The objective of this seminar is to provide the participants with the examples of the recent advances in collection, analysis and the use of big data in central banks. The seminar aims to introduce big data techniques through various case studies. The key question of how big data can help central banks to take timely policy measures by collecting and analyzing information from the economy and the financial system will be also addressed by these case studies.
• Big data collection, governance and management
• Developing real time early warning indicators using big data
• Case Study 1: Consumer confidence and (social) media sentiment
• Case Study 2: Text mining and sentiment extraction from central bank communiques
• Case Study 3: Inflation nowcasting with big data
• Case Study 4: Tracking financial vulnerability in real time using big data
Target Audience: The seminar is designed for central bankers with an interest in advances in big data and analytical techniques. The lectures will consist of introducing big data techniques through various case studies that are in current interest of various central banks. Prior knowledge of intermediate statistics and econometrics is presumed. Some experience of statistical software is recommended.