In today’s China, population aging is a more and more serious problem and it can impact economic growth in many aspects. In order to slow down the population aging and reduce its impact on economic growth, this study uses multiple linear regression model to analyze the correlations between them. As the most direct indicator to economic growth, GDP and its 4 compositions are chosen as the dependent variables. This study chooses aging ratio, aging index, labor participation rate and elderly dependency rate as variables to indicate population aging. Based on the analysis of 240 samples from the National Bureau of Statistics, it is found that each dependent variable is corresponded to the 4 variables. After comparing the VIF value and significance of each variable, the equations of multiple linear regression are drawn. It turns out that aging index is the most important influencing factor to China’s GDP, so the results can shed light on how to promote national economic growth under the background of population aging.
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Chen et al. (2024) studied this question.
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