The Neoclassical Growth of China

44 Pages Posted: 14 Jun 2023

See all articles by Jesús Fernández-Villaverde

Jesús Fernández-Villaverde

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

Lee E. Ohanian

University of California, Los Angeles (UCLA) - Department of Economics; National Bureau of Economic Research (NBER)

Wen Yao

Tsinghua University - Tsinghua University School of Economics and Management

Date Written: 2023

Abstract

This paper studies China’s four-fold increase in per capita GDP relative to the U.S. between 1995 and 2019. First, we argue that China’s growth pattern is very similar to that of several other East Asia economies that initially grew very quickly. Second, we show that a minimalist Ramsey-Cass-Koopmans model with a parsimonious TFP catch-up process can account for China’s growth path and the growth paths of other East Asia economies at a similar stage of development. The growth paths of other East Asia economies and the model predictions suggest that China’s growth will substantially slow, so much so that we find the U.S. growth rate will likely be higher than China’s by 2043. We also find that China’s income per capita will level off at roughly 44% of the U.S. level around 2100.

Keywords: China, East Asia, economic growth, Ramsey-Cass-Koopmans model, TFP catch up

JEL Classification: E100, E200, O400

Suggested Citation

Fernández-Villaverde, Jesús and Ohanian, Lee E. and Yao, Wen, The Neoclassical Growth of China (2023). CESifo Working Paper No. 10499, Available at SSRN: https://ssrn.com/abstract=4477987 or http://dx.doi.org/10.2139/ssrn.4477987

Jesús Fernández-Villaverde (Contact Author)

University of Pennsylvania - Department of Economics ( email )

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Lee E. Ohanian

University of California, Los Angeles (UCLA) - Department of Economics ( email )

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National Bureau of Economic Research (NBER)

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Wen Yao

Tsinghua University - Tsinghua University School of Economics and Management ( email )

Beijing
China

HOME PAGE: http://www.sem.tsinghua.edu.cn/en/yaow

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