Abstract:

 A new method for detecting and estimating partial structural change at an unknown common time in random effect panel regression model was considered. And the rate of convergence and asymptotic distribution of structural change estimator was derived. The least squares estimator was constructed as global minimizers of the sum of squared residuals in order to identify structural changes. The structural changes can be well estimated even in the short panel data.  Monte Carlo simulations were carried out to verify the theoretical result numerically. Empirical study with 404 China enterprises which participate in share reform showed that structural change exist or not should be detected firstly, and then data analysis and explanation is meaningful. Bias estimator or spurious regression would appear if neglect to detect structural changes.

Key words: partial structural change; panel data; random effect; return on total assets