Adam Smith Business School

Professor Matteo Barigozzi, University of Bologna

"Quasi maximum likelihood estimation of high-dimensional approximate dynamic matrix factor models via the EM algorithm" (Joint Work with Luca Trapin)
Friday, 28 February 2025. 15:00-16:30
Room 386AB, Adam Smith Business School Building

Abstract

This paper considers an approximate dynamic matrix factor model that accounts for the time series nature of the data by explicitly modelling the time evolution of the factors. We study Quasi Maximum Likelihood estimation of the model parameters based on the Expectation Maximization (EM) algorithm, implemented jointly with the Kalman smoother which gives estimates of the factors. This approach allows to easily handle arbitrary patterns of missing data. We establish the consistency of the estimated loadings and factor matrices as the sample size T and the matrix dimensions p1 and p2 diverge to infinity. The finite sample properties of the estimators are assessed through a large simulation study and an application to a financial dataset of volatility proxies.

Bio

Matteo Barigozzi is full professor of Political Economy and Econometrics at the department of Economics of the University of Bologna. Before he was Associate professor of Statistics at LSE and post-doc at ECARES (Université libre de Bruxelles). He has a PhD in Economics from Sant'Anna School of Advanced Studies in Pisa and an MSc in Physics from the University of Milano.

His current research is on the theory and applications of high-dimensional time series analysis and in particular on large dynamic factor models.

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First published: 9 February 2025