"Big Data and Machine Learning Modelling for Economic Applications"25-26 February 2021

The increasing availability of different kinds of data and the spiralling availability of modelling techniques coming from statistical/machine learning have opened the way to new insights about the economy and a wider information set for policymakers.
Banca d’Italia will provide a two-day seminar to illustrate recent advances in economic modelling, harnessing big data along with machine learning approaches.

The classes will cover a wide range of topics including:

Theory:

• Machine learning (Deep Learning) for economic forecasting (e.g. Random forests, bagging and bootstrapping techniques, etc.);
• Regression with regularization techniques (modelling and estimation with many covariates or strong non-linearities);
• Text mining for article classification and sentiment analysis;

Empirics:

• Large granular structured or unstructured data sources (administrative data, web data, news and blogging platforms, payment data, textual data);
• Distributed computing for machine learning problems and data cleansing (matching, filtering or cleaning techniques, SQL-like techniques, regular expressions);
• Big data extractions for topics relating to firms, households, finance, labour markets, or government (e.g. Google data, data from Twitter, news from Factiva, etc.)