COWLES FOUNDATION FOR RESEARCH IN
ECONOMICS Box 208281
COWLES FOUNDATION DISCUSSION PAPER NO. 1873 Automated Estimation of Vector Error Correction Models Zhipeng Liao and Peter C.B. Phillips September 2012 Model selection and associated issues of post-model selection inference
present well known challenges in empirical econometric research. These modeling issues are
manifest in all applied work but they are particularly acute in multivariate time series
settings such as cointegrated systems where multiple interconnected decisions can
materially affect the form of the model and its interpretation. In cointegrated system
modeling, empirical estimation typically proceeds in a stepwise manner that involves the
determination of cointegrating rank and autoregressive lag order in a reduced rank vector
autoregression followed by estimation and inference. This paper proposes an automated
approach to cointegrated system modeling that uses adaptive shrinkage techniques to
estimate vector error correction models with unknown cointegrating rank structure and
unknown transient lag dynamic order. These methods enable simultaneous order estimation of
the cointegrating rank and autoregressive order in conjunction with oracle-like efficient
estimation of the cointegrating matrix and transient dynamics. As such they offer
considerable advantages to the practitioner as an automated approach to the estimation of
cointegrated systems. The paper develops the new methods, derives their limit theory,
reports simulations and presents an empirical illustration with macroeconomic aggregates. |
