TL;DR
This paper develops a COVID-19-specific inflation measure for Israel using credit card data to account for changing consumption patterns, revealing that inflation biases due to lockdowns were small and temporary.
Contribution
It introduces a novel COVID-19-adjusted inflation measure based on credit card data, improving inflation accuracy during the pandemic in Israel.
Findings
Differences between adjusted and official inflation were temporary.
Housing and transportation contributed most to inflation changes.
Inflation bias from lockdowns was small and transitory.
Abstract
Significant shifts in the composition of consumer spending as a result of the COVID-19 crisis can complicate the interpretation of official inflation data, which are calculated by the Central Bureau of Statistics (CBS) based on a fixed basket of goods. We focus on Israel as a country that experienced three lockdowns, additional restrictions that significantly changed consumer behavior, and a successful vaccination campaign that has led to the lifting of most of these restrictions. We use credit card spending data to construct a consumption basket of goods representing the composition of household consumption during the COVID-19 period. We use this synthetic COVID-19 basket to calculate the adjusted inflation rate that should prevail during the pandemic period. We find that the differences between COVID-19-adjusted and CBS (unadjusted) inflation measures are transitory. Only the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsFocus
