Testing for Cointegration in Linear Quadratic Models

This paper evaluates the finite sample performance of various tests for cointegration by Monte Carlo methods. The evaluation takes place within the linear quadratic model. The results indicate sharp differences in the tests to detect cointegrating relations especially when the cost of adjustment term and the number of regressors are large. Although no single test dominates for all the parameter settings considered, overall the augmented Dickey-Fuller and the Phillips type of test (1987) seem the most reliable in terms of test size and power.