Review on Machine Learning Techniques for International Trade Trends Prediction

Now days, analyzing the past trend and make future predictions has become an important aspect for every field to growth. By analyzing the economic trends and knowing the future value of important economic variables makes a country more efficient in country’s economic planning and developing policies. This can be achieved by increased application of machine learning more effectively and accurately. In recent years, Machine Learning techniques have been suggested as alternative approach to traditional statistical methods by many authors in the field of economics. As international trade policies critically affects employment and wages of a country that is important aspect for growth of a country, for policy makers all across the world, predicting future patterns of international trade is a top priority. This paper presented a literature review of the works where machine-learning techniques have been used in international trade trends prediction. The findings reveal that there is a growing interest in developing machine learning models for economic forecasting in comparison to conventional statistical methods.