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...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.展开更多
基金supported by the National Natural Science Foundation of China(no.71773012,12026239)Natural Science Foundation of Liaoning Province LN2020J35Research Project of Dongbei University of Finance and Economics(DUFE2020Y22).
文摘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.
