The Italian National Institute of Statistics (ISTAT) is carrying out a redesign of Consumer Price Survey (CPS). The availability of Scanner Data (SD) from retail modern distribution, provided to ISTAT by Nielsen for a large number of stores selling food and grocery, is the starting point of this innovation. Indeed, SD represent a big opportunity for improving the computation of Consumer Price Index (CPI). This work aims to study the properties of alternative aggregation formulas of the elementary price index in different sampling schemes implemented on SD. Bias and efficiency of the estimated indices are evaluated through a Monte Carlo simulation.

Sampling Schemes Using Scanner Data for the Consumer Price Index / De Vitiis, Claudia; Guandalini, Alessio; Inglese, Francesca; Terribili, Marco Dionisio. - (2019), pp. 203-217. [10.1007/978-3-030-21158-5_16].

Sampling Schemes Using Scanner Data for the Consumer Price Index

Guandalini, Alessio
Secondo
;
Terribili, Marco Dionisio
Ultimo
2019

Abstract

The Italian National Institute of Statistics (ISTAT) is carrying out a redesign of Consumer Price Survey (CPS). The availability of Scanner Data (SD) from retail modern distribution, provided to ISTAT by Nielsen for a large number of stores selling food and grocery, is the starting point of this innovation. Indeed, SD represent a big opportunity for improving the computation of Consumer Price Index (CPI). This work aims to study the properties of alternative aggregation formulas of the elementary price index in different sampling schemes implemented on SD. Bias and efficiency of the estimated indices are evaluated through a Monte Carlo simulation.
2019
New Statistical Developments in Data Science
978-3-030-21157-8
978-3-030-21158-5
Consumer price index Scanner data Sampling Fixed and dynamic approach
02 Pubblicazione su volume::02a Capitolo o Articolo
Sampling Schemes Using Scanner Data for the Consumer Price Index / De Vitiis, Claudia; Guandalini, Alessio; Inglese, Francesca; Terribili, Marco Dionisio. - (2019), pp. 203-217. [10.1007/978-3-030-21158-5_16].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1336776
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