School of Mathematical Sciences

Regularization of Spatial Panel Time Series menu

Regularization of Spatial Panel Time Series

Clifford Lam, Department of Statistics, LSE
Thu, 28/02/2013 - 16:30
Seminar series: 

In this talk we introduce the need for the estimation of
cross-sectional dependence, or "network" of a panel of time series. In
spatial econometrics and other disciplines, the so-called spatial weight
matrix in a spatial lag model is always assumed known, when it is still
on debate if results of estimation can be sensitive to such assumed
known weight matrices. Since these weight matrices are often sparse, we
propose to regularize it from the data using a well-known technique by
now -- the adaptive LASSO. The technique in quantifying time dependence
is relatively new for statistics and time series literatures.
Non-asymptotic inequalities, as well as asymptotic sign consistency for
the weight matrices elements are presented with explicit rates of
convergence spelt out. A block coordinate descent algorithm is presented
together with results from simulation experiments and a real data