Testing for Cointegration in Linear Quadratic Models
用蒙特卡洛方法评估线性二次模型中多种协整检验的有限样本表现，发现调整成本项和回归元数量较大时检验效果差异显著，增广迪基-富勒检验和菲利普斯检验在检验水平和功效上最可靠。
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.