Determinants in the forecast of the gross national income of China and India from 1952 to 2015

Journal of Management Science and Engineering

Weiguo Wang¹  Xu Yan²  Angel Colmenares³ 

[1] School of Data Science and Artificial Intellegence, Dongbei University of Finance and Economics, Dalian, 116025, China;School of Mathematics, Ocean University of China, Qingdao, 266100, China;School of Statistics, Dongbei University of Finance and Economics, Dalian, 116025, China;

关键词: Gross National Income (GNI);    Stepwise;    Ridge;    Lasso;    Elastic net;    AutoRegressive Distributed Lag (ARDL);   

DOI  :  

来源: DOAJ

【 摘 要 】

In 2015, China and India's population represented approximately 35.74% of the total number of people living in the world. Due to the historical context and behavior of the most relevant indicators, this study proposes to utilize a wide variety of demographic, economic, and production indicators from 1952 to 2015 to assess their impact on the GNI in China and India. A comprehensive and new fangled modeling process with stepwise, regularization and distributed lag regression approaches is presented. Accordingly, theoretical results were corroborated through extensive diagnostic tests and an empirical check of the models' predictive capacity. The findings show that GNI in China is most influenced by variables such as reserves in foreign currency and the dependency ratio; whereas, variables of energy production and birth rate were generated for India. Therefore, it's the timing for China to relax the universal two-child policy. Due to the current value below the substitution rate, a gloomy outlook for China's future population and economy is predicted. Conversely, a positive outlook is forecasted for India, given the low price in the future of oil- India's primary raw material.

【 授权许可】

Unknown