a new pseudo-parametric approach for unit root test using singular spectrum analysis and gini-ridge regression

This article presents a novel method for conducting a unit root test utilizing a combination of singular spectrum analysis and the gini-ridge approach‎. ‎the gini-ridge approach employs a pseudo-parametric gini-ridge regression technique to estimate the coefficient from the ar(1) model while also utilizing bootstrap resampling to determine critical values for the test‎. ‎the effectiveness of the gini ridge-based stationarity test is evaluated across various probability distributions‎, ‎including the normal‎, ‎laplace‎, ‎skew-normal‎, ‎and cauchy distributions‎. ‎simulation results validate the proposed test and demonstrate its superiority of over existing procedures‎. ‎in addition‎, ‎the proposed method for‎ ‎forecasting the number mobile transactions conducted by all e-commerce companies operating in the industry‎, ‎under the supervision of shaparak and the central bank of iran‎, ‎from april 2019 to august 2024‎, ‎was evaluated‎. ‎the findings showed that this new approach has a superior ability to detect the presence of unit roots in time series data.