Testing for Cointegration Using the Johansen Methodology When Variables Are Near-Integrated

We investigate the properties of Johansen''s (1988, 1991) maximum eigenvalue and trace tests for cointegration under the empirically relevant situation of near-integrated variables. Using Monte Carlo techniques, we show that in a system with near-integrated variables, the probability of reaching an erroneous conclusion regarding the cointegrating rank of the system is generally substantially higher than the nominal size. The risk of concluding that completely unrelated series are cointegrated is therefore non-negligible. The spurious rejection rate can be reduced by performing additional tests of restrictions on the cointegrating vector(s), although it is still substantially larger than the nominal size.Economic models;cointegration, inflation, nominal interest rate, equation, nominal interest rates, sample size, statistics, real exchange rates, probability, time series, monte carlo simulations, real interest rate, confidence intervals, confidence interval, correlations, statistic, inflation rate, maximum likelihood estimation, predictability, vector autoregression, statistical model, equations, econometrics, constant term, maximum likelihood estimator, samples, number of variables, inflation rates, monte carlo simulation, hypothesis testing, correlation, monetary economics