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| Evolutionary Trend of Global Economic Policy Uncertainty：A Forecasting Analysis with EMD-ARIMA Model |
| LIN Saiyan |
| Research Center of Digital Strategic Development, the Party School of Zhejiang Provincial Committee of the Communist Party of China |
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Abstract As the vane of economic policy change, global economic policy uncertainty index has important reference value for scientific formulation of economic policy. However, the factors affecting the dynamic path of GEPU index are complex and changeable, and the process of data generation is difficult to be accurately reflected in a single time series model. Based on the idea of “decomposing before integrating”, this paper firstly decomposes the GEPU index into some readable signals with the empirical mode decomposition method, and then simulates and predicts the readable signals by using the mainstream non-stationary time series model (ARIMA). Finally, the prediction results of all kinds of readable signals are integrated. The results show that: (1)EMD-ARIMA model is better than ARIMA in fitting the data of training group and test group by comparing the predicted value with the real value; (2)Compared with ARIMA model, EMD-ARIMA model can solve the problem of prediction deviation caused by uncertainty, nonlinearity and instability of original data, and obtain higher precision prediction results. (3)Factors such as global trade and the epidemic of NCP have a significant impact on the uncertainty of global economic policy. The out-of-sample prediction results of EMD-ARIMA model showed that GEPU index increased before July 2021 and gradually stabilized from July to December 2021.
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Received: 03 May 2021
Published: 15 March 2022
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2022, Vol. 42 
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