Forecasting China's Merchandise Export Growth with Import and Exchange-Rate Changes
Main Article Content
Abstract
This study forecasts the annual growth rate of China's merchandise exports measured in current US dollars. The target variable is calculated from World Bank WDI merchandise export values [1]. The predictors include lagged export growth, import growth, exchange-rate change, China's GDP growth, and world GDP growth. The variable design reflects trade-flow persistence, external demand, and price-conversion channels discussed in the international trade literature [3, 4, 5]. The training sample is 1996-2018, and the test sample is 2019-2024. The results show that export persistence and import growth are informative, but large external shocks make the forecast errors larger than those in the GDP and consumption papers.
Downloads
Article Details
Section

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
-
All published articles are open access, with copyright shared between the authors and the journal. The journal retains the exclusive right to first publication and identifies itself as original publisher.
-
Articles are made available under a Creative Commons CC BY‑NC‑ND 4.0 license, permitting users to copy and distribute the content for non‑commercial purposes only, without modification, provided proper credit is given to authors and JCPHS.
-
Redistribution or reuse must preserve the full citation details and include a link to the license. No derivatives, adaptations, or commercial uses are permitted without prior written permission.
References
World Bank. (2026). World Development Indicators database. https://api.worldbank.org/
Tinbergen, J. (1962). Shaping the World Economy: Suggestions for an International Economic Policy. Twentieth Century Fund.
Anderson, J. E. (1979). A theoretical foundation for the gravity equation. American Economic Review, 69(1), 106-116.
Goldstein, M., & Khan, M. S. (1985). Income and price effects in foreign trade. In R. W. Jones & P. B. Kenen (Eds.), Handbook of International Economics, Vol. 2 (pp. 1041-1105). Elsevier.
Anderson, J. E., & van Wincoop, E. (2003). Gravity with gravitas: A solution to the border puzzle. American Economic Review, 93(1), 170-192. https://doi.org/10.1257/000282803321455214
Eaton, J., & Kortum, S. (2002). Technology, geography, and trade. Econometrica, 70(5), 1741-1779. https://doi.org/10.1111/1468-0262.00352
Helpman, E., Melitz, M., & Rubinstein, Y. (2008). Estimating trade flows: Trading partners and trading volumes. Quarterly Journal of Economics, 123(2), 441-487. https://doi.org/10.1162/qjec.2008.123.2.441
Baier, S. L., & Bergstrand, J. H. (2007). Do free trade agreements actually increase members' international trade? Journal of International Economics, 71(1), 72-95. https://doi.org/10.1016/j.jinteco.2006.02.005
Rose, A. K. (2000). One money, one market: Estimating the effect of common currencies on trade. Economic Policy, 15(30), 8-45. https://doi.org/10.1111/1468-0327.00056
Feenstra, R. C. (2004). Advanced International Trade: Theory and Evidence. Princeton University Press.
Breiman, L. (2001). Random Forests. Machine Learning, 45, 5-32. https://doi.org/10.1023/A:1010933404324
Varian, H. R. (2014). Big Data: New Tricks for Econometrics. Journal of Economic Perspectives, 28(2), 3-28. https://doi.org/10.1257/jep.28.2.3
Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253-263. https://doi.org/10.1080/07350015.1995.10524599
Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688. https://doi.org/10.1016/j.ijforecast.2006.03.001
Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts.