Let’s take the model to the data and reproduce figures 2.1. and 2.2 of “Cities, Agglomeration, and Spatial Equilibrium”. The focus are two cities, Chicago and Boston. These cities are chosen because both differ in how easy is to access to their city centers. Chicago is fairly easy, Boston is more complicated. Our model then implies that gradients then should reflect the differential costs to access the city centers.
So let’s begin, the first step is to get some data. To do so I’m are going to use the “tidycensus” package. This package will allow me to get data from the census website using their API. We are also going to need the help of three other packages: “sf” to handle spatial data, “dplyr” my go-to package to wrangle data, and “ggplot2” to plot my results.
require("tidycensus", quietly=TRUE) require("sf", quietly=TRUE) require("dplyr", quietly=TRUE) require("ggplot2", quietly=TRUE)In order to get access to the Census API, I need to supply a key, which can be obtained from http://api.census.gov/data/key_signup.html.
Read on for theory and a test. H/T R-bloggers