关键词: 面板协整;序列相关;动态广义最小二乘法, 检验水平

Abstract: In the cointegration model of non-stationary panel data, the dynamic ordinary least square(DOLS) estimator can eliminate the endogeneity that caused by the long-run correlation between the equilibrium error and the first difference of the regressors. And under the sequential limit theory, the estimator of the DOLS is asymptotic normality. But in small samples, the leads and lags of the first differences of the independent variables are finite, which causes the serial correlation in the equilibrium errors，and this results in the great size distortion to the DOLS estimator. In this paper, we use panel dynamic generalized least squares (DGLS) to estimate the cointegrating vectors in non-stationary homogeneous panel data, and the estimator of the DGLS still has a Gaussian sequential limit distribution. In a series Monte-Carlo experiments, we find that the estimator of the DGLS performs better in the sizes than that of the panel DOLS and FMOLS in small samples when there is serial correlation in the equilibrium errors.

Key words: Panel cointegration, Serial Correlation, DGLS, Empirical Size759