Abstract
This paper presents new perspectives and methodological instruments for verifying the validity of Benford’s law for a large given dataset. To this aim, we first propose new general tests for checking the statistical conformity of a given dataset with a generic target distribution; we also
provide the explicit representation of the asymptotic distributions of the relevant test statistics. Then,
we discuss the applicability of such novel devices to the case of Benford’s law. We implement extensive Monte Carlo simulations to investigate the size and the power of the introduced tests. Finally, we discuss the challenging theme of interpreting, in a statistically reliable way, the conformity between two distributions in the presence of a large number of observations.
Original language | English |
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Pages (from-to) | 745–761 |
Number of pages | 17 |
Journal | Stats |
Volume | 4 |
Issue number | 3 |
DOIs | |
Publication status | Published - 6 Sept 2021 |
Externally published | Yes |
Keywords
- Benford’s law; conformity tests; goodness-of-fit tests; Monte Carlo simulation; size–power graphs