CA21163 - Text, functional and other high-dimensional data in econometrics: New models, methods, applications (HiTEc)

This Action will integrate cutting-edge analytic developments involving innovative sources of information, such as text, functions, perceptions or imprecise data, in econometrics. High-dimensional, complex and unstructured economic datasets cannot be fully exploited hitherto by the existing methodologies. An international network of experts, spanning the disciplines of econometrics, mathematics, statistics and computer science, will be created, with the aim of establishing and implementing new efficient inferential procedures for using such information in econometric modelling and forecasting. User-friendly and freely available software will be produced. These results will enable applied econometricians to mine textual information gathered from newspapers, articles, opinions and sentiments recorded by poles, in combination with other complex and traditional data. New techniques for analyzing the evolution of economic indicators will help to improve forecasting. Valuable insights into economic issues will provide ample prospects for further research, as vast sources of data are still noticeably under-exploited. The potential to enhance economic data analysis will be fostered by a training programme for Early Career Investigators, and by intensifying connections among academics, stakeholders, and policy-makers. The impact will not be limited to economics and finance. The interaction with experts in other areas, such as environmental sciences or health, will facilitate the transfer of knowledge and technology. Emphasis will be given to sensor data and indicators that will alert to the vulnerability of commercial enterprises and social groups to extreme events associated with environmental hazards. Such indicators will include those relating to mortality risks.