Suppose you are a shopping mall owner, how would you design contracts with retailers? One specific question is whether you should charge retailers located near global brands, such as Nike, more. To have a data-driven answer to this question we need an estimate of cross-store spillover effects.
In this project, we use exclusive foot traffic data from a set of Chinese shopping malls to quantify spillovers. We exploit variation from within mall ad campaigns that create plausibly exogenous inflows of traffic to different areas of the mall. If say, a store is offering hot cocoa, then we can capture how much of the extra traffic to that store visits nearby stores. We can also learn whether spillovers happen to random stores or to stores that sell a similar product.
Requisite Skills and Qualifications:
With this project you will gain experience with handling large datasets and learn about the process of empirical research. At the beginning, you will help with translating Chinese advertisement data. After constructing the dataset, you will be responsible for conducting statistical analyses.
Chinese language skills and attention to details are required. Experience with Python or R is a must.
Some basic knowledge of GitHub is a plus.
Some basic understanding of Causal Inference/Econometrics is a plus.