Residual-based cointegration and non-cointegration tests for cointegrating polynomial regressions

Abstract

Cointegrating polynomial regressions (CPRs), i.e., regressions that include deterministic terms, integrated processes and powers of integrated processes as explanatory variables and stationary errors, have become prominent in several fields of applications, e.g., in the analysis of environmental Kuznets curves. A key issue, as always in cointegration analysis, is testing for the presence or absence of a cointegrating relationship. This paper discusses two complementary tests: one with the null hypothesis of cointegration and one with the null hypothesis of the absence of cointegration. It is shown that (inter alia) for the empirically most relevant case, in which only one of the integrated regressors occurs as regressor also with higher powers, critical values can be simulated and are provided for a variety of specifications. Finally, the usage of the tests is illustrated for the environmental Kuznets curve for carbon and sulfur dioxide emissions. The illustration also investigates the sensitivity of the test decisions with respect to kernel and bandwidth choices, sample size and data vintage.