The use of Big Data and, more specifically, Google Trends data in nowand 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.
Sampling and modelling issues using big data in now-casting
Benedetti R;Piersimoni F;Postiglione P;
2019-01-01
Abstract
The use of Big Data and, more specifically, Google Trends data in nowand 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.File in questo prodotto:
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-Andreano, Benedetti, Piersimoni, Postiglione, Savio - Springer (2019).pdf
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