Abstract or Introduction
The main aim of this seminar is to define, examine and present Smooth Transition Autoregressive Model (STAR) which is a model used to analyze nonlinear time-series economic data with regime-switching. In going forward, the overall structure of the seminar is designed to study the nonlinear features of production sector production index of Germany using data from January 1991 to April 2017. The author did first a Chow Test to evidence the existence of a data structural breakpoint. Then a model specification procedure given by Teräsvirta (1994) was followed. The author used, accordingly, three steps to specify the model. First, a linear AR model was developed using the data. Secondly, a linearity test against the STAR model was carried out. Once a test of the null hypothesis of linearity against non-linearity is rejected by the carried out Lagrange Multiplier (LM) test, the delay parameter d was determined. Afterwards, a choice between the LSTAR and the ESTAR model was made using a sequence of tests.
Finally, the estimation of the model is done. As the results from the set of tests indicate, the STAR model is found to be appropriate for modeling and analyzing the data.
- Quote paper
- Behailu Shiferaw Benti (Author), 2017, Smooth Transition Autoregressive Model. A study of production index of production sector in Germany, Munich, GRIN Verlag, https://www.grin.com/document/490761