A1261
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 that allows for different time series behaviours (e.g., unit-root and locally stationary processes) to interact with each other and to co-exist. From a practical perspective, this framework can estimate shifts in the predictability of non-stationary variables, test whether economic theories hold periodically, and many more implications. A time-varying Granger Representation Theorem is developed, which facilitates the establishment of the model's asymptotic properties. Then, the estimation, inferential methods, and theory for both short-run and long-run coefficients are proposed. An information criterion is further suggested 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.
