Abstract: Geospatial Economic Research in Uganda

In partnership with AidData and the Economic Policy Research Center in Kampala Uganda, I will conduct geospatial research on a variety of topics. Chief among these will be analyzing new trade avenues that have sprung up between Uganda and the newly formed South Sudan. In order to conduct this analysis, ArcGIS geospatial software will be used to generate geocoded maps of trade flows. In addition, topics related to healthcare and aid interventions will be explored, including infant mortality. Geospatial comparisons will be made between health outcomes and aid interventions in the East African Region in order to identify gaps in coverage. This research will be conducted full time for 10 weeks in Kampala, Uganda.

Andean Economic Development: A Journey

I’m Nate Marshall, a junior here at W&M. For ten weeks from May to August 2015 I will be working as an unpaid intern for Awamaki, a nonprofit in Ollantaytambo, Cuzco, Peru, a rural town in the Sacred Valley. During my time there I will be applying skills I have learned in my computer science courses to help provide necessary information systems upgrades. However, I would like to go further than that. As an economics major with a particular interest in development, I want to incorporate an economic research project into my experience. That journey begins here.

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Retracing Steps – Investigating Austrian Industrial Finance, 1870 – 1913

Hello, my name is Yik Fei Ko (Yik Fei is my first name). My hometown is Hong Kong. I am a freshman studying International Relations and Economics. I am also a member of the first cohort of William and Mary – St. Andrews Joint Degree Program. My research project this summer is on the relationship between finance and industrialization in Austria between 1870 and 1913.

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Control Variables

After compiling the panel datasets, the only thing left to do is updating the control variables. Controls are things like average personal income, number of elderly persons, number of persons of a given race or gender in a county and the number of beds of a hospital. Control variables are extremely important! Remember, we want to find the effect of unemployment on the number of Medicare patient procedures. So, let’s say we find a positive relationship between them (when we’re not using controls). It could be because counties with more minorities have higher unemployment and minorities are more likely to have Medicare and go to the hospital than whites. If this is the case, unemployment actually has no effect on procedures and is just picking up the effect of race. So last week I searched through the US census and Florida websites in search of the needed control variables and now we have as many control variables for as many years as we can. All that’s left is for the 2009/2010 data to come and be cleaned, and then we’re ready for business. I can’t wait!!!


Last week we made one awesome breakthrough with the Florida inpatient data. Unfortunately, the data collectors in Florida changed how they recorded doctor ID’s in 2006, which means that we can’t can’t follow a doctor’s behavior throughout the whole time period even though they have worked for the whole period. We broke the Florida data collector’s code, and I’ve been busy this past week running checks to make sure it actually works. I ran a test on the coded vs original doctor ID to see if they are working in the same hospital and preforming the same procedure. So far it looks good!