Regression-based analysis of cointegration systems

Javier Hualde and Javier Gómez Biscarri

No 780, Working Papers from Barcelona School of Economics

Abstract: Two estimation procedures dominate the cointegration literature: Johansen's maximum likelihood inference on vector autoregressive error correction models, and estimation of Phillips' triangular forms. This latter methodology is essentially semiparametric, focusing on estimating long run parameters by means of cointegrating regressions, but it is less used in practice than Johansen's approach, since its implementation requires prior knowledge of features such as the cointegrating rank and an appropriate set of non-cointegrated regressors. In this paper we develop a simple and automatic procedure (based on unit root and regression-based cointegration testing) which provides an estimator of the cointegrating rank and data-based just-identifying conditions for the cointegrating parameters (leading to a Phillips' triangular form). A Monte Carlo experiment and an empirical example are also provided.

Keywords: cointegrating space; Phillips' triangular form; Johansen's methodology; regression-based cointegration testing (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2015-09
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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Journal Article: Regression-based analysis of cointegration systems (2015)
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