COMBINATION OF MODELING METHODS IN THE ANALYSIS OF DEMOGRAPHIC PROCESSES AND ECONOMIC GROWTH IN CHINA

Abstract

The article demonstrates an effective combination of mathematical and computer modelling techniques, used for analyzing the dynamics of China’s macro indicators and for assessing the impact of demographic processes on economic growth. The main demographic factors affecting the macroeconomic performance of modern China are ageing population, falling birth rates, rising mortality rates, changes in the structure of the population and labour force reduction. In recent Chinese researchers’ publications three main points of view can be distinguished: most scientists believe that population ageing will slow down economic growth, that is, there is a negative correlation between population aging and long-term economic growth rates; the second group of scientists believe that population ageing, on the contrary, will contribute to economic development, as it has a significant impact on technological innovation and qualitative economic development; some scholars have found that the specific impact of population ageing on China's economy is not clear-cut. Based on this, we set out to test the relevant hypotheses by analyzing the trends of demographic processes and their impact on economic growth in modern China, based on a mixed computational methodology.

In the paper the relevant statistical data is analyzed, trends in macroeconomic processes are estimated, a dynamized Cobb-Douglas production function (PF) based on real Chinese data is built and assessed. PF and trend formulas for key indicators are used in a computer (algorithmic) system-dynamic model to forecast key demographic and economic indicators till 2030. The corresponding operators of the simulation model include real data (in the form of lookup functions until 2023) and trend formulas for the model endogenous variables. The values of GDP and GDP per capita are calculated using the constructed PF. Thus, the proposed composition of methods and models is an effective forecasting tool that can be used to conduct computer experiments to substantiate decision-making in the regulation of macroprocesses.