Forecasting China's Merchandise Export Growth with Import and Exchange-Rate Changes
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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.
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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.