In this project the student chooses some economic variable that varies across locations in the US from www.nhgis.org, e.g., average income by county. They then use statistical software (R, Python, Stata, or others) to plot this variable on a map of the US. In addition, they write up to 400 words on a topic inspired by this map. For example, if you show average income you could write about income inequality across space and some of the reasons for income inequality across space that we have learnt about or policy attempts to alleviate it. Students must hand in a pdf with the map and write up and their code that constructs the map.
Step-by-step Guide:
1. Go to www.nhgis.org and choose a year, variable, and spatial resolution you find
interesting.
2. Write down your motivation for the variable, year, and spatial resolution. See the
example proposal on Canvas for how to do that.
3. Download the data from nhgis.org, describe it, and compute summary statistics.
The final mapping project needs to have the following ingredients:
1. About 200 words that explain which variable you choose and why. We are looking for evidence that you thought about what may be interesting to look at and can explain your reasoning well. A bad motivation: “I find wages interesting and so I decided to graph wages across counties.” A great motivation “I noticed that more rural areas in the US seem to have lower incomes. I read some articles about rural poverty that suggest one of the reasons is the lack of employers in those regions. So, I choose to look at the
number of establishments per capita in each county.”
2. A description of your variable and the data you use as well as some summary statistics of it (this part is basically what you submitted as mapping project proposal).
3.. About 200 words describing what you see on the map and how it relates to your motivation. A bad description: “Wages differ widely across counties”. A great description: “There are less establishments per capita in the American heartland than on the urbanized coasts. […] . Overall, my findings confirm what I read in articles: lack of employment opportunities could be one of the reasons why rural regions tend to have lower wages.”
