Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network

Abstract

A PREPRINT -APRIL 5, 2019 Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries' data of the international trading network. A recommendation system is then used to identify the products corresponding to the production capacity of each individual country, but are somehow overlook by the country. Then, we simulate the evolution of the country's fitness if it would have followed the recommendations. The result of this work is the combination combine these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries. IntroductionInternational trade plays a considerable role in the exchange channels between countries [1,2]. It is also becoming more important as time goes on. In 1960, international trade accounted for roughly 25% of a country's total Gross Domestic Product (GDP). Nowadays it accounts for nearly 60% of countries GDP [3]. Historically, various classic economic models were developed to evaluate the dissimilarity of wealth that result from the exportation of diverse goods [4]. Models based on the gravity equation were also developed and showed to be adequate to explain many of the features of the international trade [5]. Another approach, The Product Space, attempted to illustrate how the nations will develop in the future by projecting the exports data onto a two-dimensional map and observing the diffusion of the export process [6]. Economic models mainly consist of commodity profits, geographical relations, comprehensive productivity, economic structure [7] and a series of macroeconomic elements. In practice, numerous complex external factors e.g. national policies, religious beliefs and the country's current production capacity, are key components in the international trade. Here, we also recognize that plenty of sociologists have constructed grand theories on the empirical study of Global Economic Development [8,9,10]. These methods and theories were developed by David Snyder, and Edward L. Kick [11], it was the first study of international trade and world economic growth using a network framework in American journal of sociology 1979. In Ref. [12], the authors emphasized on the importance of the global trade, and the structure of modern world system were addressed by multiple-network analysis. The complex network approach was also used in [13], and it was shown that the international trade network and the World Wide Web both have collaborative characteristics [14]. Indeed, the international trade network is a complex network in terms of structure. With this is in mind, we apply recommendation algorithms that are usually applied on e-commerce systems in order to predict the evolution of...

Recommender systems for sustainability: overview and research issues

“…For a detailed discussion of applying different CF algorithms in such application contexts, we refer to Che ( 2020 ). Furthermore, Liao et al ( 2018 ) discuss approaches to product diversification based on the concepts of social network analysis where relationships between countries and their products are analyzed for recommendation purposes.…”

“…On the macro-level, recommender systems can help to figure out new potentials overlooked by countries, that can trigger future economic welfare due to strategic future advantages (Liao et al, 2018 ). In this line of research, recommender systems can also help to establish new study programs of relevance helping to promote relevant know-how for implementing specific industries.…”

Matrix completion of world trade: An analysis of interpretability through Shapley values

“…The importance of the application of MC to economics is demonstrated by the recent work by Athey et al (2021) on MC‐based causal inference. In general, the interest of economists in MC and related techniques has increased recently (Athey & Imbens, 2019; Liao et al, 2018).…”

“…| 2709 et al (2021) on MC-based causal inference. In general, the interest of economists in MC and related techniques has increased recently (Athey & Imbens, 2019;Liao et al, 2018).…”