.

An examination of dynamic ticket pricing

Files: Red_Sox.zip

The .zip archive contains a comma-separated data file organized by year, containing a list of all StubHub ticket orders for the Boston Red Sox. The file includes information about the characteristics of the game (e.g., opponent, time-of-day, day-of-week, etc.) and other relevant order characteristics (e.g., number of tickets in order, etc.).

We'd like you to use these data to produce your best answer to the following questions:

** How do the prices consumers pay for tickets change as the game date approaches (i.e., as the number of days between transaction date and game date declines)? How does this dynamic pattern change across years?

We'd like you not only to decide what you think is the answer but also to prepare a document arguing for that based on the evidence. You should feel free to use whatever techniques you want. The goal here is not to show off hi-tech econometrics, but rather to show us how you think about data. Sometimes something as simple as a graph can do more for an argument than all the estimators in the world. Also, you need not take the structure of data as written in stone. If there are ways you'd like to transform the variables or restructure the data, please feel free. Think of this as a small research project: you have a dataset, and you need to find the best answer you can to a real-world question. You also need to justify it to an outsider (in this case, us!).

.