RERs shock adjustment is much faster than previously recorded ➜ months, not years
micro data necessary to compare relative price levels
Tradable, perfectly matched goods
Deviations of RER from normal levels increase pressure to adujust either Relative Prices or E
Adjustment margin and speeds vary by country
Argentina, Chaina, Australia ➜ mostly prices
Brazil, South Africa, UK ➜ mostly E
Motivation
Motivation
Motivation
Online Data and the Billion Prices Project
Academic Project at Mit to collect data from retailers that post prices online.
Started in 2008, joint with Roberto Rigobon (MIT)
Objective: inflation measurement and macro/international research
We collect daily data from hundreds of large retailers, for all goods sold, in 50 counteries.
How does Data Scraping work
Every day, our software downloada a public webpage, analyses its HTML code, extract price data, and stores it in a database
Alternatinve Data Sources for PPPs
Are Online Price Indices match CPIs
Our Online Price Indices match CPIs ➜ implies price change are similar
But for PPP comparisons, price levels are key.
Are Price Levels Different?
Cavallo (2015) ➜ simultaneous random sampling of online and offline prices using barcode-scanning app and crowdsourced workers
Are Price Levels Different?
Cavallo (2015) ➜ simultaneous random sampling of online and offline prices using barcode-scanning app and crowdsourced workers
PPP Series with Online Data
Methodology
A Country-level RER For tradable goods
Methodology
Methodology
Methodology
Methodology
Methodology
Methodology
Aggregate Results
Aggregate Results
Aggregate Results
Most RERs appear to fluctuate around certain levels (relative PPP)
Are these levels reasonable
Comparison to ICP
Rates of Convergence and Half-lives of RERs Shocks
There is much faster mean reversion in these RERs than in the literature
Why faster adjustment?
Micro date more volatile ➜ control for sale events, stockouts
Only tradable goods
Identical Goods across country ➜ perfect matching
Co-movement in Relative prices and E
Deviation of RER from normal level increase pressure to adjust
Adjustment may come through relative prices or the exchange rate
Magnitude persistence of each shock could matter
Implies that E co-moves with Pus/PLc the PPP exchange rate
Argentina
Brazil
UK
Australia
China
South Africa
A Vector Error Correction Model
Error Correction Model
Extension
We can further:
 Restrict the analysis to periods when the deviation is big (RERs over a given threshold)
Speeds of adjustment increase
Distinguish between devation in one sector/product vs deviation multiple sectors/products
Single-sector Deviation (eg gas prices) tend to be corrected via prices, while multi-sector deviations leads to mecro adjustments via the nominal exchange rate
Conclusions
RERs shock adjustment is much faster than previously recorded months, not years
Micro-date necessary to compare relative price levels
Tradable perfectly matched goods
Deviation of RER from normal levels increase pressure to adjust either relative price or E