This item is accessible only to the Washington University community.
Off-Campus WUSTL Users: Click the “Off-Campus Download” button below. You will be prompted to log in using your WUSTL Key.
Language
English (en)
Date of Award
2023
Author's Department
International and Area Studies
Degree Name
Bachelor of Arts (A.B.)
Restricted/Unrestricted
Restricted
Abstract
The People's Republic of China is currently experiencing both a demographic transition and economic growth slowdown. After decades of high economic growth, the gross domestic product (GDP) growth rate has decreased in a period of stagnation, giving way to speculation on whether China will fall victim to the middle-income trap (MIT). The labor force is decreasing due to the population decline, and there is serious concern of "aging before affluence." Both issues have impacted Xi Jinping's vision for the country to become a powerful player on the world stage and to reject "Westernization" that is, in his eyes, pushed onto China by the United States, among other nations. However, I argue these issues are fundamentally connected, in that demographic transition plays a key role in why China is experiencing a growth slowdown. Through an exploration of economic theories applied to data on China's labor and demographic populations, I conclude there are several issues holding China back from becoming a high-income political economy, including total government reforms that update the institutional framework to resolve fundamental issues inherent in the modern technocracy. Most importantly, however, its demographic issue must be addressed, in that there does not need to be more people but rather a shift in where existing people work, so that these changes can be implemented with the sufficient human capital.
DOI
https://doi.org/10.7936/81k0-3284
Mentor
James Wertsch
Recommended Citation
Johnson, George, "Demographic Decline and China’s Susceptibility to the Middle-Income Trap with a Slowdown in Economic Growth" (2023). Senior Honors Papers / Undergraduate Theses. 235.
The definitive version is available at https://doi.org/10.7936/81k0-3284
Comments
Accessibility Notice: This document is a scanned text that has been automatically processed using Python's Tesseract Optical Character Recognition (OCR) engine to provide a text alternative for assistive software. Formatting or character recognition discrepancies may exist.