Economic Complexity: why we like "Complexity weighted diversification"

A recent paper by Hausmann and collaborators (1) reaches the important conclusion that Complexity-weighted diversification is the essential element to predict country growth. We like this result because Complexity-weighted diversification is precisely the first equation of the Fitness algorithm that we introduced in 2012 (2,3). However, contrary to what is claimed in (1), it is incorrect to say that diversification is contained also in the ECI algorithm (4). We discuss the origin of this misunderstanding and show that the ECI algorithm contains exactly zero diversification. This is actually one of the reasons for the poor performances of ECI which leads to completely unrealistic results, as for instance, the derivation that Qatar or Saudi Arabia are industrially more competitive than China (5,6). Another important element of our new approach is the representation of the economic dynamics of countries as trajectories in the GDPpc-Fitness space (7-10). In some way also this has been rediscovered by Hausmann and collaborators and renamed as "Stream plots", but, given their weaker metrics and methods, they propose it to use it only for a qualitative insight, while ours led to quantitative and successful forecasting. The Fitness approach has paved the way to a robust and testable framework for Economic Complexity resulting in a highly competitive scheme for growth forecasting (7-10). According to a recent report by Bloomberg (9): The new Fitness method, "systematically outperforms standard methods, despite requiring much less data".

[1]  Charles D. Brummitt,et al.  Machine-learned patterns suggest that diversification drives economic development , 2018, Journal of the Royal Society Interface.

[2]  Justin Yifu Lin,et al.  Economic Development and Transition: Thought, Strategy, and Viability , 2009 .

[3]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[4]  Andrea Zaccaria,et al.  Why we like the ECI+ algorithm , 2017, 1708.01161.

[5]  Emanuele Pugliese,et al.  Economic Complexity: "Buttarla in caciara" vs a constructive approach , 2017, 1709.05272.

[6]  Mansour Alsaleh,et al.  729 new measures of economic complexity (Addendum to Improving the Economic Complexity Index) , 2017 .

[7]  Luciano Pietronero,et al.  The Heterogeneous Dynamics of Economic Complexity , 2015, PloS one.

[8]  Guido Caldarelli,et al.  A New Metrics for Countries' Fitness and Products' Complexity , 2012, Scientific Reports.

[9]  Antje Baer,et al.  New Structural Economics A Framework For Rethinking Development And Policy , 2016 .

[10]  Zhuo-Ming Ren,et al.  Nestedness in complex networks: Observation, emergence, and implications , 2019, Physics Reports.

[11]  Yicheng Zhang,et al.  Computational socioeconomics , 2019, Physics Reports.

[12]  Antonio Scala,et al.  PopRank: Ranking pages’ impact and users’ engagement on Facebook , 2018, PloS one.

[13]  Lant Pritchett,et al.  Asiaphoria Meets Regression to the Mean , 2014 .

[14]  Mansour Alsaleh,et al.  Improving the Economic Complexity Index , 2017 .

[15]  Guido Caldarelli,et al.  Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products , 2013, PloS one.

[16]  Hykel Hosni,et al.  Forecasting in Light of Big Data , 2017, Philosophy & Technology.

[17]  César A. Hidalgo,et al.  The building blocks of economic complexity , 2009, Proceedings of the National Academy of Sciences.

[18]  Andrea Tacchella,et al.  A dynamical systems approach to gross domestic product forecasting , 2018, Nature Physics.