Neglected dynamics in dynamic panel data models; consequences and detection in finite samples

The bias of various estimators for static cross‐section and panel data models is assessed in a simulation study, where the actual data generating process is a dynamic adjustment mechanism with random individual effects. It is concluded that the consequences of incorrectly estimating a static model can be rather serious. Therefore, it is important to have an accurate technique available for the detection of dynamics. Two exact similar tests for the presence of a lagged dependent variable in panel data models are developed; in some simulation experiments these tests outperform standard asymptotic test procedures. Empirical results on Engle curves for food illustrate the above issues.