Industry Upgrading: Recommendations of New Products Based on World Trade Network

Abstract

GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its competitiveness. The proximity indicator measures the similarity between products and can be used to predict the probability that a country will develop a new industry. On the other hand, the Fitness–Complexity algorithm can help to find the important products and developing countries. In this paper, we find that the maximum of the proximity between a certain product and a country’s existing products is highly correlated with the probability that the country exports this new product in the next year. In addition, we find that the more products that are related to a certain product, the higher probability of the emergence of the new product. Finally, we combine the proximity indicator and the Fitness–Complexity algorithm and then attempt to provide a recommendation list of new products that can help developing countries to upgrade their industry. A few examples are given in the end.

Product progression: a machine learning approach to forecasting industrial upgrading

“…Measuring the relatedness between countries and products is one of the main topics in the economic complexity literature 71 , given its importance to assess the feasibility of investments and strategic policies 72,73 . Starting from 2007 with the Product Space 26 , many different approaches to measure the relatedness have been proposed 11,32,[35][36][37]39,43 . With all these models in the literature, a big issue is the absence of a scientifically sound procedure to compare them and quantifying how good they are in measuring the relatedness.…”

“…• Hidalgo et al in 2007 define the Product Space 26 that is still widely used to measure relatedness 37 . It is a projection of the country-product bipartite network into the layer of the products (thus defining a proximity network of the products).…”

“…We will consider export as the economic quantity to forecast because most of the indicators used in economic complexity are derived from export data, being it regarded as a global, summarizing quantity of countries' capabilities 10,34 but also for the immediate policy implications of the capability to be able, for instance, to predict in which industrial sector a country will be competitive, say, in five years.In this paper, we propose a procedure to systematically compare different prediction approaches and, as a consequence, to scientifically validate or falsify the underlying models. Indeed, some attempts to use complex networks or econometric approaches to predict exports exist 32,[35][36][37] , but these methodologies are practically impossible to compare precisely because of the lack of a common framework to choose how to preprocess data, how to build the training and the test set, or even which indicator to use to evaluate the predictive performance. In the following, we will systematically scrutiny the steps to build a scientifically sound testing procedure to predict the evolution of the export basket of countries.…”

“…In this paper, we propose a procedure to systematically compare different prediction approaches and, as a consequence, to scientifically validate or falsify the underlying models. Indeed, some attempts to use complex networks or econometric approaches to predict exports exist 32,[35][36][37] , but these methodologies are practically impossible to compare precisely because of the lack of a common framework to choose how to preprocess data, how to build the training and the test set, or even which indicator to use to evaluate the predictive performance. In the following, we will systematically scrutiny the steps to build a scientifically sound testing procedure to predict the evolution of the export basket of countries.…”

Product Progression: a machine learning approach to forecasting industrial upgrading

“…In this paper we propose a procedure to systematically compare different prediction approaches and, as a consequence, to scientifically validate or falsify the underlying models. Indeed, some attempts to use complex networks or econometric approaches to predict exports exist [33][34][35][36] , but these methodologies are practically impossible to compare precisely because of the lack of a common framework to choose how to preprocess data, how to build the training and the test set, or even which indicator to use to evaluate the predictive performance. In the following, we will systematically scrutiny the steps to build a scientifically sound testing procedure to predict the evolution of the export basket of countries.…”