Analysis of Bilateral Trade Flow and Machine Learning Algorithms for GDP Forecasting


  • J. Sun School of International and Public Affairs, Columbia University, USA
  • Y. Suo School of Social Sciences, University of California, Irvine, USA
  • S. Park Hankuk Academy of Foreign Studies, South Korea
  • T. Xu College of Liberal Arts and Sciences, University of Connecticut, USA
  • Y. Liu Pius XI Catholic High School, Milwaukee, USA
  • W. Wang Lawrence Woodmere Academy, USA
Volume: 8 | Issue: 5 | Pages: 3432-3438 | October 2018 |


The terms imports and exports describe goods and services traded between countries. Countries import goods they cannot produce domestically or can obtain at a lower cost from another country. According to the World Trade Organization (WTO) reports, the U.S. is the world’s largest importer based on capital investment, followed by the E.U., China, Germany, and Japan. For exports, China leads the world with an official trade amount of $1.904 trillion in 2013. E.U. ranks second, followed by U.S., Germany, and Japan. Trade in goods and services is defined as a change in ownership of material resources and services between economies. Trade indicators include the sale of goods and services as well as barter transactions or goods exchanged and are measured in million USD, the percentage of GDP for net trade, and the annual export and import growth. This study analyzes imports and exports of all countries for the 1960-2017 period and evaluates the correlations in trade statistics to predict future imports and exports. Since the GDP for any country depends mainly on trade, this study examines trade data and compares various machine learning algorithms to forecast a country’s GDP.


imports, exports, GDP, trade statistics, GDP forecast


Download data is not yet available.


J. Uddin, “Time Series Behavior of Imports and Exports of Bangladesh: Evidence from Cointegration Analysis and Error Correction Model”, International Journal of Economics and Finance, Vol. 1, No. 2, pp. 156-162, 2009 DOI:

I. S. Kim, S. Liao, K. Imai, “Measuring Trade Profile with Granular Product-level Trade Data”, available at:

research/files/BIGtrade.pdf, 2018

R. Sen, “Analyzing International Trade Data in a Small Open Economy: The Case of Singapore”, ASEAN Economic Bulletin, Vol. 17, No. 1, pp. 23-35, 2000 DOI:

M. Bahmani-Oskooee, H. J. Rhee, “Are imports and exports of Korea cointegrated?”, International Economic Journal, Vol. 11, No. 1, pp. 109-114, 1997 DOI:

T. T. Cheong, “Are Malaysian exports and imports cointegrated? A comment”, Sunway Academic Journal, Vol. 2, pp. 101-107, 2005

M. Bahmani-Oskooee, “Cointegration approach to estimate the long-run trade elasticities in LDCs”, International Economic Journal, Vol. 12, No. 3, pp. 89-96, 1998 DOI:

T. C. Tang, “Are imports and exports in the OIC member countries cointegrated? A reexamination”, IIUM Journal of Economics and Management, Vol. 14, No. 1, pp. 1-31, 2006

C. K. Choong, S. C. Soo, Z. Yusop, “Are Malaysian exports and imports cointegrated?”, Sunway Academic Journal, Vol. 1, pp. 29-38, 2004

M. J. Sirgy, D. J. Lee, C. Miller, J. E. Littlefield, E. G. Atay, “The Impact of Imports and Exports on A Country’s Quality of Life”, Social Indicators Research, Vol. 83, No. 2, pp. 245-281, 2007 DOI:

A .A. J. Saaed, M. A. Hussain, “Impact of Exports and Imports on Economic Growth: Evidence from Tunisia”, Journal of Emerging Trends in Economics and Management Sciences, Vol. 6, No. 1, pp. 13-21, 2015

D. Omotor, “The Role of Exports in the Economic Growth of Nigeria: The Bounds Test Analysis”, International Journal of Economic Perspectives, Vol. 2, No. 3, pp. 222-235, 2008

F. E. Chemeda, “The Role of Exports in Economic Growth with Reference to Ethiopian Country”, Conference on Annual Meeting of American Agricultural Economics Association in Chicago, Chicago, USA, August 5-8, 2001

P. Aghion, A. Bergeaud, M. Lequien, M. Melitz, The Impact of Exports on Innovation: Theory and Evidence, National Bureau of Economic Research, 2018 DOI:

L. Charles, G. Daudin, “Eighteenth-Century International Trade Statistics. Sources and Methods”, Revue de l’OFCE, Vol. 4, pp. 7-36, 2015 DOI:

WTO, World Trade Statistical Review, WTO, 2017

M. Jerven, “On the accuracy of trade and GDP statistics in Africa: Errors of commission and omission”, Journal of African Trade, Vol. 1, No. 1, pp. 45-52, 2014 DOI:

The Central Intelligence Agency, The World Factbook, Country Comparison: Imports, available at:

The Central Intelligence Agency, The World Factbook, Country Comparison: Exports, available at:

J. Desjardins, “The Top Importers and Exporters of the World’s 18 Most Traded Goods”, available at:

Teletrac Navman, “Top 18 Imports and Exports Around the World”, available at:

Financial Stability Board, Artificial Intelligence and Machine Learning in Financial Services: Market Developments and Financial Stability Implications, Financial Stability Board, 2017

Info World, “An Intro to Genetic Algorithms”, available at:

A. M. Ticlavilca, D. M. Feuz, M. McKee, “Forecasting Agricultural Commodity Prices Using Multivariate Bayesian Machine Learning Regression”, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management. St. Louis, USA, April 19-20, 2010

M. Manaye, B. Borena, “Association Pattern Discovery of Import Export Items in Ethiopia”, HiLCoE Journal of Computer Science and Technology, Vol. 1, No. 2, pp. 82-88, 2013

S. Circlaeys, C. Kanitkar, D. Kumazawa, “Bilateral Trade Flow Prediction”, available at:, 2017

H. R. Joseph, “GDP Forecasting through Data Mining of Seaport Export-Import Records”, 9th International Conference on Data Mining, Las Vegas, USA, July 22-25, 2013

F. F. Ping, F. X. Fei, “Multivariant forecasting mode of Guangdong province port throughput with genetic algorithms and Back Propagation neural network”, Procedia – Social and Behavioral Sciences, Vol. 96, pp. 1165-1174, 2013 DOI:

M. Panella, F. Barcellona, R. L. D’Ecclesia, “Forecasting Energy Commodity Prices Using Neural Networks”, Vol. 2012, Article ID 289810, 2012 DOI:

R. G. Donaldson, M. Kamstra, “An artificial neural network - GARCH model for international stock return volatility”, Journal of Empirical Finance, Vol. 4, No. 1, pp. 17-46, 1997 DOI:

I. ur Sami, K. N. Junejo, “Predicting Future Gold Rates using Machine Learning Approach”, International Journal of Advanced Computer Science and Applications, Vol. 8, No. 12, pp. 92-99, 2017 DOI:

S. Peluso, A. Mira, P. Muliere, A. Lomi, “International Trade: a Reinforced Url Network Model”, available at:

abs/1601.03067, 2016

World Bank, Indicators, available at:


How to Cite

J. Sun, Y. Suo, S. Park, T. Xu, Y. Liu, and W. Wang, “Analysis of Bilateral Trade Flow and Machine Learning Algorithms for GDP Forecasting”, Eng. Technol. Appl. Sci. Res., vol. 8, no. 5, pp. 3432–3438, Oct. 2018.


Abstract Views: 1005
PDF Downloads: 742

Metrics Information
Bookmark and Share