Prices in Space and Time
This proposal aims to use price data for the universe of goods that have barcodes or are available online to answer three main questions: How do goods prices and product variety vary across space? What are the problems with using online prices as a substitute for offline prices to measure inflation? How do prices and quantities respond to high frequency macroeconomic shocks? In order to answer these questions, this project seeks to measure exact price indexes for goods across cities. This project is the first endeavor to investigate the sources of differences between online, offline, and BLS price indexes and to explore how daily price and consumption data respond to macroeconomic shocks.
The project will make use of several datasets. The first is ACNielsen Homescan data for the US. The second is Nikkei-POS data and ACNielsen Scantrak data covering retail sales at the barcode level for Japan and a number of foreign countries. The third database that the project will use has price and click-through information for large number retail products. Jointly, this is vastly more data than has ever been used by any economist or statistical agency. This will enable to construct daily price and demand information for millions of products in each country and compare it to data on offline sales of the same products.
The project aims to make breakthroughs in a number of dimensions. First, for academic economists, the proposed research provides the first test of whether Paul R. Krugman?s proposed mechanism that underlies his Nobel Prize winning theory of New Economic Geography is correct. Krugman argues that larger markets have greater product variety and should have lower price indexes for tradable goods. A major problem with existing cross-city measures of prices is that they do not compare identical goods. Hence, it is not possible to know whether, whether observed higher goods prices in cities are due to wealthier urban residents consuming higher quality items or due to prices of identical items. More generally, the project aims to demonstrate how barcode and online real estate data can be used to measure cost of living across locations.