Luciano  Pietronero

Prof. Dr. Luciano Pietronero

1. Department of Physics, University of Rome La Sapienza, Piazzale A. Moro 2, 00185 Rome, Italy
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Research Focus & Metrics

Academic Career Length

43Years (1984-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 March 1984 in Physical Review Letters
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LNL. Niemeyer
L. Niemeyer
LPLuciano Pietronero
Luciano Pietronero
HWH. J. Wiesmann
H. J. Wiesmann
It is shown that the simplest nontrivial stochastic model for dielectric breakdown naturally leads to fractal structures for the discharge pattern. Planar discharges are studied in detail and the results are compared with properly designed experiments.

10 October 2012 in Scientific Reports
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ATAndrea Tacchella
Andrea Tacchella
MCMatthieu Cristelli
Matthieu Cristelli
Guido CaldarelliGuido Caldarelli
Guido Caldarelli
AGAndrea Gabrielli
Andrea Gabrielli
LPLuciano Pietronero
Luciano Pietronero
Classical economic theories prescribe specialization of countries industrial production. Inspection of the country databases of exported products shows that this is not the case: successful countries are extremely diversified, in analogy with biosystems evolving in a competitive dynamical environment. The challenge is assessing quantitatively the non-monetary competitive advantage of diversification which represents the hidden potential for development and growth. Here we develop a new statistical approach based on coupled non-linear maps, whose fixed point defines a new metrics for the country Fitness and product Complexity. We show that a non-linear iteration is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We show that, given the paradigm of economic complexity, the correct and simplest approach to measure the competitiveness of countries is the one presented in this work. Furthermore our metrics appears to be economically well-grounded.

5 August 2013 in PLOS ONE
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MCMatthieu Cristelli
Matthieu Cristelli
AGAndrea Gabrielli
Andrea Gabrielli
ATAndrea Tacchella
Andrea Tacchella
Guido CaldarelliGuido Caldarelli
Guido Caldarelli
LPLuciano Pietronero
Luciano Pietronero
We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation.

30 January 2007 in Proceedings of the National Academy of Sciences
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CCCiro Cattuto
Ciro Cattuto
VLVittorio Loreto
Vittorio Loreto
LPLuciano Pietronero
Luciano Pietronero
Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and investigate the statistical properties of tag cooccurrence. We introduce a stochastic model of user behavior embodying two main aspects of collaborative tagging: ( i ) a frequency-bias mechanism related to the idea that users are exposed to each other's tagging activity; ( ii ) a notion of memory, or aging of resources, in the form of a heavy-tailed access to the past state of the system. Remarkably, our simple modeling is able to account quantitatively for the observed experimental features with a surprisingly high accuracy. This points in the direction of a universal behavior of users who, despite the complexity of their own cognitive processes and the uncoordinated and selfish nature of their tagging activity, appear to follow simple activity patterns.

1 May 2003 in Nature
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DGDiego Garlaschelli
Diego Garlaschelli
Guido CaldarelliGuido Caldarelli
Guido Caldarelli
LPLuciano Pietronero
Luciano Pietronero

1 April 2001 in Physica A: Statistical Mechanics and its Applications
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Journal Article
Closed access
LPLuciano Pietronero
Luciano Pietronero
ETE. Tosatti
E. Tosatti
VTV. Tosatti
V. Tosatti
AVA. Vespignani
A. Vespignani