Friday, August 16, 2019
Room 438 West Hall Map
This thesis proposes a method to measure fine-grained spatial differences in prices using retail barcode scanner datasets. To avoid conflating spatial price differences with differences in consumer preferences for products sold in each area, it extends the framework proposed by Redding and Weinstein to adjust price indices for product turnover, from the temporal to the spatial context. In this extension, differences in spatial product availability are considered analogous to differences in product availability across time. It describes a method to estimate these "spatial UPI" indices, and the uncertainty associated with these estimates. It then applies this method to compare the food cost of living between different counties within the state of Michigan based on the Nielsen retail scanner database.
|Source:||Happening @ Michigan from Department of Statistics Dissertation Defenses, Department of Statistics|