SMU SOE Online Seminar (Apr 5, 2021, 3pm-4.30pm): A Class of Multivariate Time-Varying Models: Theory and Practice

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TOPIC:

A CLASS OF MULTIVARIATE TIME-VARYING MODELS: THEORY AND PRACTICE

ABSTRACT Multivariate time series analyses are widely encountered in practical studies, e.g., modelling policy transmission mechanism and measuring connectedness between economic agents. To better capture the dynamics, this paper proposes a class of multivariate dynamic models with time–varying coeﬃcients, which have a general time–varying vector moving average (VMA) representation, and nest, for instance, time–varying vector autoregression (VAR), time–varying vector autoregression moving–average (VARMA), and so forth as special cases. The paper then develops a uniﬁed estimation method for the unknown quantities before an asymptotic theory for the proposed estimators is established. In the empirical study, we investigate the transmission mechanism of monetary policy using U.S. data, and uncover a fall in the volatilities of exogenous shocks. In addition, we ﬁnd that (i) monetary policy shocks have less inﬂuence on inﬂation before and during the so–called Great Moderation, (ii) inﬂation is more anchored recently, and (iii) the long–run level of inﬂation is below, but quite close to the Federal Reserve’s target of two percent after the beginning of the Great Moderation period. Keywords: Multivariate time series model, nonparametric kernel estimation, trending stationarity. Click here to view the paper. Click here to view the CV.		This seminar will be held virtually via Zoom. A confirmation email with the Zoom details will be sent to the registered email by 1 April 2021.
		PRESENTER Jiti Gao Monash University
		RESEARCH FIELDS Financial and Time Series Analysis Non and Semi-Parametric Models and Methods Panel Data and Spatial Data Analysis Statistical Theory
		DATE: 5 April 2021 (Monday)
		TIME: 3.00pm - 4.30pm

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