Time-Varying Vector Error-Correction Models: Estimation and Inference

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

No 11/23, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: This paper considers a time-varying vector error-correction model that allows for different time series behaviours (e.g., unit-root and locally stationary processes) to interact with each other to co-exist. From practical perspectives, this framework can be used to estimate shifts in the predictability of non-stationary variables, test whether economic theories hold periodically, etc. We first develop a time-varying Granger Representation Theorem, which facilitates the establishment of asymptotic properties for the model, and then propose estimation and inferential methods and theory for both short-run and long-run coefficients. We also propose an information criterion to estimate the lag length, a singular-value ratio test to determine the cointegration rank, and a hypothesis test to examine the parameter stability. To validate the theoretical findings, we conduct extensive simulations. Finally, we demonstrate the empirical relevance by applying the framework to investigate the rational expectations hypothesis of the U.S. term structure.

Keywords: cointegration; Gaussian approximations; Granger representation theorem; iterated time-varying functions; term structure of interest rates (search for similar items in EconPapers)
JEL-codes: C14 C32 E44 (search for similar items in EconPapers)
Pages: 70
Date: 2023
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (1)

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Working Paper: Time-Varying Vector Error-Correction Models: Estimation and Inference (2023)
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