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Monitoring the Spatial Correlation Among Functional Data Streams Through Moran’s Index Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Sampling and Modelling Issues Using Big Data in Now-Casting

Authors : M. Simona Andreano, Roberto Benedetti, Federica Piersimoni, Paolo Postiglione, Giovanni Savio

Published in: New Statistical Developments in Data Science

Publisher: Springer International Publishing

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Abstract

The use of Big Data and, more specifically, Google Trends data in now- and forecasting, has become common practice nowadays, even by Institutes and Organizations producing official statistics worldwide. However, the use of Big Data has many neglected implications in terms of model estimation, testing and forecasting, with a significant impact on final results and their interpretation. Using a MIDAS model with Google Trends covariates, we analyse sampling error issues and time-domain effects triggered by these digital economy new data sources.

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previous chapter Performance Comparison of Heterogeneity Measures for Count Data Models in Bayesian Perspective
next chapter Sample Design for the Integration of Population Census and Social Surveys Il Disegno Campionario per L’integrazione Del Censimento Della Popolazione e delle Indagini Sociali
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Metadata
Title
Sampling and Modelling Issues Using Big Data in Now-Casting
Authors
M. Simona Andreano
Roberto Benedetti
Federica Piersimoni
Paolo Postiglione
Giovanni Savio
Copyright Year
2019
Book
New Statistical Developments in Data Science

Print ISBN: 978-3-030-21157-8

Electronic ISBN: 978-3-030-21158-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-21158-5_14

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