Weining Wang (City University, London)

Title: Dynamic semiparametric factor model with structural breaks

Abstract: For change-point analysis of high dimensional time series, we consider a semiparametric model with dynamic structural break factors. The observations are described by a few low dimensional factors with time-invariant loading functions of covariates.  Unknown structural breaks in time models the regime switching effects introduced by exogenous shocks.  In particular, the factors are assumed to be nonstationary and follow a Vector Autoregression (VAR) process with structural breaks.  In addition, to account for the known spatial discrepancies, we introduce discrete loading functions.  We study the theoretical properties of the estimates of the loading functions and the factors. Moreover, we provide both the consistency and the asymptotic convergence results for making inference on a particular common breakpoint in time.  Importantly our results hold for both large and small breaks for the factor dependency structure.  The estimation precision is evaluated via a simulation study. Finally we present two empirical illustrations on modeling the dynamics of the minimum wage policy in China and analyzing a limit order book dataset.