers and officers have it. My life was plush in comparison.
Split Population Logit
Posted: February 3, 2011 Filed under: Data and code, Research | Tags: code, Infidelity, MLE, split population logit, Stata Leave a comment »Download ado files and code for predicted probabilities/first differences.
In many circumstances political scientists study binary dependent variables that have been measured with bias. For example, in surveys the strategic interests of actors can lead them to misrepresent an attitude or behavior to the surveyor in a non-random fashion. Data on terror or torture that are coded using media reports likely suffer from a similar bias related to factors such as freedom of the press in a country.
We, Jacqueline DeMeritt, Wonjae Hwang, Will Moore, and Andy Beger, have adapted and implemented a split population logit model in Stata to deal with those issues.
To give you an idea of what this new model allows one to do, consider the issue of self-reported infidelity between romantic partners. Using survey data, the reported rate of infidelity is about 13% of the sample. Yet common sense would suggest that this rate be higher, at least due to social desirability bias that would lead respondents who did in fact cheat lie about it to avoid the negative stigma. The split population logit model allows us to separate respondents’ rates of honesty and infidelity separately, as shown in the table excerpt from our paper. It shows for example that 41% of the sample likely cheated on their partner, but also that around three-quarters chose to lie about it when surveyed. Quite a difference from the 13% reported in the observed data.
The split population logit is implemented in Stata using these ado files. Here are also do files that calculate first differences and predicted probabilities.
Here are replication files for the simulations we used to evaluate our estimator and replication files for the infidelity example. The simulations were run through Florida State University High Performance Computing.
Paper to follow in a few weeks.
