Abstract:
We use scanner data to study the dynamics of prices and quantities in a high dimensional setting. In this setting, there are large missing data problems due to sample selection. We develop a method to solve these missing data problems. Our solution is to develop a "low rank" factor model to capture the dynamics. We assume that the dynamics of high dimensional prices and consumer demand are jointly driven by a common set of low-dimensional factors. These factors evolve according to a simple autoregressive model. In addition, we model the price process using a switching model with switching between a "regular price" process and "sale price" process. We then analyse the implications for price index calculation and for demand estimation.
Presenter: Alan Crawford (UC3M)
Title: “High dimensional high frequency retail price dynamics: accounting for missing prices and quantities”
Co-authors: Lars Nesheim (CeMMAP, UCL and IFS)