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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Simona Andreano, M., Benedetti, R., Piersimoni, F., Postiglione, P., Savio, G. (2019). Sampling and Modelling Issues Using Big Data in Now-Casting. 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_14
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