Forecasting digital economy of China using an Adaptive Lasso and grey model optimized by particle swarm optimization algorithm

Abstract

With the development of big data, Internet finance, the digital economy is developing rapidly and has become an important force to drive the continuous transformation of the global economy and society. China has put forward plans for the development of digital economy from 2021 to 2025, requiring the number of core industries of digital economy to reach 10% of GDP by 2025, while continuously improving China’s digital economy to achieve high-quality development of China’s digital economy. Aiming at China’s digital economy, we use the adaptive lasso method and select feature variables based on quantitative and qualitative perspectives, so as to predict the development trend of China’s digital economy from 2021 to 2025 based on the TDGM (1, 1, r) grey model optimized by the particle swarm algorithm. Meanwhile, we have added the comparative analyses with TDGM(1,1), Grey Verhulst, GM(1,1) models and evaluate the prediction results both Ex-ante and Ex-post, demonstrating the feasibility of the proposed model and the accuracy. Finally, we find that the future of China’s digital economy will meet the planned objectives in terms of quantity and quality, but the trend of digital economy development in quantity is faster, thanks to the development of digital technology application industry.