Economics
HMWK12 (Paper Guidelines)
This assignment builds off of HMWK 10 and HMWK 11. The goal of this assignment is to prepare you to
do a write-up for the analysis of the data from the city you chose to explore in HMWK 11.
While there is considerable flexibility in how you carry out the write-up, I’d like you to focus your efforts
on a specific question and a target audience interested in that question. Your write-up must include at
least two graphs, each of which is well labelled and documented.
Details:
Audience: local city council members
Background: the city council for the city you chose to analyze has approached you to get advice about
which policies they should enact. Policies ranging from education and policing to nutrition and housing
are all under consideration. They are very open to creative solutions and happy to entertain any
suggestions you have. The city council is particularly persuaded by policies that can be supported with
data analysis.
Topic of the Council: the city council is concerned about the well-being of children born to lower income
parents. They want to understand what factors can help children born to low income parents escape
poverty and live well. They are concerned about children of all races, all ethnicities and genders, but
recognize that there might be disparities across these demographic categories.
Necessary Items in your Write-Up:
1. Explanatory prose consisting of at least 1,000 words
2. At least 2 well-labelled figures showing relationships from the atlas data. These figures must
also be documented with a note that explains what the variables in the figure mean, and where
you obtained them.
3. A proposal of at least one policy that the council could enact, which your data analysis suggests
might help improve the well-being of children born to low income parents. Your policy proposal
should, in some way, be supported by the data analysis you provide
Suggestions:
One way to start this project is to look at the kfr_`race’_p25 variables and see which control variables
and which other variables (incarceration, *_p75 variables, etc.) bear a strong relationship to these
variables. Then think about what explanation could account for that relationship. Then, based on that
explanation, think about a policy that might increase upward mobility.
Personal narratives can be relevant, but please keep in mind that your audience is most persuaded by
what can be shown with data.
Excellent write-ups with explore several breakdowns such as those in step 5 of HMWK 10, including but
not limited to, how different factors might affect mobility differently by race and gender.
HMWK11
This assignment builds off the work you did in HMWK 10. In fact, you will be repeating what you did in
HMWK 10 almost exactly, only using a city other than San Antonio.
First, browse the map on the Opportunity Atlas data website. Pick a city other than San Antonio, with
which you are familiar. If you grew up in the US, then I would suggest the city you grew up in. If you
grew up outside the US, I would suggest picking an American city you’ve visited. If you haven’t lived in
or visited a city in the US other than San Antonio, I would suggest picking a US city that has appeared in
the news, or even just a “famous” US city like New York or L.A. This project will be easier and more fun
if you pick a city you are familiar with, where you can picture the streets, know something about the
neighborhoods and local conditions.
Step 1: Pick a city you are familiar with.
Step 2: open the atlas.csv dataset. This is a big dataset that includes all tracts in the US.
Step 3: find the commuter zone id you chose in 1. Use the variables “cz” and “czname” to help you.
Keep only the rows where the cz var is equal to the id for the city in 1.
Step 4: repeat each graph in HMWK 10 for these new data.
https://www.opportunityatlas.org/