Chaos, Solitons & Fractals 173, p. 113635.
ISSN/ISBN: Not available at this time. DOI: 10.1016/j.chaos.2023.113635
Abstract: This paper proposes a data science approach based on Benford's Law to analyse tourist flows – being tourism a relevant economic sector in Sicily. In particular, we are interested in detecting irregular patterns in the numerical data that may represent manipulations, inaccuracies or biases in the self-reported data from tourism organisations. The analysis is carried out by using monthly data for arrivals and overnight stays in hotels, B&Bs, and complementary accommodations in the seven provinces of the island from January 2016 to December 2019. We perform the analysis by employing several statistical tests and through a visual inspection of the difference between the empirical distributions and the theoretical Benford's. Conformity to Benford's distribution is mostly confirmed for the total number of overnight stays and the data considered on a yearly basis. On the contrary, we found evident deviations from Benford's Law in the empirical distribution of data broken down by nationality of tourist and accommodation type. Some comments on possible motivations for such deviations are also advanced, even though a detailed exploration of them deserves a devoted study.
Bibtex:
@article{,
title = {Benford's Law for economic data reliability: The case of tourism flows in Sicily},
journal = {Chaos, Solitons \& Fractals},
volume = {173},
pages = {113635},
year = {2023},
issn = {0960-0779},
doi = {https://doi.org/10.1016/j.chaos.2023.113635},
url = {https://www.sciencedirect.com/science/article/pii/S0960077923005362},
author = {Roy Cerqueti and Davide Provenzano},
}
Reference Type: Journal Article
Subject Area(s): Computer Science, Economics