A Survey about Smooth Transition Panel Data Analysis

In this study we are introducing a literature survey about the panel smooth transition regression models. This type of modeling has been emerged from two different strand of literature where the first one is nonlinear time series the other is the panel data analysis. Both of these fields have tackled with different type of biases in estimation process. Therefore, combining these two fields constitutes different problems in estimation. Hence, instead of giving the studies in chronological order, we preferred to explain papers with respect to problems which they have solved. In this order, first we analyze the categories of different models. For example, there are several categorizations in the panel data estimation with respect to time and cross-section dimension. Therefore every category has its own biases depending on the time and cross-section dimension. On the other hand the dynamic structure of the panel data is another important determinant in which we can classify the biases. Hence, the static and dynamic panel smooth transition models are also discussed separately in this study. Finally, smooth transition models has its’ own categories, hence we are giving these categories under the panel categorization as well.