Working Paper: NBER ID: w22111
Authors: Alberto Cavallo; Roberto Rigobon
Abstract: New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both inflation measurement and some fundamental research questions in macro and international economics. In particular, we show how online prices can be used to construct daily price indexes in multiple countries and to avoid measurement biases that distort evidence of price stickiness and international relative prices. We emphasize how Big Data technologies are providing macro and international economists with opportunities to stop treating the data as “given” and to get directly involved with data collection.
Keywords: big data; inflation measurement; online prices; consumer price index
JEL Codes: E31; F3; F4
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| online price data (P22) | daily price indexes (C43) |
| online price indexes (C43) | true inflation rates (E31) |
| online prices (P22) | price stickiness (L11) |
| law of one price (D41) | correlation between nominal exchange rates and relative prices (F31) |
| online prices anticipate changes in inflation (E31) | consumer price index (E31) |