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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bernardini, A., De Vitiis, C., Guandalini, A., Inglese, F., Terribili, M.D.: Measuring inflation through different sampling designs implemented on scanner data. Paper presented at the UNECE meeting of the group of experts, Geneve 2–4 May (2016)
Chessa, A.G., Verburg, J., Willenborg, L.: A Comparison of Price Index Methods for Scanner Data (2017)
de Haan, J., Opperdoes, E., Schut, C.M.: Item selection in the Consumer Price Index: Cut-off versus probability sampling. Surv. Methodol. 25(1), 31–41 (1999)
de Haan, J., van der Grient, H.A.: Eliminating chain drift in price indexes based on scanner data. J. Econ. 161, 36–46 (2011)
de Haan, J., Willemborg, L. and Chessa, A. G. An overview of price index methods for scanner data (2016)
De Vitiis, C., Casciano, M.C., Guandalini, A., Inglese, F., Seri, G., Terribili, M.D., Tiero, F.: Sampling design issues in the first Italian experience on scanner data. Paper presented at the Scanner Data Workshop. Rome 1–2 October (2015)
Feldmann, B.: Scanner-data-current-practice (2015). http://www.istat.it/en/files/2015/09/5-WS-Scanner-data-Rome-1-2-Oct_Feldmann-Scanner-data-current-pratice.pdf
Gábor, E., Vermeulen, P.: New evidence in elementary index bias. Working Paper, Working Paper, European Central Bank (2014)
ILO, IMF, OECD, Eurostat, United Nations, World Bank Consumer Price Index Manual: Theory and Practice. ILO Publications, Geneva (2004)
Ivancic, L., Diewert, W.E., Fox, K.J.: Scanner data, time aggregation and the construction of price indexes. J. Econ. 161(1), 24–35 (2011)
Nygaard, R.: Chain drift in a monthly chained superlative price index. Workshop on Scanner Data, Geneva, 10 May (2010)
Norberg, A.: Sampling of scanner data products offers in the Swedish CPI. Draft version 8 – Statistics. Sweden (2014)
Rosén, B.: On sampling with probability proportional to size. J. Stat. Plan. Inference 62(2), 159–191 (1997)
Sampford, M.R.: On sampling without replacement with unequal probabilities of selection. Biometrika 54(3–4), 499–513 (1967)
van der Grient, H.A., de Haan, J.: The Use of Supermarket Scanner Data in the Dutch CPI. Paper presented at the Joint ECE/ILO Workshop on Scanner Data, Eurostat (2010)
Vermeulen, B.C., Herren, H.M.: Rents in Switzerland: Sampling and Quality Adjustment. 11th Meeting - Ottawa Group - Neuchâtel 27–29 May (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
De Vitiis, C., Guandalini, A., Inglese, F., Terribili, M.D. (2019). Sampling Schemes Using Scanner Data for the Consumer Price Index. In: Petrucci, A., Racioppi, F., Verde, R. (eds) New Statistical Developments in Data Science. SIS 2017. Springer Proceedings in Mathematics & Statistics, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-030-21158-5_16
Download citation
DOI: https://doi.org/10.1007/978-3-030-21158-5_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-21157-8
Online ISBN: 978-3-030-21158-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)