A Parametric Bootstrap Approach For Panel Data Models

In this article,we study using a.parametric bootstrap(PB)approach to solve the hypothesis test and multiple comparison problem in panel data models.In the paper,the following aspects are interested.1.For a fixed one-way error component regression model(ANCOVA model),we propose simultaneous confidence intervals for all pairwise multiple comparisons in AN-COVA unbalanced design with unequal variances,using a parametric bootstrap approach.simulation results show that Type 1 error of the multiple comparison test is close to the normal level even for small samples.2.For the testing equality problem of regression coefficients in several two-way error component regression models,a parameter bootstrap approach is proposed.At the same time,we has been extended the parameter bootstrap approach the to a multiple compar-ison procedure.Some simulated numerical results indicate that the PB test,regardless of the sample sizes,values of the variance components,number of the models,performs well.