Let’s now consider a simpler framework in which a developer seeks to make a profit-maximizing decision on where to construct the edge city. To address Seminar outline: Topic IV 2 the tasks below, please open the GY457_Topic_VI_STUDENT_VERSION.xlsx document. As evident from the parameters given in the file, the developer is committed to develop an edge city on a 40,000 m2 land parcel at a floor area ratio of 1.25. Their internal rate of return (a brief description) is 6% and they face a per-square meter office space construction cost of 2,500 (in an arbitrary currency). The developer considers 11 locations at different distances from the CBD. They observe the local land prices, at which they can buy the land, as well as the current employment densities. They do not observe the office rents that can be realized at those locations. You, as consultants, have been commissioned to help the developer finding the profit-maximizing location for the edge city development.
a. To predict the market rent at the considered locations, you have collected a data set containing per-square meter office rents for a large number of buildings. Along with the rent, you have obtained information on the location of those buildings relative to the CBD. Use a scatter plot to inspect the data and use regression analysis to predict the office rents at the considered location (there are many helpful introductions into simple regression analysis if you have not done it before, see e.g. for how to do it in Excel or Stata). Please carefully inspect the scatter plot to find the appropriate functional form. The data set is in the worksheet “Observed rent data”.
b. Using the imputed office rents by location, calculate for every location in the “Working sheet” the Yearly office rent per square meter of land, the net present value (NPV) of future rents per square meter of land, the construction cost per square meter of land, and the profit per square meter of land. Check the notes in the “Working sheet” for hints on how to compute the variables. At this stage, assume that the development of the edge city has no effect on the office rent at the locations. Which location would you recommend to the developer?
c. Now, assume that that the added employment that comes with the edge city generates agglomeration economies that have a positive effect on rents. Assume that at each location (each one is a spatial unit with an area of one square kilometre), there is enough land available so that the added employment does not crowd out existing employment. For each location, compute the ratio of the employment density with the edge city over the employment density without the edge city. With the help of an appropriate elasticity (check the readings and lecture notes), compute the ratio of the rent achievable with the added agglomeration effect due to the edge city over the rent without the edge city effect. Compute the yearly office rent per square meter land, the NPV of future rents per square meter, the profit per land unit, and the total profit. Which location would you now recommend to the developer?