Dear Colleagues,

Economic Complexity and the Fitness Method:

Economic Complexity (EC) is a new field of research that consists of a radically new methodology. It describes economics as an evolutionary process of ecosystems made of industrial and financial technologies, as well as infrastructures that are all globally interconnected. The approach is multidisciplinary, addressing emerging phenomena in economics from different points of view: Analysis of complex systems, scientific methods for dynamical systems and the recent developments in big data (in the spirit of Google Page Rank, deep learning, and beyond). This approach offers new opportunities to constructively describe technological ecosystems, analyse their structures, understand their internal dynamics, as well as to introduce new metrics. It provides a new paradigm for a fundamental economic science based on data without any role of ideologies or interpretations.

A key feature of this new approach is to go from 100 parameters to zero parameters and obtain results which can be tested scientifically. This is done by focusing on the data in which the signal to noise ratio is optimal and developing iterative algorithms in the spirit, but other than Google, and optimized to the economic problem in question.

Relation to “Entropy” and Information Theory:

The last two decades have seen an exponential growth of accessible data concerning almost all human activities including economy. This happened in particular about the import-export dynamics of goods by countries and other central aspects of their economic development and of the dynamics of innovations such as patents and scientific production. Correspondingly, in the Economic science the typical response to such growth of data was to increase the number of parameters in order to reach a “more complete” description of the economic system. This approach goes in the opposite direction with respect to the usual methods of statistical physics where in order to study systems with a large number of degrees of freedom a “reduced” description in terms of few statistically motivated macroscopic thermodynamic variables, characterized by a large signal to noise ratio, is adopted. In this way, if from one hand we lose the microscopic details of the system, from the other one we gain in terms of robustness, classification and reproducibility of the description of the studied systems. Economic Fitness and Complexity was originally introduced exactly in the spirit of introducing a thermodynamic description of the import export dynamics of countries in such a way to get a robust classification of the degree of economic development of countries, of the industrial complexity of the productive sectors and to build a reliable prediction scheme for the evolution of this highly non-linear and interactive system.

Dynamics and Forecasting

The dynamics in the new GDP-Fitness space opens up to a completely new way for monitoring and forecasting. The trajectories of countries in this new space show regions of laminar and turbulent behaviour, which lead to a heterogeneous, non-linear approach to forecasting. This is similar to physical dynamical systems and modern weather forecasting. Then, the network of products and their evolutionary dynamics is built using machine learning methods. Finally, the same approach is applied to scientific production, patents and technologies, so to open up the possibility of analysing the core elements of the innovation process. All this provides a disciplined set of indicators that can be used for the industrial planning of countries and regions.

Some of these results have already attracted the attention of the scientific media of highest level like the editorials of Nature and Bloomberg Views.

http://www.nature.com/news/physicists-make-weather-forecasts-for-economies-1.16963

https://www.bloomberg.com/view/articles/2017-10-01/a-better-way-to-make-economic-forecasts

In the past two years, the IFC-World Bank has tested, in great detail, this methodology and found it better that the standard analysis. Then it was applied for the study of more than 50 countries. Our colleagues at the IFC-World Bank agree to participate in this Special Issue with about four papers.

This Special Issue of “Entropy” will provide a state-of-the-art overview of this rapidly-evolving field, which is setting the basis for a scientific foundation of industrial economics. It will stimulate further activity in the field and outline the most promising lines of evolution.

Prof. Dr. Luciano Pietronero
Dr. Andrea Tacchella
Dr. Andrea Zaccaria
Guest Editors

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• economic fitness
• complex systems
• dynamical systems
• industrial policy
• economic forecasting and planning
• innovation
• product progression network
• development economics
• statistical physics