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Updating CPI Weights Through Compositional VAR Forecasts: An Application to the Italian Index
- Source :
- Springer Proceedings in Mathematics & Statistics ISBN: 9783319739052
- Publication Year :
- 2018
- Publisher :
- Springer International Publishing, 2018.
-
Abstract
- Worldwide, monthly CPIs are mostly calculated as weighted averages of price relatives with fixed base weights. The main source of estimation of CPI weights are National Accounts, whose complexity in terms of data collection, estimation of aggregates and validation procedures leads to several months of delay in the release of the figures. This ends up in a non completely consistent Laspeyres formula since the weights do not refer to the same period as the base prices do, being older by one year and then corrected by the elapsed inflation. In this paper we propose to forecast CPI weights via a compositional VAR model, to obtain more updated weights and, consequently, a more updated measure of inflation through CPIs.
- Subjects :
- Laspeyres formula
Inflation
Estimation
Measure (data warehouse)
CPIs, Laspeyres formula, Compositional Data Analysis, CVAR
Data collection
Index (economics)
media_common.quotation_subject
National accounts
Compositional Data Analysis
Vector autoregression
CPIs
SECS-S/03 - STATISTICA ECONOMICA
CVAR
Settore SECS-S/03 - Statistica Economica
Statistics
Weighted arithmetic mean
Mathematics
media_common
Subjects
Details
- ISBN :
- 978-3-319-73905-2
- ISBNs :
- 9783319739052
- Database :
- OpenAIRE
- Journal :
- Springer Proceedings in Mathematics & Statistics ISBN: 9783319739052
- Accession number :
- edsair.doi.dedup.....be4853c48f010daa438eadfdc32b1bfa
- Full Text :
- https://doi.org/10.1007/978-3-319-73906-9_15