Time-Varying Multivariate Causal Processes

Jiti Gao (), Bin Peng (), Wei Wu () and Yayi Yan ()

No 8/22, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In this paper, we consider a wide class of time-varying multivariate causal processes that nests many classical and new examples as special cases. We first prove the existence of a weakly dependent stationary approximation for our model which is the foundation to initiate the theoretical development. Afterwards, we consider the QMLE estimation approach, and provide both point-wise and simultaneous inferences on the coefficient functions. In addition, we demonstrate the theoretical findings through both simulated and real data examples. In particular, we show the empirical relevance of our study using an application to evaluate the conditional correlations between the stock markets of China and U.S. We find that the interdependence between the two stock markets is increasing over time.

Keywords: Local linear quasi-maximum likelihood estimation; multivariate causal process simultaneous confidence interval (search for similar items in EconPapers)
JEL-codes: C14 C32 G15 (search for similar items in EconPapers)
Pages: 64
Date: 2022
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