Abstract
Central banks use structured data (micro and macro) to monitor and forecast economic activity. Recent technological developments have unveiled the potential of exploiting new sources of data to enhance the economic and statistical analyses of central banks (CBs). These sources are typically more granular and available at a higher frequency than traditional ones and cover structured (e.g., credit card transactions) and unstructured (e.g., newspaper articles, social media posts, or Google Trends) sources. They pose significant challenges from the data management and storage and security and confidentiality points of view. This chapter discusses the advantages and the challenges that CBs face in using new sources of data to carry out their functions. In addition, it describes a few successful case studies in which new data sources have been incorporated by CBs to improve their economic and forecasting analyses.
Cite
CITATION STYLE
Ghirelli, C., Hurtado, S., Pérez, J. J., & Urtasun, A. (2021). New data sources for central banks. In Data Science for Economics and Finance: Methodologies and Applications (pp. 169–194). Springer International Publishing. https://doi.org/10.1007/978-3-030-66891-4_8
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