Recent Economic Growth of China: A Forecasting Approach with Exogenous Factors
DOI:
https://doi.org/10.63671/ijsssr.v3i1.393Keywords:
Bayesian econometrics, Markov switching models, China’s economic growth, Exogenous factors, Economic forecasting, GDP growth rateAbstract
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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