Ricerc@Sapienza

Huge technical improvements in data collection and storage are nowadays taking place and allow to form an increasingly accurate picture of many economic phenomena. In order to benefit from such superior data collection, one needs appropriate statistical tools that can help to extract the most important features of the data and turn them into information.

Functional data analysis (FDA) allows to study both cross-sectional and time series data in their original full richness, in addition to traditional methods that usually focus only on a few moments and/or quantiles. For example, in studying earning distribution dynamics, one may use FDA to keep track of the evolution of the whole density function of individual income over time or, when analyzing quantities that are recorded at arbitrarily high frequency (such as e.g. asset prices, interest rates, exchange rates), FDA allows to model and estimate their evolution in continuous time. This motivates the increasingly important role that FDA is recently gaining as a field of research in statistics and econometrics.

The present activity aims at exploring the applicability of FDA, with specific interest to its time series applications. The cooperation with leading European and US experts in the field will contribute to the excellence of the output and to its international outreach.