Recent Economic Growth of China: A Forecasting Approach with Exogenous Factors

Authors

  • Yiyang Wang Faculty of Economics, Chiang Mai University, Chiang Mai, 50200, Thailand
  • Chukiat Chaiboonsri Faculty of Economics, Chiang Mai University, Chiang Mai, 50200, Thailand
  • Nisit Panthamit Faculty of Economics, Chiang Mai University, Chiang Mai, 50200, Thailand

DOI:

https://doi.org/10.63671/ijsssr.v3i1.393

Keywords:

Bayesian econometrics, Markov switching models, China’s economic growth, Exogenous factors, Economic forecasting, GDP growth rate

Abstract

This study employs Bayesian econometric methods and Markov switching models to analyze recent trends in China’s economic growth, integrating exogenous factors into a forecasting framework. Using economic data from 1983 to 2023, key variables such as global trade, foreign direct investment, consumer price index, exchange rate fluctuations, and domestic demand are examined to assess their influence on China's GDP growth. The results indicate that external factors play a significant role in shaping economic trajectories, especially in light of increasing complexities in international trade and capital flows. The Bayesian VARX model forecasts China’s GDP growth to remain between 4.5% and 5.5% from 2024 to 2028, though risks such as external demand fluctuations, demographic shifts, and real estate market uncertainties persist. Additionally, Markov switching models identify two distinct economic regimes, providing insights into China’s dynamic economic environment. This research highlights the importance of future policies focused on domestic consumption, technological innovation, demographic restructuring, and balanced regional development to ensure sustainable economic growth.

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Published

2025-06-07

Issue

Section

Articles

How to Cite

Recent Economic Growth of China: A Forecasting Approach with Exogenous Factors. (2025). International Journal of Science and Social Science Research, 3(1), 179-188. https://doi.org/10.63671/ijsssr.v3i1.393

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