Using turning point information to study economic dynamics

Procedures are developed to compute the proportion of turning points located in the sample path of time series data. It is shown that the proportion of turning points can be directly related to the data generating process. Methods for estimating model parameters are developed using counts of turning points. It is shown that the proposed method has the advantages of tractability and robustness. The later feature arises as it does not require that any of the moments of the series Y(t) exist. Tests of model specification are developed using these counts of turning points. These tests are applied to several models one including the issue of whether GDP is better modelled as trend stationary or difference stationary. Monte carlo results are presented for both the estimation and testing procedures