The authors are grateful to the Foundation for Science and Technology
(FCT, Portugal) for financial support by national funds FCT/MCTES to UNIAG, under Project
no. UIDB/04752/2020 and to INEGI under LAETA project UIDB/5022/2020.
G. Neves would also like to acknowledge the Sal City Council (Câmara Municipal do Sal)
for their support of the PhD Scholarship.
This article presents Benford’s Law applied for the first time to the
tourism context, focusing on tourism demand. This law states that in sets of random
numbers of natural events, the probability of the first digit of these numbers
being 1 is approximately 30%, of being 2 is 18%, and so on until reaching 9
with 4.6% probability. In this context, the objective is to verify if Benford’s Law
applies to the monthly numbers of overnight stays registered in the accommodation
establishments of the Island of Sal, in the period between 2000 and 2018,
to test the data reliability. This research focus on data provided by the National
Statistics Institute of Cape Verde. The Chi-Square test (χ2) was used to assess the
discrepancy between the observed and expected relative frequencies. The results
show that the observed χ2 value is higher than the χ2 critical value (5% significance
level), meaning that the number of monthly overnight stays recorded in
accommodation establishments on the Island of Sal does not follow Benford’s
Law. However, certain possible data disturbances must be considered, such as the
occurrence of specific events during that time period. Other factors that could
influence the results are the size of the data set and a sub notification in the data
collection process. These circumstances may be the cause of the non-adaptation
of the number of overnight stays to Benford’s Law. The implication of this fact on
the estimation of tourism demand is crucial for the development and optimization
of prediction models.
