Title: Matrix-valued factor model with time-varying main effects Authors:  Clifford Lam - London School of Economics and Political Science (United Kingdom) [presenting]
Zetai Cen - London School of Economics and Political Science (United Kingdom)
Abstract: The matrix-valued time-varying Main Effects Factor Model (MEFM) is introduced. MEFM is a generalisation of the traditional matrix-valued factor model (FM). We give rigorous definitions of MEFM and its identifications. We propose estimators for the time-varying grand mean, row and column main effects, and the row and column factor loading matrices for the common component. Rates of convergence for different estimators are spelt out, with asymptotic normality shown. The core rank estimator for the common component is also proposed, with the consistency of the estimators presented. We propose a test to test if FM is sufficient against the alternative that MEFM is necessary, and demonstrate the power of such a test in various simulation settings. We also demonstrate numerically the accuracy of our estimators in extended simulation experiments. A set of NYC Taxi traffic data is analysed, and our test suggests that MEFM is indeed necessary for analysing the data against a traditional FM.