Estimation of the Rigidity and Expectational Model

Abstract

The rigidity and expectational model is one of the geometric lag models which may cause problems of parameters estimation. In order to consistently estimate the model’s parameters in the ML approach, we propose an easy-to-compute procedure. This new procedure makes the polynomials in the lag operator to be fractionally integrated. A parsimonious model will be obtained when this proposed procedure is applied. And it also will be applied to very general specifications of the error term. In this paper, we employ this new procedure to analyze U.S. consumption function, and then we discuss some interesting results.