Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Series Vol. 46 , 01 December 2023
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This paper utilizes an ARIMA model to predict the future exchange rate and trade balance of China. The primary data is the monthly average exchange rate of USD/RMB, while China's monthly trade balance serves as auxiliary data. The findings indicate a projected downward trend in the USD/RMB exchange rate, continuing from 2023 to 2024 and stabilizing around 6.7 from 2024 to 2025. This implies a depreciation of the Chinese currency against the US dollar. Additionally, China's trade balance is expected to experience modest growth over the next two years, albeit at a significantly reduced rate compared to previous years. These projections highlight the challenges faced by Chinese exporters and suggest evolving global trade dynamics. The paper discusses policy implications for managing exchange rate fluctuations and sustaining balanced trade relations. It emphasizes the usefulness of the ARIMA model for forecasting exchange rates and trade balances while acknowledging the limitations and potential impact of unforeseen events or policy changes on the outcomes. The study concludes by suggesting avenues for future research to improve the accuracy and robustness of such forecasts, encouraging continued exploration in this dynamic field of study.
time series analysis, exchange rates, China's trade balances
1. Wu, Y., & Wen, X. (2016). Short-term stock price prediction based on ARIMA model. Statistics and Decision, 467(23), 83-86.
2. Liu, Y., Feng, M., & Tang, Y. (2015). The impact of exchange rate fluctuations on China's trade surplus: Direct and spillover effects. Investment Research, 34(11), 91-107.
3. Fracasso, A., Secchi, A., & Tomasi, C. (2022). Export pricing and exchange rate expectations under uncertainty. Journal of Comparative Economics, 50(1), 135-152.
4. Song, C., & Xie, Y. (2017). The impact of RMB exchange rate on China's export: Processing trade versus general trade. World Economy, 40(8), 78-102.
5. Héricourt, J., & Poncet, S. (2013). Exchange Rate Volatility, Financial Constraints, and Trade: Empirical Evidence from Chinese Firms. The World Bank Economic Review, 29(3), 550–578.
6. Fan, H., Li, Y. A., & Zhao, C. C. (2018). Margins of imports, forward-looking firms, and exchange rate movements. Journal of International Money and Finance, 81, 185-202.
7. Liu, L. (2002). The impact of exchange rate fluctuations on a country's import and export trade: An empirical analysis of the J-curve effect. Journal of Yunnan College of Finance and Trade, (03), 67-69.
8. Huang, Q., Song, P., & Li, Y. (2020). RMB exchange rate, intermediate input in imports, and the transmission effect on export prices of enterprises. Journal of International Economic Exploration, 36(12), 33-51.
9. Zeng, Z., & Zhang, Y. (2007). RMB real exchange rate appreciation and adjustment of China's export commodity structure. World Economy, (345), 16-24.
10. Chen, M. W., Lu, C., & Tian, Y. (2021). Export price and quality adjustment: The role of financial stress and exchange rate. Economic Modelling, 96, 336-345.
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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