Data and Code for: Large Shocks Travel Fast

Principal Investigator(s): View help for Principal Investigator(s) Alberto Cavallo, Harvard University. Harvard Business School. Division of Research; Francesco Lippi, Luiss University and EIEF; Ken Miyahara, University of Chicago. Social Sciences Division

Version: View help for Version V1

Name	File Type	Size	Last Modified
CODE			04/13/2024 07:14:PM
DATA			04/13/2024 07:24:PM
FIGURES			04/13/2024 07:24:PM
TABLES			04/13/2024 07:24:PM
TEMP			04/13/2024 07:14:PM
README.pdf	application/pdf	147.1 KB	09/24/2024 07:38:AM
main.m	text/x-matlab	18.8 KB	04/13/2024 03:14:PM
re_main.do	text/plain	1.1 KB	04/13/2024 03:14:PM

Project Description

Summary:

We document a sizeable increase in the frequency of price adjustments following the large energy shocks of 2022. We use a tractable New Keynesian model, calibrated to the pre-shock data, to interpret such a pattern. The calibration highlights the state-dependence of firms' decisions: prices are adjusted rapidly when markups are misaligned. In the model, a large cost shock triggers a swift increase in the frequency of price adjustments, causing a rapid pass-through from costs to prices. Time-dependent models, as the Calvo model, miss this frequency response, failing to capture the sudden inflation surge after a large shock.

Scope of Project

Subject Terms: Inflation; Prices

JEL Classification:
E50 Monetary Policy, Central Banking, and the Supply of Money and Credit: General

Geographic Coverage: France, Germany, Italy, Netherlands, Spain, United Kingdom, United States of America

Universe:

Price changes of large retailers' online stores in France, Germany, Italy, Netherlands, Spain, United Kingdom and the United States of America during 2019 and mid 2023

Data Type(s): observational data

Methodology

Data Source:

PriceStats (2023). PriceStats Microdata. PriceStats, https://www.pricestats.com (accessed August 2023).

Unit(s) of Observation: product id, price change, date, country

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Published Versions

V1 [2024-10-23]

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DDI 2.5

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