Direct cointegration testing in error-correction models
Abstract An error correction model is specified having only exact identified parameters, some of which reflect a possible departure from a cointegration model. Wald, likelihood ratio, and Lagrange multiplier statistics are derived to test for the significance of these parameters. The construction of the Wald statistic only involves linear regression, and under certain conditions the limiting distribution of the Wald statistic differs from the limiting distributions of the likelihood ratio and Lagrange multiplier statistics. A special ordering of the variables is recommended so that equal limiting distributions of the three different test statistics are obtained. The applicability of the derived testing procedures is illustrated using real demand for money, real GNP, and bond and deposit interest rates from Denmark.
|Keywords||Wald test, cointegration, error correction models, limited distributions, two-step estimation|
|Persistent URL||dx.doi.org/10.1016/0304-4076(93)01561-Y, hdl.handle.net/1765/11296|
Kleibergen, F.R., & van Dijk, H.K.. (1994). Direct cointegration testing in error-correction models. Journal of Econometrics. doi:10.1016/0304-4076(93)01561-Y