Version 1
: Received: 26 July 2018 / Approved: 26 July 2018 / Online: 26 July 2018 (11:49:41 CEST)
Version 2
: Received: 17 September 2018 / Approved: 18 September 2018 / Online: 18 September 2018 (06:13:25 CEST)
Servedio, V.D.P.; Buttà, P.; Mazzilli, D.; Tacchella, A.; Pietronero, L. A New and Stable Estimation Method of Country Economic Fitness and Product Complexity. Entropy2018, 20, 783.
Servedio, V.D.P.; Buttà, P.; Mazzilli, D.; Tacchella, A.; Pietronero, L. A New and Stable Estimation Method of Country Economic Fitness and Product Complexity. Entropy 2018, 20, 783.
Servedio, V.D.P.; Buttà, P.; Mazzilli, D.; Tacchella, A.; Pietronero, L. A New and Stable Estimation Method of Country Economic Fitness and Product Complexity. Entropy2018, 20, 783.
Servedio, V.D.P.; Buttà, P.; Mazzilli, D.; Tacchella, A.; Pietronero, L. A New and Stable Estimation Method of Country Economic Fitness and Product Complexity. Entropy 2018, 20, 783.
Abstract
We present a new method of estimating fitness of countries and complexity of products by exploiting a non-linear non-homogeneous map applied to the publicly available information on the goods exported by a country. The non homogeneous terms guarantee both convergence and stability. After a suitable rescaling of the relevant quantities, the non homogeneous terms are eventually set to zero so that this new method is parameter free. This new map reproduces the findings of the method proposed by Tacchella et al. [1], and allows for an approximate analytic solution in case of actual binarized matrices based on the Revealed Comparative Advantage (RCA) indicator. This solution is connected with a new quantity describing the neighborhood of nodes in bipartite graphs, representing in this work the relations between countries and exported products. Moreover, we define the new indicator of country net-efficiency quantifying how a country efficiently invests in capabilities able to generate innovative complex high quality products. Eventually, we demonstrate analytically the local convergence of the algorithm.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
