ITEM METADATA RECORD
Title: Pareto versus Lognormal: A maximum entropy test
Authors: Bee, M. ×
Riccaboni, Massimo
Schiavo, S. #
Issue Date: 2011
Publisher: Published by the American Physical Society through the American Institute of Physics
Series Title: Physical Review E, Statistical, Nonlinear and Soft Matter Physics vol:84 issue:2
Article number: 026104
Abstract: It is commonly found that distributions that seem to be lognormal over a broad range change to a power-law (Pareto) distribution for the last few percentiles. The distributions of many physical, natural, and social events (earthquake size, species abundance, income and wealth, as well as file, city, and firm sizes) display this structure. We present a test for the occurrence of power-law tails in statistical distributions based on maximum entropy. This methodology allows one to identify the true data-generating processes even in the case when it is neither lognormal nor Pareto. The maximum entropy approach is then compared with other widely used methods and applied to different levels of aggregation of complex systems. Our results provide support for the theory that distributions with lognormal body and Pareto tail can be generated as mixtures of lognormally distributed units.
ISSN: 1539-3755
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Department of Managerial Economics, Strategy and Innovation (MSI), Leuven
× corresponding author
# (joint) last author

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