A0374
Title: Time-varying vector error-correction models: Estimation and inference
Authors: Jiti Gao - Monash University (Australia)
Bin Peng - Monash University (Australia)
Yayi Yan - Shanghai University of Finance and Economics (China) [presenting]
Abstract: A time-varying vector error-correction model is considered to allow for different time series behaviours (e.g., unit-root and locally stationary processes) to interact with each other and co-exist. From a practical perspective, this framework can be used to estimate shifts in the predictability of non-stationary variables, test whether economic theories hold periodically, etc. A time-varying Granger representation theorem is first developed, which facilitates the establishment of asymptotic properties for the model, and then estimation and inferential methods and theory are proposed for both short-run and long-run coefficients. An information criterion is also proposed 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, extensive simulations are conducted. Finally, the empirical relevance is demonstrated by applying the framework to investigate the rational expectations hypothesis of the U.S. term structure.
